7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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Industry ndashled research program funded by EnterpriseIreland which aims to develop a PAT enabled mammalian
cell bioprocess
Modelling andPrediction
ProcessControl
Online
Sampling
AnalyticsSensors
Real timemonitoring
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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X
L
G
V
S in
F
X Biomass
G GlucoseL LactateV Volume
F Feed RateS in Inlet Substrate
Concentration
Process
Controller
Raman Probe
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983120983154983151983139983141983155983155 983107983151983150983156983154983151983148
ProcessObjective
MaximizeBiomassProductivity
ControlObjective
Maintain a lowGlucoseGlutamine level
in order to avoid a buildup of LactateAmmonia
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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amp 983124983157983150983141
983123983145983149983157983148983137983156983141
983122983141983137983148
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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bull Based on the ISA control law consisting of three control
parameters (K Td Ti)
bull Control parameters tuned via Ziegler Nichols (Closedloop) relay based tuning
Classical Control PID Controller
++= int
t
d
i dt
t de
T d eT t eK t u0
)(
)(
1
)()( τ τ
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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Setpoint OutputProcess
P
I
D
)(t Ke
int t
i
d eT
K
0)( τ τ
dt
t deKT d
)(
sum sum+
-
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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11
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Classical Control PID Controller Tuning
Ziegler Nichols closed loop with relay identification technique
71
U K PID K =
T i =
T d
=
2
U P
8
U P
= 0010558
= 04
= 01
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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12
Control Strategy Development
Output
Setpoint
Process
ModelObjectiveFunction
Optimisation
Feed
Advanced Control MPC Controller
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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13
Control Strategy Development
Industrial MPC Formulation
sumsum =
minus++
=
+
∆∆
Λ∆+minusΓ minus+
M
i
ik ik
P
i
ik t ut u
t ut Rt y M k k 1
2
)1
2
1)()(()()((min
1
Subject to
maxmin
maxmin
uuu
y y y
∆le∆le∆
lele
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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Advanced Control MPC Tuning
4 Tuning parameters
P = Prediction horizon
M = Control horizon
Γ = Output weight matrix
Λ = Input weight matrix
Offline Tuning Rules
P = Increase until no further effect
M = 1 (gt1 leads to more aggressive control)
Γ = scale on control variables = 1
Λ = Increase to avoid aggressive CO
Tuning results
P = 10
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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amp 983124983157983150983141
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983124983145983149983141
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bullSet-point Tracking
bullDisturbance Compensation
bullPropagation of Measurement Noise
Performance Off-Line Testing Criteria
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
0 50 100 150 200 250 300Time (h)
F e e d r a
t e ( L h )
Controller Output
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
0 50 100 150 200 250 300Time (h)
F e e d r a
t e ( L h )
Controller Output
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PID Disturbance Compensation
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M ) Cglc
Set-point
0
002
004
006
008
01
012
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h )
Controller Output
Disturbanceapplied
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MPC Disturbance Compensation
0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M
)
CglcSet-point
0
002
004
006
008
01
012
0 50 100 150 200 250 300Time (h)
F e e d r a
t e ( L h )
Controller Output
Disturbanceapplied
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
Fast lsquoon-offrsquo
Control
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0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c
e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006007
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h )
Controller Output
Removal oflsquoDrsquo term leadsto less abruptcontrol
Better set-point tracking
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0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
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0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
P = 10
M = 1
Γ = 1
Λ = 0
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c
e n t r a t i o n ( m M
)
CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
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e n t r a t i o n ( m M )
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0001002003004005006007
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P = 40
M = 1
Γ = 1
Λ = 0
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t e ( L h
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n t r a t i o n ( m M )
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0
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0 50 100 150 200 250 300Time (h)
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P = 40
M = 1
Γ = 1
Λ = 10000
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bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error
bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch
bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input
the control action in the presence of measurement noise canbe dampened to a more smooth control signal
bullSISOMIMO PID can only handle one input and one output
MPC is a multivariable control strategy
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bull Communication and controller configuration for real timeapplication complete
bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration
bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered
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bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies
bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study
bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales
bull Real time results are to be compared to the results gatheredon a simulation basis
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Prof Brian Glennon
Dr Jessica Whelan
PAT-Bio Research Team
Enterprise Ireland
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Industry ndashled research program funded by EnterpriseIreland which aims to develop a PAT enabled mammalian
cell bioprocess
Modelling andPrediction
ProcessControl
Online
Sampling
AnalyticsSensors
Real timemonitoring
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X
L
G
V
S in
F
X Biomass
G GlucoseL LactateV Volume
F Feed RateS in Inlet Substrate
Concentration
Process
Controller
Raman Probe
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ProcessObjective
MaximizeBiomassProductivity
ControlObjective
Maintain a lowGlucoseGlutamine level
in order to avoid a buildup of LactateAmmonia
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bull Based on the ISA control law consisting of three control
parameters (K Td Ti)
bull Control parameters tuned via Ziegler Nichols (Closedloop) relay based tuning
Classical Control PID Controller
++= int
t
d
i dt
t de
T d eT t eK t u0
)(
)(
1
)()( τ τ
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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Setpoint OutputProcess
P
I
D
)(t Ke
int t
i
d eT
K
0)( τ τ
dt
t deKT d
)(
sum sum+
-
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Classical Control PID Controller Tuning
Ziegler Nichols closed loop with relay identification technique
71
U K PID K =
T i =
T d
=
2
U P
8
U P
= 0010558
= 04
= 01
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Control Strategy Development
Output
Setpoint
Process
ModelObjectiveFunction
Optimisation
Feed
Advanced Control MPC Controller
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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Control Strategy Development
Industrial MPC Formulation
sumsum =
minus++
=
+
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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Advanced Control MPC Tuning
4 Tuning parameters
P = Prediction horizon
M = Control horizon
Γ = Output weight matrix
Λ = Input weight matrix
Offline Tuning Rules
P = Increase until no further effect
M = 1 (gt1 leads to more aggressive control)
Γ = scale on control variables = 1
Λ = Increase to avoid aggressive CO
Tuning results
P = 10
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983155983145983149983157983148983137983156983145983151983150
983085 983120983113983108 983107983151983150983156983154983151983148
983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)
983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
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983124983145983149983141
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983107983151983150983156983154983151983148983148983141983154 983120983141983154983142983151983154983149983137983150983139983141 983123983145983149983157983148983137983156983145983151983150 983122983141983155983157983148983156983155
bullSet-point Tracking
bullDisturbance Compensation
bullPropagation of Measurement Noise
Performance Off-Line Testing Criteria
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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0
5
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0 50 100 150 200 250 300
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C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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0
5
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15
20
25
30
0 50 100 150 200 250 300
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C o n c e n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983117983120983107 983123983141983156983085983152983151983145983150983156 983123983156983141983152 983124983154983137983139983147983145983150983143
0
5
10
15
20
25
30
0 50 100 150 200 250 300
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C o n c e
n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
0 50 100 150 200 250 300Time (h)
F e e d r a
t e ( L h )
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
0 50 100 150 200 250 300Time (h)
F e e d r a
t e ( L h )
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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PID Disturbance Compensation
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M ) Cglc
Set-point
0
002
004
006
008
01
012
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h )
Controller Output
Disturbanceapplied
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MPC Disturbance Compensation
0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M
)
CglcSet-point
0
002
004
006
008
01
012
0 50 100 150 200 250 300Time (h)
F e e d r a
t e ( L h )
Controller Output
Disturbanceapplied
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0
5
10
15
20
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0 50 100 150 200 250 300
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C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
Fast lsquoon-offrsquo
Control
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0
510
15
20
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0 50 100 150 200 250 300Time (h)
C o n c
e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006007
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h )
Controller Output
Removal oflsquoDrsquo term leadsto less abruptcontrol
Better set-point tracking
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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0
510
15
20
25
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0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M ) Cglc
Set-point
0
001
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F e e d - r a
t e ( L h )
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0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
P = 10
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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0
5
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C o n c
e n t r a t i o n ( m M
)
CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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0
5
10
15
20
25
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0 50 100 150 200 250 300
Time (h)
C o n c
e n t r a t i o n ( m M )
CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
Controller Output
P = 40
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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5
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0 50 100 150 200 250 300
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C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h
Controller Output
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h
Controller Output
P = 40
M = 1
Γ = 1
Λ = 10000
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error
bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch
bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input
the control action in the presence of measurement noise canbe dampened to a more smooth control signal
bullSISOMIMO PID can only handle one input and one output
MPC is a multivariable control strategy
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148
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amp 983124983157983150983141
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983105983106983106
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983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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bull Communication and controller configuration for real timeapplication complete
bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration
bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies
bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study
bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales
bull Real time results are to be compared to the results gatheredon a simulation basis
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
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983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
Prof Brian Glennon
Dr Jessica Whelan
PAT-Bio Research Team
Enterprise Ireland
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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3
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Industry ndashled research program funded by EnterpriseIreland which aims to develop a PAT enabled mammalian
cell bioprocess
Modelling andPrediction
ProcessControl
Online
Sampling
AnalyticsSensors
Real timemonitoring
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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X
L
G
V
S in
F
X Biomass
G GlucoseL LactateV Volume
F Feed RateS in Inlet Substrate
Concentration
Process
Controller
Raman Probe
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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7
983120983154983151983139983141983155983155 983107983151983150983156983154983151983148
ProcessObjective
MaximizeBiomassProductivity
ControlObjective
Maintain a lowGlucoseGlutamine level
in order to avoid a buildup of LactateAmmonia
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983140983141983158983141983148983151983152983149983141983150983156
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983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)
983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
983123983145983149983157983148983137983156983141
983122983141983137983148
983124983145983149983141
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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bull Based on the ISA control law consisting of three control
parameters (K Td Ti)
bull Control parameters tuned via Ziegler Nichols (Closedloop) relay based tuning
Classical Control PID Controller
++= int
t
d
i dt
t de
T d eT t eK t u0
)(
)(
1
)()( τ τ
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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Setpoint OutputProcess
P
I
D
)(t Ke
int t
i
d eT
K
0)( τ τ
dt
t deKT d
)(
sum sum+
-
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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Classical Control PID Controller Tuning
Ziegler Nichols closed loop with relay identification technique
71
U K PID K =
T i =
T d
=
2
U P
8
U P
= 0010558
= 04
= 01
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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12
Control Strategy Development
Output
Setpoint
Process
ModelObjectiveFunction
Optimisation
Feed
Advanced Control MPC Controller
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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13
Control Strategy Development
Industrial MPC Formulation
sumsum =
minus++
=
+
∆∆
Λ∆+minusΓ minus+
M
i
ik ik
P
i
ik t ut u
t ut Rt y M k k 1
2
)1
2
1)()(()()((min
1
Subject to
maxmin
maxmin
uuu
y y y
∆le∆le∆
lele
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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Advanced Control MPC Tuning
4 Tuning parameters
P = Prediction horizon
M = Control horizon
Γ = Output weight matrix
Λ = Input weight matrix
Offline Tuning Rules
P = Increase until no further effect
M = 1 (gt1 leads to more aggressive control)
Γ = scale on control variables = 1
Λ = Increase to avoid aggressive CO
Tuning results
P = 10
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983155983145983149983157983148983137983156983145983151983150
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983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
983123983145983149983157983148983137983156983141
983122983141983137983148
983124983145983149983141
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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bullSet-point Tracking
bullDisturbance Compensation
bullPropagation of Measurement Noise
Performance Off-Line Testing Criteria
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
0 50 100 150 200 250 300Time (h)
F e e d r a
t e ( L h )
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
0 50 100 150 200 250 300Time (h)
F e e d r a
t e ( L h )
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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PID Disturbance Compensation
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M ) Cglc
Set-point
0
002
004
006
008
01
012
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h )
Controller Output
Disturbanceapplied
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MPC Disturbance Compensation
0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M
)
CglcSet-point
0
002
004
006
008
01
012
0 50 100 150 200 250 300Time (h)
F e e d r a
t e ( L h )
Controller Output
Disturbanceapplied
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
Fast lsquoon-offrsquo
Control
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983120983113 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c
e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006007
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h )
Controller Output
Removal oflsquoDrsquo term leadsto less abruptcontrol
Better set-point tracking
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
P = 10
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c
e n t r a t i o n ( m M
)
CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
Controller Output
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c
e n t r a t i o n ( m M )
CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
Controller Output
P = 40
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h
Controller Output
P = 40
M = 1
Γ = 1
Λ = 10000
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error
bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch
bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input
the control action in the presence of measurement noise canbe dampened to a more smooth control signal
bullSISOMIMO PID can only handle one input and one output
MPC is a multivariable control strategy
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bull Communication and controller configuration for real timeapplication complete
bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration
bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
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bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies
bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study
bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales
bull Real time results are to be compared to the results gatheredon a simulation basis
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Prof Brian Glennon
Dr Jessica Whelan
PAT-Bio Research Team
Enterprise Ireland
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X
L
G
V
S in
F
X Biomass
G GlucoseL LactateV Volume
F Feed RateS in Inlet Substrate
Concentration
Process
Controller
Raman Probe
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ProcessObjective
MaximizeBiomassProductivity
ControlObjective
Maintain a lowGlucoseGlutamine level
in order to avoid a buildup of LactateAmmonia
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bull Based on the ISA control law consisting of three control
parameters (K Td Ti)
bull Control parameters tuned via Ziegler Nichols (Closedloop) relay based tuning
Classical Control PID Controller
++= int
t
d
i dt
t de
T d eT t eK t u0
)(
)(
1
)()( τ τ
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Setpoint OutputProcess
P
I
D
)(t Ke
int t
i
d eT
K
0)( τ τ
dt
t deKT d
)(
sum sum+
-
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Classical Control PID Controller Tuning
Ziegler Nichols closed loop with relay identification technique
71
U K PID K =
T i =
T d
=
2
U P
8
U P
= 0010558
= 04
= 01
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Control Strategy Development
Output
Setpoint
Process
ModelObjectiveFunction
Optimisation
Feed
Advanced Control MPC Controller
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Control Strategy Development
Industrial MPC Formulation
sumsum =
minus++
=
+
∆∆
Λ∆+minusΓ minus+
M
i
ik ik
P
i
ik t ut u
t ut Rt y M k k 1
2
)1
2
1)()(()()((min
1
Subject to
maxmin
maxmin
uuu
y y y
∆le∆le∆
lele
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Advanced Control MPC Tuning
4 Tuning parameters
P = Prediction horizon
M = Control horizon
Γ = Output weight matrix
Λ = Input weight matrix
Offline Tuning Rules
P = Increase until no further effect
M = 1 (gt1 leads to more aggressive control)
Γ = scale on control variables = 1
Λ = Increase to avoid aggressive CO
Tuning results
P = 10
M = 1
Γ = 1
Λ = 0
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amp 983124983157983150983141
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bullSet-point Tracking
bullDisturbance Compensation
bullPropagation of Measurement Noise
Performance Off-Line Testing Criteria
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
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5
10
15
20
25
30
0 50 100 150 200 250 300
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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t e ( L h )
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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0
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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21
PID Disturbance Compensation
0
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n t r a t i o n ( m M ) Cglc
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01
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F e e d - r a t e ( L h )
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Disturbanceapplied
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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MPC Disturbance Compensation
0
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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Fast lsquoon-offrsquo
Control
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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005
006007
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F e e d - r a t e ( L h )
Controller Output
Removal oflsquoDrsquo term leadsto less abruptcontrol
Better set-point tracking
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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F e e d - r a
t e ( L h )
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P = 10
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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0001002003004005006007
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F e e d - r a t e ( L h )
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
Controller Output
P = 40
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
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n t r a t i o n ( m M )
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0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
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0 50 100 150 200 250 300
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n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
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005
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0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h
Controller Output
P = 40
M = 1
Γ = 1
Λ = 10000
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error
bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch
bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input
the control action in the presence of measurement noise canbe dampened to a more smooth control signal
bullSISOMIMO PID can only handle one input and one output
MPC is a multivariable control strategy
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148
983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)
983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
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983148
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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3 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152
983122 983148 983124983145 983107 983148983148 983105 983148983145 983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
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983154983141983137983148983085983156983145983149983141
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15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983123983152983141983139983156983154983137983148
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983155983151983142983156983159983137983154983141
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983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
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983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
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983105983106983106
98309600983160983137
983139983151983150983156983154983151983148
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983125983123983106 983124983107983120983113983120
983105983106983106 983160983120983105983124 983108983137983156983137
983117983137983150983137983143983141983154
983119983120983107983119983120983107
983119983120983107
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
bull Communication and controller configuration for real timeapplication complete
bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration
bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies
bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study
bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales
bull Real time results are to be compared to the results gatheredon a simulation basis
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
Prof Brian Glennon
Dr Jessica Whelan
PAT-Bio Research Team
Enterprise Ireland
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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X
L
G
V
S in
F
X Biomass
G GlucoseL LactateV Volume
F Feed RateS in Inlet Substrate
Concentration
Process
Controller
Raman Probe
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983106983145983151983152983154983151983139983141983155983155 983117983151983140983141983148
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983085 983123983161983155983156983141983149 983151983142 983139983151983157983152983148983141983140 983119983108983109983155 983149983137983155983155 983138983137983148983137983150983139983141 983137983150983140 983154983137983156983141 983141983153983157983137983156983145983151983150983155
983085 983107983151983150983156983137983145983150983155 983137983152983152983154983151983160983145983149983137983156983141983148983161 16 983149983151983140983141983148 983152983137983154983137983149983141983156983141983154983155
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983120983154983151983139983141983155983155 983107983151983150983156983154983151983148
ProcessObjective
MaximizeBiomassProductivity
ControlObjective
Maintain a lowGlucoseGlutamine level
in order to avoid a buildup of LactateAmmonia
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150
983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983140983141983158983141983148983151983152983149983141983150983156
983085 983120983113983108 983107983151983150983156983154983151983148
983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)
983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
983123983145983149983157983148983137983156983141
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983124983145983149983141
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156
bull Based on the ISA control law consisting of three control
parameters (K Td Ti)
bull Control parameters tuned via Ziegler Nichols (Closedloop) relay based tuning
Classical Control PID Controller
++= int
t
d
i dt
t de
T d eT t eK t u0
)(
)(
1
)()( τ τ
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Setpoint OutputProcess
P
I
D
)(t Ke
int t
i
d eT
K
0)( τ τ
dt
t deKT d
)(
sum sum+
-
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Classical Control PID Controller Tuning
Ziegler Nichols closed loop with relay identification technique
71
U K PID K =
T i =
T d
=
2
U P
8
U P
= 0010558
= 04
= 01
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Control Strategy Development
Output
Setpoint
Process
ModelObjectiveFunction
Optimisation
Feed
Advanced Control MPC Controller
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13
Control Strategy Development
Industrial MPC Formulation
sumsum =
minus++
=
+
∆∆
Λ∆+minusΓ minus+
M
i
ik ik
P
i
ik t ut u
t ut Rt y M k k 1
2
)1
2
1)()(()()((min
1
Subject to
maxmin
maxmin
uuu
y y y
∆le∆le∆
lele
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Advanced Control MPC Tuning
4 Tuning parameters
P = Prediction horizon
M = Control horizon
Γ = Output weight matrix
Λ = Input weight matrix
Offline Tuning Rules
P = Increase until no further effect
M = 1 (gt1 leads to more aggressive control)
Γ = scale on control variables = 1
Λ = Increase to avoid aggressive CO
Tuning results
P = 10
M = 1
Γ = 1
Λ = 0
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983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983155983145983149983157983148983137983156983145983151983150
983085 983120983113983108 983107983151983150983156983154983151983148
983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)
983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
983123983145983149983157983148983137983156983141
983122983141983137983148
983124983145983149983141
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bullSet-point Tracking
bullDisturbance Compensation
bullPropagation of Measurement Noise
Performance Off-Line Testing Criteria
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
0 50 100 150 200 250 300Time (h)
F e e d r a
t e ( L h )
Controller Output
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
0 50 100 150 200 250 300Time (h)
F e e d r a
t e ( L h )
Controller Output
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PID Disturbance Compensation
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M ) Cglc
Set-point
0
002
004
006
008
01
012
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h )
Controller Output
Disturbanceapplied
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MPC Disturbance Compensation
0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M
)
CglcSet-point
0
002
004
006
008
01
012
0 50 100 150 200 250 300Time (h)
F e e d r a
t e ( L h )
Controller Output
Disturbanceapplied
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
Fast lsquoon-offrsquo
Control
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0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c
e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006007
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h )
Controller Output
Removal oflsquoDrsquo term leadsto less abruptcontrol
Better set-point tracking
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0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
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0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
P = 10
M = 1
Γ = 1
Λ = 0
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c
e n t r a t i o n ( m M
)
CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
Controller Output
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c
e n t r a t i o n ( m M )
CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
Controller Output
P = 40
M = 1
Γ = 1
Λ = 0
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5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h
Controller Output
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h
Controller Output
P = 40
M = 1
Γ = 1
Λ = 10000
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bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error
bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch
bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input
the control action in the presence of measurement noise canbe dampened to a more smooth control signal
bullSISOMIMO PID can only handle one input and one output
MPC is a multivariable control strategy
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983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148
983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)
983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
983123983145983149983157983148983137983156983141
983122983141983137983148
983124983145983149983141
983148
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983122 983148 983124983145 983107 983148983148 983105 983148983145 983145
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983123983152983141983139983156983154983137983148
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983155983151983142983156983159983137983154983141
983123983152983141983139983156983154983137983148
983142983145983148983141
983107983137983148983145983138983154983137983156983145983151983150
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
983141983150983143983145983150983141
983110983141983141983140 983120983157983149983152
983125983123983106983124983141983160983156 983142983145983148983141
983154983141983137983140983159983154983145983156983141
983110983145983148983141 983108983145983154983141983139983156983151983154983161
983124983141983160983156 983142983145983148983141
983154983141983137983140983159983154983145983156983141
983124983141983160983156 983142983145983148983141
983154983141983137983140983159983154983145983156983141
983123983141983154983145983137983148
15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156
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983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983120983154983151983138983141
983123983152983141983139983156983154983137983148
983137983139983153983157983145983155983145983156983145983151983150
983155983151983142983156983159983137983154983141
983123983152983141983139983156983154983137983148
983142983145983148983141
983107983137983148983145983138983154983137983156983145983151983150
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
983141983150983143983145983150983141
983105983106983106
98309600983160983137
983139983151983150983156983154983151983148
983155983161983155983156983141983149
983125983123983106 983124983107983120983113983120
983105983106983106 983160983120983105983124 983108983137983156983137
983117983137983150983137983143983141983154
983119983120983107983119983120983107
983119983120983107
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
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bull Communication and controller configuration for real timeapplication complete
bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration
bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies
bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study
bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales
bull Real time results are to be compared to the results gatheredon a simulation basis
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
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983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
Prof Brian Glennon
Dr Jessica Whelan
PAT-Bio Research Team
Enterprise Ireland
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983085 983123983161983155983156983141983149 983151983142 983139983151983157983152983148983141983140 983119983108983109983155 983149983137983155983155 983138983137983148983137983150983139983141 983137983150983140 983154983137983156983141 983141983153983157983137983156983145983151983150983155
983085 983107983151983150983156983137983145983150983155 983137983152983152983154983151983160983145983149983137983156983141983148983161 16 983149983151983140983141983148 983152983137983154983137983149983141983156983141983154983155
983085 983125983155983141983140 983137 983140983145983142983142983141983154983141983150983156983145983137983148 983141983158983151983148983157983156983145983151983150 983152983137983154983137983149983141983156983141983154 983151983152983156983145983149983145983155983137983156983145983151983150983137983148983143983151983154983145983156983144983149 983156983151 983142983145983156 983156983144983141 983152983137983154983137983149983141983156983141983154 983158983137983148983157983141983155 983159983145983156983144 983156983144983141 983152983151983155983155983145983138983148983141 983154983137983150983143983141983155
983139983151983150983155983156983154983137983145983150983141983140 983138983137983155983141983140 983151983150 983152983157983138983148983145983155983144983141983140 983158983137983148983157983141983155
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983120983154983151983139983141983155983155 983107983151983150983156983154983151983148
ProcessObjective
MaximizeBiomassProductivity
ControlObjective
Maintain a lowGlucoseGlutamine level
in order to avoid a buildup of LactateAmmonia
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983140983141983158983141983148983151983152983149983141983150983156
983085 983120983113983108 983107983151983150983156983154983151983148
983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)
983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
983123983145983149983157983148983137983156983141
983122983141983137983148
983124983145983149983141
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bull Based on the ISA control law consisting of three control
parameters (K Td Ti)
bull Control parameters tuned via Ziegler Nichols (Closedloop) relay based tuning
Classical Control PID Controller
++= int
t
d
i dt
t de
T d eT t eK t u0
)(
)(
1
)()( τ τ
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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Setpoint OutputProcess
P
I
D
)(t Ke
int t
i
d eT
K
0)( τ τ
dt
t deKT d
)(
sum sum+
-
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Classical Control PID Controller Tuning
Ziegler Nichols closed loop with relay identification technique
71
U K PID K =
T i =
T d
=
2
U P
8
U P
= 0010558
= 04
= 01
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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Control Strategy Development
Output
Setpoint
Process
ModelObjectiveFunction
Optimisation
Feed
Advanced Control MPC Controller
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13
Control Strategy Development
Industrial MPC Formulation
sumsum =
minus++
=
+
∆∆
Λ∆+minusΓ minus+
M
i
ik ik
P
i
ik t ut u
t ut Rt y M k k 1
2
)1
2
1)()(()()((min
1
Subject to
maxmin
maxmin
uuu
y y y
∆le∆le∆
lele
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Advanced Control MPC Tuning
4 Tuning parameters
P = Prediction horizon
M = Control horizon
Γ = Output weight matrix
Λ = Input weight matrix
Offline Tuning Rules
P = Increase until no further effect
M = 1 (gt1 leads to more aggressive control)
Γ = scale on control variables = 1
Λ = Increase to avoid aggressive CO
Tuning results
P = 10
M = 1
Γ = 1
Λ = 0
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983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983155983145983149983157983148983137983156983145983151983150
983085 983120983113983108 983107983151983150983156983154983151983148
983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)
983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
983123983145983149983157983148983137983156983141
983122983141983137983148
983124983145983149983141
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bullSet-point Tracking
bullDisturbance Compensation
bullPropagation of Measurement Noise
Performance Off-Line Testing Criteria
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
0 50 100 150 200 250 300Time (h)
F e e d r a
t e ( L h )
Controller Output
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
0 50 100 150 200 250 300Time (h)
F e e d r a
t e ( L h )
Controller Output
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PID Disturbance Compensation
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M ) Cglc
Set-point
0
002
004
006
008
01
012
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h )
Controller Output
Disturbanceapplied
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MPC Disturbance Compensation
0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M
)
CglcSet-point
0
002
004
006
008
01
012
0 50 100 150 200 250 300Time (h)
F e e d r a
t e ( L h )
Controller Output
Disturbanceapplied
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
Fast lsquoon-offrsquo
Control
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0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c
e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006007
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h )
Controller Output
Removal oflsquoDrsquo term leadsto less abruptcontrol
Better set-point tracking
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0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
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0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
P = 10
M = 1
Γ = 1
Λ = 0
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c
e n t r a t i o n ( m M
)
CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
Controller Output
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c
e n t r a t i o n ( m M )
CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
Controller Output
P = 40
M = 1
Γ = 1
Λ = 0
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h
Controller Output
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h
Controller Output
P = 40
M = 1
Γ = 1
Λ = 10000
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bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error
bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch
bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input
the control action in the presence of measurement noise canbe dampened to a more smooth control signal
bullSISOMIMO PID can only handle one input and one output
MPC is a multivariable control strategy
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983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148
983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)
983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
983123983145983149983157983148983137983156983141
983122983141983137983148
983124983145983149983141
983148
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983142983145983148983141
983107983137983148983145983138983154983137983156983145983151983150
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983107983151983150983156983154983151983148
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983141983150983143983145983150983141
983105983106983106
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983119983120983107
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
bull Communication and controller configuration for real timeapplication complete
bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration
bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies
bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study
bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales
bull Real time results are to be compared to the results gatheredon a simulation basis
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
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983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
Prof Brian Glennon
Dr Jessica Whelan
PAT-Bio Research Team
Enterprise Ireland
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983120983154983151983139983141983155983155 983107983151983150983156983154983151983148
ProcessObjective
MaximizeBiomassProductivity
ControlObjective
Maintain a lowGlucoseGlutamine level
in order to avoid a buildup of LactateAmmonia
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983140983141983158983141983148983151983152983149983141983150983156
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amp 983124983157983150983141
983123983145983149983157983148983137983156983141
983122983141983137983148
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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bull Based on the ISA control law consisting of three control
parameters (K Td Ti)
bull Control parameters tuned via Ziegler Nichols (Closedloop) relay based tuning
Classical Control PID Controller
++= int
t
d
i dt
t de
T d eT t eK t u0
)(
)(
1
)()( τ τ
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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Setpoint OutputProcess
P
I
D
)(t Ke
int t
i
d eT
K
0)( τ τ
dt
t deKT d
)(
sum sum+
-
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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Classical Control PID Controller Tuning
Ziegler Nichols closed loop with relay identification technique
71
U K PID K =
T i =
T d
=
2
U P
8
U P
= 0010558
= 04
= 01
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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12
Control Strategy Development
Output
Setpoint
Process
ModelObjectiveFunction
Optimisation
Feed
Advanced Control MPC Controller
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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13
Control Strategy Development
Industrial MPC Formulation
sumsum =
minus++
=
+
∆∆
Λ∆+minusΓ minus+
M
i
ik ik
P
i
ik t ut u
t ut Rt y M k k 1
2
)1
2
1)()(()()((min
1
Subject to
maxmin
maxmin
uuu
y y y
∆le∆le∆
lele
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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Advanced Control MPC Tuning
4 Tuning parameters
P = Prediction horizon
M = Control horizon
Γ = Output weight matrix
Λ = Input weight matrix
Offline Tuning Rules
P = Increase until no further effect
M = 1 (gt1 leads to more aggressive control)
Γ = scale on control variables = 1
Λ = Increase to avoid aggressive CO
Tuning results
P = 10
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983155983145983149983157983148983137983156983145983151983150
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amp 983124983157983150983141
983123983145983149983157983148983137983156983141
983122983141983137983148
983124983145983149983141
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bullSet-point Tracking
bullDisturbance Compensation
bullPropagation of Measurement Noise
Performance Off-Line Testing Criteria
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0
5
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0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
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C o n c e n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
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C o n c e
n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
0 50 100 150 200 250 300Time (h)
F e e d r a
t e ( L h )
Controller Output
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
0 50 100 150 200 250 300Time (h)
F e e d r a
t e ( L h )
Controller Output
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PID Disturbance Compensation
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M ) Cglc
Set-point
0
002
004
006
008
01
012
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h )
Controller Output
Disturbanceapplied
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MPC Disturbance Compensation
0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M
)
CglcSet-point
0
002
004
006
008
01
012
0 50 100 150 200 250 300Time (h)
F e e d r a
t e ( L h )
Controller Output
Disturbanceapplied
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
Fast lsquoon-offrsquo
Control
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0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c
e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006007
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h )
Controller Output
Removal oflsquoDrsquo term leadsto less abruptcontrol
Better set-point tracking
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0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
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0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
P = 10
M = 1
Γ = 1
Λ = 0
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5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c
e n t r a t i o n ( m M
)
CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
Controller Output
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c
e n t r a t i o n ( m M )
CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
Controller Output
P = 40
M = 1
Γ = 1
Λ = 0
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h
Controller Output
P = 40
M = 1
Γ = 1
Λ = 10000
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155
bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error
bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch
bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input
the control action in the presence of measurement noise canbe dampened to a more smooth control signal
bullSISOMIMO PID can only handle one input and one output
MPC is a multivariable control strategy
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148
983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)
983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
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983148
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983122 983148 983124983145 983107 983148983148 983105 983148983145 983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983120983154983151983138983141
983123983152983141983139983156983154983137983148
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983155983151983142983156983159983137983154983141
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983142983145983148983141
983107983137983148983145983138983154983137983156983145983151983150
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
983141983150983143983145983150983141
983110983141983141983140 983120983157983149983152
983125983123983106983124983141983160983156 983142983145983148983141
983154983141983137983140983159983154983145983156983141
983110983145983148983141 983108983145983154983141983139983156983151983154983161
983124983141983160983156 983142983145983148983141
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983124983141983160983156 983142983145983148983141
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983123983141983154983145983137983148
15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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15 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152
983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983120983154983151983138983141
983123983152983141983139983156983154983137983148
983137983139983153983157983145983155983145983156983145983151983150
983155983151983142983156983159983137983154983141
983123983152983141983139983156983154983137983148
983142983145983148983141
983107983137983148983145983138983154983137983156983145983151983150
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
983141983150983143983145983150983141
983105983106983106
98309600983160983137
983139983151983150983156983154983151983148
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983117983137983150983137983143983141983154
983119983120983107983119983120983107
983119983120983107
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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bull Communication and controller configuration for real timeapplication complete
bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration
bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies
bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study
bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales
bull Real time results are to be compared to the results gatheredon a simulation basis
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
Prof Brian Glennon
Dr Jessica Whelan
PAT-Bio Research Team
Enterprise Ireland
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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8
983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150
983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983140983141983158983141983148983151983152983149983141983150983156
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983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
983123983145983149983157983148983137983156983141
983122983141983137983148
983124983145983149983141
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bull Based on the ISA control law consisting of three control
parameters (K Td Ti)
bull Control parameters tuned via Ziegler Nichols (Closedloop) relay based tuning
Classical Control PID Controller
++= int
t
d
i dt
t de
T d eT t eK t u0
)(
)(
1
)()( τ τ
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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Setpoint OutputProcess
P
I
D
)(t Ke
int t
i
d eT
K
0)( τ τ
dt
t deKT d
)(
sum sum+
-
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Classical Control PID Controller Tuning
Ziegler Nichols closed loop with relay identification technique
71
U K PID K =
T i =
T d
=
2
U P
8
U P
= 0010558
= 04
= 01
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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12
Control Strategy Development
Output
Setpoint
Process
ModelObjectiveFunction
Optimisation
Feed
Advanced Control MPC Controller
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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13
Control Strategy Development
Industrial MPC Formulation
sumsum =
minus++
=
+
∆∆
Λ∆+minusΓ minus+
M
i
ik ik
P
i
ik t ut u
t ut Rt y M k k 1
2
)1
2
1)()(()()((min
1
Subject to
maxmin
maxmin
uuu
y y y
∆le∆le∆
lele
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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Advanced Control MPC Tuning
4 Tuning parameters
P = Prediction horizon
M = Control horizon
Γ = Output weight matrix
Λ = Input weight matrix
Offline Tuning Rules
P = Increase until no further effect
M = 1 (gt1 leads to more aggressive control)
Γ = scale on control variables = 1
Λ = Increase to avoid aggressive CO
Tuning results
P = 10
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983155983145983149983157983148983137983156983145983151983150
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983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
983123983145983149983157983148983137983156983141
983122983141983137983148
983124983145983149983141
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bullSet-point Tracking
bullDisturbance Compensation
bullPropagation of Measurement Noise
Performance Off-Line Testing Criteria
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5
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0 50 100 150 200 250 300
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C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
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C o n c e n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
0 50 100 150 200 250 300Time (h)
F e e d r a
t e ( L h )
Controller Output
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
0 50 100 150 200 250 300Time (h)
F e e d r a
t e ( L h )
Controller Output
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PID Disturbance Compensation
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M ) Cglc
Set-point
0
002
004
006
008
01
012
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h )
Controller Output
Disturbanceapplied
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MPC Disturbance Compensation
0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M
)
CglcSet-point
0
002
004
006
008
01
012
0 50 100 150 200 250 300Time (h)
F e e d r a
t e ( L h )
Controller Output
Disturbanceapplied
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
Fast lsquoon-offrsquo
Control
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0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c
e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006007
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h )
Controller Output
Removal oflsquoDrsquo term leadsto less abruptcontrol
Better set-point tracking
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510
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Set-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
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510
15
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30
0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
P = 10
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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0
5
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C o n c
e n t r a t i o n ( m M
)
CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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0
5
10
15
20
25
30
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C o n c
e n t r a t i o n ( m M )
CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
Controller Output
P = 40
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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0
5
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15
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C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
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007
0 50 100 150 200 250 300Time (h)
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t e ( L h
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
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C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h
Controller Output
P = 40
M = 1
Γ = 1
Λ = 10000
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155
bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error
bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch
bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input
the control action in the presence of measurement noise canbe dampened to a more smooth control signal
bullSISOMIMO PID can only handle one input and one output
MPC is a multivariable control strategy
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150
983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148
983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)
983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
983123983145983149983157983148983137983156983141
983122983141983137983148
983124983145983149983141
983148
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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3 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152
983122 983148 983124983145 983107 983148983148 983105 983148983145 983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983122983137983149983137983150
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983155983151983142983156983159983137983154983141
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983142983145983148983141
983107983137983148983145983138983154983137983156983145983151983150
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
983141983150983143983145983150983141
983110983141983141983140 983120983157983149983152
983125983123983106983124983141983160983156 983142983145983148983141
983154983141983137983140983159983154983145983156983141
983110983145983148983141 983108983145983154983141983139983156983151983154983161
983124983141983160983156 983142983145983148983141
983154983141983137983140983159983154983145983156983141
983124983141983160983156 983142983145983148983141
983154983141983137983140983159983154983145983156983141
983123983141983154983145983137983148
15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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15 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152
983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983155983151983142983156983159983137983154983141
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983142983145983148983141
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983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
983141983150983143983145983150983141
983105983106983106
98309600983160983137
983139983151983150983156983154983151983148
983155983161983155983156983141983149
983125983123983106 983124983107983120983113983120
983105983106983106 983160983120983105983124 983108983137983156983137
983117983137983150983137983143983141983154
983119983120983107983119983120983107
983119983120983107
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
bull Communication and controller configuration for real timeapplication complete
bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration
bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies
bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study
bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales
bull Real time results are to be compared to the results gatheredon a simulation basis
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
Prof Brian Glennon
Dr Jessica Whelan
PAT-Bio Research Team
Enterprise Ireland
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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9
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bull Based on the ISA control law consisting of three control
parameters (K Td Ti)
bull Control parameters tuned via Ziegler Nichols (Closedloop) relay based tuning
Classical Control PID Controller
++= int
t
d
i dt
t de
T d eT t eK t u0
)(
)(
1
)()( τ τ
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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Setpoint OutputProcess
P
I
D
)(t Ke
int t
i
d eT
K
0)( τ τ
dt
t deKT d
)(
sum sum+
-
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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11
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Classical Control PID Controller Tuning
Ziegler Nichols closed loop with relay identification technique
71
U K PID K =
T i =
T d
=
2
U P
8
U P
= 0010558
= 04
= 01
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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12
Control Strategy Development
Output
Setpoint
Process
ModelObjectiveFunction
Optimisation
Feed
Advanced Control MPC Controller
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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13
Control Strategy Development
Industrial MPC Formulation
sumsum =
minus++
=
+
∆∆
Λ∆+minusΓ minus+
M
i
ik ik
P
i
ik t ut u
t ut Rt y M k k 1
2
)1
2
1)()(()()((min
1
Subject to
maxmin
maxmin
uuu
y y y
∆le∆le∆
lele
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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Advanced Control MPC Tuning
4 Tuning parameters
P = Prediction horizon
M = Control horizon
Γ = Output weight matrix
Λ = Input weight matrix
Offline Tuning Rules
P = Increase until no further effect
M = 1 (gt1 leads to more aggressive control)
Γ = scale on control variables = 1
Λ = Increase to avoid aggressive CO
Tuning results
P = 10
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983155983145983149983157983148983137983156983145983151983150
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983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
983123983145983149983157983148983137983156983141
983122983141983137983148
983124983145983149983141
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bullSet-point Tracking
bullDisturbance Compensation
bullPropagation of Measurement Noise
Performance Off-Line Testing Criteria
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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0
5
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30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
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0
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20
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30
0 50 100 150 200 250 300
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C o n c e n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
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F e e d - r a
t e ( L h )
Controller Output
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
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C o n c e
n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
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F e e d r a
t e ( L h )
Controller Output
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0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
0 50 100 150 200 250 300Time (h)
F e e d r a
t e ( L h )
Controller Output
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PID Disturbance Compensation
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M ) Cglc
Set-point
0
002
004
006
008
01
012
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h )
Controller Output
Disturbanceapplied
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MPC Disturbance Compensation
0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M
)
CglcSet-point
0
002
004
006
008
01
012
0 50 100 150 200 250 300Time (h)
F e e d r a
t e ( L h )
Controller Output
Disturbanceapplied
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5
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15
20
25
30
0 50 100 150 200 250 300
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C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
Fast lsquoon-offrsquo
Control
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983120983113 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c
e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006007
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h )
Controller Output
Removal oflsquoDrsquo term leadsto less abruptcontrol
Better set-point tracking
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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P = 10
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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F e e d - r a t e ( L h )
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P = 40
M = 1
Γ = 1
Λ = 0
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F e e d - r a t e ( L h
Controller Output
P = 40
M = 1
Γ = 1
Λ = 10000
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error
bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch
bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input
the control action in the presence of measurement noise canbe dampened to a more smooth control signal
bullSISOMIMO PID can only handle one input and one output
MPC is a multivariable control strategy
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148
983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)
983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
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bull Communication and controller configuration for real timeapplication complete
bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration
bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered
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bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies
bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study
bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales
bull Real time results are to be compared to the results gatheredon a simulation basis
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983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
Prof Brian Glennon
Dr Jessica Whelan
PAT-Bio Research Team
Enterprise Ireland
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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Setpoint OutputProcess
P
I
D
)(t Ke
int t
i
d eT
K
0)( τ τ
dt
t deKT d
)(
sum sum+
-
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Classical Control PID Controller Tuning
Ziegler Nichols closed loop with relay identification technique
71
U K PID K =
T i =
T d
=
2
U P
8
U P
= 0010558
= 04
= 01
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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Control Strategy Development
Output
Setpoint
Process
ModelObjectiveFunction
Optimisation
Feed
Advanced Control MPC Controller
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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Control Strategy Development
Industrial MPC Formulation
sumsum =
minus++
=
+
∆∆
Λ∆+minusΓ minus+
M
i
ik ik
P
i
ik t ut u
t ut Rt y M k k 1
2
)1
2
1)()(()()((min
1
Subject to
maxmin
maxmin
uuu
y y y
∆le∆le∆
lele
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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Advanced Control MPC Tuning
4 Tuning parameters
P = Prediction horizon
M = Control horizon
Γ = Output weight matrix
Λ = Input weight matrix
Offline Tuning Rules
P = Increase until no further effect
M = 1 (gt1 leads to more aggressive control)
Γ = scale on control variables = 1
Λ = Increase to avoid aggressive CO
Tuning results
P = 10
M = 1
Γ = 1
Λ = 0
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bullSet-point Tracking
bullDisturbance Compensation
bullPropagation of Measurement Noise
Performance Off-Line Testing Criteria
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PID Disturbance Compensation
0
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01
012
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Controller Output
Disturbanceapplied
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MPC Disturbance Compensation
0
510
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20
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C o n c e n t r a t i o n ( m M
)
CglcSet-point
0
002
004
006
008
01
012
0 50 100 150 200 250 300Time (h)
F e e d r a
t e ( L h )
Controller Output
Disturbanceapplied
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Fast lsquoon-offrsquo
Control
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0
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Set-point
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Removal oflsquoDrsquo term leadsto less abruptcontrol
Better set-point tracking
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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F e e d - r a
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P = 10
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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)
CglcSet-point
0001002003004005006007
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F e e d - r a t e ( L h )
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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0
5
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0 50 100 150 200 250 300
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C o n c
e n t r a t i o n ( m M )
CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
Controller Output
P = 40
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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n t r a t i o n ( m M )
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0
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007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h
Controller Output
P = 40
M = 1
Γ = 1
Λ = 10000
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error
bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch
bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input
the control action in the presence of measurement noise canbe dampened to a more smooth control signal
bullSISOMIMO PID can only handle one input and one output
MPC is a multivariable control strategy
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148
983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)
983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
983123983145983149983157983148983137983156983141
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983148
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3 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152
983122 983148 983124983145 983107 983148983148 983105 983148983145 983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983155983151983142983156983159983137983154983141
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983142983145983148983141
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983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
983141983150983143983145983150983141
983110983141983141983140 983120983157983149983152
983125983123983106983124983141983160983156 983142983145983148983141
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983110983145983148983141 983108983145983154983141983139983156983151983154983161
983124983141983160983156 983142983145983148983141
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15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156
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983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983120983154983151983138983141
983123983152983141983139983156983154983137983148
983137983139983153983157983145983155983145983156983145983151983150
983155983151983142983156983159983137983154983141
983123983152983141983139983156983154983137983148
983142983145983148983141
983107983137983148983145983138983154983137983156983145983151983150
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
983141983150983143983145983150983141
983105983106983106
98309600983160983137
983139983151983150983156983154983151983148
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983125983123983106 983124983107983120983113983120
983105983106983106 983160983120983105983124 983108983137983156983137
983117983137983150983137983143983141983154
983119983120983107983119983120983107
983119983120983107
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
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bull Communication and controller configuration for real timeapplication complete
bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration
bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies
bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study
bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales
bull Real time results are to be compared to the results gatheredon a simulation basis
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
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983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
Prof Brian Glennon
Dr Jessica Whelan
PAT-Bio Research Team
Enterprise Ireland
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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Classical Control PID Controller Tuning
Ziegler Nichols closed loop with relay identification technique
71
U K PID K =
T i =
T d
=
2
U P
8
U P
= 0010558
= 04
= 01
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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Control Strategy Development
Output
Setpoint
Process
ModelObjectiveFunction
Optimisation
Feed
Advanced Control MPC Controller
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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13
Control Strategy Development
Industrial MPC Formulation
sumsum =
minus++
=
+
∆∆
Λ∆+minusΓ minus+
M
i
ik ik
P
i
ik t ut u
t ut Rt y M k k 1
2
)1
2
1)()(()()((min
1
Subject to
maxmin
maxmin
uuu
y y y
∆le∆le∆
lele
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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Advanced Control MPC Tuning
4 Tuning parameters
P = Prediction horizon
M = Control horizon
Γ = Output weight matrix
Λ = Input weight matrix
Offline Tuning Rules
P = Increase until no further effect
M = 1 (gt1 leads to more aggressive control)
Γ = scale on control variables = 1
Λ = Increase to avoid aggressive CO
Tuning results
P = 10
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983155983145983149983157983148983137983156983145983151983150
983085 983120983113983108 983107983151983150983156983154983151983148
983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)
983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
983123983145983149983157983148983137983156983141
983122983141983137983148
983124983145983149983141
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bullSet-point Tracking
bullDisturbance Compensation
bullPropagation of Measurement Noise
Performance Off-Line Testing Criteria
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983120983113983108 983123983141983156983085983152983151983145983150983156 983123983156983141983152 983124983154983137983139983147983145983150983143
0
5
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n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
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0
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t e ( L h )
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0
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n t r a t i o n ( m M ) Cglc
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F e e d r a
t e ( L h )
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0
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PID Disturbance Compensation
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n t r a t i o n ( m M ) Cglc
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01
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F e e d - r a t e ( L h )
Controller Output
Disturbanceapplied
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MPC Disturbance Compensation
0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M
)
CglcSet-point
0
002
004
006
008
01
012
0 50 100 150 200 250 300Time (h)
F e e d r a
t e ( L h )
Controller Output
Disturbanceapplied
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t e ( L h )
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Fast lsquoon-offrsquo
Control
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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Removal oflsquoDrsquo term leadsto less abruptcontrol
Better set-point tracking
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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0
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F e e d - r a
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P = 10
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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0
5
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0 50 100 150 200 250 300
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C o n c
e n t r a t i o n ( m M
)
CglcSet-point
0001002003004005006007
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F e e d - r a t e ( L h )
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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0
5
10
15
20
25
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0 50 100 150 200 250 300
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C o n c
e n t r a t i o n ( m M )
CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
Controller Output
P = 40
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
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15
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C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
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005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h
Controller Output
P = 40
M = 1
Γ = 1
Λ = 10000
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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31
983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155
bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error
bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch
bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input
the control action in the presence of measurement noise canbe dampened to a more smooth control signal
bullSISOMIMO PID can only handle one input and one output
MPC is a multivariable control strategy
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150
983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148
983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)
983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
983123983145983149983157983148983137983156983141
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983124983145983149983141
983148
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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3 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152
983122 983148 983124983145 983107 983148983148 983105 983148983145 983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150
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983120983154983151983138983141
983123983152983141983139983156983154983137983148
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983155983151983142983156983159983137983154983141
983123983152983141983139983156983154983137983148
983142983145983148983141
983107983137983148983145983138983154983137983156983145983151983150
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
983141983150983143983145983150983141
983110983141983141983140 983120983157983149983152
983125983123983106983124983141983160983156 983142983145983148983141
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983110983145983148983141 983108983145983154983141983139983156983151983154983161
983124983141983160983156 983142983145983148983141
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15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150
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983120983154983151983138983141
983123983152983141983139983156983154983137983148
983137983139983153983157983145983155983145983156983145983151983150
983155983151983142983156983159983137983154983141
983123983152983141983139983156983154983137983148
983142983145983148983141
983107983137983148983145983138983154983137983156983145983151983150
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
983141983150983143983145983150983141
983105983106983106
98309600983160983137
983139983151983150983156983154983151983148
983155983161983155983156983141983149
983125983123983106 983124983107983120983113983120
983105983106983106 983160983120983105983124 983108983137983156983137
983117983137983150983137983143983141983154
983119983120983107983119983120983107
983119983120983107
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
bull Communication and controller configuration for real timeapplication complete
bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration
bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies
bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study
bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales
bull Real time results are to be compared to the results gatheredon a simulation basis
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
Prof Brian Glennon
Dr Jessica Whelan
PAT-Bio Research Team
Enterprise Ireland
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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Control Strategy Development
Output
Setpoint
Process
ModelObjectiveFunction
Optimisation
Feed
Advanced Control MPC Controller
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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13
Control Strategy Development
Industrial MPC Formulation
sumsum =
minus++
=
+
∆∆
Λ∆+minusΓ minus+
M
i
ik ik
P
i
ik t ut u
t ut Rt y M k k 1
2
)1
2
1)()(()()((min
1
Subject to
maxmin
maxmin
uuu
y y y
∆le∆le∆
lele
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156
Advanced Control MPC Tuning
4 Tuning parameters
P = Prediction horizon
M = Control horizon
Γ = Output weight matrix
Λ = Input weight matrix
Offline Tuning Rules
P = Increase until no further effect
M = 1 (gt1 leads to more aggressive control)
Γ = scale on control variables = 1
Λ = Increase to avoid aggressive CO
Tuning results
P = 10
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150
983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983155983145983149983157983148983137983156983145983151983150
983085 983120983113983108 983107983151983150983156983154983151983148
983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)
983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
983123983145983149983157983148983137983156983141
983122983141983137983148
983124983145983149983141
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bullSet-point Tracking
bullDisturbance Compensation
bullPropagation of Measurement Noise
Performance Off-Line Testing Criteria
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983120983113983108 983123983141983156983085983152983151983145983150983156 983123983156983141983152 983124983154983137983139983147983145983150983143
0
5
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0 50 100 150 200 250 300
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C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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0
5
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C o n c e n t r a t i o n ( m M )
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0
001
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005
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F e e d - r a
t e ( L h )
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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0
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n t r a t i o n ( m M ) Cglc
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F e e d r a
t e ( L h )
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0
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Set-point
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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PID Disturbance Compensation
0
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n t r a t i o n ( m M ) Cglc
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0
002
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006
008
01
012
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Controller Output
Disturbanceapplied
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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MPC Disturbance Compensation
0
510
15
20
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)
CglcSet-point
0
002
004
006
008
01
012
0 50 100 150 200 250 300Time (h)
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t e ( L h )
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Disturbanceapplied
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Fast lsquoon-offrsquo
Control
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006007
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h )
Controller Output
Removal oflsquoDrsquo term leadsto less abruptcontrol
Better set-point tracking
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
P = 10
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c
e n t r a t i o n ( m M
)
CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c
e n t r a t i o n ( m M )
CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
Controller Output
P = 40
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h
Controller Output
P = 40
M = 1
Γ = 1
Λ = 10000
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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31
983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155
bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error
bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch
bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input
the control action in the presence of measurement noise canbe dampened to a more smooth control signal
bullSISOMIMO PID can only handle one input and one output
MPC is a multivariable control strategy
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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32
983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150
983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148
983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)
983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
983123983145983149983157983148983137983156983141
983122983141983137983148
983124983145983149983141
983148
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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33
3 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152
983122 983148 983124983145 983107 983148983148 983105 983148983145 983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983120983154983151983138983141
983123983152983141983139983156983154983137983148
983137983139983153983157983145983155983145983156983145983151983150
983155983151983142983156983159983137983154983141
983123983152983141983139983156983154983137983148
983142983145983148983141
983107983137983148983145983138983154983137983156983145983151983150
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
983141983150983143983145983150983141
983110983141983141983140 983120983157983149983152
983125983123983106983124983141983160983156 983142983145983148983141
983154983141983137983140983159983154983145983156983141
983110983145983148983141 983108983145983154983141983139983156983151983154983161
983124983141983160983156 983142983145983148983141
983154983141983137983140983159983154983145983156983141
983124983141983160983156 983142983145983148983141
983154983141983137983140983159983154983145983156983141
983123983141983154983145983137983148
15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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15 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152
983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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36
983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150
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983120983154983151983138983141
983123983152983141983139983156983154983137983148
983137983139983153983157983145983155983145983156983145983151983150
983155983151983142983156983159983137983154983141
983123983152983141983139983156983154983137983148
983142983145983148983141
983107983137983148983145983138983154983137983156983145983151983150
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
983141983150983143983145983150983141
983105983106983106
98309600983160983137
983139983151983150983156983154983151983148
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983125983123983106 983124983107983120983113983120
983105983106983106 983160983120983105983124 983108983137983156983137
983117983137983150983137983143983141983154
983119983120983107983119983120983107
983119983120983107
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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37
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
bull Communication and controller configuration for real timeapplication complete
bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration
bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies
bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study
bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales
bull Real time results are to be compared to the results gatheredon a simulation basis
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
Prof Brian Glennon
Dr Jessica Whelan
PAT-Bio Research Team
Enterprise Ireland
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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13
Control Strategy Development
Industrial MPC Formulation
sumsum =
minus++
=
+
∆∆
Λ∆+minusΓ minus+
M
i
ik ik
P
i
ik t ut u
t ut Rt y M k k 1
2
)1
2
1)()(()()((min
1
Subject to
maxmin
maxmin
uuu
y y y
∆le∆le∆
lele
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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14
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Advanced Control MPC Tuning
4 Tuning parameters
P = Prediction horizon
M = Control horizon
Γ = Output weight matrix
Λ = Input weight matrix
Offline Tuning Rules
P = Increase until no further effect
M = 1 (gt1 leads to more aggressive control)
Γ = scale on control variables = 1
Λ = Increase to avoid aggressive CO
Tuning results
P = 10
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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15
983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150
983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983155983145983149983157983148983137983156983145983151983150
983085 983120983113983108 983107983151983150983156983154983151983148
983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)
983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
983123983145983149983157983148983137983156983141
983122983141983137983148
983124983145983149983141
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983107983151983150983156983154983151983148983148983141983154 983120983141983154983142983151983154983149983137983150983139983141 983123983145983149983157983148983137983156983145983151983150 983122983141983155983157983148983156983155
bullSet-point Tracking
bullDisturbance Compensation
bullPropagation of Measurement Noise
Performance Off-Line Testing Criteria
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983120983113983108 983123983141983156983085983152983151983145983150983156 983123983156983141983152 983124983154983137983139983147983145983150983143
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983120983113983108 983123983141983156983085983152983151983145983150983156 983123983156983141983152 983124983154983137983139983147983145983150983143
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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19
983117983120983107 983123983141983156983085983152983151983145983150983156 983123983156983141983152 983124983154983137983139983147983145983150983143
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
0 50 100 150 200 250 300Time (h)
F e e d r a
t e ( L h )
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983117983120983107 983123983141983156983085983152983151983145983150983156 983123983156983141983152 983124983154983137983139983147983145983150983143
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
0 50 100 150 200 250 300Time (h)
F e e d r a
t e ( L h )
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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21
PID Disturbance Compensation
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M ) Cglc
Set-point
0
002
004
006
008
01
012
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h )
Controller Output
Disturbanceapplied
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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22
MPC Disturbance Compensation
0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M
)
CglcSet-point
0
002
004
006
008
01
012
0 50 100 150 200 250 300Time (h)
F e e d r a
t e ( L h )
Controller Output
Disturbanceapplied
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983120983113983108 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
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C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
Fast lsquoon-offrsquo
Control
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983120983113 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c
e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006007
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h )
Controller Output
Removal oflsquoDrsquo term leadsto less abruptcontrol
Better set-point tracking
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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510
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0
001
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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0001002003004005006007
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Time (h)
F e e d - r a t e ( L h )
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P = 40
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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C o n c e
n t r a t i o n ( m M )
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0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h
Controller Output
P = 40
M = 1
Γ = 1
Λ = 10000
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155
bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error
bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch
bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input
the control action in the presence of measurement noise canbe dampened to a more smooth control signal
bullSISOMIMO PID can only handle one input and one output
MPC is a multivariable control strategy
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148
983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)
983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
983123983145983149983157983148983137983156983141
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983124983145983149983141
983148
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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3 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152
983122 983148 983124983145 983107 983148983148 983105 983148983145 983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983142983145983148983141
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983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
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983154983141983137983148983085983156983145983149983141
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983110983141983141983140 983120983157983149983152
983125983123983106983124983141983160983156 983142983145983148983141
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15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
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983105983106983106
98309600983160983137
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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bull Communication and controller configuration for real timeapplication complete
bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration
bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies
bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study
bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales
bull Real time results are to be compared to the results gatheredon a simulation basis
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
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983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
Prof Brian Glennon
Dr Jessica Whelan
PAT-Bio Research Team
Enterprise Ireland
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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Advanced Control MPC Tuning
4 Tuning parameters
P = Prediction horizon
M = Control horizon
Γ = Output weight matrix
Λ = Input weight matrix
Offline Tuning Rules
P = Increase until no further effect
M = 1 (gt1 leads to more aggressive control)
Γ = scale on control variables = 1
Λ = Increase to avoid aggressive CO
Tuning results
P = 10
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983155983145983149983157983148983137983156983145983151983150
983085 983120983113983108 983107983151983150983156983154983151983148
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983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
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bullSet-point Tracking
bullDisturbance Compensation
bullPropagation of Measurement Noise
Performance Off-Line Testing Criteria
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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PID Disturbance Compensation
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Disturbanceapplied
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MPC Disturbance Compensation
0
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Fast lsquoon-offrsquo
Control
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Removal oflsquoDrsquo term leadsto less abruptcontrol
Better set-point tracking
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M = 1
Γ = 1
Λ = 0
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
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P = 40
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
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0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h
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P = 40
M = 1
Γ = 1
Λ = 10000
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155
bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error
bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch
bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input
the control action in the presence of measurement noise canbe dampened to a more smooth control signal
bullSISOMIMO PID can only handle one input and one output
MPC is a multivariable control strategy
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150
983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148
983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)
983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
983123983145983149983157983148983137983156983141
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983148
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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3 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152
983122 983148 983124983145 983107 983148983148 983105 983148983145 983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
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983154983141983137983148983085983156983145983149983141
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983110983141983141983140 983120983157983149983152
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15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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98309600983160983137
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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bull Communication and controller configuration for real timeapplication complete
bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration
bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies
bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study
bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales
bull Real time results are to be compared to the results gatheredon a simulation basis
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
Prof Brian Glennon
Dr Jessica Whelan
PAT-Bio Research Team
Enterprise Ireland
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983155983145983149983157983148983137983156983145983151983150
983085 983120983113983108 983107983151983150983156983154983151983148
983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)
983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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bullSet-point Tracking
bullDisturbance Compensation
bullPropagation of Measurement Noise
Performance Off-Line Testing Criteria
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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PID Disturbance Compensation
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Disturbanceapplied
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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MPC Disturbance Compensation
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Fast lsquoon-offrsquo
Control
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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Removal oflsquoDrsquo term leadsto less abruptcontrol
Better set-point tracking
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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P = 10
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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F e e d - r a t e ( L h )
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P = 40
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
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n t r a t i o n ( m M )
CglcSet-point
0
001
002
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007
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h
Controller Output
P = 40
M = 1
Γ = 1
Λ = 10000
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155
bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error
bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch
bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input
the control action in the presence of measurement noise canbe dampened to a more smooth control signal
bullSISOMIMO PID can only handle one input and one output
MPC is a multivariable control strategy
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148
983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)
983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
983123983145983149983157983148983137983156983141
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983148
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983122 983148 983124983145 983107 983148983148 983105 983148983145 983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983107983137983148983145983138983154983137983156983145983151983150
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
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983110983141983141983140 983120983157983149983152
983125983123983106983124983141983160983156 983142983145983148983141
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983110983145983148983141 983108983145983154983141983139983156983151983154983161
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15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
983141983150983143983145983150983141
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98309600983160983137
983139983151983150983156983154983151983148
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983119983120983107983119983120983107
983119983120983107
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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bull Communication and controller configuration for real timeapplication complete
bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration
bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies
bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study
bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales
bull Real time results are to be compared to the results gatheredon a simulation basis
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
Prof Brian Glennon
Dr Jessica Whelan
PAT-Bio Research Team
Enterprise Ireland
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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bullSet-point Tracking
bullDisturbance Compensation
bullPropagation of Measurement Noise
Performance Off-Line Testing Criteria
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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PID Disturbance Compensation
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Disturbanceapplied
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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MPC Disturbance Compensation
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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Fast lsquoon-offrsquo
Control
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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Removal oflsquoDrsquo term leadsto less abruptcontrol
Better set-point tracking
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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0001002003004005006007
0 50 100 150 200 250 300
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F e e d - r a t e ( L h )
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
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P = 40
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
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P = 40
M = 1
Γ = 1
Λ = 10000
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error
bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch
bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input
the control action in the presence of measurement noise canbe dampened to a more smooth control signal
bullSISOMIMO PID can only handle one input and one output
MPC is a multivariable control strategy
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150
983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148
983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)
983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
983123983145983149983157983148983137983156983141
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983124983145983149983141
983148
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983122 983148 983124983145 983107 983148983148 983105 983148983145 983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
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983110983141983141983140 983120983157983149983152
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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bull Communication and controller configuration for real timeapplication complete
bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration
bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies
bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study
bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales
bull Real time results are to be compared to the results gatheredon a simulation basis
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
Prof Brian Glennon
Dr Jessica Whelan
PAT-Bio Research Team
Enterprise Ireland
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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PID Disturbance Compensation
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MPC Disturbance Compensation
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Fast lsquoon-offrsquo
Control
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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Removal oflsquoDrsquo term leadsto less abruptcontrol
Better set-point tracking
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Γ = 1
Λ = 0
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M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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P = 40
M = 1
Γ = 1
Λ = 10000
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error
bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch
bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input
the control action in the presence of measurement noise canbe dampened to a more smooth control signal
bullSISOMIMO PID can only handle one input and one output
MPC is a multivariable control strategy
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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amp 983124983157983150983141
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
983141983150983143983145983150983141
983105983106983106
98309600983160983137
983139983151983150983156983154983151983148
983155983161983155983156983141983149
983125983123983106 983124983107983120983113983120
983105983106983106 983160983120983105983124 983108983137983156983137
983117983137983150983137983143983141983154
983119983120983107983119983120983107
983119983120983107
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3739
37
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
bull Communication and controller configuration for real timeapplication complete
bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration
bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3839
38
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies
bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study
bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales
bull Real time results are to be compared to the results gatheredon a simulation basis
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3939
39
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
Prof Brian Glennon
Dr Jessica Whelan
PAT-Bio Research Team
Enterprise Ireland
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 1839
18
983120983113983108 983123983141983156983085983152983151983145983150983156 983123983156983141983152 983124983154983137983139983147983145983150983143
0
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983117983120983107 983123983141983156983085983152983151983145983150983156 983123983156983141983152 983124983154983137983139983147983145983150983143
0
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983117983120983107 983123983141983156983085983152983151983145983150983156 983123983156983141983152 983124983154983137983139983147983145983150983143
0
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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21
PID Disturbance Compensation
0
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n t r a t i o n ( m M ) Cglc
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Disturbanceapplied
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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MPC Disturbance Compensation
0
510
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)
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0
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0 50 100 150 200 250 300Time (h)
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t e ( L h )
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Disturbanceapplied
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983120983113983108 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
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0 50 100 150 200 250 300
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n t r a t i o n ( m M )
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0
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F e e d - r a
t e ( L h )
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Fast lsquoon-offrsquo
Control
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2439
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983120983113 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
510
15
20
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30
0 50 100 150 200 250 300Time (h)
C o n c
e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006007
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h )
Controller Output
Removal oflsquoDrsquo term leadsto less abruptcontrol
Better set-point tracking
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2539
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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
510
15
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0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M ) Cglc
Set-point
0
001
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F e e d - r a
t e ( L h )
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2639
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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
510
15
20
25
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0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
P = 10
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2739
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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
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0 50 100 150 200 250 300
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C o n c
e n t r a t i o n ( m M
)
CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2839
28
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
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30
0 50 100 150 200 250 300
Time (h)
C o n c
e n t r a t i o n ( m M )
CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
Controller Output
P = 40
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2939
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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
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0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
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005
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007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3039
30
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h
Controller Output
P = 40
M = 1
Γ = 1
Λ = 10000
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3139
31
983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155
bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error
bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch
bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input
the control action in the presence of measurement noise canbe dampened to a more smooth control signal
bullSISOMIMO PID can only handle one input and one output
MPC is a multivariable control strategy
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3239
32
983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150
983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148
983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)
983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
983123983145983149983157983148983137983156983141
983122983141983137983148
983124983145983149983141
983148
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3339
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3 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152
983122 983148 983124983145 983107 983148983148 983105 983148983145 983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3439
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983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150
983122983137983149983137983150
983120983154983151983138983141
983123983152983141983139983156983154983137983148
983137983139983153983157983145983155983145983156983145983151983150
983155983151983142983156983159983137983154983141
983123983152983141983139983156983154983137983148
983142983145983148983141
983107983137983148983145983138983154983137983156983145983151983150
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
983141983150983143983145983150983141
983110983141983141983140 983120983157983149983152
983125983123983106983124983141983160983156 983142983145983148983141
983154983141983137983140983159983154983145983156983141
983110983145983148983141 983108983145983154983141983139983156983151983154983161
983124983141983160983156 983142983145983148983141
983154983141983137983140983159983154983145983156983141
983124983141983160983156 983142983145983148983141
983154983141983137983140983159983154983145983156983141
983123983141983154983145983137983148
15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3539
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15 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152
983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3639
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983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150
983122983137983149983137983150
983120983154983151983138983141
983123983152983141983139983156983154983137983148
983137983139983153983157983145983155983145983156983145983151983150
983155983151983142983156983159983137983154983141
983123983152983141983139983156983154983137983148
983142983145983148983141
983107983137983148983145983138983154983137983156983145983151983150
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
983141983150983143983145983150983141
983105983106983106
98309600983160983137
983139983151983150983156983154983151983148
983155983161983155983156983141983149
983125983123983106 983124983107983120983113983120
983105983106983106 983160983120983105983124 983108983137983156983137
983117983137983150983137983143983141983154
983119983120983107983119983120983107
983119983120983107
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3739
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983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
bull Communication and controller configuration for real timeapplication complete
bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration
bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3839
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983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies
bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study
bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales
bull Real time results are to be compared to the results gatheredon a simulation basis
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
Prof Brian Glennon
Dr Jessica Whelan
PAT-Bio Research Team
Enterprise Ireland
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 1939
19
983117983120983107 983123983141983156983085983152983151983145983150983156 983123983156983141983152 983124983154983137983139983147983145983150983143
0
5
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0 50 100 150 200 250 300
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C o n c e
n t r a t i o n ( m M ) Cglc
Set-point
0
001
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003
004
005
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0 50 100 150 200 250 300Time (h)
F e e d r a
t e ( L h )
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983117983120983107 983123983141983156983085983152983151983145983150983156 983123983156983141983152 983124983154983137983139983147983145983150983143
0
5
10
15
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0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M ) Cglc
Set-point
0
001
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004
005
006
0 50 100 150 200 250 300Time (h)
F e e d r a
t e ( L h )
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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PID Disturbance Compensation
0
5
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25
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0 50 100 150 200 250 300
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C o n c e
n t r a t i o n ( m M ) Cglc
Set-point
0
002
004
006
008
01
012
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h )
Controller Output
Disturbanceapplied
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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MPC Disturbance Compensation
0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M
)
CglcSet-point
0
002
004
006
008
01
012
0 50 100 150 200 250 300Time (h)
F e e d r a
t e ( L h )
Controller Output
Disturbanceapplied
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2339
23
983120983113983108 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
Fast lsquoon-offrsquo
Control
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2439
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983120983113 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c
e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006007
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h )
Controller Output
Removal oflsquoDrsquo term leadsto less abruptcontrol
Better set-point tracking
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2539
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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2639
26
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
P = 10
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2739
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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c
e n t r a t i o n ( m M
)
CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2839
28
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c
e n t r a t i o n ( m M )
CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
Controller Output
P = 40
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2939
29
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3039
30
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h
Controller Output
P = 40
M = 1
Γ = 1
Λ = 10000
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3139
31
983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155
bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error
bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch
bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input
the control action in the presence of measurement noise canbe dampened to a more smooth control signal
bullSISOMIMO PID can only handle one input and one output
MPC is a multivariable control strategy
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3239
32
983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150
983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148
983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)
983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
983123983145983149983157983148983137983156983141
983122983141983137983148
983124983145983149983141
983148
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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33
3 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152
983122 983148 983124983145 983107 983148983148 983105 983148983145 983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3439
34
983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150
983122983137983149983137983150
983120983154983151983138983141
983123983152983141983139983156983154983137983148
983137983139983153983157983145983155983145983156983145983151983150
983155983151983142983156983159983137983154983141
983123983152983141983139983156983154983137983148
983142983145983148983141
983107983137983148983145983138983154983137983156983145983151983150
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
983141983150983143983145983150983141
983110983141983141983140 983120983157983149983152
983125983123983106983124983141983160983156 983142983145983148983141
983154983141983137983140983159983154983145983156983141
983110983145983148983141 983108983145983154983141983139983156983151983154983161
983124983141983160983156 983142983145983148983141
983154983141983137983140983159983154983145983156983141
983124983141983160983156 983142983145983148983141
983154983141983137983140983159983154983145983156983141
983123983141983154983145983137983148
15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3539
35
15 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152
983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3639
36
983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150
983122983137983149983137983150
983120983154983151983138983141
983123983152983141983139983156983154983137983148
983137983139983153983157983145983155983145983156983145983151983150
983155983151983142983156983159983137983154983141
983123983152983141983139983156983154983137983148
983142983145983148983141
983107983137983148983145983138983154983137983156983145983151983150
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
983141983150983143983145983150983141
983105983106983106
98309600983160983137
983139983151983150983156983154983151983148
983155983161983155983156983141983149
983125983123983106 983124983107983120983113983120
983105983106983106 983160983120983105983124 983108983137983156983137
983117983137983150983137983143983141983154
983119983120983107983119983120983107
983119983120983107
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
bull Communication and controller configuration for real timeapplication complete
bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration
bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies
bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study
bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales
bull Real time results are to be compared to the results gatheredon a simulation basis
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
Prof Brian Glennon
Dr Jessica Whelan
PAT-Bio Research Team
Enterprise Ireland
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2039
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983117983120983107 983123983141983156983085983152983151983145983150983156 983123983156983141983152 983124983154983137983139983147983145983150983143
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
0 50 100 150 200 250 300Time (h)
F e e d r a
t e ( L h )
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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21
PID Disturbance Compensation
0
5
10
15
20
25
30
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Time (h)
C o n c e
n t r a t i o n ( m M ) Cglc
Set-point
0
002
004
006
008
01
012
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h )
Controller Output
Disturbanceapplied
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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22
MPC Disturbance Compensation
0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M
)
CglcSet-point
0
002
004
006
008
01
012
0 50 100 150 200 250 300Time (h)
F e e d r a
t e ( L h )
Controller Output
Disturbanceapplied
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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23
983120983113983108 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
Fast lsquoon-offrsquo
Control
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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24
983120983113 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c
e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006007
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h )
Controller Output
Removal oflsquoDrsquo term leadsto less abruptcontrol
Better set-point tracking
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2539
25
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
P = 10
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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27
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c
e n t r a t i o n ( m M
)
CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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28
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c
e n t r a t i o n ( m M )
CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
Controller Output
P = 40
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2939
29
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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30
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h
Controller Output
P = 40
M = 1
Γ = 1
Λ = 10000
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3139
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983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155
bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error
bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch
bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input
the control action in the presence of measurement noise canbe dampened to a more smooth control signal
bullSISOMIMO PID can only handle one input and one output
MPC is a multivariable control strategy
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3239
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983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150
983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148
983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)
983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
983123983145983149983157983148983137983156983141
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983148
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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3 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152
983122 983148 983124983145 983107 983148983148 983105 983148983145 983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983123983152983141983139983156983154983137983148
983137983139983153983157983145983155983145983156983145983151983150
983155983151983142983156983159983137983154983141
983123983152983141983139983156983154983137983148
983142983145983148983141
983107983137983148983145983138983154983137983156983145983151983150
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
983141983150983143983145983150983141
983110983141983141983140 983120983157983149983152
983125983123983106983124983141983160983156 983142983145983148983141
983154983141983137983140983159983154983145983156983141
983110983145983148983141 983108983145983154983141983139983156983151983154983161
983124983141983160983156 983142983145983148983141
983154983141983137983140983159983154983145983156983141
983124983141983160983156 983142983145983148983141
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983123983141983154983145983137983148
15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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15 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152
983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150
983122983137983149983137983150
983120983154983151983138983141
983123983152983141983139983156983154983137983148
983137983139983153983157983145983155983145983156983145983151983150
983155983151983142983156983159983137983154983141
983123983152983141983139983156983154983137983148
983142983145983148983141
983107983137983148983145983138983154983137983156983145983151983150
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
983141983150983143983145983150983141
983105983106983106
98309600983160983137
983139983151983150983156983154983151983148
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983125983123983106 983124983107983120983113983120
983105983106983106 983160983120983105983124 983108983137983156983137
983117983137983150983137983143983141983154
983119983120983107983119983120983107
983119983120983107
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
bull Communication and controller configuration for real timeapplication complete
bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration
bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies
bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study
bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales
bull Real time results are to be compared to the results gatheredon a simulation basis
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
Prof Brian Glennon
Dr Jessica Whelan
PAT-Bio Research Team
Enterprise Ireland
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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PID Disturbance Compensation
0
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Disturbanceapplied
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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MPC Disturbance Compensation
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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t e ( L h )
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Fast lsquoon-offrsquo
Control
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983120983113 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
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e n t r a t i o n ( m M ) Cglc
Set-point
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006007
0 50 100 150 200 250 300Time (h)
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Removal oflsquoDrsquo term leadsto less abruptcontrol
Better set-point tracking
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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0
510
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F e e d - r a
t e ( L h )
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P = 10
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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0
5
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0 50 100 150 200 250 300
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C o n c
e n t r a t i o n ( m M
)
CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
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0 50 100 150 200 250 300
Time (h)
C o n c
e n t r a t i o n ( m M )
CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
Controller Output
P = 40
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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C o n c e
n t r a t i o n ( m M )
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0
001
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007
0 50 100 150 200 250 300Time (h)
F e e d - r a
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Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
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0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
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005
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007
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h
Controller Output
P = 40
M = 1
Γ = 1
Λ = 10000
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3139
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983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155
bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error
bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch
bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input
the control action in the presence of measurement noise canbe dampened to a more smooth control signal
bullSISOMIMO PID can only handle one input and one output
MPC is a multivariable control strategy
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3239
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983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150
983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148
983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)
983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
983123983145983149983157983148983137983156983141
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983148
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983155983151983142983156983159983137983154983141
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983142983145983148983141
983107983137983148983145983138983154983137983156983145983151983150
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
983141983150983143983145983150983141
983110983141983141983140 983120983157983149983152
983125983123983106983124983141983160983156 983142983145983148983141
983154983141983137983140983159983154983145983156983141
983110983145983148983141 983108983145983154983141983139983156983151983154983161
983124983141983160983156 983142983145983148983141
983154983141983137983140983159983154983145983156983141
983124983141983160983156 983142983145983148983141
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15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983120983154983151983138983141
983123983152983141983139983156983154983137983148
983137983139983153983157983145983155983145983156983145983151983150
983155983151983142983156983159983137983154983141
983123983152983141983139983156983154983137983148
983142983145983148983141
983107983137983148983145983138983154983137983156983145983151983150
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
983141983150983143983145983150983141
983105983106983106
98309600983160983137
983139983151983150983156983154983151983148
983155983161983155983156983141983149
983125983123983106 983124983107983120983113983120
983105983106983106 983160983120983105983124 983108983137983156983137
983117983137983150983137983143983141983154
983119983120983107983119983120983107
983119983120983107
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3739
37
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
bull Communication and controller configuration for real timeapplication complete
bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration
bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3839
38
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies
bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study
bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales
bull Real time results are to be compared to the results gatheredon a simulation basis
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3939
39
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
Prof Brian Glennon
Dr Jessica Whelan
PAT-Bio Research Team
Enterprise Ireland
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2239
22
MPC Disturbance Compensation
0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M
)
CglcSet-point
0
002
004
006
008
01
012
0 50 100 150 200 250 300Time (h)
F e e d r a
t e ( L h )
Controller Output
Disturbanceapplied
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2339
23
983120983113983108 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
Fast lsquoon-offrsquo
Control
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2439
24
983120983113 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c
e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006007
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h )
Controller Output
Removal oflsquoDrsquo term leadsto less abruptcontrol
Better set-point tracking
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2539
25
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2639
26
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
P = 10
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2739
27
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c
e n t r a t i o n ( m M
)
CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2839
28
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c
e n t r a t i o n ( m M )
CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
Controller Output
P = 40
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2939
29
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3039
30
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h
Controller Output
P = 40
M = 1
Γ = 1
Λ = 10000
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3139
31
983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155
bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error
bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch
bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input
the control action in the presence of measurement noise canbe dampened to a more smooth control signal
bullSISOMIMO PID can only handle one input and one output
MPC is a multivariable control strategy
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3239
32
983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150
983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148
983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)
983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
983123983145983149983157983148983137983156983141
983122983141983137983148
983124983145983149983141
983148
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3339
33
3 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152
983122 983148 983124983145 983107 983148983148 983105 983148983145 983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3439
34
983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150
983122983137983149983137983150
983120983154983151983138983141
983123983152983141983139983156983154983137983148
983137983139983153983157983145983155983145983156983145983151983150
983155983151983142983156983159983137983154983141
983123983152983141983139983156983154983137983148
983142983145983148983141
983107983137983148983145983138983154983137983156983145983151983150
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
983141983150983143983145983150983141
983110983141983141983140 983120983157983149983152
983125983123983106983124983141983160983156 983142983145983148983141
983154983141983137983140983159983154983145983156983141
983110983145983148983141 983108983145983154983141983139983156983151983154983161
983124983141983160983156 983142983145983148983141
983154983141983137983140983159983154983145983156983141
983124983141983160983156 983142983145983148983141
983154983141983137983140983159983154983145983156983141
983123983141983154983145983137983148
15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3539
35
15 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152
983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3639
36
983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150
983122983137983149983137983150
983120983154983151983138983141
983123983152983141983139983156983154983137983148
983137983139983153983157983145983155983145983156983145983151983150
983155983151983142983156983159983137983154983141
983123983152983141983139983156983154983137983148
983142983145983148983141
983107983137983148983145983138983154983137983156983145983151983150
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
983141983150983143983145983150983141
983105983106983106
98309600983160983137
983139983151983150983156983154983151983148
983155983161983155983156983141983149
983125983123983106 983124983107983120983113983120
983105983106983106 983160983120983105983124 983108983137983156983137
983117983137983150983137983143983141983154
983119983120983107983119983120983107
983119983120983107
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3739
37
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
bull Communication and controller configuration for real timeapplication complete
bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration
bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3839
38
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies
bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study
bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales
bull Real time results are to be compared to the results gatheredon a simulation basis
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3939
39
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
Prof Brian Glennon
Dr Jessica Whelan
PAT-Bio Research Team
Enterprise Ireland
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2339
23
983120983113983108 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
Fast lsquoon-offrsquo
Control
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2439
24
983120983113 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c
e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006007
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h )
Controller Output
Removal oflsquoDrsquo term leadsto less abruptcontrol
Better set-point tracking
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2539
25
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2639
26
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
P = 10
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2739
27
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c
e n t r a t i o n ( m M
)
CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2839
28
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c
e n t r a t i o n ( m M )
CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
Controller Output
P = 40
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
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0 50 100 150 200 250 300
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C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
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004
005
006
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0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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30
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h
Controller Output
P = 40
M = 1
Γ = 1
Λ = 10000
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3139
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983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155
bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error
bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch
bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input
the control action in the presence of measurement noise canbe dampened to a more smooth control signal
bullSISOMIMO PID can only handle one input and one output
MPC is a multivariable control strategy
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3239
32
983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150
983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148
983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)
983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
983123983145983149983157983148983137983156983141
983122983141983137983148
983124983145983149983141
983148
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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3 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152
983122 983148 983124983145 983107 983148983148 983105 983148983145 983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150
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983120983154983151983138983141
983123983152983141983139983156983154983137983148
983137983139983153983157983145983155983145983156983145983151983150
983155983151983142983156983159983137983154983141
983123983152983141983139983156983154983137983148
983142983145983148983141
983107983137983148983145983138983154983137983156983145983151983150
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
983141983150983143983145983150983141
983110983141983141983140 983120983157983149983152
983125983123983106983124983141983160983156 983142983145983148983141
983154983141983137983140983159983154983145983156983141
983110983145983148983141 983108983145983154983141983139983156983151983154983161
983124983141983160983156 983142983145983148983141
983154983141983137983140983159983154983145983156983141
983124983141983160983156 983142983145983148983141
983154983141983137983140983159983154983145983156983141
983123983141983154983145983137983148
15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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15 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152
983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150
983122983137983149983137983150
983120983154983151983138983141
983123983152983141983139983156983154983137983148
983137983139983153983157983145983155983145983156983145983151983150
983155983151983142983156983159983137983154983141
983123983152983141983139983156983154983137983148
983142983145983148983141
983107983137983148983145983138983154983137983156983145983151983150
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
983141983150983143983145983150983141
983105983106983106
98309600983160983137
983139983151983150983156983154983151983148
983155983161983155983156983141983149
983125983123983106 983124983107983120983113983120
983105983106983106 983160983120983105983124 983108983137983156983137
983117983137983150983137983143983141983154
983119983120983107983119983120983107
983119983120983107
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
bull Communication and controller configuration for real timeapplication complete
bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration
bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies
bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study
bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales
bull Real time results are to be compared to the results gatheredon a simulation basis
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
Prof Brian Glennon
Dr Jessica Whelan
PAT-Bio Research Team
Enterprise Ireland
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2439
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983120983113 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
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Set-point
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Controller Output
Removal oflsquoDrsquo term leadsto less abruptcontrol
Better set-point tracking
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
510
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t e ( L h )
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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0
510
15
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0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M ) Cglc
Set-point
0
001
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003
004
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0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
P = 10
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
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C o n c
e n t r a t i o n ( m M
)
CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c
e n t r a t i o n ( m M )
CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
Controller Output
P = 40
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
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0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
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003
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005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h
Controller Output
P = 40
M = 1
Γ = 1
Λ = 10000
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3139
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983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155
bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error
bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch
bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input
the control action in the presence of measurement noise canbe dampened to a more smooth control signal
bullSISOMIMO PID can only handle one input and one output
MPC is a multivariable control strategy
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3239
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983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150
983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148
983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)
983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
983123983145983149983157983148983137983156983141
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983124983145983149983141
983148
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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3 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152
983122 983148 983124983145 983107 983148983148 983105 983148983145 983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983155983151983142983156983159983137983154983141
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983142983145983148983141
983107983137983148983145983138983154983137983156983145983151983150
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
983141983150983143983145983150983141
983110983141983141983140 983120983157983149983152
983125983123983106983124983141983160983156 983142983145983148983141
983154983141983137983140983159983154983145983156983141
983110983145983148983141 983108983145983154983141983139983156983151983154983161
983124983141983160983156 983142983145983148983141
983154983141983137983140983159983154983145983156983141
983124983141983160983156 983142983145983148983141
983154983141983137983140983159983154983145983156983141
983123983141983154983145983137983148
15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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15 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152
983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
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983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150
983122983137983149983137983150
983120983154983151983138983141
983123983152983141983139983156983154983137983148
983137983139983153983157983145983155983145983156983145983151983150
983155983151983142983156983159983137983154983141
983123983152983141983139983156983154983137983148
983142983145983148983141
983107983137983148983145983138983154983137983156983145983151983150
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
983141983150983143983145983150983141
983105983106983106
98309600983160983137
983139983151983150983156983154983151983148
983155983161983155983156983141983149
983125983123983106 983124983107983120983113983120
983105983106983106 983160983120983105983124 983108983137983156983137
983117983137983150983137983143983141983154
983119983120983107983119983120983107
983119983120983107
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3739
37
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
bull Communication and controller configuration for real timeapplication complete
bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration
bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3839
38
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies
bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study
bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales
bull Real time results are to be compared to the results gatheredon a simulation basis
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3939
39
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
Prof Brian Glennon
Dr Jessica Whelan
PAT-Bio Research Team
Enterprise Ireland
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2539
25
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2639
26
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
P = 10
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2739
27
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c
e n t r a t i o n ( m M
)
CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2839
28
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c
e n t r a t i o n ( m M )
CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
Controller Output
P = 40
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2939
29
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3039
30
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h
Controller Output
P = 40
M = 1
Γ = 1
Λ = 10000
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3139
31
983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155
bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error
bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch
bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input
the control action in the presence of measurement noise canbe dampened to a more smooth control signal
bullSISOMIMO PID can only handle one input and one output
MPC is a multivariable control strategy
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3239
32
983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150
983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148
983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)
983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
983123983145983149983157983148983137983156983141
983122983141983137983148
983124983145983149983141
983148
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3339
33
3 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152
983122 983148 983124983145 983107 983148983148 983105 983148983145 983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3439
34
983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150
983122983137983149983137983150
983120983154983151983138983141
983123983152983141983139983156983154983137983148
983137983139983153983157983145983155983145983156983145983151983150
983155983151983142983156983159983137983154983141
983123983152983141983139983156983154983137983148
983142983145983148983141
983107983137983148983145983138983154983137983156983145983151983150
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
983141983150983143983145983150983141
983110983141983141983140 983120983157983149983152
983125983123983106983124983141983160983156 983142983145983148983141
983154983141983137983140983159983154983145983156983141
983110983145983148983141 983108983145983154983141983139983156983151983154983161
983124983141983160983156 983142983145983148983141
983154983141983137983140983159983154983145983156983141
983124983141983160983156 983142983145983148983141
983154983141983137983140983159983154983145983156983141
983123983141983154983145983137983148
15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3539
35
15 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152
983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3639
36
983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150
983122983137983149983137983150
983120983154983151983138983141
983123983152983141983139983156983154983137983148
983137983139983153983157983145983155983145983156983145983151983150
983155983151983142983156983159983137983154983141
983123983152983141983139983156983154983137983148
983142983145983148983141
983107983137983148983145983138983154983137983156983145983151983150
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
983141983150983143983145983150983141
983105983106983106
98309600983160983137
983139983151983150983156983154983151983148
983155983161983155983156983141983149
983125983123983106 983124983107983120983113983120
983105983106983106 983160983120983105983124 983108983137983156983137
983117983137983150983137983143983141983154
983119983120983107983119983120983107
983119983120983107
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3739
37
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
bull Communication and controller configuration for real timeapplication complete
bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration
bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3839
38
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies
bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study
bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales
bull Real time results are to be compared to the results gatheredon a simulation basis
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3939
39
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
Prof Brian Glennon
Dr Jessica Whelan
PAT-Bio Research Team
Enterprise Ireland
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2639
26
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
510
15
20
25
30
0 50 100 150 200 250 300Time (h)
C o n c e n t r a t i o n ( m M ) Cglc
Set-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h )
Controller Output
P = 10
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2739
27
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c
e n t r a t i o n ( m M
)
CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2839
28
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c
e n t r a t i o n ( m M )
CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
Controller Output
P = 40
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2939
29
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3039
30
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h
Controller Output
P = 40
M = 1
Γ = 1
Λ = 10000
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3139
31
983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155
bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error
bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch
bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input
the control action in the presence of measurement noise canbe dampened to a more smooth control signal
bullSISOMIMO PID can only handle one input and one output
MPC is a multivariable control strategy
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3239
32
983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150
983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148
983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)
983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
983123983145983149983157983148983137983156983141
983122983141983137983148
983124983145983149983141
983148
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3339
33
3 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152
983122 983148 983124983145 983107 983148983148 983105 983148983145 983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3439
34
983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150
983122983137983149983137983150
983120983154983151983138983141
983123983152983141983139983156983154983137983148
983137983139983153983157983145983155983145983156983145983151983150
983155983151983142983156983159983137983154983141
983123983152983141983139983156983154983137983148
983142983145983148983141
983107983137983148983145983138983154983137983156983145983151983150
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
983141983150983143983145983150983141
983110983141983141983140 983120983157983149983152
983125983123983106983124983141983160983156 983142983145983148983141
983154983141983137983140983159983154983145983156983141
983110983145983148983141 983108983145983154983141983139983156983151983154983161
983124983141983160983156 983142983145983148983141
983154983141983137983140983159983154983145983156983141
983124983141983160983156 983142983145983148983141
983154983141983137983140983159983154983145983156983141
983123983141983154983145983137983148
15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3539
35
15 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152
983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3639
36
983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150
983122983137983149983137983150
983120983154983151983138983141
983123983152983141983139983156983154983137983148
983137983139983153983157983145983155983145983156983145983151983150
983155983151983142983156983159983137983154983141
983123983152983141983139983156983154983137983148
983142983145983148983141
983107983137983148983145983138983154983137983156983145983151983150
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
983141983150983143983145983150983141
983105983106983106
98309600983160983137
983139983151983150983156983154983151983148
983155983161983155983156983141983149
983125983123983106 983124983107983120983113983120
983105983106983106 983160983120983105983124 983108983137983156983137
983117983137983150983137983143983141983154
983119983120983107983119983120983107
983119983120983107
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3739
37
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
bull Communication and controller configuration for real timeapplication complete
bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration
bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3839
38
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies
bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study
bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales
bull Real time results are to be compared to the results gatheredon a simulation basis
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3939
39
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
Prof Brian Glennon
Dr Jessica Whelan
PAT-Bio Research Team
Enterprise Ireland
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2739
27
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c
e n t r a t i o n ( m M
)
CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2839
28
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c
e n t r a t i o n ( m M )
CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
Controller Output
P = 40
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2939
29
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3039
30
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h
Controller Output
P = 40
M = 1
Γ = 1
Λ = 10000
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3139
31
983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155
bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error
bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch
bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input
the control action in the presence of measurement noise canbe dampened to a more smooth control signal
bullSISOMIMO PID can only handle one input and one output
MPC is a multivariable control strategy
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3239
32
983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150
983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148
983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)
983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
983123983145983149983157983148983137983156983141
983122983141983137983148
983124983145983149983141
983148
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3339
33
3 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152
983122 983148 983124983145 983107 983148983148 983105 983148983145 983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3439
34
983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150
983122983137983149983137983150
983120983154983151983138983141
983123983152983141983139983156983154983137983148
983137983139983153983157983145983155983145983156983145983151983150
983155983151983142983156983159983137983154983141
983123983152983141983139983156983154983137983148
983142983145983148983141
983107983137983148983145983138983154983137983156983145983151983150
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
983141983150983143983145983150983141
983110983141983141983140 983120983157983149983152
983125983123983106983124983141983160983156 983142983145983148983141
983154983141983137983140983159983154983145983156983141
983110983145983148983141 983108983145983154983141983139983156983151983154983161
983124983141983160983156 983142983145983148983141
983154983141983137983140983159983154983145983156983141
983124983141983160983156 983142983145983148983141
983154983141983137983140983159983154983145983156983141
983123983141983154983145983137983148
15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3539
35
15 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152
983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3639
36
983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150
983122983137983149983137983150
983120983154983151983138983141
983123983152983141983139983156983154983137983148
983137983139983153983157983145983155983145983156983145983151983150
983155983151983142983156983159983137983154983141
983123983152983141983139983156983154983137983148
983142983145983148983141
983107983137983148983145983138983154983137983156983145983151983150
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
983141983150983143983145983150983141
983105983106983106
98309600983160983137
983139983151983150983156983154983151983148
983155983161983155983156983141983149
983125983123983106 983124983107983120983113983120
983105983106983106 983160983120983105983124 983108983137983156983137
983117983137983150983137983143983141983154
983119983120983107983119983120983107
983119983120983107
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3739
37
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
bull Communication and controller configuration for real timeapplication complete
bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration
bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3839
38
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies
bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study
bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales
bull Real time results are to be compared to the results gatheredon a simulation basis
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3939
39
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
Prof Brian Glennon
Dr Jessica Whelan
PAT-Bio Research Team
Enterprise Ireland
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2839
28
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c
e n t r a t i o n ( m M )
CglcSet-point
0001002003004005006007
0 50 100 150 200 250 300
Time (h)
F e e d - r a t e ( L h )
Controller Output
P = 40
M = 1
Γ = 1
Λ = 0
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2939
29
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3039
30
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h
Controller Output
P = 40
M = 1
Γ = 1
Λ = 10000
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3139
31
983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155
bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error
bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch
bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input
the control action in the presence of measurement noise canbe dampened to a more smooth control signal
bullSISOMIMO PID can only handle one input and one output
MPC is a multivariable control strategy
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3239
32
983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150
983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148
983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)
983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
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983148
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3339
33
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983122 983148 983124983145 983107 983148983148 983105 983148983145 983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3439
34
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983142983145983148983141
983107983137983148983145983138983154983137983156983145983151983150
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
983141983150983143983145983150983141
983110983141983141983140 983120983157983149983152
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983154983141983137983140983159983154983145983156983141
983123983141983154983145983137983148
15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3539
35
15 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152
983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3639
36
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983122983137983149983137983150
983120983154983151983138983141
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983155983151983142983156983159983137983154983141
983123983152983141983139983156983154983137983148
983142983145983148983141
983107983137983148983145983138983154983137983156983145983151983150
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
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983119983120983107
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3739
37
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
bull Communication and controller configuration for real timeapplication complete
bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration
bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3839
38
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies
bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study
bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales
bull Real time results are to be compared to the results gatheredon a simulation basis
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3939
39
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
Prof Brian Glennon
Dr Jessica Whelan
PAT-Bio Research Team
Enterprise Ireland
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2939
29
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a
t e ( L h
Controller Output
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3039
30
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h
Controller Output
P = 40
M = 1
Γ = 1
Λ = 10000
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3139
31
983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155
bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error
bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch
bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input
the control action in the presence of measurement noise canbe dampened to a more smooth control signal
bullSISOMIMO PID can only handle one input and one output
MPC is a multivariable control strategy
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3239
32
983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150
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983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3339
33
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3439
34
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983122983137983149983137983150
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983107983151983150983156983154983151983148
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3539
35
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983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3639
36
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983107983151983150983156983154983151983148
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3739
37
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
bull Communication and controller configuration for real timeapplication complete
bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration
bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3839
38
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies
bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study
bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales
bull Real time results are to be compared to the results gatheredon a simulation basis
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3939
39
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
Prof Brian Glennon
Dr Jessica Whelan
PAT-Bio Research Team
Enterprise Ireland
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3039
30
983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Time (h)
C o n c e
n t r a t i o n ( m M )
CglcSet-point
0
001
002
003
004
005
006
007
0 50 100 150 200 250 300Time (h)
F e e d - r a t e ( L h
Controller Output
P = 40
M = 1
Γ = 1
Λ = 10000
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3139
31
983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155
bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error
bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch
bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input
the control action in the presence of measurement noise canbe dampened to a more smooth control signal
bullSISOMIMO PID can only handle one input and one output
MPC is a multivariable control strategy
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3239
32
983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150
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983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
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983148
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3339
33
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3439
34
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983142983145983148983141
983107983137983148983145983138983154983137983156983145983151983150
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
983141983150983143983145983150983141
983110983141983141983140 983120983157983149983152
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983154983141983137983140983159983154983145983156983141
983110983145983148983141 983108983145983154983141983139983156983151983154983161
983124983141983160983156 983142983145983148983141
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983124983141983160983156 983142983145983148983141
983154983141983137983140983159983154983145983156983141
983123983141983154983145983137983148
15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3539
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15 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152
983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3639
36
983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150
983122983137983149983137983150
983120983154983151983138983141
983123983152983141983139983156983154983137983148
983137983139983153983157983145983155983145983156983145983151983150
983155983151983142983156983159983137983154983141
983123983152983141983139983156983154983137983148
983142983145983148983141
983107983137983148983145983138983154983137983156983145983151983150
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141
983141983150983143983145983150983141
983105983106983106
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983139983151983150983156983154983151983148
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983117983137983150983137983143983141983154
983119983120983107983119983120983107
983119983120983107
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3739
37
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
bull Communication and controller configuration for real timeapplication complete
bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration
bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3839
38
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies
bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study
bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales
bull Real time results are to be compared to the results gatheredon a simulation basis
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3939
39
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
Prof Brian Glennon
Dr Jessica Whelan
PAT-Bio Research Team
Enterprise Ireland
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3139
31
983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155
bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error
bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch
bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input
the control action in the presence of measurement noise canbe dampened to a more smooth control signal
bullSISOMIMO PID can only handle one input and one output
MPC is a multivariable control strategy
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3239
32
983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150
983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148
983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)
983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
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983148
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3339
33
3 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152
983122 983148 983124983145 983107 983148983148 983105 983148983145 983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3439
34
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983155983151983142983156983159983137983154983141
983123983152983141983139983156983154983137983148
983142983145983148983141
983107983137983148983145983138983154983137983156983145983151983150
983149983151983140983141983148 amp
983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141
983107983151983150983156983154983151983148
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983154983141983137983140983159983154983145983156983141
983123983141983154983145983137983148
15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3539
35
15 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152
983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3639
36
983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150
983122983137983149983137983150
983120983154983151983138983141
983123983152983141983139983156983154983137983148
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983155983151983142983156983159983137983154983141
983123983152983141983139983156983154983137983148
983142983145983148983141
983107983137983148983145983138983154983137983156983145983151983150
983149983151983140983141983148 amp
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983107983151983150983156983154983151983148
983149983151983140983141983148 amp
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983141983150983143983145983150983141
983105983106983106
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983139983151983150983156983154983151983148
983155983161983155983156983141983149
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983119983120983107
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3739
37
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
bull Communication and controller configuration for real timeapplication complete
bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration
bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3839
38
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies
bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study
bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales
bull Real time results are to be compared to the results gatheredon a simulation basis
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3939
39
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
Prof Brian Glennon
Dr Jessica Whelan
PAT-Bio Research Team
Enterprise Ireland
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3239
32
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983107983151983150983142983145983143983157983154983141
amp 983124983157983150983141
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983124983145983149983141
983148
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3339
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3 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152
983122 983148 983124983145 983107 983148983148 983105 983148983145 983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3439
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983149983151983140983141983148 amp
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983107983151983150983156983154983151983148
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983141983150983143983145983150983141
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983123983141983154983145983137983148
15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3539
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15 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152
983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3639
36
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983142983145983148983141
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983149983151983140983141983148 amp
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983107983151983150983156983154983151983148
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983119983120983107
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3739
37
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
bull Communication and controller configuration for real timeapplication complete
bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration
bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3839
38
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies
bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study
bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales
bull Real time results are to be compared to the results gatheredon a simulation basis
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3939
39
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
Prof Brian Glennon
Dr Jessica Whelan
PAT-Bio Research Team
Enterprise Ireland
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3339
33
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3439
34
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983123983141983154983145983137983148
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3539
35
15 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152
983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3639
36
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983107983151983150983156983154983151983148
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983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3739
37
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
bull Communication and controller configuration for real timeapplication complete
bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration
bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3839
38
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies
bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study
bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales
bull Real time results are to be compared to the results gatheredon a simulation basis
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3939
39
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
Prof Brian Glennon
Dr Jessica Whelan
PAT-Bio Research Team
Enterprise Ireland
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3439
34
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983149983151983140983141983148 amp
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983107983151983150983156983154983151983148
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983123983141983154983145983137983148
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3539
35
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983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3639
36
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983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3739
37
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
bull Communication and controller configuration for real timeapplication complete
bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration
bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3839
38
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies
bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study
bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales
bull Real time results are to be compared to the results gatheredon a simulation basis
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3939
39
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
Prof Brian Glennon
Dr Jessica Whelan
PAT-Bio Research Team
Enterprise Ireland
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3539
35
15 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152
983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3639
36
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3739
37
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
bull Communication and controller configuration for real timeapplication complete
bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration
bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3839
38
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies
bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study
bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales
bull Real time results are to be compared to the results gatheredon a simulation basis
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3939
39
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
Prof Brian Glennon
Dr Jessica Whelan
PAT-Bio Research Team
Enterprise Ireland
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3639
36
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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3739
37
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
bull Communication and controller configuration for real timeapplication complete
bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration
bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3839
38
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies
bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study
bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales
bull Real time results are to be compared to the results gatheredon a simulation basis
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3939
39
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
Prof Brian Glennon
Dr Jessica Whelan
PAT-Bio Research Team
Enterprise Ireland
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3739
37
983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155
bull Communication and controller configuration for real timeapplication complete
bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration
bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3839
38
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies
bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study
bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales
bull Real time results are to be compared to the results gatheredon a simulation basis
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3939
39
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
Prof Brian Glennon
Dr Jessica Whelan
PAT-Bio Research Team
Enterprise Ireland
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3839
38
983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147
bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies
bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study
bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales
bull Real time results are to be compared to the results gatheredon a simulation basis
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3939
39
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
Prof Brian Glennon
Dr Jessica Whelan
PAT-Bio Research Team
Enterprise Ireland
7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven
httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3939
39
983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155
Prof Brian Glennon
Dr Jessica Whelan
PAT-Bio Research Team
Enterprise Ireland