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Lecture 13: PID Control System Design/

Tuning Fine Tuning

12. PID Control System Design/Tuning Method II:Continuous Cycling Method Plants

Review of Ziegler-Nichols Tuning/Design Methods

Fine Tuning

Case Study and Examples

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Process Reaction PID Tuning Method

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Ziegler Nichols Tuning Methods

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Process Reaction PID Tuning Method

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Kplant, T and L Note: Actuator is included as a part

of the plant to obtain the aboveparameters

P I D

Plant

Plant

Plant

K R (reps/min) T (mins)

1 TP 0 0

K L

0.9 T 0.3PI 0

K L L

1.2 T 0.5PID 0.5L

K L L

P I D

Plant

Plant

Plant

K T (mins) T (mins)

1 TP 0

K L

0.9 T LPI 0

K L 0.3

1.2 TPID 2L 0.5L

K L

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t1

28.3%y%

x%

y%

63.2%y%

t2

TL

Almost done

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Continuous Cycling PID Tuning Method

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Ziegler Nichols Tuning Methods

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Continuous Cycling PID Tuning Formula

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Continuous Cycling PID Tuning Method

Required parameters

Kcr and Pcr

Closed control loop parameters

P I D

cr

cr

cr

crcr

cr

K R (reps/min) T (mins)

P 0.50K 0 0

1.2PI 0.45K 0

P

P2PID 0.60K

P 8

P I D

cr

cr

cr

cr

cr cr

K (mins) T (mins)

P 0.50K 0

PPI 0.45K 0

1.2

PPID 0.60K 0.5P

8

T

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Pcr

Almost done

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Review: Ziegler-Nichols Tuning/Design

Methods

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PID parameters obtained from the Ziegler-Nichols tuning rules

can serve as a quantitative start point

An educated good guess

At least stable and safe to the plants

Reasonably fast response

Control performance may not be optimal or even satisfactory

Based on a lot of assumptions which the actual plant may not meet

Plant non-linearity

Fine-tuning can improve the PID controller performance

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Fine Tuning

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Based on desired performance

Minimum rising time/settling time but stable

Minimum overshoot/maximum stability but reasonably quick

Compromise between the above two (5%

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Fine Tuning

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Guidelines The following table

Practice/experience/knowledge of the plant

RESPONSERISE

TIME

OVER-

SHOOT

SETTLING

TIME

OFFSET

ERROR

Used

information

P (Kp) No definite trend Present

I (Ri)

Zero Past

D (Td) Minor Minor No effect in

theoryFuture

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Fine Tuning of Proportional Gain and Integral

Reset

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Things in common for KP and RI Increase in either of the above will

Reduce control error faster

Achieve faster response

Decrease in either of the above will Increase the stability

Decrease oscillation

Decrease overshoot

How do we know which parameters should be fine-tuned?

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Fine Tuning of Proportional Gain and Integral

Reset

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Inherent Difference

Proportional control (using current error information) has an instant control

effect in response to set point change or disturbance

Proportional to the magnitude of the current error

Maximum error occurs when there is a sudden change in set point or disturbance

Integral reset (using past information) does not have an instant control effect

in response to set point change or disturbance

Proportional to the accumulation (integration) of error

Maximum integration of error occurs before the sign of error changes

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Fine Tuning of Proportional Gain and Integral

Reset

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Simple one-D fine-tuning strategy

If the control has a sluggish response at the beginning, increase the

proportional gain first

If the control has a sluggish response at the end, increase the integral reset first Two-D fine-tuning strategy

An increase/decrease in proportional gain tends to shift the step response

upwards/downwards and simultaneously increase/decrease the amplitude of

the overshoot.

An increase/decrease in integral reset tends to change the shape of the stepresponse by increasing/decreasing the damping ratio.

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1-12 AE 8120 Bldg Control & Automation Systems

Too sluggish at theend, increase RI

Too sluggish at thebeginning, increase KP

Unstable or too fast at thebeginning, reduce KP

Sluggish at both ends,increase both KP and RI

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Case Study

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MatLab SimuLink Simulator Steps

Plant parameter identification

PID Tuning

Fine-Tuning

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