Piloted Simulation of Fault Detection, Isolation and Reconfiguration Algorithms for a Civil

Transport Aircraft

S. Ganguli, G. Papageorgiou, S. Glavaški, M. ElgersmaHoneywell Advanced Technology GNC

Presented by: G. Papageorgiou

george.papageorgiou@honeywell.com

SAE ConferenceOctober 2005

#NCC-1-334 with NASA Langley Research Center#NAS1-00107 with NASA Langley Research Center

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Aircraft Control Surfaces

• Commanded Control Surfaces (via autopilot):- Aileron Difference- Average Elevator- Rudder

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Piloted Simulation Setup

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IFD vs Matlab: Comparative plots

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CUPRSys Overview

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CUPRSys Algorithms – Aircraft Model• Express aircraft dynamics as sum of nominal nonlinear function and a linear

combination of (nonlinear) basis functions.

),( uxfx ),(),(0 uxHbuxfx

• Aircraft equations:

)()(

)(11

13

MMJJJ

FFgevv

T

Tm

Tvx ][ TTu ][

),,(~00

)()()(

1

1

0,11

0,1

3 vHbBJ

IFFJJJ

FFgevv m

T

Tm

),,(~ bcbdiagB

||||

||||

||||2

21 ~),,(

v

v

vv

SBSS

vvb

106H

IM

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Flight Conditions

Reduction of effectiveness faults and various maneuvers

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Matlab Simulation (Low Cruise Pitch Down)

- No Fault-. 75% Fault.. Reconfigured- Command

Pilot modeledby Prop. Gain

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Flight Card

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Low Cruise – 10 deg Pitch Down (No fault)

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Low Cruise – 10 deg Pitch Down (75% e fault)

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Low Cruise – 10 deg Pitch Down (Reconfiguration)

Larger command

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Low Cruise – 10 deg Pitch Down (Reconfiguration)

Smaller command

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Cooper Harper Ratings & Pilot Workload - LC

Low Cruise

|| ||2pedalforce

ecolumnforcwheelforce

LP HPs1

workloadpilot

(5 rad/s) (2 rad/s)*

* R. Mercadante, “Piloted Simulation Verification of a Control Reconfiguration for a Fighter Aircraft under Impairment”, AGARD No. 456, Toulouse, France, 1989

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FDI Performance

• Performance measured by:- False-alarms

1 LC pitch-up maneuver, and during flare tasks (ground effects not modeled?)

- Missed detection (none, but sensitivity to small faults not tested)- Accuracy of identified fault

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Lessons Learnt and Recommendations

• Limitations- CUPRSys uses and sensors – typically not available- Feel system model not available for design

• Current deficiencies of CUPRSys- On-board aircraft model uses exact replica of Engine Model- H-matrix and Threshold Functions vary with flight condition

• Gain reconfiguration vs control re-allocation- CUPRSys restricted to gain reconfiguration (commanding

through autopilot)- Control authority of additional surfaces can restore flying qualities

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Conclusions & Future Work

• Piloted simulations conducted at LaRC suggest- Robust control law- Promising FDIR capabilities (need more validation sims with

control re-allocation)

• Future Work- Utilize control allocation- Accommodate sensor dynamics and noise- Accommodate turbulence- Expanded set of failures

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Pilot Cueing

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Integration Flight Deck (IFD)

• Piloted Simulations were conducted at the LaRC IFD facility.

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Acknowledgement

• Thanks to the NASA Team for their support, encouragement and various helpful discussions:- Pat Murphy- Steve Derry- Gus Taylor- Rob Rivers- Tom Bundick- Christine Belcastro

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www.honeywell.com

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NASA Aviation Safety & Security Program• NASA AvSSP

- $500 million*- Reduce commercial aviation accident rate by 80% by 2007*

(* http://www.nasa.gov/centers/langley/news/factsheets/AvSP-factsheet.html)

http://avsp.larc.nasa.gov/program.html

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AMASF Program Overview

• Phase I (mid-sized commuter aircraft)- FDI technologies for selected failures (stuck/floating actuators,

reduction of control surface effectiveness) + icing- Pilot Cueing strategies- Control Reconfiguration

• Phase II (mid-sized civil transport aircraft)- Transition of algorithms to new aircraft- Algorithms + display integrated to CUPRSys- Failure type: reduction of control surface effectiveness

• Phase III- Piloted simulation at LaRC

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CUPRSys Algorithms – Reconfigurable CLAW

• Based on Dynamic Inversion

Cxyuxgxfx

)()(

• Desired Dynamics

• Control Law (under certain assumptions)

),( yyTy cdes

))(),(())(( 1 xCfyyTxCgu c

DI P + I

r

e

a

K

*c

c

Cp

desVg

dtd

des

des

rqp

)sin(

)(sin)1(

yVg

zVg

nrnq

p

co

c

+ feedforward

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CUPRSys Algorithms – Reconfigurable CLAW• Controller bandwidths

- High dynamic pressure (High/Low Cruise): [p C* ] = [2.0 1.25 1.0] rad/s

- Low dynamic pressure (near Approach): [p C* ] = [2.5 0.75 0.75] rad/s

• Inceptor Scalings- Wheel (85 deg): 0.25 (deg/s)/deg- Column (-9.2 to 13.3 deg): 2.00 (deg/s)/deg- Pedal (4 inch): 0.02 rad/inch

• Anti-windup (software limiting)

fiKb 1/s Kb

desyInversion

u

fc

cyy

Kaw

sat lim

y

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CUPRSys Algorithms – Fault Detection

• Residual Generator

Angular Acceleration

EstimatorNoise

Rejection

dtdu

tmeasuremen residualerr

LPc

c

c

Cp

* abs( )

• Threshold Function

threshold

Bias

Turbulence Rejection

z

y

x

nnn

Scaled, Added

Scaled, Added

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CUPRSys Algorithms – Fault Isolation

• RLS Estimator:

After acquiring k samples:

Over-determined linear algebra problem:

Weighted Least Squares problem:

Solved using standard RLS Estimation algorithm with forgetting factor.

),(),(0 uxHbMuxfx I

)],(,),,([)],(,),,([

111

0111011

kkkk

kkIk

uxbuxbGuxfxuxfxMF

)( 0 HHHGF kk

),(),0( 0 kkk GWHGHF

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CUPRSys Algorithms – Fault Isolation

• H-Matrix Convergence Criterion

• H-Matrix Update- H-matrix for FD (Residual Generator)- H-matrix for CLAW

• Signal Injection- Trade-off between sufficient excitation time and quick FDIR- Simultaneous doublet commands (4 sec) in all three axes

0.5 deg/s p 0.5 deg/s C*

1 deg

ji

jiHdtd

,

),( ji

jiH,

),(and

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High Cruise – 10 deg Pitch Down (No fault)

+ lightturbulence

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High Cruise – 10 deg Pitch Down (75% e fault)

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High Cruise – 10 deg Pitch Down (Reconfiguration)

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Cooper Harper Ratings & Pilot Workload

High Cruise

|| ||2pedalforce

ecolumnforcwheelforce

LP HPs1

workloadpilot