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Piloted Simulation of Fault Detection, Isolation and Reconfiguration Algorithms for a Civil Transport Aircraft. S. Ganguli, G. Papageorgiou, S. Glavaški, M. Elgersma Honeywell Advanced Technology GNC Presented by: G. Papageorgiou george.papageorgiou@honeywell.com SAE Conference October 2005.
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Piloted Simulation of Fault Detection, Isolation and Reconfiguration Algorithms for a Civil Transport Aircraft S. Ganguli, G. Papageorgiou, S. Glavaški, M. Elgersma Honeywell Advanced Technology GNC Presented by: G. Papageorgiou george.papageorgiou@honeywell.com SAE Conference October 2005 #NCC-1-334 with NASA Langley Research Center #NAS1-00107 with NASA Langley Research Center
Aircraft Control Surfaces • Commanded Control Surfaces (via autopilot): • Aileron Difference • Average Elevator • Rudder
CUPRSys Algorithms – Aircraft Model • Express aircraft dynamics as sum of nominal nonlinear function and a linear combination of (nonlinear) basis functions. • Aircraft equations:
Flight Conditions Reduction of effectiveness faults and various maneuvers
Matlab Simulation (Low Cruise Pitch Down) Pilot modeled by Prop. Gain - No Fault -. 75% Fault .. Reconfigured - Command
Low Cruise – 10 deg Pitch Down (Reconfiguration) Larger command
Low Cruise – 10 deg Pitch Down (Reconfiguration) Smaller command
Cooper Harper Ratings & Pilot Workload - LC (5 rad/s) (2 rad/s)* LP || ||2 HP Low Cruise * R. Mercadante, “Piloted Simulation Verification of a Control Reconfiguration for a Fighter Aircraft under Impairment”, AGARD No. 456, Toulouse, France, 1989
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
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
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
Integration Flight Deck (IFD) • Piloted Simulations were conducted at the LaRC IFD facility.
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
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
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
CUPRSys Algorithms – Reconfigurable CLAW • Based on Dynamic Inversion • Desired Dynamics • Control Law (under certain assumptions) + feedforward DI P + I K
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) fc Inversion Kb fiKb 1/s Kaw sat lim
CUPRSys Algorithms – Fault Detection • Residual Generator Angular Acceleration Estimator Scaled, Added Noise Rejection • Threshold Function abs( ) LP Scaled, Added Bias Turbulence Rejection
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.
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 and
High Cruise – 10 deg Pitch Down (No fault) + light turbulence
Cooper Harper Ratings & Pilot Workload LP || ||2 HP High Cruise