Fault Detection and Diagnosis for GTM UAV with Dual Unscented Kalman Filter

This paper presents an applicable procedure for Fault Detection and Diagnosis (FDD) in a realistic nonlinear six degree-of-freedom unmanned aerial vehicle (UAV) model. The work has been developed based on the Matlab/Simulink environment of the NASA Generic Transport Model (GTM) UAV under the NASA Aviation Safety Program (AvSP). By introducing the partial loss fault in aircraft actuators into the GTM model, the dual Unscented Kalman Filter (UKF) algorithm is implemented for online estimation of both flight states and fault parameters, and for making statistical decisions associated with fault detection and diagnosis.

[1]  G. Balas,et al.  Development of linear-parameter-varying models for aircraft , 2004 .

[2]  Christine M. Belcastro,et al.  AirSTAR: A UAV Platform for Flight Dynamics and Control System Testing , 2006 .

[3]  Youmin Zhang,et al.  Fault Diagnosis for A Ship Propulsion Benchmark: Part I , 1999 .

[4]  Youmin Zhang,et al.  Bibliographical review on reconfigurable fault-tolerant control systems , 2003, Annu. Rev. Control..

[5]  Rudolph van der Merwe,et al.  The unscented Kalman filter for nonlinear estimation , 2000, Proceedings of the IEEE 2000 Adaptive Systems for Signal Processing, Communications, and Control Symposium (Cat. No.00EX373).

[6]  Matthew Ruschmann,et al.  Probing the NASA generic transport aircraft in real-time for health monitoring , 2011, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference.

[7]  Jeffrey K. Uhlmann,et al.  New extension of the Kalman filter to nonlinear systems , 1997, Defense, Security, and Sensing.

[8]  Peter J Seiler,et al.  Reachability and Region of Attraction Analysis Applied to GTM Dynamic Flight Envelope Assessment , 2009 .

[9]  Youmin Zhang,et al.  Design of integrated fault detection, diagnosis and reconfigurable control systems , 1999, Proceedings of the 38th IEEE Conference on Decision and Control (Cat. No.99CH36304).

[10]  Jeffrey Michael Barker.  Linear-parameter-varying gain-scheduled control of aerospace systems , 1999 .