论文信息 - Fault Detection and Diagnosis of a Certain UAV Based on Dual Unscented Kalman Filter

Fault Detection and Diagnosis of a Certain UAV Based on Dual Unscented Kalman Filter

This paper presents an applicable procedure of integrated fault detection and diagnosis for an unmanned aerial vehicle aircraft model. The implementation of a Fault detection and diagnosis (FDD) scheme in handling partial control effector fault cases based on a dual unscented Kalman filter (DUKF) and a Baysian rule for detection and isolation decision making. Simulation results show satisfactory results for detecting and diagnosing the control effectors failures.

Li Li | Hua-min Zhang | Hua Zhang | Li Li

[1] Richard D. Braatz,et al. Fault Detection and Diagnosis in Industrial Systems , 2001 .

[2] R. V. Jategaonkar,et al. Aerodynamic Parameter Estimation from Flight Data Applying Extended and Unscented Kalman Filter , 2010 .

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