A linear parameter-varying (LPV) model-based synthesis, tuning and assessment methodology is developed and applied for the design of a robust fault detection and diagnosis (FDD) system for several types of flight actuator faults such as jamming, runaway, oscillatory failure, or loss of efficiency. The robust fault detection is achieved by using a synthesis approach based on an accurate approximation of the nonlinear actuator–control surface dynamics via an LPV model and an optimal tuning of the free parameters of the FDD system using multi-objective optimization techniques. Real-time signal processing is employed for identification of different fault types. The assessment of the FDD system robustness has been performed using both standard Monte-Carlo methods as well as advanced worst-case search based optimization-driven robustness analysis. A supplementary industrial validation performed on the AIRBUS actuator test bench for the monitoring of jamming, confirmed the satisfactory performance of the FDD system in a true industrial setting.
LPV model-based robust diagnosis of flight actuator faults
Control Engineering Practice ; 31 ; 135-147
2014
13 Seiten, 26 Quellen
Article (Journal)
English
Adaptive sliding mode control robust to actuator faults
Tema Archive | 2007
|Adaptive sliding mode control robust to actuator faults
SAGE Publications | 2007
|Adaptive sliding mode control robust to actuator faults
Online Contents | 2007
|A Fault-tolerant Flight Controller Design for Actuator Faults
British Library Conference Proceedings | 2001
|Diagnosis of Actuator Faults in AUVs Based on Neural Networks
British Library Conference Proceedings | 2005
|