Fault diagnosis and reconfigurable control for flight control systems with actuator failures

Author(s):  
Kemin Zhou ◽  
P.K. Rachinayani ◽  
N. Liu ◽  
Zhang Ren ◽  
J. Aravena
2016 ◽  
Vol 38 (12) ◽  
pp. 1480-1490 ◽  
Author(s):  
Jianchen Wang ◽  
Xiaohui Qi

Model-based fault diagnosis has attracted considerable attention from researchers and developers of flight control systems, thanks to its hardware simplicity and cost-effectiveness. However, the airplane model, which is adopted commonly in fault diagnosis, only exists theoretically and is linearized in approximation. For this reason, uncertainties such as system non-linearity and subjectivity will degrade the fault diagnosis results. In this paper, we propose a novel actuator fault diagnosis scheme for flight control systems based on model identification techniques. With this scheme, system identification can be achieved with a linear model that uses a closed-loop subspace model identification algorithm, and a non-linear model that uses an extended state observer and neural networks. On this basis, the current actuator fault is estimated using an adaptive two-stage Kalman filter. Finally, the non-linear six-degree-of-freedom model of a B747 airplane is simulated in the Matlab/Simulink environment, where the effectiveness of the proposed scheme is verified from fault diagnosis tests.


2000 ◽  
Vol 23 (3) ◽  
pp. 412-419 ◽  
Author(s):  
R. A. Hess ◽  
W. Siwakosit ◽  
J. Chung

2019 ◽  
Vol 304 ◽  
pp. 04018 ◽  
Author(s):  
Andrea De Martin ◽  
Giovanni Jacazio ◽  
Massimo Sorli

Literature on PHM is focused on research dedicated to the definition of new algorithms to achieve better failures prognosis or earlier and more accurate fault diagnosis, but lacks of examples on the design of novel PHM frameworks and the practical issues related with their implementation. This paper describes a roadmap for the design of a novel Prognostics and Health Management system while making reference to a real-case scenario applied to electro-mechanical actuators for flight control systems.


2011 ◽  
Vol 15 ◽  
pp. 220-224 ◽  
Author(s):  
Liu Xiaoxiong ◽  
Chen Kang ◽  
Qiu Yueheng ◽  
Sun Liyuan

2008 ◽  
Vol 19 (5) ◽  
pp. 1017-1023 ◽  
Author(s):  
Guo Yuying ◽  
Jiang Bin ◽  
Zhang Youmin ◽  
Wang Jianfei

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