Adaptive Observer based Fault Tolerant Control for Aircraft Engine with Sensors and Actuators Faults

The fault tolerant control on the basis of adaptive observer for aircraft engine with both sensors faults and actuators faults is considered in this paper. The adaptive observer can reconstruct the fault signal when the sensors and actuators faults appear simultaneously. And the obtained fault estimation signals are sent to the input and output terminals of the controller respectively to offset the faults of actuators and sensors. The aircraft engine fault tolerant control system is constructed as a result. It is proven that the faults estimation errors are stable by Lyapunov theory. Simulation on the two typical operation points of aircraft engine shows that the fault tolerant control system can effectively reduce the impact of sensor and actuator failures on the system.

[1]  Dragoslav D. Šiljak,et al.  Reliable control using multiple control systems , 1980 .

[2]  Williams R. Wells,et al.  Failure state detection of aircraft engine output sensors , 1977 .

[3]  A. Willsky,et al.  A generalized likelihood ratio approach to the detection and estimation of jumps in linear systems , 1976 .

[4]  Lingfei Xiao,et al.  Fault identification for turboshaft engines based on fractional-order sliding mode observer , 2017, 2017 Eighth International Conference on Intelligent Control and Information Processing (ICICIP).

[5]  Ten-Huei Guo,et al.  Using Neural Networks for Sensor Validation , 1998 .

[6]  W.C. Merrill,et al.  A real time microcomputer implementation of sensor failure detection for turbofan engines , 1990, IEEE Control Systems Magazine.

[7]  Bin Jiang,et al.  Sliding Mode Fault Tolerant Control with Adaptive Diagnosis for Aircraft Engines , 2018 .

[8]  Ron J. Patton,et al.  Fault-Tolerant Control: The 1997 Situation , 1997 .

[9]  Yixin Diao,et al.  Stable fault-tolerant adaptive fuzzy/neural control for a turbine engine , 2001, IEEE Trans. Control. Syst. Technol..

[10]  Mario Innocenti,et al.  Sensor validation using hardware-based on-line learning neural networks , 1998 .

[11]  Lingfei Xiao,et al.  Robust Fault Identification of Turbofan Engines Sensors Based on Fractional-Order Integral Sliding Mode Observer , 2019 .

[12]  H. A. Spang,et al.  Failure detection and correction for turbofan engines , 1977 .

[13]  Xi Wang,et al.  A fault-tolerant control approach for aircraft engine using a bank of LMI-based UIO filters , 2011, 2011 International Conference on Electronics, Communications and Control (ICECC).

[14]  T.-H. Guo,et al.  Sensor failure detection and recovery by neural networks , 1991, IJCNN-91-Seattle International Joint Conference on Neural Networks.

[15]  Sanjay Garg,et al.  NASA Glenn Research in Controls and Diagnostics for Intelligent Aerospace Propulsion Systems , 2005 .

[16]  A. Niederlinski A heuristic approach to the design of linear multivariable interacting control systems , 1971 .