A fast terminal sliding mode fault-tolerant control strategy based on adaptive neural network sliding mode observer was proposed for the possible failure of electromechanical servo system. The neural network was introduced into the adaptive sliding mode observer to estimate the fault, so as to improve the accuracy of state estimation and fault diagnosis. An active fault-tolerant controller was designed by using the state estimation value of the observer, combining the parameter adaptive technology and the fast terminal sliding mode control method. The parameter adaptive rate was designed to estimate the parameter uncertainty, and the feedforward compensation technology was used to compensate the fault and parameter uncertainty. A robust term with adaptive gain was designed to overcome the disturbance of unknown upper bound. Using Lyapunov theorem, it is proved that the proposed control method can achieve bounded stability of the system. A large number of simulation and experimental results verify that the controller has good fault tolerance, control accuracy and response speed in case of system failure.
Zheng-yin YANG,Jian HU,Jian-yong YAO,Ying-zhe SHA,Qiu-yu SONG. Fault-tolerant control based on adaptive neural network sliding mode observer. Journal of ZheJiang University (Engineering Science), 2022, 56(8): 1656-1665.
Fig.3Block diagram of fault-tolerant control strategy
Fig.4Comparison of tracking errors of position commands of different controllers
Fig.5Estimation of instability parameters in system
Fig.6Fault estimation error
Fig.7Errors in system position and velocity observations
控制器
Me/(°)
μ/(°)
σ/(°)
PID
0.0105
0.0065
0.0032
快速终端滑模
0.0070
0.0043
0.0020
主动容错快速终端滑模
0.0028
0.0017
0.0010
Tab.1Performance specifications of each controller
Fig.8Structure diagram of servo control experimental platform
Fig.9Comparison of tracking errors of three controllers under working condition one
Fig.10Comparison of tracking errors of three controllers under working condition two
Fig.11Comparison of tracking errors of three controllers under working condition three
控制器
Me/(°)
μ/(°)
σ/(°)
PID
0.0472
0.0197
0.0121
快速终端滑模
0.0337
0.0114
0.0100
主动容错快速终端滑模
0.0306
0.0109
0.0081
Tab.2Controller performance index of condition one
控制器
Me/(°)
μ/(°)
σ/(°)
PID
0.0416
0.0180
0.0108
快速终端滑模
0.0390
0.0140
0.0087
主动容错快速终端滑模
0.0299
0.0098
0.0084
Tab.3Controller performance index of condition two
控制器
Me/(°)
μ/(°)
σ/(°)
PID
0.0636
0.0345
0.0121
快速终端滑模
0.0384
0.0228
0.0073
主动容错快速终端滑模
0.0334
0.0182
0.0063
Tab.4Controller performance index of condition three
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