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Fault tolerant control for strict-feedback nonlinear system via event-triggered adaptive algorithms
Chao He1, Jiaxian Wang1, Sanyang Liu1
1School of Mathematics and Statistics, Xidian University, 710071, China.
Abstract:
In this paper, the event-triggered adaptive fault tolerant tracking control for the strict-feedback nonlinear system with mismatched unknown parameters, external disturbances and actuator faults is addressed. A novel adaptive fault tolerant mechanism is presented to overcome the difficulty arising from the actuator faults and mismatched parameters, where the parameters estimators are generated from discrete state governed by the state dependent event-triggered mechanism. Furthermore, by introducing the auxiliary dynamic, it is shown that all the signals of the system are ultimately bounded and the asymptotical output tracking error is within a small residual set including origin which can be modified arbitrarily small by tuning the control coefficients. Based on the presented adaptive fault tolerant mechanism, the robust event-triggered mechanism and adaptive algorithm are further developed and the boundedness of all the variables of the system is shown. What is more, it is proved that both of the presented event-triggered mechanisms are Zeno-free. Finally, the control effectiveness of the proposed fault tolerant strategy is discussed and verified by a numerical example and the single-link manipulator.
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