Neural networks‐based adaptive finite‐time prescribed performance fault‐tolerant control of switched nonlinear systems
Xinjun Wang, Ben Niu, Ping Zhao, Xinmin Song
Abstract
Summary In this article, the adaptive finite‐time fault‐tolerant control problem is considered for a class of switched nonlinear systems in nonstrict‐feedback form with actuator fault. The problem of finite‐time fault‐tolerant control is solved by introducing a finite‐time performance function. Meanwhile, the completely unknown nonlinear functions exist in the switched system are identified by the neural networks. Based on the common Lyapunov function method with adaptive backstepping technique, the finite‐time fault‐tolerant controller is designed. The proposed control strategy can guarantee that the tracking error converges to a prescribed zone at a finite‐time and all system variables remain semiglobally practical finite‐time stable. Numerical examples are offered to verify the feasibility of the theoretical result.