Affiliation:
1. College of Mathematical Sciences Bohai University Jinzhou China
2. College of Information Science and Engineering Northeastern University Shenyang China
Abstract
AbstractIn this article, the issue of adaptive predefined‐time control for high‐order switched systems is researched. Neural networks (NNs) are introduced to approximate the uncertain nonlinear functions. In particular, a novel predefined‐time convergence filter is proposed to refrain from the problem of repeated differentiation of virtual controllers. On the basis of the backstepping recursion technique and the common Lyapunov function (CLF) approach, a neural adaptive predefined‐time dynamic surface control (DSC) scheme is proposed that can demonstrate all the signals in closed‐loop systems are bounded and the tracking error can converge to a small area near zero within predefined time. The simulation results illustrate the effectiveness of the proposed control scheme.
Funder
National Natural Science Foundation of China