Adaptive neural network tracking control for a class of switched nonlinear systems with input delay

Abstract This paper investigates the issue of adaptive tracking control for switched nonlinear systems with time-varying input delay and external perturbations. An improved method is proposed to convert a delayed system into a delay-free system by employing the integral term of control information. Based on the backstepping approach, the designed adaptive controller can ensure that all states of the closed-loop system are semi-globally uniformly ultimately bounded. Meanwhile, the output of system can follow the desired tracking trajectory, in which all switching signals satisfy average dwell time constraint. Two simulation examples are utilized to indicate the effectiveness of the theoretical results.

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Adaptive neural network tracking control for a class of switched nonlinear systems with input delay

Semantic Scholar · Engineering · 2019

Abstract

Abstract This paper investigates the issue of adaptive tracking control for switched nonlinear systems with time-varying input delay and external perturbations. An improved method is proposed to convert a delayed system into a delay-free system by employing the integral term of control information. Based on the backstepping approach, the designed adaptive controller can ensure that all states of the closed-loop system are semi-globally uniformly ultimately bounded. Meanwhile, the output of system can follow the desired tracking trajectory, in which all switching signals satisfy average dwell time constraint. Two simulation examples are utilized to indicate the effectiveness of the theoretical results.

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