Adaptive Neural Control with Prespecified Tracking Accuracy for a Class of Switched Systems Subject to Input Delay

Xu Zhang,Jing Li,Jian Wu,Wu Ai

doi:10.1155/2019/6920372

Abstract

This paper is concerned with the adaptive tracking control design for a class of uncertain switched systems subject to input delay. Unlike the existing results on uncertain switched systems, the new proposed control scheme ensures that the tracking error converges to the accuracy given a priori according to the requirement. To achieve this aim, some nonnegative switching functions are introduced to replace the conventional Lyapunov function. In addition, neural networks are used to approximate the unknown simultaneous domination functions. By combining the backstepping technique and some common nonnegative switching functions, a stable adaptive neural controller is established. It can be shown that the closed-loop system is semiglobally uniformly ultimately bounded (SGUUB) and the tracking error satisfies the predefined accuracy. The effectiveness of the proposed control scheme is verified by a simulation example.

Highlights

As we all know, switched systems are a special class of hybrid systems, which have been paid much attention due to their practical applications
It is worth pointing out that the mentioned references focus on dealing with the control problem for the switched systems without unknown system functions
Inspired by the above discussions, this paper addresses the adaptive neural tracking control problem for a class of uncertain switched systems subject to input delay

Summary

Introduction

As we all know, switched systems are a special class of hybrid systems, which have been paid much attention due to their practical applications. By using the technique of adding a power integrator, Fu et al [5] discuss the finite-time control problem, and an adaptive controller is constructed to achieve the globally finite-time stabilization of the switched nonlinear systems with the powers of positive odd rational numbers. Input delay plays an increasing important role in the real engineering systems It has been attracted much attention, and numerous results have been presented in [30,31,32,33,34,35,36,37,38]. Inspired by the above discussions, this paper addresses the adaptive neural tracking control problem for a class of uncertain switched systems subject to input delay. The number of adaptive learning parameters can be reduced

Preliminaries

Simulation Examples

Findings

Conclusions