Tracking Stabilization For A Class Of Switched Nonlinear Systems With Time Delay Based On RBF Neural Networks

Author

Long, Fei ; Fei, Shumin

Author_Institution

Dept. of Autom. control, Southeast Univ., Nanjing

Volume

2

fYear

2005

Firstpage

930

Lastpage

934

Abstract

An adaptive feedback control scheme and a switching strategy for the output tracking stabilization of switched nonlinear systems with time-delay are presented by using RBF (radial basis function) neural network The RBF neural networks is used to compensate adaptively for the unknown nonlinear parts of switched nonlinear systems, and the approximation errors of RBF neural networks are introduced to the adaptive law in order to improve the tracking quality of the systems. The controller and switching strategy can guarantee asymptotic stability of tracking error for the overall system

Keywords

adaptive control; asymptotic stability; delays; feedback; neurocontrollers; nonlinear control systems; radial basis function networks; time-varying systems; RBF neural networks; adaptive feedback control; asymptotic stability; output tracking stabilization; radial basis function neural network; switched nonlinear system; time delay; Adaptive control; Adaptive systems; Approximation error; Asymptotic stability; Control systems; Delay effects; Feedback control; Neural networks; Nonlinear systems; Programmable control;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks and Brain, 2005. ICNN&B '05. International Conference on

Conference_Location

Beijing

Print_ISBN

0-7803-9422-4

Type

conf

DOI

10.1109/ICNNB.2005.1614772

Filename

1614772