The Stability of a Class of Nonlinear System Using Radial Basis Neural Networks

Author

Li Zili ; Chen Zenqiang ; Yuan Zhuzhi

Author_Institution

Dept. of Autom., Nankai Univ., Tiajin, China

fYear

2006

fDate

7-11 Aug. 2006

Firstpage

756

Lastpage

760

Abstract

This paper researches the robust control stabilization problem of a continuous nonlinear system with time-invarying delays in the state vector. A sufficient condition of the system stabilization is achieved through radial basis neural network (RBF) approximating unknown function, and an adaptive neural controller of time-delay independent is obtained. A good result is got for the stabilization control of the large time-delay system.

Keywords

Lyapunov matrix equations; Lyapunov methods; adaptive control; continuous systems; delay systems; delays; function approximation; neurocontrollers; nonlinear control systems; radial basis function networks; robust control; Lyapunov function; adaptive neural controller; continuons nonlinear system; function approximation; radial basis neural networks; robust control stabilization; state vector; time-delay system; time-invarying delays; Adaptive control; Control systems; Delay systems; Neural networks; Nonlinear control systems; Nonlinear systems; Programmable control; Robust control; Robust stability; Sufficient conditions; Lyapunov function; Nonlinear system; RBF neural networks; robust stability; time-delay system;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Conference, 2006. CCC 2006. Chinese

Conference_Location

Harbin

Print_ISBN

7-81077-802-1

Type

conf

DOI

10.1109/CHICC.2006.280735

Filename

4060625