CMAC NN-based adaptive control of non-affine nonlinear systems

Author

Xiaojun, Guo ; Yanli, Han ; Hu Yunan ; Youan, Zhang

Author_Institution

Dept. of Autom. Control. Eng., Naval Aeronaut. Eng. Acad., China

Volume

5

fYear

2000

fDate

2000

Firstpage

3303

Abstract

Based on the implicit theorem and variable structure control (VSC), an adaptive control method is proposed for a class of non-affine nonlinear systems using CMAC neural networks (NN). The proposed controller ensures that the output of the system tracks a given bounded reference signal and that the output tracking error converges to the origin. The neural network weight learning laws are determined by Lyapunov stability theory and the stability of the closed loop system is guaranteed. The simulation results have shown the effectiveness of the proposed method

Keywords

Lyapunov methods; adaptive control; cerebellar model arithmetic computers; closed loop systems; control system synthesis; neurocontrollers; nonlinear control systems; stability; variable structure systems; CMAC NN-based adaptive control; Lyapunov stability theory; bounded reference signal; neural network weight learning laws; nonaffine nonlinear system; output tracking error; variable structure control; Adaptive control; Aerospace engineering; Automatic control; Closed loop systems; Control systems; Error correction; Neural networks; Nonlinear control systems; Nonlinear systems; Trajectory;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on

Conference_Location

Hefei

Print_ISBN

0-7803-5995-X

Type

conf

DOI

10.1109/WCICA.2000.863137

Filename

863137