Adaptive Neuro-Fuzzy Control of Non-Affine Nonlinear Systems

Author

Jia, Li ; Ge, Shuzhi Sam ; Chiu, Min-Sen

Author_Institution

Dept. of Chem. & Biomolecular Eng., Nat. Univ. of Singapore

fYear

2005

fDate

27-29 June 2005

Firstpage

286

Lastpage

291

Abstract

In this paper, an adaptive neuro-fuzzy controller is investigated for a class of non-affine nonlinear systems. Firstly, rigorous description and quantification of the approximation error of the neuro-fuzzy controller are discussed. Then a novel updating algorithm to adapt the weights, centers, and widths of the neuro-fuzzy controller is presented based on Lyapunov stability theory. It is shown that the proposed design method is able to guarantee the stability of the closed-loop system and the convergence of the tracking error. Finally, simulation results illustrate the effectiveness of the proposed adaptive neuro-fuzzy control scheme

Keywords

Lyapunov methods; adaptive control; closed loop systems; control system synthesis; fuzzy control; neurocontrollers; nonlinear control systems; stability; Lyapunov stability theory; adaptive neuro-fuzzy control; closed-loop system; nonaffine nonlinear systems; Adaptive control; Approximation error; Control systems; Convergence; Design methodology; Lyapunov method; Nonlinear control systems; Nonlinear systems; Programmable control; Stability;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control, 2005. Proceedings of the 2005 IEEE International Symposium on, Mediterrean Conference on Control and Automation

Conference_Location

Limassol

ISSN

2158-9860

Print_ISBN

0-7803-8936-0

Type

conf

DOI

10.1109/.2005.1467029

Filename

1467029