Robust Adaptive Control of Nonaffine Nonlinear Systems Using Radial Basis Function Neural Networks

Author

Karimi, B. ; Menhaj, M.B. ; Saboori, I.

Author_Institution

Amirkabir Univ. of Technol., Tehran

fYear

2006

fDate

6-10 Nov. 2006

Firstpage

495

Lastpage

500

Abstract

In this paper, the problem of noise rejection for a class of nonaffine nonlinear systems with parameter uncertainty is considered. We develop a neuro adaptive controller with guaranteed stability by introducing a robust adaptive bound based on Lyapunov stability analysis. A radial-basis function type neural network is used in the paper. To show the effectiveness of the proposed controller, the nonlinear Van der Pol oscillator has been chosen as a case study. Simulation results are very promising

Keywords

Lyapunov methods; adaptive control; neurocontrollers; nonlinear control systems; radial basis function networks; relaxation oscillators; robust control; Lyapunov stability analysis; neuro adaptive controller; noise rejection; nonaffine nonlinear systems; nonlinear Van der Pol oscillator; parameter uncertainty; radial basis function neural networks; robust adaptive control; Adaptive control; Lyapunov method; Noise robustness; Nonlinear systems; Programmable control; Radial basis function networks; Robust control; Robust stability; Stability analysis; Uncertain systems; Radial basis neural network (RBNN); nonaffine nonlinear system; robust adaptive control;

fLanguage

English

Publisher

ieee

Conference_Titel

IEEE Industrial Electronics, IECON 2006 - 32nd Annual Conference on

Conference_Location

Paris

ISSN

1553-572X

Print_ISBN

1-4244-0390-1

Type

conf

DOI

10.1109/IECON.2006.347327

Filename

4152871