Fuzzy adaptive control of multivariable nonlinear systems

Author

Goléa, Noureddine ; Goléa, Amar

Author_Institution

EE Inst., Oum El-Bouaghi Univ., Oum. El-Bouaghi, Algeria

Volume

1

fYear

2002

fDate

6/24/1905 12:00:00 AM

Firstpage

330

Lastpage

334

Abstract

Based on Takagi-Sugeno (TS) fuzzy systems, we present a direct fuzzy model-following adaptive control for multivariable (MIMO) nonlinear systems. The use of the TS fuzzy systems allows the inclusion of a priori information in terms of qualitative knowledge about the plant operating points or analytical conventional linear regulators. It is proven, using Lyapunov stability, that this adaptive scheme is robust against external disturbance, approximation error and input gain variation, and achieves asymptotic tracking of a stable reference model. The effectiveness of the proposed fuzzy approach is demonstrated, by simulation, on a two-link robot model

Keywords

Lyapunov methods; MIMO systems; feedback; fuzzy control; fuzzy systems; matrix algebra; model reference adaptive control systems; multivariable control systems; nonlinear control systems; position control; robots; robust control; Lyapunov stability; MIMO nonlinear systems; Takagi-Sugeno fuzzy systems; a priori information; analytical conventional linear regulators; direct fuzzy model-following adaptive control; multivariable nonlinear systems; qualitative knowledge; two-link robot model; Adaptive control; Fuzzy control; Fuzzy systems; Information analysis; Lyapunov method; MIMO; Nonlinear systems; Regulators; Robust stability; Takagi-Sugeno model;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems, 2002. FUZZ-IEEE'02. Proceedings of the 2002 IEEE International Conference on

Conference_Location

Honolulu, HI

Print_ISBN

0-7803-7280-8

Type

conf

DOI

10.1109/FUZZ.2002.1005011

Filename

1005011