Fuzzy model reference adaptive control

Author

Golea, Noureddine ; Golea, Amar ; Benmahammed, Khier

Author_Institution

Electr. Eng. Inst., Oum-El-Bouaghi Univ., Algeria

Volume

10

Issue

4

fYear

2002

fDate

8/1/2002 12:00:00 AM

Firstpage

436

Lastpage

444

Abstract

This paper investigates a fuzzy model reference adaptive controller (FMRAC) for continuous-time multiple-input-multiple-output (MIMO) nonlinear systems. The proposed adaptive scheme uses a Takagi-Seguno (TS) fuzzy adaptive system, which allows for the inclusion of a priori information in terms of qualitative knowledge about the plant operating points or analytical regulators (e.g., state feedback) for those operating points. A proportional-integral update law is used to obtain a fast parameters adaptation. Stability and robustness of this adaptive scheme are established using Lyapunov stability tools. The simulation results, for a two-link robot, confirm the performance of the proposed approach.

Keywords

Lyapunov methods; MIMO systems; fuzzy control; model reference adaptive control systems; multivariable control systems; nonlinear control systems; robust control; two-term control; FMRAC; Lyapunov stability tools; PI update law; TS fuzzy adaptive system; Takagi-Seguno fuzzy adaptive system; Takagi-Sugeno fuzzy adaptive system; analytical regulators; continuous-time MIMO nonlinear systems; continuous-time multiple-input-multiple-output nonlinear systems; fuzzy MRAC; fuzzy model reference adaptive controller; plant operating points; proportional-integral update law; qualitative knowledge; robustness; state feedback; two-link robot; Adaptive control; Adaptive systems; Fuzzy control; Fuzzy systems; Information analysis; MIMO; Nonlinear control systems; Nonlinear systems; Programmable control; Robust stability;

fLanguage

English

Journal_Title

Fuzzy Systems, IEEE Transactions on

Publisher

ieee

ISSN

1063-6706

Type

jour

DOI

10.1109/TFUZZ.2002.800694

Filename

1022865