Taylor versus fuzzy-bases-function expansions for MRAC

Author

Elshafei, Abdel-Latif

Author_Institution

Dept. of Electr. Eng., United Arab Emirates Univ., Al-Ain, United Arab Emirates

Volume

1

fYear

1998

fDate

1-4 Sep 1998

Firstpage

633

Abstract

The tracking problem for a class of nonlinear systems is investigated. The system is assumed to have a known structure but varying or unknown parameters. In the paper by Yin et al. (1995), a fuzzy model reference adaptive controller (MRAC) is derived. The derivation is extended to handle unstructured uncertainties. Simultaneously, a new MRAC is derived based on Taylor series expansion. The performances of both controllers are checked for various operating conditions including external disturbances and unmodeled dynamics. Output tracking is ensured while parameter tracking is achieved in special cases

Keywords

Lyapunov methods; adaptive control; dynamics; fuzzy control; model reference adaptive control systems; nonlinear systems; series (mathematics); stability; tracking; Lyapunov function; Taylor series; dynamics; fuzzy control; model reference adaptive control; nonlinear systems; stability; tracking; Adaptive control; Context modeling; Fuzzy control; Fuzzy systems; Least squares approximation; Mathematical model; Neural networks; Nonlinear systems; Programmable control; Taylor series;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Applications, 1998. Proceedings of the 1998 IEEE International Conference on

Conference_Location

Trieste

Print_ISBN

0-7803-4104-X

Type

conf

DOI

10.1109/CCA.1998.728582

Filename

728582