DocumentCode :
2317328
Title :
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
Link To Document :
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