Fuzzy multiple reference models adaptive control and simulation study

Author

Ji, Zhi-cheng ; Zhu, Rong-Jia ; Shen, Yan-xia

Author_Institution

Inst. of Electr. Autom., Southern Yangtze Univ., Wuxi, China

Volume

5

fYear

2005

fDate

18-21 Aug. 2005

Firstpage

2747

Abstract

A new method of fuzzy multiple reference models adaptive control (FMRMAC) for dealing with significant and unpredictable system parameter variations is presented. In this method, different suitable reference models are chosen by fuzzy rules when changes occurred to the model parameters. A successful application to the speed servo system of dynamic model of brushless DC motor (BLDCM) shows this method works well with high dynamic performance under the condition of command speed change and load torque disturbance.

Keywords

adaptive control; brushless DC motors; fuzzy control; fuzzy logic; servomotors; brushless DC motor; command speed change; dynamic model parameter; dynamic performance; fuzzy multiple reference models adaptive control; fuzzy rules; load torque disturbance; speed servo system; unpredictable system parameter variation; Adaptive algorithm; Adaptive control; Control system synthesis; Control systems; Fuzzy control; Fuzzy logic; Fuzzy systems; Mathematical model; Nonlinear dynamical systems; Power system modeling; BLDCM; Fuzzy selection; Matlab; Multiple reference models adaptive control;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on

Conference_Location

Guangzhou, China

Print_ISBN

0-7803-9091-1

Type

conf

DOI

10.1109/ICMLC.2005.1527410

Filename

1527410