Performance of 4 phase SRM for various controllers and optimized using genetic algorithm

Author

Poorani, S.

Author_Institution

Dept. of EEE, Sona Coll. of Technol., Salem, India

fYear

2010

fDate

15-17 June 2010

Firstpage

587

Lastpage

592

Abstract

This paper presents the idea of using the Switched Reluctance Motor (SRM) as an alternative to previously used drives, in wide good and other industrial applications. In order to show the advantage of the SRM, the speed control of a switched reluctance motor (SRM) is designed by blending two artificial intelligence techniques, genetic algorithms and fuzzy PI control. Here the Genetic Algorithm (GA) is used to optimize the rules of fuzzy inference system. The importance of the fuzzy PI controller is highlighted by comparing the performance of various control approaches, including PI control and fuzzy control for speed control of SRM motor drive in terms of rise time, settling time, overshoot and it is optimized using GA.

Keywords

PI control; fuzzy control; fuzzy systems; genetic algorithms; machine control; reluctance motor drives; velocity control; 4 phase SRM; artificial intelligence; fuzzy PI controller; fuzzy inference system; genetic algorithm; motor drive; speed control; switched reluctance motor; Algorithm design and analysis; Artificial intelligence; Electrical equipment industry; Fuzzy control; Fuzzy systems; Genetic algorithms; Pi control; Reluctance machines; Reluctance motors; Velocity control; Genetic Algorithm; PI controller; Switched reluctance motor; fuzzy PI controller; fuzzy logic controller;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Electronics and Applications (ICIEA), 2010 the 5th IEEE Conference on

Conference_Location

Taichung

Print_ISBN

978-1-4244-5045-9

Electronic_ISBN

978-1-4244-5046-6

Type

conf

DOI

10.1109/ICIEA.2010.5517056

Filename

5517056