Genetic algorithm based optimal design of fuzzy logic controller for active magnetic bearings

Author

Reddy, Anand Shivanappa ; Agarwal, Praveen Kumar ; Chand, Satish

Author_Institution

Dept. of Mech. Eng., MNNIT, Allahabad, India

fYear

2014

Firstpage

1

Lastpage

6

Abstract

The performance of fuzzy logic controller (FLC) depends on the experts´ knowledge for tuning its parameters. In the present work to automate this process, genetic algorithm (GA) based optimized FLC design is proposed. FLC is designed for the contactless active magnetic bearing (AMB) having nonlinear characteristics. Membership functions of FLC are tuned by GA based optimization process. The performance of the optimized FLC is compared with PD controller and manually tuned FLC for various initial displaced positions of the AMB rotor.

Keywords

control system synthesis; fuzzy control; genetic algorithms; magnetic bearings; magnetic variables control; nonlinear control systems; AMB; FLC; GA; active magnetic bearing; fuzzy logic controller design; genetic algorithm; membership function; nonlinear characteristic; parameter tuning; Genetic algorithms; Niobium; Rotors; Sociology; Statistics; Steady-state; Tuning; Active magnetic bearing; fuzzy logic controller; genetic algorithms; optimization;

fLanguage

English

Publisher

ieee

Conference_Titel

Power, Control and Embedded Systems (ICPCES), 2014 International Conference on

Print_ISBN

978-1-4799-5910-5

Type

conf

DOI

10.1109/ICPCES.2014.7062812

Filename

7062812