PSO-based Evolutionary Optimization for Parameter Identification of an Induction Motor

Author

Karimi, Ali ; Choudhry, Muhammad A. ; Feliachi, Ali

Author_Institution

West Virginia Univ., Morgantown

fYear

2007

fDate

Sept. 30 2007-Oct. 2 2007

Firstpage

659

Lastpage

664

Abstract

In this paper a particle swarm optimization (PSO) algorithm with a constriction factor is applied to identify the parameters of an induction motor. The variables used to estimate electrical and mechanical parameters are the measured stator currents and voltages. Performance of the identification scheme is demonstrated through simulation and compared with parameters obtained with a nonlinear least square technique. The estimated parameters compare well with the actual parameters.

Keywords

induction motors; least squares approximations; parameter estimation; particle swarm optimisation; evolutionary optimization; induction motor; nonlinear least square technique; parameter identification; particle swarm optimization algorithm; Evolutionary computation; Genetic algorithms; Induction motors; Least squares methods; Motor drives; Parameter estimation; Particle swarm optimization; Stators; Testing; Voltage; Constriction Factor; Induction Motor; Nonlinear Least Squares; Parameter Identification; Particle Swarm Optimization;

fLanguage

English

Publisher

ieee

Conference_Titel

Power Symposium, 2007. NAPS '07. 39th North American

Conference_Location

Las Cruces, NM

Print_ISBN

978-1-4244-1726-1

Electronic_ISBN

978-1-4244-1726-1

Type

conf

DOI

10.1109/NAPS.2007.4402380

Filename

4402380