PSO-based evolutionary optimization for parameter identification of an induction motor

被引：15

作者：

Karimi, Ali ^{[1
]}

Choudhry, Muhammad A. ^{[1
]}

Feliachi, Ali ^{[1
]}

机构：

[1] W Virginia Univ, Adv Power & Elect Res Ctr, Morgantown, WV 26506 USA

来源：

2007 39TH NORTH AMERICAN POWER SYMPOSIUM, VOLS 1 AND 2 | 2007年

关键词：

induction motor; Particle Swarm Optimization; constriction factor; parameter identification; nonlinear least squares;

D O I：

10.1109/NAPS.2007.4402380

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

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.

引用

页码：659 / 664

页数：6

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