Parameter identification of induction motors: Least squares vs. genetic algorithms

被引：0

作者：

Alonge, F ^{[1
]}

D'Ippolito, F ^{[1
]}

Raimondi, FM ^{[1
]}

机构：

[1] Univ Palermo, Ist Automat & Sistemist, Fac Engn, I-90128 Palermo, Italy

来源：

MOTION CONTROL (MC'98) | 1999年

关键词：

induction motors; parameter identification; least squares; genetic algorithms;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper deals with Least Square (LS) techniques and Genetic Algorithms (GA) for off-line identification of parameters of induction motors starting from the knowledge of stator currents and voltages and velocity. In view of employing LS algorithms for analytical identification, filtering of experimentally acquired data is performed by anticausal filters. Methods based on GA search for parameters which match at best the input-output behaviour of the motor. Both methods are investigated and compared by means of experiments carried out on a 1-kW induction motor. Copyright (C) 1998 IFAC.

引用

页码：341 / 346

页数：6