|本期目录/Table of Contents|

[1]陈振锋,钟彦儒,李洁,等.感应电机参数辨识三种智能算法的比较[J].电机与控制学报,2010,(11):7-12.
 CHEN Zhen-feng,ZHONG Yan-ru,LI Jie.Comparison of three intelligent optimization algorithms for parameter identification of induction motors[J].,2010,(11):7-12.
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《电机与控制学报》[ISSN:1007-449X/CN:23-1 408/TM]

卷:
期数:
2010年11
页码:
7-12
栏目:
出版日期:
2010-11-30

文章信息/Info

Title:
Comparison of three intelligent optimization algorithms for parameter identification of induction motors
作者:
陈振锋; 钟彦儒; 李洁;
西安理工大学自动化与信息工程学院;
Author(s):
CHEN Zhen-feng; ZHONG Yan-ru; LI Jie
School of Automation and Information Engineering; Xi\’an University of Technology; Xi\’an 710048; China
关键词:
感应电机 矢量控制 参数辨识 智能优化算法
Keywords:
induction motors vector control parameter identification intelligent optimization algorithm
分类号:
TM346
DOI:
-
文献标志码:
A
摘要:
针对感应电机参数辨识,采用3种智能优化算法,即遗传算法、蚁群算法、微粒群算法。感应电机的实际输出电流和电气模型的观测电流之间的差值被作为目标函数不断对电气模型中的参数进行更新,从而辨识全部的感应电机参数。变速运行实验是在电机不带负载的情况下进行的。通过实验,对感应电机参数辨识3种智能优化算法进行比较,并得出结论。遗传算法可以得到最准确的电机参数,微粒群算法次之,蚁群算法最差。蚁群算法所需时间最短,遗传算法次之,微粒群算法最长。
Abstract:
Genetic algorithm,ant colony optimization and particle swarm optimization were introduced and applied to the parameter identification of an induction motor for vector control.The errors between the actual stator current output of an induction motor and the stator current output of the model were used as the criterion to correct the model parameters,so as to identify all the parameters of an induction motor.Experiments were conducted on speed-varying operation with no load.The three kinds of optimization alg...

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备注/Memo:
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更新日期/Last Update: 2011-01-11