基于柯西变异粒子群算法的永磁同步电机参数辨识

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Abstract The variation of permanent magnet synchronous motor(PMSM) parameters has an effect on the performance of vector control servo system, so they must to be identified at real time. The stator is equaled to 1st order inertia system and the mathematical model is built under d-q coordinates. A particle swarm optimization(PSO) based on mean best position and Cauchy mutation combined search is proposed and used to identify the resister, inductor and flux linkage of the stator. Both the simulation and the experiment examples demonstrate that the proposed algorithm has powerful optimizing ability, good stability and higher optimizing precision and good performance.

Key words： PMSM parameter identification particle swarm optimization Cauchy mutation

Received: 06 November 2012 Published: 05 November 2014

PACS:

TM315

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	Articles by authors
	Fu Xiaoli
	Gu Hongbing
	Chen Guocheng
	Zou Junzhong
	Zhang Jian

Cite this article:

Fu Xiaoli,Gu Hongbing,Chen Guocheng等. Permanent Magnet Synchronous Motors Parameters Identification Based on Cauchy Mutation Particle Swarm Optimization[J]. Transactions of China Electrotechnical Society, 2014, 29(5): 127-131.

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http://dgjsxb.ces-transaction.com/EN/ OR http://dgjsxb.ces-transaction.com/EN/Y2014/V29/I5/127

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