基于改进布谷鸟搜索算法的永磁同步电机参数辨识

doi:10.3969/j.issn.1000-1158.2017.05.24

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Abstract Based on improved cuckoo search algorithm, a kind of parameter identification method of permanent magnet synchronous motor is proposed. In view of the deficiency of cuckoo search algorithm, designing the fuzzy reasoning based on cloud membership to adjust the probability of an alien egg discovered by host nests and using adaptive variable step method to adjust step size of Lévy flights. The improved algorithm can accelerate the convergence speed and improve the local and global optimization ability by increasing the diversity of the population. Permanent magnet synchronous motor multi-parameter identification results show that improved cuckoo algorithm can effectively identify the motor parameters, and compared with the unmodified algorithm, the improved algorithm show the effectiveness and superior performance.

Key words： metrology permanent magnet synchronous motor cloud membership fuzzy reasoning cuckoo search algorithm parameter identification

Received: 14 December 2015 Published: 11 August 2017

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TB97

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	Articles by authors
	WU Zhong-qiang
	DU Chun-qi
	ZHANG Wei
	LI Feng

Cite this article:

WU Zhong-qiang,DU Chun-qi,ZHANG Wei, et al. The Parameter Identification of Permanent Magnet Synchronous Motor Based on Improved Cuckoo Search Algorithm[J]. Acta Metrologica Sinica, 2017, 38(5): 631-636.

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http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2017.05.24 OR http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2017/V38/I5/631

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