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Optimization design for permanent magnet drive based on entropy-weight and hybrid surrogate model(PDF)

[ISSN:1007-449X/CN:23-1 408/TM]

Issue:
2016年06
Page:
102-107
Research Field:
Publishing date:

Info

Title:
Optimization design for permanent magnet drive based on entropy-weight and hybrid surrogate model
Author(s):
LI Zhao WANG Da-zhi SHI Tong-yu ZHENG Di
( School of Information Science & Engineering,Northeastern University,Shenyang 110004,China)
Keywords:
permanent magnet drive hybrid surrogate model entropy-weight method optimal weighting method adaptive weight particle swarm optimization particle swarm optimization
PACS:
TH 133
DOI:
10. 15938 / j. emc. 2016. 06. 013
Abstract:
Permanent magnet drive ( PMD) design problems were studied and an optimization design ap-proach based on hybrid surrogate model and improved entropy-weight was put forward. Firstly by combi-ning the response surface method ( RSM ) ,Kriging method and support vector machine regression ( SVR) ,a hybrid surrogate model of optimizing parameters and response variables was built,in which the optimal weighting method based on cross validation error is used; Secondly the improved entropy-weight was introduced to transform the multi-indexes of PMD into a single composite one,and the mathematical model was built,which was solved by adaptive weight particle swarm optimization particle swarm optimiza-tion( AWPSO) ; Finally the parameters results were analyzed with finite element method and experimental validation. The results show that the proposed method is superior to other methods,and the structural pa-rameters are reasonable and effective. And the expected results are derived.

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Last Update: 2016-08-20