基于熵权与混合代理模型的永磁驱动器的优化设计
针对永磁驱动器（PMD）的结构设计问题,提出一种基于改进熵权法结合混合代理模型的优化设计方法。首先利用基于交叉验证误差的最优加权法,将响应曲面法、克里金法以及支持向量机回归结合起来,构建PMD的参数变量与响应变量之间的混合代理模型;然后引入改进的熵权法,将PMD的多指标转化为单一综合指标,并建立其优化的数学模型,通过自适应权重粒子群优化算法求解;最后对结果进行有限元仿真分析和实验室仿真平台验证。研究结果表明,所提出的优化设计方法优于其它方法,得到的PMD结构参数合理有效,较好的实现了PMD的多目标优化设计。...
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| Published in | 电机与控制学报 Vol. 20; no. 6; pp. 102 - 108 |
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| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| Published |
东北大学信息科学与工程学院，辽宁沈阳，110004
2016
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1007-449X |
| DOI | 10.15938/j.emc.2016.06.013 |
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| Abstract | 针对永磁驱动器（PMD）的结构设计问题,提出一种基于改进熵权法结合混合代理模型的优化设计方法。首先利用基于交叉验证误差的最优加权法,将响应曲面法、克里金法以及支持向量机回归结合起来,构建PMD的参数变量与响应变量之间的混合代理模型;然后引入改进的熵权法,将PMD的多指标转化为单一综合指标,并建立其优化的数学模型,通过自适应权重粒子群优化算法求解;最后对结果进行有限元仿真分析和实验室仿真平台验证。研究结果表明,所提出的优化设计方法优于其它方法,得到的PMD结构参数合理有效,较好的实现了PMD的多目标优化设计。 |
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| AbstractList | TH133; 针对永磁驱动器（ PMD）的结构设计问题，提出一种基于改进熵权法结合混合代理模型的优化设计方法。首先利用基于交叉验证误差的最优加权法，将响应曲面法、克里金法以及支持向量机回归结合起来，构建PMD的参数变量与响应变量之间的混合代理模型；然后引入改进的熵权法，将PMD的多指标转化为单一综合指标，并建立其优化的数学模型，通过自适应权重粒子群优化算法求解；最后对结果进行有限元仿真分析和实验室仿真平台验证。研究结果表明，所提出的优化设计方法优于其它方法，得到的PMD结构参数合理有效，较好的实现了PMD的多目标优化设计。 针对永磁驱动器（PMD）的结构设计问题,提出一种基于改进熵权法结合混合代理模型的优化设计方法。首先利用基于交叉验证误差的最优加权法,将响应曲面法、克里金法以及支持向量机回归结合起来,构建PMD的参数变量与响应变量之间的混合代理模型;然后引入改进的熵权法,将PMD的多指标转化为单一综合指标,并建立其优化的数学模型,通过自适应权重粒子群优化算法求解;最后对结果进行有限元仿真分析和实验室仿真平台验证。研究结果表明,所提出的优化设计方法优于其它方法,得到的PMD结构参数合理有效,较好的实现了PMD的多目标优化设计。 |
| Abstract_FL | 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 . |
| Author | 李召 王大志 时统宇 郑迪 |
| AuthorAffiliation | 东北大学信息科学与工程学院,辽宁沈阳110004 |
| AuthorAffiliation_xml | – name: 东北大学信息科学与工程学院，辽宁沈阳，110004 |
| Author_FL | WANG Da-zhi ZHENG Di SHI Tong-yu LI Zhao |
| Author_FL_xml | – sequence: 1 fullname: LI Zhao – sequence: 2 fullname: WANG Da-zhi – sequence: 3 fullname: SHI Tong-yu – sequence: 4 fullname: ZHENG Di |
| Author_xml | – sequence: 1 fullname: 李召 王大志 时统宇 郑迪 |
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| Copyright | Copyright © Wanfang Data Co. Ltd. All Rights Reserved. |
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| DocumentTitleAlternate | Optimization design for permanent magnet drive based on entropy-weight and hybrid surrogate model |
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| EndPage | 108 |
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| Keywords | 熵权法 混合代理模型 自适应权重粒子群算法 最优加权法 永磁驱动器 adaptive weight particle swarm optimization particle swarm optimization permanent magnet drive optimal weighting method hybrid surrogate model entropy-weight method |
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| Notes | LI Zhao, WANG Da-zhi, SHI Tong-yu, ZHENG Di （School of Information Science ＆ Engineering, Northeastern University, Shenyang 110004, China） permanent magnet drive; hybrid surrogate model; entropy-weight method ; optimal weighting method ; adaptive weight particle swarm optimization particle swarm optimization Permanent magnet drive （PMD） design problems were studied and an optimization design approach based on hybrid surrogate model and improved entropy-weight was put forward. Firstly by combining 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 optimization （AWPSO） ; Finall |
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| PublicationTitle | 电机与控制学报 |
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| Publisher | 东北大学信息科学与工程学院，辽宁沈阳，110004 |
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| Snippet | 针对永磁驱动器（PMD）的结构设计问题,提出一种基于改进熵权法结合混合代理模型的优化设计方法。首先利用基于交叉验证误差的最优加权法,将响应曲面法、克里金法以及支持向量... TH133; 针对永磁驱动器（ PMD）的结构设计问题，提出一种基于改进熵权法结合混合代理模型的优化设计方法。首先利用基于交叉验证误差的最优加权法，将响应曲面法、克里金法以... |
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| SubjectTerms | 最优加权法 永磁驱动器 混合代理模型 熵权法 自适应权重粒子群算法 |
| Title | 基于熵权与混合代理模型的永磁驱动器的优化设计 |
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