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论文:2014,Vol:32,Issue(1):111-117 |
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引用本文： |
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宋受俊, 葛乐飞, 蒋艳玲. 基于文化粒子群算法的开关磁阻电机多目标优化设计[J]. 西北工业大学 |
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Song Shoujun, Ge Lefei, Jiang Yanling. Multi-Objective Optimal Design of Switched Reluctance Machine Based on Cultural Particle Swarm Optimization Algorithm[J]. Northwestern polytechnical university |
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| 基于文化粒子群算法的开关磁阻电机多目标优化设计 |
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| 宋受俊, 葛乐飞, 蒋艳玲 |
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| 西北工业大学 自动化学院, 陕西 西安 710072 |
| 摘要: |
| 特殊的结构和控制方法使得开关磁阻电机(SRM)具有多变量、强耦合、高非线性等特点,如何快速而准确的得到最优设计方案一直是研究的热点与难点。首先将粒子群算法(PSO)与文化算法(CA)相结合,构建了文化粒子群优化算法(CPSOA),通过将PSO嵌入到CA架构,实现了不同空间群体的并行进化,提高了PSO的优化精度与效率。然后,采用传统设计方法得到了SRM的初始设计方案,并进行了初步校核。最后,针对一定的目标和约束,以参数对性能的影响模式为基础,利用CPSOA对初始方案进行了优化,得到了关键几何尺寸和控制参数的全局最优解。 |
| 关键词:
开关磁阻电机
优化设计
文化算法
粒子群算法
并行进化
效率
转矩脉动
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| Multi-Objective Optimal Design of Switched Reluctance Machine Based on Cultural Particle Swarm Optimization Algorithm |
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| Song Shoujun, Ge Lefei, Jiang Yanling |
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| Department of Automatic Control, Northwestern Polytechnical University, Xi'an 710072, China |
| Abstract: |
| A switched reluctance machine(SRM) has multiple variables,strong coupling and highly nonlinear characteristics due to its special structure and control method. This paper constructs the cultural particle swarm optimization algorithm(CPSOA) by combining particle swarm optimization(PSO) and cultural algorithm(CA). By embedding the PSO into the CA framework,it realized the parallel evolution of population in different spaces and thus enhances the accuracy and efficiency of the PSO. Then it obtains the initial design scheme of the SRM with the traditional design method and carries out its preliminary tests. Finally,with certain objectives and constraints and on the basis of the parameters' influence mode on performances,it uses CPSOA to optimize the initial design scheme,thus obtaining the globally optimal solutions of key geometric dimensions and control parameters. |
| Key words:
algorithms
efficiency
global optimization
particle swarm optimization (PSO)
cultural algorithm (CA)
optimal design
parallel evolution
switched reluctance machine (SRM)
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| 收稿日期: 2012-05-16
修回日期:
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| DOI: |
| 基金项目: 国家自然科学基金(51107100);教育部博士点基金(20116102120033);陕西省自然科学基金(2011GQ7001);陕西省留学人员科技活动项目择优资助;西北工业大学基础研究基金(JC201119);西北工业大学“翱翔之星”计划资助 |
| 通讯作者:
Email： |
| 作者简介: 宋受俊(1981-),西北工业大学副教授,主要从事电驱动系统性能计算、优化设计及控制方法研究。
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