基于比例策略的多目标PSO的感应电机参数辨识

系统仿真学报 ›› 2016, Vol. 28 ›› Issue (7): 1489-1496.

基于比例策略的多目标PSO的感应电机参数辨识

黄松¹, 田娜¹, 王艳¹, 纪志成^1,2

1.江南大学物联网工程学院, 无锡 214122;
2.轻工过程先进控制教育部重点实验室, 无锡 214122

收稿日期:2015-01-12 修回日期:2015-08-22 出版日期:2016-07-08 发布日期:2020-06-04
作者简介:黄松(1984-),男,湖北随州,博士生,研究方向为电机与智能控制;田娜(1983-),女,河北石家庄,博士,研究方向为智能控制技术。
基金资助:
国家自然科学基金(61572238),国家高技术研究发展计划(2014AA041505); 江苏省杰出青年基金(BK20160001)

Study of IM Parameter Identification Using Multi-objective Particle Swarm Optimization with Proportional Guided Strategy

Huang Song¹, Tian Na¹, Wang Yan¹, Ji Zhicheng^1,2

1. School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China;
2. Key Laboratory of Advanced Process Control for Light Industry, Ministry of Education, Wuxi 214122, China

Received:2015-01-12 Revised:2015-08-22 Online:2016-07-08 Published:2020-06-04

摘要/Abstract

摘要： 建立了感应电机多参数多目标辨识模型,提出了一种基于Pareto最优集和比例策略个体最优项的多目标粒子群算法对感应电机参数进行辨识。Pareto最优集不需要考虑各个目标的加权系数,避免了感应电机辨识目标系数选择的主观性,比例策略能更好地平衡从个体最优和全局最优学习经验的能力。通过在Matlab/Simulink中进行验证,结果证明该算法能提高感应电机参数的辨识精度,具有更好的性能。

关键词: 粒子群算法, 个体最优项, 感应电机, 参数辨识, Pareto最优集

Abstract: A multi-parameter and multi-objective identification model of induction motor was established, and a multi-objective particle swarm optimization based on Pareto set and all personal-best positions guided strategy was proposed and applied to the identification model. Not considerring the weighted coefficient of each objective, Pareto set is able to avoid subjective choice of the coefficients of multi-objective identification and proportion strategy with all personal-best positions guided could balance the learning ability from personal-best positions and global-best position. Having verified the performance on Matlab/Simulink, the results show that the proposed algorithm is able to improve parameter identification accuracy, and has a better performance.

Key words: particle swarm optimization, personal-best, induction motor, parameter identification, Pareto set

中图分类号:

TP18
TM85

黄松, 田娜, 王艳, 纪志成. 基于比例策略的多目标PSO的感应电机参数辨识[J]. 系统仿真学报, 2016, 28(7): 1489-1496.

Huang Song, Tian Na, Wang Yan, Ji Zhicheng. Study of IM Parameter Identification Using Multi-objective Particle Swarm Optimization with Proportional Guided Strategy[J]. Journal of System Simulation, 2016, 28(7): 1489-1496.

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