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计量学报  2024, Vol. 45 Issue (12): 1868-1875    DOI: 10.3969/j.issn.1000-1158.2024.12.17
  电磁学计量 本期目录 | 过刊浏览 | 高级检索 |
基于多项优化哈里斯鹰算法的同步电机参数辨识
廖正霖,沈艳霞
江南大学物联网工程学院,江苏 无锡 214000
Identification of Synchronous Motor Parameters Using Multi-link Improvement Harris Hawks Optimization
LIAO Zhenglin,SHEN Yanxia
School of Internet of Things Engineering, Jiangnan University, Wuxi, Jiangsu 21400, China
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摘要 针对永磁同步电机(PMSM)参数辨识领域的传统方法存在难以同时辨识多参数、辨识精度不够高等问题,提出一种参数辨识算法。该算法中采用了哈里斯鹰优化算法。为了提高参数辨识的准确度和稳定性,从3个方面对哈里斯鹰算法进行改进:首先,从种群的初始化方向引入Logistic混沌映射来初始化鹰群的位置,增加种群的多样性,加快辨识算法的收敛速度;其次,从鹰群位置更新的角度考虑,通过随机反向学习策略优化鹰群中位置最差个体,使算法的模糊性和随机性提高,增强全局搜索性能,使辨识结果更精确;最后,为了防止过早收敛,将目前的最佳个体位置保留进入下一次迭代,改善传统哈里斯鹰算法易陷入局部最优和精度下降的问题。在基于PMSM电压方程建立的数学模型基础上,将多项优化的哈里斯鹰算法(MIHHO)和标准哈里斯鹰算法(HHO)、粒子群算法(PSO)以及麻雀搜索算法(SSA)进行测试。经过仿真和实验证明,MIHHO对于PMSM参数辨识具有更加优秀的稳定性、收敛速度以及更高的辨识精度。
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廖正霖
沈艳霞
关键词 电学测量永磁同步电机哈里斯鹰算法参数辨识Logistic混沌映射随机反向学习策略    
Abstract:Aiming at the problems of the traditional methods in the field of parameter identification of permanent magnet synchronous motor (PMSM),it is difficult to identify multiple parameters at the same time and the identification accuracy is not high enough,parameter identification algorithm is proposed,in which the Harris Eagle optimization algorithm is adopted.In order to improve the accuracy and stability of the identification algorithm,this thesis improves the Harris Eagle algorithm from three aspects:First,the position of the eagle colony is initialized by introducing Logistic chaotic mapping from the direction of population initialization,increasing the diversity of the population and speeding up the convergence of the identification algorithm.Secondly,from the perspective of eagle position update,the random reverse learning strategy is used to optimize the worst position individual in the eagle group,so as to improve the fuzziness and randomness of the algorithm,enhance the global search performance,and make the identification results more accurate.Finally,in order to prevent premature convergence,the current optimal individual position is retained into the next iteration to improve the problem that the traditional Harris Eagle algorithm is prone to local optimization and precision decline.On the basis of the mathematical model based on PMSM voltage equation,MIHHO algorithm and standard Harris Eagle algorithm (HHO),particle swarm optimization (PSO) and Sparrow search algorithm (SSA) are tested.The results show that MIHHO algorithm has better stability,convergence speed and higher identification accuracy for PMSM parameter identification.
Key wordselectrical measurement    permanent magnet synchronous motor    Harris hawks optimization    parameter identification    Logistic chaotic mapping    random reverse learning strategy
收稿日期: 2024-03-16      发布日期: 2024-12-18
PACS:  TB971  
通讯作者: 沈艳霞(1973-),江苏无锡人,江南大学博士生导师,主要从事高性能电机驱动控制研究。Email: shenyx@jiangnan.edu.cn     E-mail: shenyx@jiangnan.edu.cn
作者简介: 廖正霖(1996-),江西赣州人,江南大学硕士研究生,研究方向为电力电子与电力传动。Email: 1271317770@qq.com
引用本文:   
廖正霖,沈艳霞. 基于多项优化哈里斯鹰算法的同步电机参数辨识[J]. 计量学报, 2024, 45(12): 1868-1875.
LIAO Zhenglin,SHEN Yanxia. Identification of Synchronous Motor Parameters Using Multi-link Improvement Harris Hawks Optimization. Acta Metrologica Sinica, 2024, 45(12): 1868-1875.
链接本文:  
http://jlxb.china-csm.org:81/Jwk_jlxb/CN/10.3969/j.issn.1000-1158.2024.12.17     或     http://jlxb.china-csm.org:81/Jwk_jlxb/CN/Y2024/V45/I12/1868
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