基于多项优化哈里斯鹰算法的同步电机参数辨识  

Identification of Synchronous Motor Parameters Using Multi-link Improvement Harris Hawks Optimization

作　　者：廖正霖 沈艳霞[1] LIAO Zhenglin;SHEN Yanxia(School of Internet of Things Engineering,Jiangnan University,Wuxi,Jiangsu 21400,China)

机构地区：[1]江南大学物联网工程学院,江苏无锡214000

出　　处：《计量学报》2024年第12期1868-1875,共8页Acta Metrologica Sinica

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。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.

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 

分 类 号：TB971[一般工业技术—计量学]