基于改进布谷鸟搜索算法的永磁同步电机参数辨识  

The Parameter Identification of Permanent Magnet Synchronous Motor Based on Improved Cuckoo Search Alaorithm

作　　者：吴忠强[1] 杜春奇[1] 张伟[1] 李峰[1] 

机构地区：[1]燕山大学工业计算机控制工程河北省重点实验室,河北秦皇岛066004

出　　处：《计量学报》2017年第5期631-636,共6页Acta Metrologica Sinica

基　　金：国家自然科学基金委员会与宝钢集团有限公司联合资助项目(U1260203);河北省自然科学基金(F2016203006)

摘　　要：提出一种基于改进布谷鸟搜索算法的永磁同步电机参数辨识方法。针对布谷鸟搜索算法的不足,采用基于云隶属度的模糊推理调整巢主鸟发现外来鸟蛋的概率;采用自适应变步长的方法调整Lévy飞行步长。改进后的算法通过增加种群之间的多样性以加快收敛速度,提高了局部和全局寻优能力。永磁同步电机多参数辨识结果表明,改进布谷鸟搜索算法能有效地辨识电机各参数,与未改进算法相比,验证了改进算法的有效性和优越性能。Based on improved cuckoo search algorithm, a kind of parameter identification method of permanent magnet synchronous motor is proposed. In view of the deficiency of cuckoo search algorithm, designing the fuzzy reasoning based on cloud membership to adjust the probability of an alien egg discovered by host nests and using adaptive variable step method to adjust step size of L6vy flights. The improved algorithm can accelerate the convergence speed and improve the local and global optimization ability by increasing the diversity of the population. Permanent magnet synchronous motor muhiparameter identification results show that improved cuckoo algorithm can effectively identify the motor parameters, and compared with the unmodified algorithm, the improved algorithm show the effectiveness and superior performance.

关 键 词：计量学 永磁同步电机 云隶属度 模糊推理 布谷鸟搜索算法 参数辨识 

分 类 号：TB97[一般工业技术—计量学]