|本期目录/Table of Contents|

[1]林国汉,章兢,刘朝华,等. 改进综合学习粒子群算法的PMSM参数辨识[J].电机与控制学报,2015,19(01):51-57.[doi:10. 15938/j. emc.2015.01.008]
 LIN Guo-han ZHANG Jing LIU Zhao-hua ZHAO Kui-yin. Parameter identification of PMSM using improved comprehensivelearning particle swarm optimization[J].,2015,19(01):51-57.[doi:10. 15938/j. emc.2015.01.008]
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 改进综合学习粒子群算法的PMSM参数辨识(PDF)
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《电机与控制学报》[ISSN:1007-449X/CN:23-1 408/TM]

卷:
19
期数:
2015年01
页码:
51-57
栏目:
出版日期:
2015-01-15

文章信息/Info

Title:
 Parameter identification of PMSM using improved comprehensive
learning particle swarm optimization
作者:
 林国汉 12章兢 1刘朝华3赵葵银2
 1.湖南大学 电气与信息工程学院,湖南长沙410082 ; 2湖南工程学院电气信息学院,湖南湘潭411101;
3.湖南科技大学 信息与电气工程学院 湖南 湘潭 411201
Author(s):
 LIN Guo-han 1’2ZHANG Jing 1LIU Zhao-hua 3ZHAO Kui-yin 2
 1. College of Electrical and Information Engineering, Hunan University,Changsha 410082,China;
2. College of Information and Electrical Engineering, Hunan Institute of Engineering, Xiangtan 411101,China;
3. School of Electrical&Information Engineering, Hunan University of Science and Technology,Xiangtan 411201,China
关键词:
 参数辨识永磁同步电机粒子群优化算法高斯扰动增长率算子
Keywords:
 Keywords:parameter identificationpermanent magnet synchronous motor particle swarm optimizationGaussian disturbancegrowth operator
分类号:
TM 341 , TM 351
DOI:
10. 15938/j. emc.2015.01.008
文献标志码:
A
摘要:
摘要:为了解决永磁同步电机(permanent magnet synchronous motor, PMSM)多参数辨识问题,提
出一种改进综合学习粒子群优化算法。针对综合学习粒子群算法后期搜索效率低的缺陷,所提算
法引入反映粒子状态的增长率算子,通过该算子动态调整综合学习粒子群算法的关键参数,并根据
增长率算子判断种群中粒子所处状态,对处于停滞状态的粒子实施高斯扰动,使粒子能在解空间中
进行有效搜索。将所提改进算法应用于永磁同步电机多参数辨识,该方法仅需采样电机的定子电
流、电压和转速信号。实验结果表明,改进综合学习粒子群优化方法能够准电阻,d轴和q轴电感和永磁体磁链等参数。
Abstract:
 Abstract:An improved compressive particle swarm optimization algorithm(ICLPSO)for identification of
the permanent magnet synchronous motor( PMSM) parameters was proposed. Aiming at the drawback of
CLPSO,in the proposed algorithm the growth operator was introduced,with which changed the value of
acceleration coefficient dynamically and judged the statue of particles. Using Gaussian disturbance,the
particles in stagnant state effectively search in the solution space. The ICLPSO was employed to identify
the parameters permanent magnet synchronous motor( PMSM).The proposed method needs only to sam-
ple and to store the data of the motor stator current, voltage and rotor speed. Experimental results on
PMSM electrical parameter identification show that the proposed method accurately identifies the stator re-
sistance,d-axis inductance,q-axis inductance and the permanent magnet flux.

参考文献/References:

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备注/Memo

备注/Memo:
 基金项目:国家自然科学基金(61174140);中国博士后面上基金(2013 M540628 ) ;湖南省重点实验室开放基金(10K017)
更新日期/Last Update: 2015-07-21