|本期目录/Table of Contents|

[1]石建飞,戈宝军,吕艳玲,等. 永磁同步电机在线参数辨识方法研究[J].电机与控制学报,2018,22(03):17-24.[doi:10.15938/j.emc.2018.03.003]
 SHI Jian-fei,GE Bao-jun,L Yan-ling,et al. Research of parameter identification of permanent magnetsynchronous motor on line[J].,2018,22(03):17-24.[doi:10.15938/j.emc.2018.03.003]
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《电机与控制学报》[ISSN:1007-449X/CN:23-1 408/TM]

卷:
22
期数:
2018年03
页码:
17-24
栏目:
出版日期:
2018-03-15

文章信息/Info

Title:
 Research of parameter identification of permanent magnetsynchronous motor on line
作者:
 石建飞12 戈宝军1 吕艳玲1 韩继超1
 ( 1. 哈尔滨理工大学 电气与电子工程学院,黑龙江 哈尔滨 150080;2. 黑龙江八一农垦大学 信息技术学院,黑龙江 大庆 163319)
Author(s):
 SHI Jian-fei12 GE Bao-jun1 L Yan-ling1 HAN Ji-chao1
  (1. School of Electrical and Electronic Engineering,Harbin University of Science and Technology,Harbin 150080,China;2. College of Information Technology,Heilongjiang Bayi Agricultural University,Daqing 163319,China)
关键词:
永磁同步电机 参数辨识 折息递推最小二乘 数据饱和
Keywords:
 permanent magnet synchronous motors parameter identification discount recursive leastsquare data saturation
分类号:
TM341
DOI:
10.15938/j.emc.2018.03.003
文献标志码:
A
摘要:
 针对在永磁同步电机参数辨识过程中,由于“数据饱和”和噪声影响,导致传统的递推最小二乘法存在参数估计误差大和收敛慢的问题。利用改进的递推最小二乘法提高参数辨识的精度和收敛速度,以满足伺服系统在不同工况下动态性能。首先,结合永磁同步电机数学模型,设计了一种折息递推最小二乘辨识算法,通过在传统的最小二乘法中引入“折息因子”增强了算法的灵活性。然后,通过对存在白噪声干扰的永磁同步电机模型进行辨识算法的动态仿真。最后,利用搭建的实验测试平台进行算法的实验验证。仿真和实验结果表明提出的折息递推最小二乘算法,在参数辨识过程中降低了旧数据对辨识结果的影响,增强了算法对噪声干扰的鲁棒性,提高参数辨识结果的准确性和实时性。
Abstract:
 n the process of parameter identification of permanent magnet synchronous motor,due to theinfluence of data saturation and noise,the traditional recursive least squares has the problems of high er-ror and slow convergence in the parameter estimation. Using the improved recursive least squares algo-rithm can improve the identification accuracy and rate of convergence,thus meet the dynamic perform-ance of servo system under different working conditions. First of all,combined with the mathematicalmodel of the permanent magnet synchronous motor,a discount recursive least squares identification algo-rithm was designed,and the flexibility of the algorithm was enhanced by introducing the “discount fac-tor”in the traditional recursive least square. Then,dynamic simulation of identification algorithm wasfinished of the motor with white noise model. Finally,
experiments were carried out using the experimen-tal test platform. The simulation and experimental results show that the discount recursive least squaresalgorithm effectively reduce the influence of old data on the identification results and enhances the robust-ness to noise interference,and improves the accuracy of parameters identification and real time.

参考文献/References:

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备注/Memo

备注/Memo:
 收稿日期: 2017 - 07 - 13
基金项目: 国家自然科学基金( 51407049) ; 黑龙江省青年科学基金( QC2016066)
作者简介: 石建飞( 1975—) ,男,博士研究生,研究方向为风力发电机系统及其控制;
戈宝军( 1960—) ,男,博士,教授,博士生导师,研究方向为大电机设计与特种电机设计;
吕艳玲( 1975—) ,女,博士,副教授,研究方向为大型电机及其系统运行分析;
韩继超( 1986—) ,男,博士,讲师,研究方向为大型电机内电磁、发热和通风冷却
更新日期/Last Update: 2018-06-30