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山东大学学报(工学版) ›› 2018, Vol. 48 ›› Issue (1): 112-116.doi: 10.6040/j.issn.1672-3961.0.2015.403

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基于在线粒子群优化方法的IPMSM驱动电流和速度控制器

宋正强1,杨辉玲1,肖丹2   

  1. 1. 扬州市职业大学电气与汽车工程学院, 江苏 扬州 2250092; 2. 新南威尔士大学电子工程系, 悉尼 00098G, 澳大利亚
  • 收稿日期:2015-12-04 出版日期:2018-02-20 发布日期:2015-12-04
  • 作者简介:宋正强(1974— ),男,湖北宜城人,副教授,博士,主要研究方向为电气工程与电机控制.E-mail:13270561735@163.com
  • 基金资助:
    江苏省中青年骨干教师海外留学基金资助项目

Current and speed controllers driven by IPMSM based on online particle swarm optimization method

SONG Zhengqiang1, YANG Huiling1, XIAO Dan2   

  1. 1. School of Electrical and Automotive Engineering, Yangzhou Polytechnic College, Yangzhou 225009, Jiangsu, China;
    2. Department of Electronic Engineering, University of New South Wales, Sydney 00098G, Austrilia
  • Received:2015-12-04 Online:2018-02-20 Published:2015-12-04

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摘要： 利用在线粒子群优化方法(particle swarm optimization, PSO)设计内埋式永磁同步电动机(interior permanent magnet synchronous motor, IPMSM)电流和速度控制器。在该驱动系统中,空间矢量调制技术产生两电平逆变器开关控制信号。为了更加真实地模拟实际运行环境,仿真试验中考虑了逆变器的非线性特性,如死区时间、触发信号门槛值以及开关器件的电压降落。电机驱动系统中的PI控制器参数采用在线PSO算法进行实时调节,采样周期设为100 μs,硬件试验平台为DSPACE1104,且优化的目标函数值可以根据系统的动态和静态运行情况而改变。指令信号采用一阶阶跃信号。将PSO算法与传统的PI控制方法进行仿真和试验比较,结果表明采用PSO方法具有更好的鲁棒性和动态特性。

关键词: 智能控制, 永磁同步电机, 在线粒子群优化

Abstract: A novel online particle swarm optimization method was proposed to design speed and current controller of vector controlled interior permanent magnet synchronous motor. In the proposed drive system, the space vector modulation technique was employed to generate the switching signals for a two-level voltage-source inverter. In order to simulate the system in the practical condition, the non-linearity of the inverter was also taken into account due to the dead-time, threshold and voltage drop of the switching devices. Speed and PI current controller gains were optimized with PSO online, sampling period was 100 μs, hardware test platform was DSPACE1104, and the fitness function was changed according to the system dynamic and steady states. The proposed optimization algorithm was compared with conventional PI control method in the condition of step speed change and stator resistance variation, which showed that the proposed online optimization method had better robustness and dynamic characteristics compared with conventional PI controller design.

Key words: online PSO, permanent magnet synchronous motor, intelligent control

中图分类号: 

  • TM351
[1] 祁春清,宋正强. 基于粒子群优化模糊控制器永磁同步电机控制J]. 中国电机工程学报,2006, 26(17):158-162. QI Chunqing, SONG Zhengqiang. Controlling of permanent-magnet synchronous machine based on particle swarm optimization fuzzy logical controller[J]. Proceedings of the Chinese Society for Electrical Engineering, 2006, 26(17):158-162.
[2] RAHAM M F, HAQUE M E, TANG L, et al. Problems associated with the direct torque control of an interior permanent-magnet synchronous motor drive and their remedies[J]. IEEE Transactions on Industrial Electronics, 2004, 51(4):799-809.
[3] LIU Wenxin, LIU Li, CHUNG Il-Yop, et al. Real-time particle swarm optimization based parameter identification applied to permanent magnet synchronous machine[J]. Applied Soft Computing, 2011, 11(2):2556-2564.
[4] KENNEDY J, EBERHART E. Particle swarm optimization [J]. IEEE International Conference on Neural Networks, 1995, 4(8):1942-1948.
[5] YAN Shuai, XU Dianguo, GUI Xianguo,et al. Online particle swarm optimization design of speed controller considering anti-windup for pmsm drive system[C] //IEEE Annual Power Electronics Specialists Conference. New York, USA: IEEE, 2007:2273-2277.
[6] LIN F J, LIN C H. On-line gain-tuning IP controller using RFNN[J]. IEEE Transactions on Aerospace & Electronic System, 2001, 37(2):655-670.
[7] MOHAMED ARI. Adaptive self-tuning speed control for permanent-magnet synchronous motor drive with dead time[J]. IEEE Transactions on Energy Conversion, 2007, 21(4):855-862.
[8] LIDOZZI A SOLERO L CRESCIMBINI F, et al. Direct tuning strategy for speed controlled PMSM drives[C] //IEEE International Symposium on Industrial Electronics. New York, USA: IEEE, 2010:1265-1270.
[9] LEE S B. Closed-loop estimation of permanent magnet synchronous motor parameters by PI controller gain tuning[J]. IEEE Transactions on Energy Conversion, 2007, 21(4):863-870.
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