Intelligent control for permanent magnet synchronous motor with improved particle swarm optimization

  • Authors:

  • Song Zhengqiang;Hou Zhijian;Jiang Chuanwen

  • Affiliations:

  • School of Electronics, Information and Electrical Engineering, Shanghai Jiaotong University, Shanghai, China;School of Electronics, Information and Electrical Engineering, Shanghai Jiaotong University, Shanghai, China;School of Electronics, Information and Electrical Engineering, Shanghai Jiaotong University, Shanghai, China

  • Venue:
  • ISTASC'05 Proceedings of the 5th WSEAS/IASME International Conference on Systems Theory and Scientific Computation
  • Year:
  • 2005

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Abstract

This paper presents a new intelligent controller for a permanent-magnet synchronous machine in a HEV (hybrid-electric vehicle) application. IPSO (Improved Particle Swarm Optimization) will be used to optimize three proportional parameters ka, kb, ku of FLC (Fuzzy Logical Controller) online increasing the robustness of overall system. Finally, the overall system will be simulated under various operating conditions. The use of IPSO as an optimization algorithm makes the drive robust, with faster dynamic response, higher accuracy and intensitive to load variation. The system is tested using a step change signal of load. The simulation results show good dynamic response with fast recovery time.