• DocumentCode
    3096009
  • Title

    Fuzzy based direct torque control of PMSM drive using an Extended Kalman Filter

  • Author

    Liu, Ying-pei ; Wan, Jian-ru ; Yuan, Chen-hu ; Li, Guang-ye

  • Author_Institution
    Sch. of Electr. Eng. & Autom., Tianjin Univ., Tianjin, China
  • Volume
    2
  • fYear
    2009
  • fDate
    12-15 July 2009
  • Firstpage
    647
  • Lastpage
    651
  • Abstract
    There are big ripples on current and flux linkage and electromagnet torque under traditional direct torque control (DTC) on motor drive system. To solve these problems, fuzzy controller is designed to instead traditional hysteretic comparator, and zero voltage vectors are used to further reduce ripples. Rotor speed is estimated online by extended Kalman filter (EKF) algorithm. Speed sensorless DTC permanent magnet synchronous motor (PMSM) drive is realized. Rapid torque response and strong robustness of DTC are maintained, and the ripples on flux linkage and torque are greatly reduced. Meanwhile, system is robust to motor parameters and load disturbance. The system dynamic and static performances are dramatically improved. The simulation results have verified the feasibility and effectiveness of this method.
  • Keywords
    Kalman filters; control system synthesis; fuzzy control; machine vector control; permanent magnet motors; stability; synchronous motor drives; torque control; velocity control; PMSM drive; current ripple reduction; direct torque control; dynamic performance; electromagnet torque; extended Kalman filter; flux linkage; fuzzy controller design; load disturbance; motor drive system; robustness; rotor speed estimation; speed sensorless DTC permanent magnet synchronous motor drive; static performance; torque response; zero voltage vectors; Couplings; Electromagnets; Fuzzy control; Hysteresis; Motor drives; Permanent magnet motors; Robustness; Sensorless control; Torque control; Voltage control; DTC; EKF; Fuzzy control; PMSM;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2009 International Conference on
  • Conference_Location
    Baoding
  • Print_ISBN
    978-1-4244-3702-3
  • Electronic_ISBN
    978-1-4244-3703-0
  • Type

    conf

  • DOI
    10.1109/ICMLC.2009.5212429
  • Filename
    5212429