• DocumentCode
    2067474
  • Title

    Speed Control Based Particle Swarm Optimizing Clonal Algorithm for AC Induction Motor

  • Author

    Qiang, Wang ; Jun, Chen ; Jianxiu, Xiao ; Jian, Sun

  • Author_Institution
    Coll. of Electr. Eng. & Inf. Technol., China Three Gorges Univ., Yichang, China
  • Volume
    1
  • fYear
    2010
  • fDate
    14-15 Aug. 2010
  • Firstpage
    34
  • Lastpage
    37
  • Abstract
    An intelligent optimizing algorithm, particle swarm optimizing clonal algorithm (PSOCA) was introduced in this paper, which combined the clonal selection mechanism of the immune system with the evolution equation of particle swarm optimization. It had the ability of global searching. The PSOCA improves the diversity of antibody population and its convergence speed, by using effectively the past information of the antibodies and their cooperation. Based on the PSOCA, a PID controller (PCA-PID) is designed, which can modify its parameters dynamically to adapt time varying control objects. PCA-PID controller is exerted to control AC speed system, then its control performance is compared with that of the other two controllers designed by PSO and clonal selection algorithm respectively. The simulation results show that PCA-PID has better control performance, compared with the other two controllers.
  • Keywords
    angular velocity control; induction motors; particle swarm optimisation; three-term control; AC induction motor; PID controller; global searching; intelligent optimizing algorithm; particle swarm optimizing clonal algorithm; speed control; Algorithm design and analysis; Control systems; Convergence; Induction motors; Particle swarm optimization; Stators; Torque; AC speed system; PID controller; clone selection; immune system; particle swarm optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Engineering (ICIE), 2010 WASE International Conference on
  • Conference_Location
    Beidaihe, Hebei
  • Print_ISBN
    978-1-4244-7506-3
  • Electronic_ISBN
    978-1-4244-7507-0
  • Type

    conf

  • DOI
    10.1109/ICIE.2010.16
  • Filename
    5571743