• DocumentCode
    2270674
  • Title

    Particle Swarm Optimizing Clonal Algorithm to Design an Intellegent PID Controller with Application to 3-2-1 Stewart Platform

  • Author

    Sun, Jian ; Ding, Yong-Sheng ; Hao, Kuang-Rong

  • Author_Institution
    Coll. of Inf. Sci. & Techenology, Donghua Univ., Shanghai
  • Volume
    3
  • fYear
    2008
  • fDate
    20-22 Dec. 2008
  • Firstpage
    627
  • Lastpage
    632
  • Abstract
    An intelligent optimizing algorithm, particle swarm optimizing clonal algorithm (PSOCA) is introduced in this paper, which combines the clonal selection mechanism of the immune system with the evolution equation of particle swarm optimization. It has 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 (PSOCA-PI) is designed, which can modify its parameters dynamically to adapt time varying control objects. PSOCA-PID controller is exerted to control 3-2-1Stewart platform, 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 PSOCA-PID has better control performance, compared with the other two controllers.
  • Keywords
    control system synthesis; manipulators; particle swarm optimisation; three-term control; time-varying systems; 3-2-1 Stewart platform; evolution equation; global searching; intelligent PID controller design; particle swarm optimizing clonal algorithm; Algorithm design and analysis; Control systems; Delay effects; Design optimization; Equations; Immune system; Particle swarm optimization; Sliding mode control; Three-term control; Zinc; PID controller; Stewart platform; clone selection; immune system; particle swarm optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Information Technology Application, 2008. IITA '08. Second International Symposium on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-0-7695-3497-8
  • Type

    conf

  • DOI
    10.1109/IITA.2008.387
  • Filename
    4740074