• DocumentCode
    694756
  • Title

    Optimization of PID Parameters Based on Improved Particle-Swarm-Optimization

  • Author

    Xinming Fan ; Jianzhong Cao ; Hongtao Yang ; Xiaokun Dong ; Chen Liu ; Zhendong Gong ; Qingquan Wu

  • Author_Institution
    Xi´an Inst. of Opt. & Precision Mech., Xi´an, China
  • fYear
    2013
  • fDate
    7-8 Dec. 2013
  • Firstpage
    393
  • Lastpage
    397
  • Abstract
    Because the PID parameter settings obtained by classical method fail to achieve the best control performances, this paper proposes an improved particle swarm optimization (IPSO) algorithm with non-linear inertial weight changes and border buffer. Unlike the original PSO, the inertial weight changes instead of linearly. In addition, we provide a border buffer to the slopping-over particles, making them to fall in the explored space of optima to enhance the diversity of the particle swarm. The simulation experiments show that the system whose parameters are optimized by IPSO has better performances. Meanwhile, it proves the effectiveness of the improved particle swarm optimization.
  • Keywords
    nonlinear control systems; particle swarm optimisation; three-term control; IPSO algorithm; PID parameters; improved particle swarm optimization; nonlinear inertial weight; Convergence; Equations; Mathematical model; Optimization; PD control; Particle swarm optimization; Vectors; PID controller; Particle Swarm Optimization; System simulation; parameters tuning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science and Cloud Computing Companion (ISCC-C), 2013 International Conference on
  • Conference_Location
    Guangzhou
  • Type

    conf

  • DOI
    10.1109/ISCC-C.2013.99
  • Filename
    6973624