• DocumentCode
    2083654
  • Title

    Parameters optimization of fuzzy controller based on PSO

  • Author

    Wang, Dongyun ; Wang, Guan ; Hu, Rong

  • Author_Institution
    Sch. of Electron. Inf., Zhongyuan Univ. of Technol., Zhengzhou, China
  • Volume
    1
  • fYear
    2008
  • fDate
    17-19 Nov. 2008
  • Firstpage
    599
  • Lastpage
    603
  • Abstract
    Pendulum, a natural unstable nonlinear system, is a powerful tool to check the control theory and control algorithm. Fuzzy logic can control nonlinear systems that would be difficult or impossible to model mathematically, which opens the door for controlling systems that would normally be deemed unfeasible for automation. Note that if too many inputs and outputs are chosen for a single implementation since rules defining their interrelations must also be defined defining the rule base quickly becomes complex. In this article, Synthetic error and synthetic error variety is introduced to reduce the input variates and the control rule of fuzzy controller. The performance of the fuzzy controller is sensitive to the variety of scaling factors whose role is to allow the fuzzy controller to match the external world to be controlled. Improved Particle Swarm Optimization is investigated to tune scaling factors of the fuzzy controller for the inverted pendulum.
  • Keywords
    fuzzy control; nonlinear control systems; optimal control; particle swarm optimisation; pendulums; PSO; fuzzy control; fuzzy logic; inverted pendulum; parameters optimization; particle swarm optimization; synthetic error; unstable nonlinear system; Automatic control; Control system synthesis; Control systems; Control theory; Error correction; Fuzzy control; Fuzzy logic; Mathematical model; Nonlinear control systems; Nonlinear systems; improved particle swarm optimization; pendulum on clined rail; scaling factor;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent System and Knowledge Engineering, 2008. ISKE 2008. 3rd International Conference on
  • Conference_Location
    Xiamen
  • Print_ISBN
    978-1-4244-2196-1
  • Electronic_ISBN
    978-1-4244-2197-8
  • Type

    conf

  • DOI
    10.1109/ISKE.2008.4731001
  • Filename
    4731001