• DocumentCode
    2989926
  • Title

    Intelligent Neural Sliding Control for Planetary Gear Type Inverted Pendulum Mechanism

  • Author

    Huang, Y.J. ; Hsu, C.Y. ; Kuo, T.C. ; Lin, J.

  • Author_Institution
    Yuan Ze Univ., Jung-Li
  • fYear
    2007
  • fDate
    1-3 Oct. 2007
  • Firstpage
    493
  • Lastpage
    498
  • Abstract
    An intelligent neural sliding controller is developed for planetary train type inverted pendulum mechanism. The control methodology is based on the sliding mode control. The switching function in the normal control law is replaced with a bipolar sigmoid function. A fuzzy neural network is used to identify the pendulum dynamics. Adaptive tuning law is derived. The bipolar sigmoid function is thus adjusted according to the result of the identification process.
  • Keywords
    adaptive control; control system synthesis; fuzzy control; fuzzy neural nets; gears; neurocontrollers; nonlinear control systems; pendulums; variable structure systems; adaptive tuning law; bipolar sigmoid function; fuzzy neural network; intelligent neural sliding mode control; planetary train type gear inverted pendulum; Control systems; Friction; Fuzzy control; Fuzzy neural networks; Gears; Intelligent control; Planets; Robust control; Servomotors; Sliding mode control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control, 2007. ISIC 2007. IEEE 22nd International Symposium on
  • Conference_Location
    Singapore
  • ISSN
    2158-9860
  • Print_ISBN
    978-1-4244-0440-7
  • Electronic_ISBN
    2158-9860
  • Type

    conf

  • DOI
    10.1109/ISIC.2007.4450935
  • Filename
    4450935