• DocumentCode
    3119430
  • Title

    Passive fuzzy control for uncertain nonlinear stochastic inverted pendulum robot system

  • Author

    Chang, Wen-Jer ; Jheng, Sin-Sian ; Ku, Cheung-Chieh

  • Author_Institution
    Dept. of Marine Eng., Nat. Taiwan Ocean Univ., Keelung, Taiwan
  • fYear
    2011
  • fDate
    27-30 June 2011
  • Firstpage
    2213
  • Lastpage
    2218
  • Abstract
    This paper presents a passive fuzzy controller design method for stabilizing the uncertain nonlinear stochastic inverted pendulum robot system. Through Takagi-Sugeno (T-S) fuzzy modeling approach, the complex nonlinear properties can be described by combining several linear sub-systems and determined membership functions. The Ito stochastic differential equation is employed to represent dynamics of systems in this paper. Applying the modeling approach, the T-S fuzzy model with multiplicative noise can be built for describing the nonlinear stochastic system. Besides, the uncertainties of the controlled system are considered in this paper for dealing with molding errors and varying parameters. Hence, the robust control problem is also discussed and investigated in this paper. Finally, the numerical simulations are proposed to show the effectiveness of the present design approach.
  • Keywords
    control system synthesis; differential equations; fuzzy control; nonlinear control systems; pendulums; robots; robust control; stochastic systems; uncertain systems; Ito stochastic differential equation; T-S fuzzy model; Takagi-Sugeno fuzzy modeling approach; nonlinear stochastic system; passive fuzzy control; robust control problem; uncertain nonlinear stochastic inverted pendulum robot system; Asymptotic stability; Mathematical model; Noise; Robots; Robustness; Stability analysis; Stochastic processes; T-S fuzzy model; multiplicative noise; passive; uncertain;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems (FUZZ), 2011 IEEE International Conference on
  • Conference_Location
    Taipei
  • ISSN
    1098-7584
  • Print_ISBN
    978-1-4244-7315-1
  • Electronic_ISBN
    1098-7584
  • Type

    conf

  • DOI
    10.1109/FUZZY.2011.6007460
  • Filename
    6007460