• DocumentCode
    1875669
  • Title

    A min-max control synthesis for uncertain nonlinear systems based on fuzzy T-S model

  • Author

    Kolemishevska-Gugulovska, T. ; Stankovski, Mile ; Rudas, Imre J. ; Nan Jiang ; Juanwei Jing

  • Author_Institution
    Fac. of Electr. Eng. & Inf. Technol., SS Cyril & Methodius Univ. in Skopje, Skopje, Macedonia
  • fYear
    2012
  • fDate
    6-8 Sept. 2012
  • Firstpage
    303
  • Lastpage
    310
  • Abstract
    The min-max robust control synthesis for uncertain nonlinear systems is solved using Takagi-Sugeno fuzzy model and fuzzy state observer. Existence conditions are derived for the output feedback min-max control in the sense of Lyapunov asymptotic stability and formulated in terms of linear matrix inequalities. The convex optimization algorithm is used to obtain the minimum upper bound on performance and the optimum parameters of mini-max controller. The close-loop system is asymptotically stable under the worst case disturbances and uncertainty. Benchmark of inverted pendulum plant is used to demonstrate the robust performance within a much larger equilibrium region of attraction achieved by the proposed design.
  • Keywords
    Lyapunov methods; asymptotic stability; closed loop systems; control system synthesis; convex programming; feedback; fuzzy control; linear matrix inequalities; minimax techniques; nonlinear control systems; observers; pendulums; robust control; uncertain systems; Lyapunov asymptotic stability; Takagi-Sugeno fuzzy model; asymptotically stable; close-loop system; convex optimization algorithm; equilibrium region of attraction; fuzzy T-S model; fuzzy state observer; inverted pendulum plant; linear matrix inequality; min-max control synthesis; min-max robust control synthesis; mini-max controller; minimum upper bound; optimum parameters; output feedback min-max control; robust performance; uncertain nonlinear systems; uncertainty; worst case disturbances; Asymptotic stability; Bismuth; Control systems; Mathematical model; Nonlinear systems; Observers; Uncertainty; Fuzzy T-S models; fuzzy observer; nonlinear systems; optimum intelligent control; robust control; uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems (IS), 2012 6th IEEE International Conference
  • Conference_Location
    Sofia
  • Print_ISBN
    978-1-4673-2276-8
  • Type

    conf

  • DOI
    10.1109/IS.2012.6335234
  • Filename
    6335234