• DocumentCode
    115164
  • Title

    Reduced-order fuzzy modeling for nonlinear switched systems

  • Author

    Xiaojie Su ; Peng Shi ; Ligang Wu ; Lixian Zhang ; Yuxin Zhao

  • Author_Institution
    Coll. of Autom., Chongqing Univ., Chongqing, China
  • fYear
    2014
  • fDate
    15-17 Dec. 2014
  • Firstpage
    3627
  • Lastpage
    3630
  • Abstract
    In this paper, the problem of model approximation is investigated for T-S fuzzy switched system with stochastic disturbance. For a high-order considered system, our attention is focused on the construction of a reduced-order model, which not only approximates the original system well with a Hankel-norm performance but also translates it into a lower-dimensional linear switched system. By average dwell time approach and the piecewise Lyapunov function technique, a sufficient condition is first proposed to guarantee the mean-square exponential stability with a Hankel-norm error performance for the error system. The model approximation is then converted into a convex optimization problem by using a linearization procedure.
  • Keywords
    Lyapunov methods; asymptotic stability; convex programming; fuzzy control; linear systems; linearisation techniques; nonlinear control systems; reduced order systems; stochastic systems; Hankel-norm error performance; Hankel-norm performance; T-S fuzzy switched system; Takagi-Sugeno system; average dwell time approach; convex optimization; linearization procedure; lower-dimensional linear switched system; mean-square exponential stability; model approximation; nonlinear switched systems; piecewise Lyapunov function technique; reduced-order fuzzy modeling; stochastic disturbance; sufficient condition; Approximation methods; Educational institutions; Reduced order systems; Stochastic processes; Switched systems; Switches;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on
  • Conference_Location
    Los Angeles, CA
  • Print_ISBN
    978-1-4799-7746-8
  • Type

    conf

  • DOI
    10.1109/CDC.2014.7039953
  • Filename
    7039953