• DocumentCode
    2904908
  • Title

    Stability analysis of T-S fuzzy-model-based control systems using fuzzy Lyapunov function

  • Author

    Lam, H.K. ; Narimani, M. ; Lai, J.C.Y. ; Leung, F.H.F.

  • Author_Institution
    Div. of Eng., King´´s Coll. London, London
  • fYear
    2008
  • fDate
    1-6 June 2008
  • Firstpage
    931
  • Lastpage
    938
  • Abstract
    This paper investigates the system stability of T-S fuzzy-model-based control systems based on an improved fuzzy Lyapunov function. Various non-PDC (parallel distribution compensation) fuzzy controllers are proposed to close the feedback loop. The characteristic of T-S fuzzy model is considered to facilitate the stability analysis. Under a particular case, the time-derivative information of the membership functions vanishes, which simplifies the stability analysis and leads to relaxed stability analysis results. A general case is then considered. An improved non-PDC fuzzy controller is proposed based on the properties of the T-S fuzzy model. The improved non-PDC fuzzy controller exhibits a favourable property to relax the stability conditions. Based on the fuzzy Lyapunov function, stability conditions in terms of linear matrix inequalities are derived to guarantee the system stability. Simulation examples are given to illustrate the effectiveness of the proposed non-PDC fuzzy control schemes.
  • Keywords
    Lyapunov methods; closed loop systems; compensation; feedback; fuzzy control; linear matrix inequalities; stability; T-S fuzzy model; control system; feedback closed loop; fuzzy Lyapunov function; linear matrix inequality; nonPDC fuzzy controller; parallel distribution compensation; system stability; Control system synthesis; Control systems; Feedback loop; Fuzzy control; Fuzzy systems; Linear matrix inequalities; Lyapunov method; Mathematical model; Nonlinear control systems; Stability analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems, 2008. FUZZ-IEEE 2008. (IEEE World Congress on Computational Intelligence). IEEE International Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1098-7584
  • Print_ISBN
    978-1-4244-1818-3
  • Electronic_ISBN
    1098-7584
  • Type

    conf

  • DOI
    10.1109/FUZZY.2008.4630481
  • Filename
    4630481