• DocumentCode
    836591
  • Title

    Stability Conditions for LMI-Based Fuzzy Control From Viewpoint of Membership Functions

  • Author

    Lian, Kuang-Yow ; Tu, Hui-Wen ; Liou, Jeih-Jang

  • Author_Institution
    Dept. of Electr. Eng., Chung Yuan Christian Univ., Chung-li
  • Volume
    14
  • Issue
    6
  • fYear
    2006
  • Firstpage
    874
  • Lastpage
    884
  • Abstract
    In this paper, we investigate the stability conditions for linear matrix inequality (LMI)-based fuzzy control design. Especially, we focus on the dependence of the stability upon membership functions. In general, the membership functions in the rule bases of Takagi-Sugeno (T-S) fuzzy model and controllers are the same and restricted between 0 and 1. In contrast to this setting, we obtain some new results when different membership functions are considered and their values lying outside the interval of [0,1] are allowed. Applying Lyapunov equation and a convex hull of fuzzy subsystems, we first establish a relationship between the stable interval characteristic polynomial and a set of feasible LMIs. Then Kharitonov´s theorem gives an insight for the solvability of stabilization problems using LMI-based design and, this leads that the membership functions have an influence on stability. On the other hand, the LMI condition leads to the well-known results for LMI-based fuzzy control design. We further indicate that the different LMI conditions arise due to the same or different membership functions and find their own applications on adaptive fuzzy control. Finally, if the unit interval constraint is removed, an LMI condition for global stability is obtained
  • Keywords
    Lyapunov methods; adaptive control; control system synthesis; fuzzy control; linear matrix inequalities; stability; LMI; Lyapunov equation; Takagi-Sugeno fuzzy model; adaptive fuzzy control; linear matrix inequality; membership function; stability condition; Equations; Fuzzy control; Fuzzy sets; Fuzzy systems; Linear matrix inequalities; Lyapunov method; Nonlinear control systems; Nonlinear systems; Polynomials; Stability analysis; Adaptive stabilization; Takagi–Sugeno (T–S) fuzzy model; global stabilization; linear matrix inequality (LMI); stability;
  • fLanguage
    English
  • Journal_Title
    Fuzzy Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1063-6706
  • Type

    jour

  • DOI
    10.1109/TFUZZ.2006.886366
  • Filename
    4016085