A new LMI-based approach to relaxed quadratic stabilization of T-S fuzzy control systems

  • Authors:

  • Chun-Hsiung Fang;Yung-Sheng Liu;Shih-Wei Kau;Lin Hong;Ching-Hsiang Lee

  • Affiliations:

  • Dept. of Electr. Eng., Nat. Kaohsiung Univ. of Appl. Sci., Taiwan;-;-;-;-

  • Venue:
  • IEEE Transactions on Fuzzy Systems
  • Year:
  • 2006

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Abstract

This paper proposes a new quadratic stabilization condition for Takagi-Sugeno (T-S) fuzzy control systems. The condition is represented in the form of linear matrix inequalities (LMIs) and is shown to be less conservative than some relaxed quadratic stabilization conditions published recently in the literature. A rigorous theoretic proof is given to show that the proposed condition can include previous results as special cases. In comparison with conventional conditions, the proposed condition is not only suitable for designing fuzzy state feedback controllers but also convenient for fuzzy static output feedback controller design. The latter design work is quite hard for T-S fuzzy control systems. Based on the LMI-based conditions derived, one can easily synthesize controllers for stabilizing T-S fuzzy control systems. Since only a set of LMIs is involved, the controller design is quite simple and numerically tractable. Finally, the validity and applicability of the proposed approach are successfully demonstrated in the control of a continuous-time nonlinear system.