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International Journal of Control, Automation and Systems v.3 no.2, 2005년, pp.225 - 235   피인용횟수: 1

Robust Stabilization of Uncertain Nonlinear Systems via Fuzzy Modeling and Numerical Optimization Programming

Lee Jongbae    (Korea Electronics Technology Institute   ); Park Chang-Woo    (Korea Electronics Technology Institute   ); Sung Ha-Gyeong    (Korea Electronics Technology Institute   ); Lim Joonhong    (School of Electrical Engineering and Computer Science, Hanyang University  );
  • 초록

    This paper presents the robust stability analysis and design methodology of the fuzzy feedback linearization control systems. Uncertainty and disturbances with known bounds are assumed to be included in the Takagi-Sugeno (TS) fuzzy models representing the nonlinear plants. $L_2$ robust stability of the closed system is analyzed by casting the systems into the diagonal norm bounded linear differential inclusions (DNLDI) formulation. Based on the linear matrix inequality (LMI) optimization programming, a numerical method for finding the maximum stable ranges of the fuzzy feedback linearization control gains is also proposed. To verify the effectiveness of the proposed scheme, the robust stability analysis and control design examples are given.


  • 주제어

    feedback linearization .   fuzzy control .   linear matrix inequalities .   Takagi-Sugeno fuzzy model.  

  • 참고문헌 (17)

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  • 이 논문을 인용한 문헌 (1)

    1. 2007. "" International Journal of Control, Automation and Systems, 5(3): 349~354     

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  • 박창우 (12)

  • 성하경 (9)

  • Lim, Joon-Hong (21)

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