International Journal of Control, Automation, and Systems

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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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)
  • Published : 2005.06.01
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Abstract

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.

Keywords

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