Robust stable feedback linearization of fuzzy modeled nonlinear systems via LMI's

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/sub 2/ robust stability...

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Bibliographic Details
Main Authors: PARK, Chang-Woo, MOON, Chan-Woo, LEE, Jong-Bae, KIM, Young-Ouk, SUNG, Ha-Gyeong
Format: Conference Proceeding
Language:English
Subjects:
Applied sciences
Artificial intelligence
Computer science
control theory
systems
Control systems
Design methodology
Exact sciences and technology
Fuzzy control
Fuzzy systems
Linear feedback control systems
Nonlinear systems
Robust stability
Robustness
Takagi-Sugeno model
Uncertainty
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Summary: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/sub 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.
ISSN:1098-7584
DOI:10.1109/FUZZY.2004.1375345