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Robust Output Feedback Guaranteed Cost Control of Uncertain Fuzzy Systems with Immeasurable Premise Variables
Author(s) -
Jun Yoneyama
Publication year - 2007
Publication title -
journal of advanced computational intelligence and intelligent informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.172
H-Index - 20
eISSN - 1343-0130
pISSN - 1883-8014
DOI - 10.20965/jaciii.2007.p0745
Subject(s) - premise , control theory (sociology) , computer science , fuzzy control system , fuzzy logic , variable (mathematics) , state variable , robustness (evolution) , robust control , controller (irrigation) , nonlinear system , control variable , compensation (psychology) , mathematical optimization , control (management) , mathematics , artificial intelligence , machine learning , philosophy , psychoanalysis , mathematical analysis , linguistics , chemistry , biology , psychology , biochemistry , quantum mechanics , agronomy , thermodynamics , physics , gene
This paper is concerned with robust output feedback stabilization with guaranteed cost of uncertain Takagi-Sugeno fuzzy systems with immeasurable premise variables. When we consider Takagi-Sugeno fuzzy systems, the selection of premise variables plays an important role. If the premise variable is the state of the system, then a fuzzy system describes a wide class of nonlinear systems. However, the state is not measurable in the output feedback control problem. In this case, a control design based on parallel distributed compensation is impossible because a controller depends on immeasurable premise variables. In this paper, we consider the robust output feedback stabilization problem with guaranteed cost where the premise variable is not measurable. We formulate this problem as a robust stabilization of uncertain linear systems. Numerical examples are given to illustrate our theory.

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