Open AccessNonlinear Model Following Control via Takagi-Sugeno Fuzzy Model
Author(s) -
Tadanari Taniguchi,
Kazuo Tanaka
Publication year - 1999
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 - 1883-8014
pISSN - 1343-0130
DOI - 10.20965/jaciii.1999.p0068
Subject(s) - control theory (sociology) , nonlinear system , computer science , linear matrix inequality , controller (irrigation) , fuzzy logic , fuzzy control system , compensation (psychology) , nonlinear control , reference model , control (management) , control engineering , mathematical optimization , mathematics , artificial intelligence , engineering , biology , psychoanalysis , physics , quantum mechanics , software engineering , psychology , agronomy
This paper presents a unified approach toward regulation and servocontrol problems as special cases of a nonlinear model following control via the Takagi-Sugeno fuzzy model. New parallel distributed compensation (PDC) is presented for realizing a nonlinear model following control. The new PDC fuzzy controller mirrors the structures of two Takagi-Sugeno fuzzy models representing a nonlinear system and nonlinear reference model. First, we derive linear matrix inequality (LMI) conditions to linearize the error system between the feedback system and the nonlinear reference model. A controller is designed using LMI conditions. Design examples verify the usefulness of nonlinear model following control.
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