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Fuzzy Control Using Piecewise Linear Membership Functions Based on Knowledge of Tuning a PID Controller
Author(s) -
Ken’ichiro Hayashi,
Akifumi Otsubo,
Kazuhiko Shiranita
Publication year - 2001
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.2001.p0071
Subject(s) - pid controller , control theory (sociology) , computer science , fuzzy logic , controller (irrigation) , defuzzification , fuzzy control system , piecewise linear function , membership function , fuzzy set , fuzzy number , control (management) , control engineering , artificial intelligence , mathematics , temperature control , engineering , agronomy , geometry , biology
Tuning control parameters of a fuzzy controller depends on trial-and-error. How this can be accomplished efficiently is an important subject in fuzzy control that should be investigated. We propose a method in which membership functions of a fuzzy controller can be simply set up using the knowledge of tuning parameters in a conventional PID controller. In this method, fuzzy control is realized as follows: Piecewise linear membership functions determined using the knowledge of tuning parameters in a PID controller are set up in antecedent parts of four fuzzy control rules having simple structures. Then the simplified inference method that enables high-speed inference is applied to fuzzy control rules.

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