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A NEURO‐FUZZY SYSTEM DESIGN METHODOLOGY FOR VIBRATION CONTROL
Author(s) -
Yang S. M.,
Tung Y. J.,
Liu Y. C.
Publication year - 2005
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1111/j.1934-6093.2005.tb00401.x
Subject(s) - neuro fuzzy , adaptive neuro fuzzy inference system , fuzzy set operations , fuzzy logic , defuzzification , fuzzy classification , fuzzy control system , fuzzy number , fuzzy associative matrix , computer science , membership function , artificial intelligence , control theory (sociology) , mathematics , fuzzy set , control engineering , control (management) , engineering
Fuzzy system has been known to provide a framework for handling uncertainties and imprecision by taking linguistic information from human experts. However, difficulties arise in determining effectively the fuzzy system configuration, i.e. , the number of rules, input and output membership functions. A neuro‐fuzzy system design methodology by combining neural network and fuzzy logic is developed in this paper to adaptively adjust the fuzzy membership functions and dynamically optimize the linguistic‐fuzzy rules. The structure of a five‐layer feedforward network is shown to determine systematically the correct fuzzy logic rules, tune optimally (in the sense of local region) the parameters of the membership functions, and perform accurately the fuzzy inference. It is shown both numerically and experimentally that engineering applications of the neuro‐fuzzy system to vibration control have been very successful.