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Control of dynamic systems using fuzzy logic and neural networks
Author(s) -
Patrikar Ajay,
Provence John
Publication year - 1993
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.4550080605
Subject(s) - computer science , fuzzy logic , adaptive neuro fuzzy inference system , artificial neural network , neuro fuzzy , fuzzy control system , artificial intelligence , fuzzy electronics , feed forward , fuzzy associative matrix , defuzzification , feedforward neural network , fuzzy set operations , fuzzy number , fuzzy set , control engineering , engineering
Abstract The use of artificial neural network is proposed for high‐speed processing of rules in fuzzy logic controller (FLC). the logic element of an FLC is replaced by a single hidden layer feedforward network. the input and output fuzzy subsets are expressed it of numerical patterns. the network is trained using the back‐propagation algori to establish fuzzy associations between the input and output fuzzy subsets. the inference mechanism of the network is compared with that of compositional law of inference. In the proposed implementation of FLC, all the rules are processed in paralle. This implementation has potential for high‐speed processing of rules if the network is realized in hardware. the use of neural networks in fuzzy logic self‐organizing is also ivestigated. © 1993 John Wiley & Sons, Inc.