A functional-link-based fuzzy neural network for temperature control

Cheng-Hung Chen, Chin-Teng Lin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

25 Scopus citations

Abstract

This study presents a functional-link-based fuzzy neural network (FLFNN) structure for temperature control. The proposed FLFNN controller uses functional link neural networks (FLNN) that can generate a nonlinear combination of the input variables as the consequent part of the fuzzy rules. An online learning algorithm, which consists of structure learning and parameter learning, is also presented. The structure learning depends on the entropy measure to determine the number of fuzzy rules. The parameter learning, based on the gradient descent method, can adjust the shape of the membership function and the corresponding weights of the FLNN. Simulation result of temperature control has been given to illustrate the performance and effectiveness of the proposed model.
Original languageEnglish
Title of host publication2007 IEEE SYMPOSIUM ON FOUNDATIONS OF COMPUTATIONAL INTELLIGENCE, VOLS 1 AND 2
Place of PublicationNEW YORK,USA
PublisherIEEE
Pages53
ISBN (Print)978-1-4244-0703-3
DOIs
StatePublished - 2007
Event2007 IEEE Symposium on Foundations of Computational Intelligence, FOCI 2007 - Honolulu, HI, United States
Duration: 1 Apr 20075 Apr 2007

Publication series

Name2007 IEEE SYMPOSIUM ON FOUNDATIONS OF COMPUTATIONAL INTELLIGENCE, VOLS 1 AND 2
PublisherIEEE

Conference

Conference2007 IEEE Symposium on Foundations of Computational Intelligence, FOCI 2007
CountryUnited States
CityHonolulu, HI
Period1/04/075/04/07

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