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Indexed by:期刊论文

Date of Publication:2012-07-01

Journal:ASIAN JOURNAL OF CONTROL

Included Journals:SCIE、EI、Scopus

Volume:14

Issue:4

Page Number:1127-1132

ISSN No.:1561-8625

Key Words:Orthogonal transforms; fuzzy model; non-linear systems; fuzzy competitive learning

Abstract:This paper is concerned with the application of orthogonal transforms and fuzzy competitive learning to extract fuzzy rules from data. The least square algorithm with orthogonal transforms is proposed to supervise the progress of fuzzy competitive learning. First of all, competitive learning takes place in the product space of system inputs and outputs and each cluster corresponds to a fuzzy IFTHEN rule. The fuzzy relation matrix, confirmed by fuzzy competitive learning, is studied by the orthogonal least square algorithm. The validity of fuzzy rules is obtained by analyzing the effect of orthogonal vectors in the fuzzy model, and subsequently removing less important ones. The structure identification and parameter identification of the fuzzy model are simultaneously confirmed in the proposed algorithm. Using simulation results as an example, the fuzzy model of non-linear systems can be built by using the proposed algorithm. Copyright (c) 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society