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论文类型：期刊论文

发表时间：2012-07-01

发表刊物：ASIAN JOURNAL OF CONTROL

收录刊物：SCIE、EI、Scopus

卷号：14

期号：4

页面范围：1127-1132

ISSN号：1561-8625

关键字：Orthogonal transforms; fuzzy model; non-linear systems; fuzzy competitive learning

摘要：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