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Indexed by:期刊论文

Date of Publication:2022-06-29

Journal:计算机学报

Affiliation of Author(s):电子信息与电气工程学部

Issue:11

Page Number:1977-1981

ISSN No.:0254-4164

Abstract:For dynamic systems with complex, ill-conditioned, or nonlinear characteristics, the fuzzy modeling method based on fuzzy sets is very effective to describe the properties of the systems. The orthogonal transform and fuzzy clustering algorithm are used to extract fuzzy rules from sampling data in the paper. The results acquired from fuzzy clustering algorithm are transformed to confirm the fuzzy rules by means of the orthogonal least squares. The classical Gram-Schmidt method is used to acquire the important rules and remove the bad important rules. The parameters of fuzzy model are estimated by using the proposed method. The structure identification and the parameter identification of fuzzy model are synchronously confirmed in the proposed algorithm. With the illustration of the simulating results, the fuzzy model of non-linear system can be built by using the proposed algorithm.

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