Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/79978
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Type: Journal article
Title: Approximation to a class of non-autonomous systems by dynamic fuzzy inference marginal linearization method
Author: Wang, D.
Song, W.
Shi, P.
Li, H.
Citation: Information Sciences, 2013; 245:197-217
Publisher: Elsevier Science Inc
Issue Date: 2013
ISSN: 0020-0255
Statement of
Responsibility: 
De-Gang Wang, Wen-Yan Song, Peng Shi, Hong-Xing Li
Abstract: In this paper, a dynamic fuzzy inference marginal linearization (DFIML) method is proposed for modeling nonlinear dynamic systems. This method can transfer a group of input-output data into a time-variant fuzzy system with variable coefficients. It is shown that solutions of time-variant fuzzy systems generalized by DFIML method are universal approximators to solutions of a class of non-autonomous systems. Also the analytical solutions of these time-variant fuzzy systems can be obtained. Finally, a simulation example is provided to illustrate the validity and potential of the developed techniques. © 2012 Elsevier Inc. All rights reserved.
Keywords: Fuzzy inference
Fuzzy system
Non-autonomous system
Universal approximators
Rights: © 2013 Elsevier Inc. All rights reserved.
DOI: 10.1016/j.ins.2013.05.011
Appears in Collections:Aurora harvest
Electrical and Electronic Engineering publications

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