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|Scopus||Web of Science®||Altmetric|
|Title:||Approximation to a class of non-autonomous systems by dynamic fuzzy inference marginal linearization method|
|Citation:||Information Sciences, 2013; 245:197-217|
|Publisher:||Elsevier Science Inc|
|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.|
|Rights:||© 2013 Elsevier Inc. All rights reserved.|
|Appears in Collections:||Aurora harvest|
Electrical and Electronic Engineering publications
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