Approximation to a class of non-autonomous systems by dynamic fuzzy inference marginal linearization method

  • Authors:
  • De-Gang Wang;Wen-Yan Song;Peng Shi;Hong-Xing Li

  • Affiliations:
  • -;-;-;-

  • Venue:
  • Information Sciences: an International Journal
  • Year:
  • 2013

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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.