FUZZY MODELING BY SUCCESSIVE ESTIMATION OF RULES

Abstract

This paper presents an algorithm for automatically deriving fuzzy rules directly from a set of input-output data of a process for the purpose of modeling. The rules are extracted by a method termed successive estimation. This method is used to generate a model without truncating the number of fired rules, to within user specified accuracy and without requiring an in-depth understanding of the underlying process. Results obtained by the algorithm are in good agreement with the available data on the speed-current characteristics of a dc series motor.


JMDMES Vol.2(1) 2003: 71-81