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Min-max tuning of fuzzy models with uncertain data

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3 Author(s)
Kumar, M. ; Center for Life Sci. Autom., Rostock Univ., Germany ; Stoll, R. ; Stoll, N.

This study deals with the robust tuning of a fuzzy model with uncertain data in a deterministic framework. We consider the on-line identification of an interpretable fuzzy model without making any assumption and requiring a priori knowledge of upper bounds, statistics, and distribution of data uncertainties. The tuning of the fuzzy model parameters is based on the robust (min-max) solution of a regularized least-squares constrained optimization problem. The simulation studies are carried out to show the better performance of our approach.

Published in:

Industrial Electronics Society, 2005. IECON 2005. 31st Annual Conference of IEEE

Date of Conference:

6-10 Nov. 2005