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Technical Brief

An experimental validation of a new method for multimodel identification

[+] Author and Article Information
Anis Messaoud

Associate Professor Department of Electrical Engineering, National School of Engineers of Gabes, University of Gabes Tunisia
messaoud_anis@yahoo.fr

Ridha Ben Abdennour

Professor Department of Electrical Engineering, National School of Engineers of Gabes, University of Gabes Tunisia
ridha.benabdennour@enig.rnu.tn

1Corresponding author.

ASME doi:10.1115/1.4037530 History: Received October 03, 2016; Revised July 14, 2017

Abstract

In this paper, we propose a new method for an optimal systematic determination of models'base for multimodel identification. This method is based on the neural classification of data set picked out on a considered system. The obtained cluster centers are exploited to provide the weighting functions and to deduce the corresponding dispersions and their models'base. A simulation example and an experimental validation on a chemical reactor are presented to evaluate the effectiveness of the proposed method.

Copyright (c) 2017 by ASME
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