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Closed-loop Identification of Hammerstein Systems Using Hybrid Neural Model Identified by Genetic Algorithms

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2 Author(s)
O. M. M. Vall ; Ecole Nationale d’Ingénieurs de Tunis, Tunisia ; M. Radhi

In this paper we present an approach for the closed loop identification of Hammerstein systems. In this approach we propose modelling the system to be identified by a hybrid neural model, which is composed of a neural network (NN), connected in series with a linear model. To optimize the proposed model, genetic algorithms are used. The system to be identified is in closed-loop with variable structure controller (CSV) in order to have a command signal rich in commutations and consequently a good identification. A simulation example is given in order to show the effectiveness of the proposed approach

Published in:

International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce (CIMCA-IAWTIC'06)  (Volume:2 )

Date of Conference:

28-30 Nov. 2005