Int. J. of Applied Mathematics, Computational Science and Systems Engineering



Poles optimization of MIMO ARX-Laguerre model using genetic algorithm

Author(s): Marwa Yousfi, Tarek Garna, Chakib Ben Njima

Abstract: In this paper, we propose the poles otimization of the linear MIMO ARX-laguerre model using genetic algorithm. This model is obtained by decompsing the MIMO ARX model on orthonormal and independent Laguerre bases allowing the filtering of the inputs and outputs of the system using the orthonormal functions of Laguerre. The resulting model, called MIMO ARX-Laguerre, ensures a reduction in the parametric complexity with respect to the number of parameters with a simple recursive vector representation. However, this reduction is conditioned by an optimal choice of the Laguerre pole characterizing each base. To do this, we propose to optimize, by exploiting the genetic algorithm, the Laguerre poles of the MIMO ARX-laguerre model. The optimization of the Laguerre poles is validated by a numerical simulation to the CSTR Benchmark

Keywords: MIMO ARX-laguerre model, laguerre poles, optimization, genetic algorithm, CSTR Benchmark

Pages: 78-85


Ιnt. J. of Applied Mathematics, Computational Science and Systems Engineering (published by International Academic Publications)


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