Title: Multimodel software sensor for a harvested fish population system

Authors: Achraf Ait Kaddour; El Houssine El Mazoudi; Noureddine Elalami

Addresses: Department of Electrical Engineering, Ecole Mohammadia D'Ingénieurs EMI, Avenue Ibnsina, B.P. 765, Agdal, Rabat, Morocco ' Laboratoire de Recherche en Economie de l'Energie, Environnement et Ressources, Département d'Economie, Cadi Ayyad University, Daoudiate B.P. 2380, Marrakech, Morocco ' Department of Electrical Engineering, Ecole Mohammadia D'Ingénieurs EMI, Avenue Ibnsina, B.P. 765, Agdal, Rabat, Morocco

Abstract: In this work, we deal with the stock estimation problem for a harvested fish population described by a continuous stage structured model. In this model, the fishing effort is considered as a control term, the stage classes as states and the quantity of captured fish as a measured output. The goal of this paper is to show how some techniques from non-linear control theory combined with fuzzy systems theory can be applied for the approximate estimation of the immeasurable state variables using only the observed data together with the dynamical model describing the evolution of the system. To achieve this objective, we use first a Takagi-Sugeno multimodel to represent the continuous non-linear model. Next, we develop a technique for designing a multimodel observer corresponding to this system and show its asymptotic convergence. The design conditions are given in linear matrix inequalities (LMI) terms that can be solved efficiently using existing numerical tools. The simulation results demonstrate the effectiveness of the proposed method.

Keywords: harvested fish population; stage structured model; stock estimation; Takagi-Sugeno; software sensors; linear matrix inequalities; LMIs; dynamic modelling; nonlinear control; fuzzy set theory; fuzzy logic; simulation.

DOI: 10.1504/IJMIC.2013.054037

International Journal of Modelling, Identification and Control, 2013 Vol.19 No.1, pp.52 - 63

Published online: 27 Sep 2014 *

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