MODELING A NONLINEAR LIQUID LEVEL SYSTEM BY CELLULAR NEURAL NETWORKS

Norberto Hernandez-Romero (), Juan Carlos Seck-Tuoh-Mora (), Manuel Gonzalez-Hernandez (), Joselito Medina-Marin () and Juan Flores
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Norberto Hernandez-Romero: Centro de Investigación Avanzada en Ingeniería Industrial, Universidad Autónoma del Estado de Hidalgo, Pachuca Hidalgo 42184, México
Juan Carlos Seck-Tuoh-Mora: Centro de Investigación Avanzada en Ingeniería Industrial, Universidad Autónoma del Estado de Hidalgo, Pachuca Hidalgo 42184, México
Manuel Gonzalez-Hernandez: Centro de Investigación Avanzada en Ingeniería Industrial, Universidad Autónoma del Estado de Hidalgo, Pachuca Hidalgo 42184, México
Joselito Medina-Marin: Centro de Investigación Avanzada en Ingeniería Industrial, Universidad Autónoma del Estado de Hidalgo, Pachuca Hidalgo 42184, México

International Journal of Modern Physics C (IJMPC), 2010, vol. 21, issue 04, 489-501

Abstract: This paper presents the analogue simulation of a nonlinear liquid level system composed by two tanks; the system is controlled using the methodology of exact linearization via state feedback by cellular neural networks (CNNs). The relevance of this manuscript is to show how a block diagram representing the analogue modeling and control of a nonlinear dynamical system, can be implemented and regulated by CNNs, whose cells may contain numerical values or arithmetic and control operations. In this way the dynamical system is modeled by a set of local-interacting elements without need of a central supervisor.

Keywords: Cellular neural networks; nonlinear systems; block diagrams; 05.10.-a; 07.05.Tp; 87.16.-A; 87.18.Sn (search for similar items in EconPapers)
Date: 2010
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DOI: 10.1142/S0129183110015245

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