MODELING A NONLINEAR LIQUID LEVEL SYSTEM BY CELLULAR NEURAL NETWORKS
2010 ◽
Vol 21
(04)
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pp. 489-501
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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.
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1995 ◽
Vol 8
(6)
◽
pp. 689-701
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Keyword(s):
2018 ◽
pp. 235-245
Keyword(s):
1995 ◽
Vol 31
(6)
◽
pp. 1484-1491
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Keyword(s):