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Title of Journal: Neural Comput Applic

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Abbravation: Neural Computing and Applications

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Springer-Verlag

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1433-3058

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Neural networksbased adaptive control for a class

Authors: Emil Petre Dan Selişteanu Dorin Şendrescu Cosmin Ionete
Publish Date: 2009/06/19
Volume: 19, Issue: 2, Pages: 169-178
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Abstract

The paper studies the design and analysis of a neural adaptive control strategy for a class of square nonlinear bioprocesses with incompletely known and timevarying dynamics In fact an adaptive controller based on a dynamical neural network used as a model of the unknown plant is developed The neural controller design is achieved by using an input–output feedback linearization technique The adaptation laws of neural network weights are derived from a Lyapunov stability property of the closedloop system The convergence of the system tracking error to zero is guaranteed without the need of network weights convergence The resulted control method is applied in a depollution control problem in the case of a wastewater treatment bioprocess belonging to the square nonlinear class for which kinetic dynamics are strongly nonlinear time varying and not exactly known

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