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Journal Articles Journal of Food Engineering Year : 2010

Nonlinear predictive control based on artificial neural network model for industrial crystallization

Cédric Damour
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Michel Benne
Brigitte Grondin-Perez
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  • PersonId : 970429
Jean-Pierre Chabriat

Abstract

This paper illustrates the benefits of a nonlinear model based predictive control (NMPC) strategy for setpoint tracking control of an industrial crystallization process. A neural networks model is used as internal model to predict process outputs. An optimization problem is solved to compute future control actions taking into account real-time control objectives. Furthermore, a more suitable output variable is used for process control: the mass of crystals in the solution is used instead of the traditional electrical conductivity. The performance of the NMPC implementation is assessed via simulation results based on industrial data.
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hal-01202296 , version 1 (19-09-2015)

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Cédric Damour, Michel Benne, Brigitte Grondin-Perez, Jean-Pierre Chabriat. Nonlinear predictive control based on artificial neural network model for industrial crystallization. Journal of Food Engineering, 2010, 99 (2), pp.225--231. ⟨10.1016/j.jfoodeng.2010.02.027⟩. ⟨hal-01202296⟩
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