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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
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Brigitte Grondin-Perez
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Jean-Pierre Chabriat
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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.

Dates and versions

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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