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Optimisation dynamique en temps-réel d’un procédé de polymérisation par greffage

Abstract : In a schematic way, process optimization consists of three basic steps: (i) modeling, in which a (phenomenological) model of the process is developed, (ii) problem formulation, in which the criterion of Performance, constraints and decision variables are defined, (iii) the resolution of the optimal problem, in which the optimal profiles of the decision variables are determined. It is important to emphasize that these optimal profiles guarantee the optimality for the model used. When applied to the process, these profiles are optimal only when the model perfectly describes the behavior of the process, which is very rarely the case in practice. Indeed, uncertainties about model parameters, process disturbances, and structural model errors mean that the optimal profiles of the model-based decision variables will probably not be optimal for the process. The objective of this thesis is to develop a conceptual strategy for using experimental measurements online so that the process not only satisfies the necessary conditions, but also the optimal conditions. This conceptual development will in particular be based on recent advances in deterministic optimization (the stochastic methods will not be dealt with in this work) of processes based on the estimation of the state variables that are not measured by a moving horizon observer. A dynamic real-time optimization (D-RTO) methodology has been developed and applied to a batch reactor where polymer grafting reactions take place. The objective is to determine the on-line reactor temperature profile that minimizes the batch time while meeting terminal constraints on the overall conversion rate and grafting efficiency
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Submitted on : Thursday, April 18, 2019 - 9:52:40 AM
Last modification on : Wednesday, November 3, 2021 - 7:09:36 AM


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  • HAL Id : tel-02103102, version 1



Ryad Bousbia-Salah. Optimisation dynamique en temps-réel d’un procédé de polymérisation par greffage. Génie des procédés. Université de Lorraine, 2018. Français. ⟨NNT : 2018LORR0242⟩. ⟨tel-02103102⟩



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