A partial differential equation model predictive control strategy: Application to autoclave composite processing

Abstract : A general framework for a partial differential equation (PDE) model predictive control problem is formulated. A first principle model of the system, described by a semi-linear PDE system with boundary control, is employed in a model predictive control (MPC) framework. Here, the aim is to determine, off-line (i.e. without process measurement), the theoretical optimal behavior of the process that will be used during on-line MPC. Input and output constraints are handled in the optimization task using a non-linear programming method. This strategy is evaluated for the optimization of processing temperatures during the manufacture of thick-sectioned polymer composite laminates. The off-line optimization task consists of determining the optimal temperature profile, otherwise known as the cure cycle. Moreover, for this particular process, the existence of a feasible constrained optimization problem is discussed through the design of a constraint bound.
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Computers and Chemical Engineering, Elsevier, 2004, 28 (4), pp.545-556. 〈10.1016/j.compchemeng.2003.08.007〉
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Dernière modification le : jeudi 7 février 2019 - 16:43:34
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Pascal Dufour, Youssoufi Touré, Dennis J Michaud, Prasad S. Dhurjati. A partial differential equation model predictive control strategy: Application to autoclave composite processing. Computers and Chemical Engineering, Elsevier, 2004, 28 (4), pp.545-556. 〈10.1016/j.compchemeng.2003.08.007〉. 〈hal-00351748v2〉

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