Journal
COMPUTERS & CHEMICAL ENGINEERING
Volume 28, Issue 4, Pages 545-556Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compchemeng.2003.08.007
Keywords
model predictive control; distributed parameter model; nonlinear programming; trajectory optimization; composite manufacturing; autoclave curing process
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A general framework for a partial differential equation (PDE) model predictive control (MPC) 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 nonlinear 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. (C) 2003 Elsevier Ltd. All rights reserved.
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