期刊
COMPUTERS & CHEMICAL ENGINEERING
卷 28, 期 4, 页码 545-556出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compchemeng.2003.08.007
关键词
model predictive control; distributed parameter model; nonlinear programming; trajectory optimization; composite manufacturing; autoclave curing process
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.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据