Stochastic optimization for optimal and model-predictive control

被引:52
作者
Banga, JR
Irizarry-Rivera, R
Seider, WD [1 ]
机构
[1] Univ Penn, Dept Chem Engn, Philadelphia, PA 19104 USA
[2] CSIC, IIM, Chem Engn Lab, Vigo 36208, Spain
关键词
D O I
10.1016/S0098-1354(97)00226-3
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The integrated-controlled-random-search for dynamic systems (ICRS/DS) method is improved to include a moving-grid strategy and is applied to more challenging problems including: (1) the optimal control of a fed-batch bioreactor, a plug-flow reactor exhibiting a singular are, the van der Pol oscillator; and (2) the model-predictive control (MPC) of the Czochralski (CZ) crystallization process. This technique has several advantages over the gradient-based optimization methods with respect to convergence to the global optimum and the handling of singular arcs and non-differentiable expressions. Furthermore, its implementation is very simple and avoids tedious transformations that may be required by other methods. In MPC, a nonlinear program is solved to adjust the manipulated variables so as to minimize a control objective. The major difficulty in MPC implementation is in the handling of the dynamic constraints. The ICRS/DS method is applied for the control of the CZ crystallization process and is shown to be an attractive alternative to: (1) sequential integration and optimization, (2) the use of finite element/orthogonal collocation to convert the ODEs to algebraic constraints, and (3) successive linearization of the ODEs. (C) 1998 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:603 / 612
页数:10
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