Repetitive model predictive control applied to a simulated moving bed chromatography system

被引：92

作者：

Natarajan, S ^{[1
]}

Lee, JH ^{[1
]}

机构：

[1] Purdue Univ, Sch Chem Engn, W Lafayette, IN 47907 USA

来源：

COMPUTERS & CHEMICAL ENGINEERING | 2000年 / 24卷 / 2-7期

关键词：

repetitive control; model predictive control; periodic systems; SMB chromatography;

D O I：

10.1016/S0098-1354(00)00493-2

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In this payer, we investigate the application of the repetitive model predictive control (RMPC) technique on a simulated moving bed (SMB) process that performs continuous chromatographic separation of a phenylalanine- tryptophan mixture. RMPC is a model-based control technique developed by incorporating the basic concept from repetitive control into the model predictive control technique; it is specifically suited for continuous processes with periodic operation patterns or behavior. Balanced model reduction is used to reduce a finite difference approximation of a PDE model drawn from a material balance of the SMB system. The reduced order state space model is used for the control calculation. Start-up control of the SMB process is simulated and the results are presented. (C) 2000 Elsevier Science Ltd. All rights reserved.

引用

页码：1127 / 1133

页数：7

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