Control-relevant Multiple Linear Modeling of Simulated Moving Bed Chromatography

被引：5

作者：

Sharma, Girish ^{[1
]}

Vignesh, S. V. ^{[1
]}

Hariprasad, K. ^{[1
]}

Bhartiya, Sharad ^{[1
]}

机构：

[1] Indian Inst Technol, Dept Chem Engn, Bombay 400076, Maharashtra, India

来源：

IFAC PAPERSONLINE | 2015年 / 48卷 / 08期

关键词：

Simulated moving bed chromatography; separation process; cyclic steady state; glucose-fructose system; multiple linear modeling; Bayesian approach; PREDICTIVE CONTROL; OPTIMIZATION;

D O I：

10.1016/j.ifacol.2015.09.013

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this work, we propose a control-relevant multiple linear modeling approach for simulated moving bed chromatography (SMBC) by linearizing the first principles model at carefully chosen equilibrium points. Subsequently, sub-models to account for port switching for each of the linear model are obtained. Model aggregation is done using Bayesian weighting to generate multiple model predictions for the nonlinear dynamics of SMBC. The multiple model approach is validated using simulations for cyclic steady state (CSS) of SMB as well as for a transition between two optimal CSS points for separation of a glucose-fructose mixture. (C) 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

引用

页码：477 / 482

页数：6

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