DRSM Model for the Optimization and Control of Batch Processes

被引:4
作者
Wang, Zhenyu
Klebanov, Nikolai
Georgakis, Christos [1 ]
机构
[1] Tufts Univ, Dept Chem & Biol Engn, Medford, MA 02155 USA
来源
IFAC PAPERSONLINE | 2016年 / 49卷 / 07期
关键词
Data-Driven Modeling; Optimization; Model-based Control; Batch Process; Dynamics; Nonlinear Models; IDENTIFICATION;
D O I
10.1016/j.ifacol.2016.07.216
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Current Optimization and Model Predictive Control practices for batch processes are implemented using two models, one for determining the optimal trajectories and another identified around those trajectories for control purposes. Here we use the recently developed Dynamic Response Surface Modeling methodology from which the optimal trajectories and the local linear or nonlinear state-space models for control purposes are obtained. Because concentration measurements at each batch run are very infrequent, this might be the most attractive way to obtain a dynamic model for control purposes. (C) 2016, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
引用
收藏
页码:55 / 60
页数:6
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