Control-Relevant Decomposition of Process Networks via Optimization-Based Hierarchical Clustering

被引:41
|
作者
Heo, Seongmin [1 ,2 ]
Daoutidis, Prodromos [1 ]
机构
[1] Univ Minnesota, Dept Chem Engn & Mat Sci, 421 Washington Ave SE, Minneapolis, MN 55455 USA
[2] Korea Adv Inst Sci & Technol, Dept Chem & Biomol Engn, 291 Daehak Ro, Taejon 305701, South Korea
基金
美国国家科学基金会;
关键词
control; optimization; process control; networks; hierarchical clustering; community detection; MODEL-PREDICTIVE CONTROL; CONTROL CONFIGURATIONS; PLANTWIDE CONTROL; RELATIVE GAIN; DESIGN; SELECTION; COMMUNICATION; ALGORITHM; SYSTEMS;
D O I
10.1002/aic.15323
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
A systematic method is proposed for control-relevant decomposition of complex process networks. Specifically, hierarchical clustering methods are adopted to identify constituent subnetworks such that the components of each subnetwork are strongly interacting while different subnetworks are loosely coupled. Optimal clustering is determined through the solution of integer optimization problems. The concept of relative degree is used to measure distance between subnetworks and compactness of subnetworks. The application of the proposed method is illustrated using an example process network. (C) 2016 American Institute of Chemical Engineers
引用
收藏
页码:3177 / 3188
页数:12
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