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Control‐relevant decomposition of process networks via optimization‐based hierarchical clustering
Authors:Seongmin Heo  Prodromos Daoutidis
Affiliation:Dept. of Chemical Engineering and Materials Science, University of Minnesota, Minneapolis, MN
Abstract: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. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3177–3188, 2016
Keywords:control  optimization  process control  networks  hierarchical clustering  community detection
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