Network decomposition for distributed control through community detection in input–output bipartite graphs. (April 2018)

• Record Type: Journal Article
• Authors: Tang, Wentao; Daoutidis, Prodromos
• Is Part Of: Journal of process control. Volume 64(2018)
• Page Start: 7
• Page End: 14
• Publication Date: 2018-04
• Subjects: Distributed control -- Network decomposition -- Control architecture design; Process control -- Periodicals; Fabrication -- Contrôle -- Périodiques; Process control; Periodicals; Electronic journals; 660.281
• DOI: 10.1016/j.jprocont.2018.01.009
• Languages: English
• ISSNs: 0959-1524

Abstract

Highlights: The decomposition of network systems for distributed control is considered. A weighted input-output bipartite graph is constructed based on short-time responses. The decomposition is obtained by modularity-based community detection. The proposed method is applied to a chemical process network example. Abstract: This paper addresses the decomposition of network systems for distributed control. We construct a novel weighted input–output bipartite graph representation of control systems, in which the input–output edge weights capture topological connectivity and short-time response sensitivities. We then introduce community detection as a network-theoretic tool to generate a decomposition with strong intra-subsystem interactions and weak inter-subsystem interactions. A modularity-based graph bisection procedure is applied recursively to determine the optimal decomposition. The proposed method is applied to a chemical process network example.