Modularity-based control structure selection for process networks: An extension to distributed parameter systems

Lixia Kang, Manjiri Moharir, Ali Almansoori, Prodromos Daoutidis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

This paper deals with obtaining the optimal control configuration for process networks comprising lumped and distributed parameter systems. Equation graphs that capture structural interactions among the input and output variables of first-order hyperbolic PDE systems with different types of actuations are proposed, which are combined with equation graphs of lumped parameter systems. Using these equation graphs, parameters that quantify structural coupling (relative degrees, characteristic indices) are calculated, on the basis of which, the optimal decentralized control configuration is identified. Agglomerative hierarchical clustering is then applied to obtain candidates for block-decentralized control configurations. A modularity maximization algorithm is used to select the optimal block-decentralized control configuration.

Original languageEnglish (US)
Title of host publication2017 American Control Conference, ACC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1145-1150
Number of pages6
ISBN (Electronic)9781509059928
DOIs
StatePublished - Jun 29 2017
Event2017 American Control Conference, ACC 2017 - Seattle, United States
Duration: May 24 2017May 26 2017

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619

Other

Other2017 American Control Conference, ACC 2017
Country/TerritoryUnited States
CitySeattle
Period5/24/175/26/17

Bibliographical note

Publisher Copyright:
© 2017 American Automatic Control Council (AACC).

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