Decomposition and Distributed Control of Integrated Lumped and Distributed Parameter Process Networks

Manjiri Moharir, Davood Babaei Pourkargar, Ali Almansoori, Prodromos Daoutidis

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

1 Scopus citations

Abstract

This work considers the problem of achieving model-based plant-wide control of a prototypical process network comprising interconnected lumped and distributed parameter systems. A community detection algorithm is used to obtain an optimal decomposition of this network for distributed control. The community detection is performed on a novel graph representation of the dynamics of the network, which accounts systematically for the interconnections among the variables of the process systems, including the different types of variables of the distributed parameter systems. The resulting distributed model predictive control implementation is shown to be computationally tractable, with performance close to that of centralized model predictive control.

Original languageEnglish (US)
Title of host publication2018 IEEE Conference on Decision and Control, CDC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2908-2913
Number of pages6
ISBN (Electronic)9781538613955
DOIs
StatePublished - Jan 18 2019
Event57th IEEE Conference on Decision and Control, CDC 2018 - Miami, United States
Duration: Dec 17 2018Dec 19 2018

Publication series

NameProceedings of the IEEE Conference on Decision and Control
Volume2018-December
ISSN (Print)0743-1546

Conference

Conference57th IEEE Conference on Decision and Control, CDC 2018
Country/TerritoryUnited States
CityMiami
Period12/17/1812/19/18

Bibliographical note

Funding Information:
Partial financial support from the Khalifa University of Science and Technology is gratefully acknowledged.

Publisher Copyright:
© 2018 IEEE.

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