Distributed Estimation and Nonlinear Model Predictive Control Using Community Detection

Davood B. Pourkargar, Manjiri Moharir, Ali Almansoori, Prodromos Daoutidis

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

A combined distributed moving horizon estimation and distributed model predictive control architecture is proposed to address the distributed output-feedback control problem for nonlinear process systems. Community detection based on modularity maximization is used to generate separate optimal decompositions for the estimation and control problems on the basis of suitable graphs. The process of benzene alkylation with ethylene is used as a case study to illustrate the application and computational advantages of the proposed control strategy.

Original languageEnglish (US)
Pages (from-to)13495-13507
Number of pages13
JournalIndustrial and Engineering Chemistry Research
Volume58
Issue number30
DOIs
StatePublished - Jul 31 2019

Bibliographical note

Funding Information:
Financial support from the Department of Chemical Engineering, Khalifa University of Science, Technology, and Research, Abu Dhabi, UAE, is gratefully acknowledged.

Publisher Copyright:
© 2019 American Chemical Society.

Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.

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