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

29 Scopus citations


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 languageBritish English
Pages (from-to)13495-13507
Number of pages13
JournalIndustrial and Engineering Chemistry Research
Issue number30
StatePublished - 31 Jul 2019


Dive into the research topics of 'Distributed Estimation and Nonlinear Model Predictive Control Using Community Detection'. Together they form a unique fingerprint.

Cite this