Distributed model predictive control of process networks: Impact of control architecture

Davood Babaei Pourkargar, Ali Almansoori, Prodromos Daoutidis

Research output: Contribution to journalArticlepeer-review

15 Scopus citations


This paper investigates the impact of control architecture design on the distributed model predictive control (MPC) of nonlinear complex process networks. A sequential distributed MPC structure is synthesized to regulate a nonlinear system whose dynamics are decomposed into multiple subsystems by community detection methods. The closed-loop performance and computational effort of employing centralized and sequential distributed MPC structures is analyzed for a reactor-separator integrated process.

Original languageEnglish (US)
Pages (from-to)12452-12457
Number of pages6
Issue number1
StatePublished - Jul 2017


  • Distributed process control
  • control architecture
  • integrated process systems
  • model predictive control
  • network decomposition

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