Integrated production scheduling and model predictive control of continuous processes

Michael Baldea*, Juan Du, Jungup Park, Iiro Harjunkoski

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

39 Citations (Scopus)

Abstract

The integration of production management and process control decisions is critical for improving economic performance of the chemical supply chain. A novel framework for integrating production scheduling and model predictive control (MPC) for continuous processes is proposed. Our framework is predicated on using a low-dimensional time scale-bridging model (SBM) that captures the closed-loop process dynamics over the longer time scales that are relevant to scheduling calculations. The SBM is used as a constraint in a mixed-integer dynamic formulation of the scheduling problem. To synchronize the scheduling and MPC calculations, a novel scheduling-oriented MPC concept is proposed, whereby the SBM is incorporated in the expression of the controller as a (soft) dynamic constraint and allows for obtaining an explicit description of the closed-loop process dynamics. Our framework scales favorably with system size and provides desirable closed-loop stability and performance properties for the resulting integrated scheduling and control problem.

Original languageEnglish
Pages (from-to)4179-4190
Number of pages12
JournalAIChE Journal
Volume61
Issue number12
DOIs
Publication statusPublished - 1 Dec 2015
MoE publication typeA1 Journal article-refereed

Keywords

  • Integrated scheduling and control
  • Model predictive control
  • Production scheduling

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