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Scalable distributed model predictive control for constrained systems

Research output: Contribution to journalArticle

Original languageEnglish
Pages (from-to)407-414
Number of pages8
JournalAutomatica
Volume93
Early online date9 Apr 2018
DOIs
DateAccepted/In press - 15 Feb 2018
DateE-pub ahead of print - 9 Apr 2018
DatePublished (current) - 1 Jul 2018

Abstract

A distributed model predictive control strategy is proposed for subsystems sharing a limited resource. Self-organized Time Division Multiple Access is used to coordinate subsystem controllers in a sequence such that no two re-optimize simultaneously. This new approach requires no central coordination or pre-organized optimizing sequence. The scheme guarantees satisfaction of coupled constraints despite dynamic entry and exit of subsystems.

    Research areas

  • Distributed model predictive control, Constrained systems, Scalable DMPC

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  • Full-text PDF (accepted author manuscript)

    Rights statement: This is the author accepted manuscript (AAM). The final published version (version of record) is available online via ELSEVIER at https://www.sciencedirect.com/science/article/pii/S0005109818301377?via%3Dihub . Please refer to any applicable terms of use of the publisher.

    Accepted author manuscript, 404 KB, PDF document

    Licence: Unspecified

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