Passivity and Decentralized MPC of Switched Graph-Based Power Flow Systems∗

Herschel C. Pangborn, Justin P. Koeln, Andrew G. Alleyne

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Scopus citations


This paper presents a decentralized approach to certifying closed-loop passivity for a class of switched graph-based dynamic models. The switched modeling framework is particularly suited to power flow systems in which paths of power flow are switched on and off. Passivity is shown to be preserved under the interconnection of multiple such graph-based models, allowing for the formation of passive 'systems of systems.' Decentralized Model Predictive Controllers paired with each system can then be formulated with a passivity-preserving constraint to ensure closed-loop stability. This allows complex energy systems to be stabilized with decentralized or distributed control architectures, while centralized control may not be practical due to the inherent computational complexity or communication bandwidth limitations. A numerical example demonstrates the efficacy of the proposed approach on a fluid tank system.

Original languageEnglish (US)
Title of host publication2018 Annual American Control Conference, ACC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Print)9781538654286
StatePublished - Aug 9 2018
Externally publishedYes
Event2018 Annual American Control Conference, ACC 2018 - Milwauke, United States
Duration: Jun 27 2018Jun 29 2018

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619


Other2018 Annual American Control Conference, ACC 2018
Country/TerritoryUnited States

Bibliographical note

Funding Information:
*This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant Number DGE-1144245, the National Science Foundation Engineering Research Center for Power Optimization of Electro-Thermal Systems (POETS) with cooperative agreement EEC-1449548, and the Air Force Research Laboratory.

Publisher Copyright:
© 2018 AACC.


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