TY - GEN
T1 - Passivity and Decentralized MPC of Switched Graph-Based Power Flow Systems∗
AU - Pangborn, Herschel C.
AU - Koeln, Justin P.
AU - Alleyne, Andrew G.
N1 - 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.
PY - 2018/8/9
Y1 - 2018/8/9
N2 - 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.
AB - 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.
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U2 - 10.23919/ACC.2018.8431722
DO - 10.23919/ACC.2018.8431722
M3 - Conference contribution
AN - SCOPUS:85050619499
SN - 9781538654286
T3 - Proceedings of the American Control Conference
SP - 198
EP - 203
BT - 2018 Annual American Control Conference, ACC 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 Annual American Control Conference, ACC 2018
Y2 - 27 June 2018 through 29 June 2018
ER -