Stability of decentralized model predictive control of graph-based power flow systems via passivity

Justin P. Koeln, Andrew G. Alleyne

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

This work presents a passivity-based stability guarantee for the decentralized control of nonlinear power flow systems. This class of systems is characterized using a graph-based modeling approach, where vertices represent capacitive elements that store energy and edges represent power flow between these capacitive elements. Due to their complexity and size, these power flow systems are often decomposed into dynamically coupled subsystems, where this coupling stems from the exchange of power between subsystems. Each subsystem has a corresponding model predictive controller that can be part of a decentralized, distributed, or larger hierarchical control structure. By exploiting the structure of the coupling between subsystems, stability of the closed-loop system is guaranteed by augmenting each model predictive controller with a local passivity constraint.

Original languageEnglish (US)
Pages (from-to)29-34
Number of pages6
JournalAutomatica
Volume82
DOIs
StatePublished - Aug 1 2017
Externally publishedYes

Bibliographical note

Funding Information:
Research supported by the National Science Foundation Graduate Research Fellowship Program, the Air Force Research Laboratory (AFRL) under grant number FA8650-14-C-2517, and the National Science Foundation Engineering Research Center for Power Optimization of Electro Thermal Systems (POETS) with cooperative agreement EEC-1449548. The material in this paper was not presented at any conference. This paper was recommended for publication in revised form by Associate Editor Giancarlo Ferrari-Trecate under the direction of Editor Ian R. Petersen.

Publisher Copyright:
© 2017 Elsevier Ltd

Keywords

  • Decentralization
  • Graph theory
  • Large scale complex systems
  • Model predictive control
  • Passivity

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