Instant Distributed Model Predictive Control for Constrained Linear Systems

Martin Figura, Lanlan Su, Vijay Gupta, Masaki Inoue

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

2 Citations (Scopus)


Distributed optimal control has emerged as an exciting possibility; however, existing algorithms tend to require excessive computational time and thus may not be able to stabilize systems with fast dynamics. We develop instant distributed model predictive control (iDMPC) with a realization of the primal-dual algorithm embedded in the controller dynamics. Under assumptions on fast communication, we show that the input and state trajectories of iDMPC are equivalent to a centralized suboptimal MPC scheme. We utilize a dissipativity analysis to show that the closed-loop system trajectories asymptotically converge to a desired reference.

Original languageEnglish
Title of host publication2020 American Control Conference, ACC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781538682661
Publication statusPublished - 2020 Jul
Event2020 American Control Conference, ACC 2020 - Denver, United States
Duration: 2020 Jul 12020 Jul 3

Publication series

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


Conference2020 American Control Conference, ACC 2020
Country/TerritoryUnited States

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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