Distributed Model Predictive Control with Suboptimality and Stability Guarantees

Research output: Contribution to conferencePaper, not in proceedingpeer-review

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Abstract

Theory for Distributed Model Predictive Control (DMPC) is developed based on dual decomposition of the convex optimization problem that is solved in each time sample. The process to be controlled is an interconnection of several subsystems, where each subsystem corresponds to a node in a graph. We present a stopping criterion for the DMPC scheme that can be locally verified by each node and that guarantees closed loop suboptimality above a pre-specified level and asymptotic stability of the interconnected system.
Original languageEnglish
Pages7272-7277
Publication statusPublished - 2010
Event49th IEEE Conference on Decision and Control - Atlanta, Georgia, United States
Duration: 2010 Dec 15 → …

Conference

Conference49th IEEE Conference on Decision and Control
Country/TerritoryUnited States
CityAtlanta, Georgia
Period2010/12/15 → …

Subject classification (UKÄ)

  • Control Engineering

Free keywords

  • Distributed Model Predictive Control
  • stability
  • sub-optimality

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