Dynamic Dual Decomposition for Distributed Control

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

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We show how dynamic price mechanisms can be used for decomposition and distributed optimization of control systems.

A classical method to deal with optimization constraints is Lagrange relaxation, where dual variables are introduced in the optimization objective. When variables of different subproblems are connected by such constraints, the dual variables can be interpreted as prices in a market mechanism serving to achieve mutual agreement between the subproblems. In this paper, the same idea is used for decomposition of optimal control problems, with dynamics in both decision variables and prices. We show how the prices can be used for decentralized verification that a control law or trajectory stays within a prespecified distance from optimality. For example, approximately optimal decentralized controllers can be obtained by using simplified models for decomposition and more accurate local models for control.
Original languageEnglish
Publication statusPublished - 2009
EventAmerican Control Conference 2009 - St Louis, MO, United States
Duration: 2009 Jun 102009 Jun 12


ConferenceAmerican Control Conference 2009
Country/TerritoryUnited States
CitySt Louis, MO

Subject classification (UKÄ)

  • Control Engineering


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