Dynamic Dual Decomposition for Distributed Control
Rantzer, Anders LU
(2009)
American Control Conference 2009
p.884-888
- Abstract
- 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... (More) - 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. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/1453983
- author
- Rantzer, Anders
LU
- organization
- publishing date
- 2009
- type
- Contribution to conference
- publication status
- published
- subject
- pages
- 884 - 888
- conference name
- American Control Conference 2009
- conference location
- St Louis, MO, United States
- conference dates
- 2009-06-10 - 2009-06-12
- external identifiers
-
- wos:000270044900146
- scopus:70449672733
- project
- CHAT
- AEOLUS
- LCCC-distributed
- language
- English
- LU publication?
- yes
- id
- a3dc38f3-3f66-4a5e-9b2e-de34e61ebc48 (old id 1453983)
- date added to LUP
- 2016-04-04 13:43:13
- date last changed
- 2023-11-16 10:38:47
@misc{a3dc38f3-3f66-4a5e-9b2e-de34e61ebc48,
abstract = {{We show how dynamic price mechanisms can be used for decomposition and distributed optimization of control systems.<br/><br>
<br/><br>
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.}},
author = {{Rantzer, Anders}},
language = {{eng}},
pages = {{884--888}},
title = {{Dynamic Dual Decomposition for Distributed Control}},
url = {{https://lup.lub.lu.se/search/files/6188832/8146098.pdf}},
year = {{2009}},
}