A Decomposition Algorithm for Mean-Variance Economic Model Predictive Control of Stochastic Linear Systems

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

This paper presents a decomposition algorithm for solving the optimal control problem (OCP) that arises in Mean-Variance Economic Model Predictive Control of stochastic linear systems. The algorithm applies the alternating direction method of multipliers to a reformulation of the OCP that decomposes into small independent subproblems. We test the decomposition algorithm using a simple power management case study, in which the OCP is formulated as a convex quadratic program. Simulations show that the decomposition algorithm scales linearly in the number of uncertainty scenarios. Moreover, a parallel implementation of the algorithm is several orders of magnitude faster than state-of-the-art convex quadratic programming algorithms, provided that the number of uncertainty scenarios is large.
Original languageEnglish
Title of host publicationProceedings of the IEEE International Symposium on Intelligent Control (ISIC) 2014, Part of 2014 IEEE Multi-conference on Systems and Control
PublisherIEEE
Publication date2014
Pages1086-1093
ISBN (Electronic)978-1-4799-7406-1
DOIs
Publication statusPublished - 2014
Event2014 IEEE Multi-Conference on Systems and Control - Antibes Congress Center, Antibes, France
Duration: 8 Oct 201410 Oct 2014
http://www.msc2014.org/

Conference

Conference2014 IEEE Multi-Conference on Systems and Control
LocationAntibes Congress Center
CountryFrance
CityAntibes
Period08/10/201410/10/2014
OtherAlso include the IEEE International Symposium on Intelligent Control (ISIC) 2014
Internet address

Cite this

Sokoler, L. E., Dammann, B., Madsen, H., & Jørgensen, J. B. (2014). A Decomposition Algorithm for Mean-Variance Economic Model Predictive Control of Stochastic Linear Systems. In Proceedings of the IEEE International Symposium on Intelligent Control (ISIC) 2014, Part of 2014 IEEE Multi-conference on Systems and Control (pp. 1086-1093). IEEE. https://doi.org/10.1109/ISIC.2014.6967612
Sokoler, Leo Emil ; Dammann, Bernd ; Madsen, Henrik ; Jørgensen, John Bagterp. / A Decomposition Algorithm for Mean-Variance Economic Model Predictive Control of Stochastic Linear Systems. Proceedings of the IEEE International Symposium on Intelligent Control (ISIC) 2014, Part of 2014 IEEE Multi-conference on Systems and Control. IEEE, 2014. pp. 1086-1093
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title = "A Decomposition Algorithm for Mean-Variance Economic Model Predictive Control of Stochastic Linear Systems",
abstract = "This paper presents a decomposition algorithm for solving the optimal control problem (OCP) that arises in Mean-Variance Economic Model Predictive Control of stochastic linear systems. The algorithm applies the alternating direction method of multipliers to a reformulation of the OCP that decomposes into small independent subproblems. We test the decomposition algorithm using a simple power management case study, in which the OCP is formulated as a convex quadratic program. Simulations show that the decomposition algorithm scales linearly in the number of uncertainty scenarios. Moreover, a parallel implementation of the algorithm is several orders of magnitude faster than state-of-the-art convex quadratic programming algorithms, provided that the number of uncertainty scenarios is large.",
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Sokoler, LE, Dammann, B, Madsen, H & Jørgensen, JB 2014, A Decomposition Algorithm for Mean-Variance Economic Model Predictive Control of Stochastic Linear Systems. in Proceedings of the IEEE International Symposium on Intelligent Control (ISIC) 2014, Part of 2014 IEEE Multi-conference on Systems and Control. IEEE, pp. 1086-1093, 2014 IEEE Multi-Conference on Systems and Control, Antibes, France, 08/10/2014. https://doi.org/10.1109/ISIC.2014.6967612

A Decomposition Algorithm for Mean-Variance Economic Model Predictive Control of Stochastic Linear Systems. / Sokoler, Leo Emil; Dammann, Bernd; Madsen, Henrik; Jørgensen, John Bagterp.

Proceedings of the IEEE International Symposium on Intelligent Control (ISIC) 2014, Part of 2014 IEEE Multi-conference on Systems and Control. IEEE, 2014. p. 1086-1093.

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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T1 - A Decomposition Algorithm for Mean-Variance Economic Model Predictive Control of Stochastic Linear Systems

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PY - 2014

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N2 - This paper presents a decomposition algorithm for solving the optimal control problem (OCP) that arises in Mean-Variance Economic Model Predictive Control of stochastic linear systems. The algorithm applies the alternating direction method of multipliers to a reformulation of the OCP that decomposes into small independent subproblems. We test the decomposition algorithm using a simple power management case study, in which the OCP is formulated as a convex quadratic program. Simulations show that the decomposition algorithm scales linearly in the number of uncertainty scenarios. Moreover, a parallel implementation of the algorithm is several orders of magnitude faster than state-of-the-art convex quadratic programming algorithms, provided that the number of uncertainty scenarios is large.

AB - This paper presents a decomposition algorithm for solving the optimal control problem (OCP) that arises in Mean-Variance Economic Model Predictive Control of stochastic linear systems. The algorithm applies the alternating direction method of multipliers to a reformulation of the OCP that decomposes into small independent subproblems. We test the decomposition algorithm using a simple power management case study, in which the OCP is formulated as a convex quadratic program. Simulations show that the decomposition algorithm scales linearly in the number of uncertainty scenarios. Moreover, a parallel implementation of the algorithm is several orders of magnitude faster than state-of-the-art convex quadratic programming algorithms, provided that the number of uncertainty scenarios is large.

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Sokoler LE, Dammann B, Madsen H, Jørgensen JB. A Decomposition Algorithm for Mean-Variance Economic Model Predictive Control of Stochastic Linear Systems. In Proceedings of the IEEE International Symposium on Intelligent Control (ISIC) 2014, Part of 2014 IEEE Multi-conference on Systems and Control. IEEE. 2014. p. 1086-1093 https://doi.org/10.1109/ISIC.2014.6967612