Bauso, D., Quanyan, Z. and Basar, T. (2012) Mixed integer optimal compensation: Decompositions and mean-field approximations. In: Proceedings of the American Control Conference. 2012 American Control Conference, June 27-29, 2012, Montréal, Canada. , 2663 - 2668. ISBN 9781457710957
Abstract
Mixed integer optimal compensation deals with optimizing integer- and real-valued control variables to compensate disturbances in dynamic systems. The mixed integer nature of controls might be a cause of intractability for instances of larger dimensions. To tackle this issue, we propose a decomposition method which turns the original n-dimensional problem into n independent scalar problems of lot sizing form. Each scalar problem is then reformulated as a shortest path one and solved through linear programming over a receding horizon. This last reformulation step mirrors a standard procedure in mixed integer programming. We apply the decomposition method to a mean-field coupled multi-agent system problem, where each agent seeks to compensate a combination of the exogenous signal and the local state average. We discuss a large population mean-field type of approximation as well as the application of predictive control methods. © 2012 AACC American Automatic Control Council).
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2012 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 03 Feb 2016 15:04 |
Last Modified: | 20 Mar 2018 23:19 |
Published Version: | http://dx.doi.org/10.1109/ACC.2012.6315277 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.1109/ACC.2012.6315277 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:89712 |