CORE
🇺🇦
make metadata, not war
Services
Services overview
Explore all CORE services
Access to raw data
API
Dataset
FastSync
Content discovery
Recommender
Discovery
OAI identifiers
OAI Resolver
Managing content
Dashboard
Bespoke contracts
Consultancy services
Support us
Support us
Membership
Sponsorship
Community governance
Advisory Board
Board of supporters
Research network
About
About us
Our mission
Team
Blog
FAQs
Contact us
unknown
Mixed integer optimal compensation: Decompositions and mean-field approximations
Authors
T. Basar
D. Bauso
Z. Quanyan
Publication date
1 June 2012
Publisher
'Institute of Electrical and Electronics Engineers (IEEE)'
Doi
Cite
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)
Similar works
Full text
Open in the Core reader
Download PDF
Available Versions
White Rose Research Online
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:eprints.whiterose.ac.uk:89...
Last time updated on 02/08/2016