Publication
Non-centralized control for flow-based distribution networks: A game-theoretical insight
Journal Article (2017)
Journal
Journal of the Franklin Institute
Pages
5771-5796
Volume
354
Number
14
Doc link
http://dx.doi.org/10.1016/j.jfranklin.2017.06.021
File
Authors
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Barreiro-Gomez, Julian
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Ocampo Martínez, Carlos A.
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Quijano Silva, Nicanor
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Maestre Torreblanca, José María
Projects associated
Abstract
This paper solves a data-driven control problem for a flow-based distribution network with two objectives: a resource allocation and a fair distribution of costs. These objectives represent both cooperation and competition directions. It is proposed a solution that combines either a centralized or distributed cooperative game approach using the Shapley value to determine a proper partitioning of the system and a fair communication cost distribution. On the other hand, a decentralized noncooperative game approach computing the Nash equilibrium is used to achieve the control objective of the resource allocation under a non-complete information topology. Furthermore, an invariant-set property is presented and the closed-loop system stability is analyzed for the non-cooperative game approach. Another contribution regarding the cooperative game approach is an alternative way to compute the Shapley value for the proposed specific characteristic function. Unlike the classical cooperative-games approach, which has a limited application due to the combinatorial explosion issues, the alternative method allows calculating the Shapley value in polynomial time and hence can be applied to large-scale problems.
Categories
automation, optimisation.
Author keywords
Flow-based distribution networks, population games, Nash equilibrium, cooperative games, Shapley value, dynamic resource allocation, partitioning approach, distributed control
Scientific reference
J. Barreiro-Gomez, C. Ocampo-Martínez, N. Quijano and J.M. Maestre. Non-centralized control for flow-based distribution networks: A game-theoretical insight. Journal of the Franklin Institute, 354(14): 5771-5796, 2017.
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