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Published in:
2013 | OriginalPaper | Chapter
Distributed Optimization and State Based Ordinal Potential Games
Authors : Jianliang Zhang, Guangzhou Zhao, Donglian Qi
Published in: Intelligent Computing for Sustainable Energy and Environment
Publisher: Springer Berlin Heidelberg
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The focus of this paper is to develop a theoretical framework to analyze and address distributed optimization problem in multi-agent systems based on the cooperative control methodology and game theory. First the sensing/communication matrix is introduced and the minimal communication requirement among the agents is provided. Based on the matrix communication model, the state based ordinal potential game is designed to capture the optimal solution. It is worth noting that the proposed methodology can guarantee the distributed optimization problem converge to desired system level objective, even though the corresponding communication topologies may be local, time-varying and intermittent. Simulations on a multi-agent consensus problem are provided to verify the validness of the proposed methodology.