文章基本信息

标题：Game-Theoretic Feedback-Based Optimization
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作者：Anurag Agarwal ; John W. Simpson-Porco ; Lacra Pavel 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2022
卷号：55
期号：13
页码：174-179
DOI：10.1016/j.ifacol.2022.07.255
语种：English
出版社：Elsevier
摘要：AbstractThis paper examines the intersection between feedback-based optimization problems and distributed Nash equilibrium seeking algorithms. We consider a modification of typical GNE-seeking problems with affine coupling constraints, wherein each agent's objective additionally depends on the measurable output of a nonlinear input-output mapping. Operator-theoretic methods are leveraged to develop an online distributed algorithm for this class of problems, with convergence criteria provided. We illustrate the algorithm via an application to coordination of distributed energy resources in a power distribution feeder.
关键词：KeywordsGame-theorynetwork gamesDistributed optimizationMulti-agent systemsGeneralized Nash equilibriumPower systems