Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/159487
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dc.contributor.authorLi, Xiuxianen_US
dc.contributor.authorYi, Xinleien_US
dc.contributor.authorXie, Lihuaen_US
dc.date.accessioned2022-06-21T08:41:26Z-
dc.date.available2022-06-21T08:41:26Z-
dc.date.issued2020-
dc.identifier.citationLi, X., Yi, X. & Xie, L. (2020). Distributed online optimization for multi-agent networks with coupled inequality constraints. IEEE Transactions On Automatic Control, 66(8), 3575-3591. https://dx.doi.org/10.1109/TAC.2020.3021011en_US
dc.identifier.issn0018-9286en_US
dc.identifier.urihttps://hdl.handle.net/10356/159487-
dc.description.abstractThis article investigates the distributed online optimization problem over a multi-agent network subject to local set constraints and coupled inequality constraints, which has a lot of applications in many areas, such as wireless sensor networks, power systems, and plug-in electric vehicles. In this problem, the cost function at each time step is the sum of local cost functions with each of them being gradually revealed to its corresponding agent, and meanwhile only local functions in coupled inequality constraints are accessible to each agent. To address this problem, a modified primal-dual algorithm, called distributed online primal-dual push-sum algorithm, is developed in this article, which does not rest on any assumption on parameter boundedness and is applicable to unbalanced networks. It is shown that the proposed algorithm is sublinear for both the dynamic regret and the violation of coupled inequality constraints. Finally, the theoretical results are supported by a simulation example.en_US
dc.description.sponsorshipMinistry of Education (MOE)en_US
dc.language.isoenen_US
dc.relationRG72en_US
dc.relation.ispartofIEEE Transactions on Automatic Controlen_US
dc.rights© 2020 IEEE. All rights reserved.en_US
dc.subjectEngineering::Electrical and electronic engineeringen_US
dc.titleDistributed online optimization for multi-agent networks with coupled inequality constraintsen_US
dc.typeJournal Articleen
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.identifier.doi10.1109/TAC.2020.3021011-
dc.identifier.scopus2-s2.0-85107736181-
dc.identifier.issue8en_US
dc.identifier.volume66en_US
dc.identifier.spage3575en_US
dc.identifier.epage3591en_US
dc.subject.keywordsCoupled Inequality Constraintsen_US
dc.subject.keywordsDistributed Online Optimizationen_US
dc.description.acknowledgementThis work was supported by the Ministry of Education of Singapore under MoE Tier 1 Research Grant RG72.en_US
item.grantfulltextnone-
item.fulltextNo Fulltext-
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