Distributed optimization algorithm for discrete-time heterogeneous multi-agent systems with nonuniform stepsizes

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dc.contributor.author Mo, L.
dc.contributor.author Li, J.
dc.contributor.author Huang, Jian
dc.date.accessioned 2019-09-26T11:56:23Z
dc.date.available 2019-09-26T11:56:23Z
dc.date.issued 2019-06-27
dc.identifier.citation Mo, L., Li, J. and Huang, J. (2019) 'Distributed Optimization Algorithm for Discrete-Time Heterogeneous Multi-Agent Systems With Nonuniform Stepsizes', IEEE Access, 87303-87312. (7pp.) DOI: 10.1109/ACCESS.2019.2925414 en
dc.identifier.volume 7 en
dc.identifier.startpage 87303 en
dc.identifier.endpage 87312 en
dc.identifier.uri http://hdl.handle.net/10468/8623
dc.identifier.doi 10.1109/ACCESS.2019.2925414 en
dc.description.abstract This paper is devoted to the distributed optimization problem of heterogeneous multi-agent systems, where the communication topology is jointly strongly connected and the dynamics of each agent is the first-order or second-order integrator. A new distributed algorithm is first designed for each agent based on the local objective function and the local neighbors' information that each agent can access. By a model transformation, the original closed-loop system is converted into a time-varying system and the system matrix of which is a stochastic matrix at any time. Then, by the properties of the stochastic matrix, it is proven that all agents' position states can converge to the optimal solution of a team objective function provided the union communication topology is strongly connected. Finally, the simulation results are provided to verify the effectiveness of the distributed algorithm proposed in this paper. en
dc.description.sponsorship Beijing Educational Committee Foundation (Grant KM201910011007, PXM2019_014213 _000007);Beijing Natural Science Foundation (Grant Z180005); National Natural Science Foundation of China (Grant 61772063). en
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher Institute of Electrical and Electronics Engineers Inc. en
dc.relation.uri https://ieeexplore.ieee.org/document/8747511
dc.rights © The Author(s) 2019. This work is licensed under a Creative Commons Attribution 3.0 License. For more information, see http://creativecommons.org/licenses/by/3.0/ en
dc.rights.uri http://creativecommons.org/licenses/by/3.0/ en
dc.subject Closed loop systems en
dc.subject Discrete time systems en
dc.subject Distributed control en
dc.subject Matrix algebra en
dc.subject Multi-agent systems en
dc.subject Optimisation en
dc.subject Stochastic processes en
dc.subject Time-varying systems en
dc.subject Communication topology en
dc.subject Nonuniform stepsizes en
dc.subject Discrete-time heterogeneous multiagent systems en
dc.subject Stochastic matrix en
dc.subject System matrix en
dc.subject Time-varying system en
dc.subject Local objective function en
dc.subject Distributed optimization algorithim en
dc.subject Optimization en
dc.subject Linear programming en
dc.subject Distributed algorithims en
dc.subject Laplace equations en
dc.subject Topology en
dc.subject Distributed optimization en
dc.subject Heterogeneous en
dc.title Distributed optimization algorithm for discrete-time heterogeneous multi-agent systems with nonuniform stepsizes en
dc.type Article (peer-reviewed) en
dc.internal.authorcontactother Jian Huang, School of Mathematical Sciences, University College Cork, Cork, Ireland. +353-21-490-3000 Email:j.huang@ucc.ie en
dc.internal.availability Full text available en
dc.description.version Published Version en
dc.contributor.funder Beijing Educational Committee Foundation en
dc.contributor.funder Beijing Municipal Natural Science Foundation en
dc.contributor.funder National Natural Science Foundation of China en
dc.description.status Peer reviewed en
dc.identifier.journaltitle IEEE Access en
dc.internal.IRISemailaddress j.huang@ucc.ie en
dc.identifier.eissn 2169-3536


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© The Author(s) 2019. This work is licensed under a Creative Commons Attribution 3.0 License. For more information, see http://creativecommons.org/licenses/by/3.0/ Except where otherwise noted, this item's license is described as © The Author(s) 2019. This work is licensed under a Creative Commons Attribution 3.0 License. For more information, see http://creativecommons.org/licenses/by/3.0/
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