Optimal topology for consensus using genetic algorithm

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dc.contributor.authorMondal, Sabyasachi
dc.contributor.authorTsourdos, Antonios
dc.date.accessioned2020-07-16T15:41:07Z
dc.date.available2020-07-16T15:41:07Z
dc.date.freetoread2021-05-09
dc.date.issued2020-05-08
dc.description.abstractIn the Multi-Agent Systems (MAS), graph network topologies play a crucial role in building consensus among the connected agents. Consensus may be achieved on many network graphs using distributed control theory. However, the optimal network topology is not addressed in most of the literature, which is an important part of building stable consensus among networked agents. In this paper, the optimal topology is obtained irrespective of the agent dynamics by using two-dimensional Genetic Algorithm (GA), which is a new approach in this context. Simulation result for agents with first, and second-order linear dynamic is obtained. These results show that the proposed method achieves consensus using the optimal network topology satisfactorily.en_UK
dc.identifier.citationMondal S, Tsourdos A. (2020) Optimal topology for consensus using genetic algorithm. Neurocomputing, Volume 404, September 2020, pp.1-49en_UK
dc.identifier.cris27210464
dc.identifier.issn0925-2312
dc.identifier.urihttps://doi.org/10.1016/j.neucom.2020.04.107
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/15559
dc.language.isoenen_UK
dc.publisherElsevieren_UK
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectOptimal topologyen_UK
dc.subjectTwo-dimensional Genetic Algorithmen_UK
dc.subjectDistributed controlen_UK
dc.subjectMulti-Agent System (MAS)en_UK
dc.subjectConsensusen_UK
dc.titleOptimal topology for consensus using genetic algorithmen_UK
dc.typeArticleen_UK

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