Evolutionary game theory based multi-objective optimization for control allocation of over-actuated system

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dc.contributor.author Park, On
dc.contributor.author Shin, Hyo-Sang
dc.contributor.author Tsourdos, Antonios
dc.date.accessioned 2020-02-11T16:05:57Z
dc.date.available 2020-02-11T16:05:57Z
dc.date.issued 2019-11-25
dc.identifier.citation Park O, Shin H-S and Tsourdos A. Evolutionary game theory based multi-objective optimization for control allocation of over-actuated system. IFAC-PapersOnLine, Volume 52, Issue 12, 2019, pp. 310-315 en_UK
dc.identifier.issn 2405-8963
dc.identifier.uri https://doi.org/10.1016/j.ifacol.2019.11.261
dc.identifier.uri http://dspace.lib.cranfield.ac.uk/handle/1826/15118
dc.description.abstract This research presents multi-objective optimization for control allocation problem based on the Evolutionary Game Theory to solve distribution of redundant control input on the over actuated system in real-time. Optimizing the conflicting objectives, an evolutionary game theory based approach with replicator dynamics is used to find the optimal weighting using the weighted sum method. The main idea of this method is that the best strategy or dominant solution can be selected as a solution that survives among other non-dominant solutions. The Evolutionary Game Theory considers strategies as a player and investigates how these strategies can survive using replicator dynamics with payoff matrix. The numerical simulation results show the optimal weightings selected by Evolutionary Game and how the payoff has been changed in replicator dynamics. en_UK
dc.language.iso en en_UK
dc.publisher Elsevier en_UK
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International *
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/4.0/ *
dc.subject Multi-Objective Optimization en_UK
dc.subject Weighted Sum Method en_UK
dc.subject Evolutionary Game Theory en_UK
dc.subject Replicator Dynamics en_UK
dc.subject Evolutionary Stable Strategy en_UK
dc.subject Control Allocation en_UK
dc.title Evolutionary game theory based multi-objective optimization for control allocation of over-actuated system en_UK
dc.type Article en_UK


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