Cooperative target assignment for unmanned combat aerial vehicles based on Bayesian optimization algorithm with decision graphs

Lu Cao, An Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

In order to solve target assignment problems for unmanned combat aerial vehicles (UCAVs) during the process of UCAVs cooperative control, a cooperative target assignment methodology based on the Bayesian optimization algorithm with decision graphs (DBOA) is put forward. Firstly, considering enemies, ourselves and internal conflicts of UCAVs, a cooperative target assignment mathematical model is established. Then, avoiding trapping in local optimal solutions, the Bayesian network is constructing to guide and optimize evolution capabilities of the population. Finally, the simulation results show that the Bayesian optimization algorithm with decision graphs has a rapid convergence speed and can obtain the optimal solution. The results also demonstrate that the assignment methodology above owns a good time efficiency and assignment effect.

Original languageEnglish
Title of host publicationProceedings - 2013 9th International Conference on Natural Computation, ICNC 2013
PublisherIEEE Computer Society
Pages439-443
Number of pages5
ISBN (Print)9781467347143
DOIs
StatePublished - 2013
Event2013 9th International Conference on Natural Computation, ICNC 2013 - Shenyang, China
Duration: 23 Jul 201325 Jul 2013

Publication series

NameProceedings - International Conference on Natural Computation
ISSN (Print)2157-9555

Conference

Conference2013 9th International Conference on Natural Computation, ICNC 2013
Country/TerritoryChina
CityShenyang
Period23/07/1325/07/13

Keywords

  • Bayesian optimization algorithm with decision graphs
  • cooperative target assignment
  • global optimization
  • unmanned combat aerial vehicles

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