The reentry trajectory optimization of spacecraft based on genetic algorithm particle swarm optimization

Research output: Contribution to conferencePaperpeer-review

Abstract

The genetic algorithm particle swarm optimization is a concise, effective and stable algorithm to solve the hierarchical problem based on GA algorithm. In this paper, considering the advantages of the GAPSO, the modified GAPSO is proposed to optimize the reentry performance of the spacecraft. The objectives of the reentry problem are to maximize the cross range and minimize the total heat applied to the spacecraft. The simulation results demonstrate that the modified GAPSO technique presents a reliable, efficient, and accurate method for determining optimal reentry performances.

Original languageEnglish
StatePublished - 2014
Event3rd International Workshop on Advanced Computational Intelligence and Intelligent Informatics, IWACIII 2013 - Shanghai, China
Duration: 18 Oct 201321 Oct 2013

Conference

Conference3rd International Workshop on Advanced Computational Intelligence and Intelligent Informatics, IWACIII 2013
Country/TerritoryChina
CityShanghai
Period18/10/1321/10/13

Keywords

  • Genetic algorithm
  • Particle swarm optimization
  • Reentry trajectory optimization

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