A hybrid layout optimization method based on genetic and differential evolution for Flat-panel (FP) microsatellite

Hao Zhang, Jun Zhou, Guanghui Liu, Jianguo Guo, Zhenxin Feng

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

1 Scopus citations

Abstract

Flat-panel (FP) satellites are a novel type of microsatellite configuration, and a hybrid algorithmic layout optimization method is studied in this paper to solve the problem of its large moment of inertia. The method is implemented by two-level algorithms of genetic and differential evolution, in which the genetic algorithm is used to realize the optimal allocation of components within different satellite modules to ensure the mass balance between satellite modules; the differential evolution algorithm further plans the positions of components within the modules and enables the satellite to obtain the optimal moment of inertia and layout scheme. Finally, the effectiveness of the proposed method is verified by the case of layout optimization of remote sensing satellites.

Original languageEnglish
Title of host publicationProceedings of the 43rd Chinese Control Conference, CCC 2024
EditorsJing Na, Jian Sun
PublisherIEEE Computer Society
Pages2052-2057
Number of pages6
ISBN (Electronic)9789887581581
DOIs
StatePublished - 2024
Event43rd Chinese Control Conference, CCC 2024 - Kunming, China
Duration: 28 Jul 202431 Jul 2024

Publication series

NameChinese Control Conference, CCC
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference43rd Chinese Control Conference, CCC 2024
Country/TerritoryChina
CityKunming
Period28/07/2431/07/24

Keywords

  • differential evolution algorithm
  • Genetic algorithm
  • layout optimization
  • Microsatellite
  • moment of inertia

Fingerprint

Dive into the research topics of 'A hybrid layout optimization method based on genetic and differential evolution for Flat-panel (FP) microsatellite'. Together they form a unique fingerprint.

Cite this