Genetic Algorithm-Based Re-Entry Trajectory Optimization and Footprint Determination for Lifting Body Spacecraft

Qian Peng, Jianguo Guo, Shengjiang Yang

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

3 Scopus citations

Abstract

The re-entry trajectory optimization and the footprint determination for constrained vehicle are important and challenging. This paper presents genetic algorithm (GA)-based optimization schemes considering various constraints and control objectives to generate the optimal re-entry trajectory and solve the footprint problem for lifting body spacecraft. The model of re-entry lifting body spacecraft is constructed with constraints. The re-entry phase is divided into initial entry phase and equilibrium glide phase according to the characteristics of aerodynamic environment. Then, the GA-based optimization schemes are designed for these two sub-phases considering different constraints and control objectives. In addition, the steps of determining inner and outer boundaries are proposed to obtain the enclosed range of footprint. Simulation results indicate that the proposed GA-based optimization schemes are remarkable and effective to find out the optimal initial entry and equilibrium glide trajectories and the footprint.

Original languageEnglish
Title of host publicationAdvances in Guidance, Navigation and Control - Proceedings of 2020 International Conference on Guidance, Navigation and Control, ICGNC 2020
EditorsLiang Yan, Haibin Duan, Xiang Yu
PublisherSpringer Science and Business Media Deutschland GmbH
Pages1369-1379
Number of pages11
ISBN (Print)9789811581540
DOIs
StatePublished - 2022
EventInternational Conference on Guidance, Navigation and Control, ICGNC 2020 - Tianjin, China
Duration: 23 Oct 202025 Oct 2020

Publication series

NameLecture Notes in Electrical Engineering
Volume644 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

ConferenceInternational Conference on Guidance, Navigation and Control, ICGNC 2020
Country/TerritoryChina
CityTianjin
Period23/10/2025/10/20

Keywords

  • Footprint
  • Genetic algorithm
  • Re-entry trajectory
  • Trajectory optimization

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