Optimal spacecraft rendezvous using genetic algorithms

Young Ha Kim, David B. Spencer

Research output: Contribution to journalArticle

84 Citations (Scopus)

Abstract

The optimal rendezvous of two spacecraft are examined using a genetic algorithm. The minimum fuel solution of the optimal rendezvous contains many local optima, as well as discontinuities in the solution. These local optima and discontinuities make locating a global optimal solution difficult. Genetic algorithms are effective in solving these kinds of problems. The goal is to find the thrust time history that includes the magnitude and direction of the velocity change and the burn position, such that the boundary conditions are satisfied to an acceptable level and in a reasonable time. In addition, the number of thrust arcs and the maximum magnitude of the velocity change are regulated. This method was used on three test cases: 1) the Hohmann transfer, 2) the bielliptic transfer, and 3) rendezvous with two impulses. The results of the Hohmann and the bielliptic transfers match the analytical solutions within the resolution of the variables of the genetic algorithm. Although the result from the rendezvous with two impulses is not exact, the configuration of the trajectory is similar to the analytical solution.

Original languageEnglish (US)
Pages (from-to)859-865
Number of pages7
JournalJournal of Spacecraft and Rockets
Volume39
Issue number6
DOIs
StatePublished - Jan 1 2002

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space rendezvous
Space rendezvous
rendezvous
genetic algorithms
genetic algorithm
spacecraft
Genetic algorithms
discontinuity
thrust
impulses
Spacecraft
boundary condition
trajectory
Trajectories
Boundary conditions
arcs
trajectories
histories
boundary conditions
history

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering
  • Space and Planetary Science

Cite this

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Optimal spacecraft rendezvous using genetic algorithms. / Kim, Young Ha; Spencer, David B.

In: Journal of Spacecraft and Rockets, Vol. 39, No. 6, 01.01.2002, p. 859-865.

Research output: Contribution to journalArticle

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