Maximum-likelihood estimation optimizer for constrained, time-optimal satellite reorientation

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The Covariance Matrix Adaptation-Evolutionary Strategy (CMA-ES) method provides a high-quality estimate of the control solution for an unconstrained satellite reorientation problem, and rapid, useful guesses needed for high-fidelity methods that can solve time-optimal reorientation problems with multiple path constraints. The CMA-ES algorithm offers two significant advantages over heuristic methods such as Particle Swarm or Bacteria Foraging Optimization: it builds an approximation to the covariance matrix for the cost function, and uses that to determine a direction of maximum likelihood for the search, reducing the chance of stagnation; and it achieves second-order, quasi-Newton convergence behavior. Copyright

Original languageEnglish (US)
Title of host publication64th International Astronautical Congress 2013, IAC 2013
PublisherInternational Astronautical Federation, IAF
Pages4729-4734
Number of pages6
ISBN (Print)9781629939094
StatePublished - Jan 1 2013
Event64th International Astronautical Congress 2013, IAC 2013 - Beijing, China
Duration: Sep 23 2013Sep 27 2013

Publication series

NameProceedings of the International Astronautical Congress, IAC
Volume6
ISSN (Print)0074-1795

Other

Other64th International Astronautical Congress 2013, IAC 2013
CountryChina
CityBeijing
Period9/23/139/27/13

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering
  • Astronomy and Astrophysics
  • Space and Planetary Science

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  • Cite this

    Melton, R. G. (2013). Maximum-likelihood estimation optimizer for constrained, time-optimal satellite reorientation. In 64th International Astronautical Congress 2013, IAC 2013 (pp. 4729-4734). (Proceedings of the International Astronautical Congress, IAC; Vol. 6). International Astronautical Federation, IAF.