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

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12 Scopus citations


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 Optimisation: 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 behaviour.

Original languageEnglish (US)
Pages (from-to)185-192
Number of pages8
JournalActa Astronautica
StatePublished - 2014

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering


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