TY - GEN
T1 - Maximum-likelihood estimation optimizer for constrained, time-optimal satellite reorientation
AU - Melton, Robert G.
PY - 2013/1/1
Y1 - 2013/1/1
N2 - 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
AB - 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
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M3 - Conference contribution
AN - SCOPUS:84904683225
SN - 9781629939094
T3 - Proceedings of the International Astronautical Congress, IAC
SP - 4729
EP - 4734
BT - 64th International Astronautical Congress 2013, IAC 2013
PB - International Astronautical Federation, IAF
T2 - 64th International Astronautical Congress 2013, IAC 2013
Y2 - 23 September 2013 through 27 September 2013
ER -