TY - GEN
T1 - Particle swarm optimization of low-thrust orbital transfers and rendezvous
AU - Pontani, Mauro
AU - Conway, Bruce A.
PY - 2011
Y1 - 2011
N2 - The particle swarm optimization technique is a population-based stochastic method developed in recent years and successfully applied in several fields of research. It represents a very intuitive (and easy to program) methodology for global optimization, inspired by the behavior of bird flocks while searching for food. The particle swarm optimization technique attempts to take advantage of the mechanism of information sharing that affects the overall behavior of a swarm, with the intent of determining the optimal values of the unknown parameters of the problem under consideration. In this research the technique is applied to determining optimal low-thrust orbit transfers and rendezvous. Hamiltonian methods are employed to translate the related optimal control problems into parameter optimization problems. Thus the parameters sought by the PSO are primarily initial values of the costates and the final time if that is unspecified. The PSO is extremely easy to program. Nevertheless, it proves to be effective, reliable, and numerically accurate in solving the optimization problems considered in this work.
AB - The particle swarm optimization technique is a population-based stochastic method developed in recent years and successfully applied in several fields of research. It represents a very intuitive (and easy to program) methodology for global optimization, inspired by the behavior of bird flocks while searching for food. The particle swarm optimization technique attempts to take advantage of the mechanism of information sharing that affects the overall behavior of a swarm, with the intent of determining the optimal values of the unknown parameters of the problem under consideration. In this research the technique is applied to determining optimal low-thrust orbit transfers and rendezvous. Hamiltonian methods are employed to translate the related optimal control problems into parameter optimization problems. Thus the parameters sought by the PSO are primarily initial values of the costates and the final time if that is unspecified. The PSO is extremely easy to program. Nevertheless, it proves to be effective, reliable, and numerically accurate in solving the optimization problems considered in this work.
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M3 - Conference contribution
AN - SCOPUS:80053402051
SN - 9780877035695
T3 - Advances in the Astronautical Sciences
SP - 889
EP - 908
BT - Spaceflight Mechanics 2011 - Advances in the Astronautical Sciences
T2 - 21st AAS/AIAA Space Flight Mechanics Meeting
Y2 - 13 February 2011 through 17 February 2011
ER -