Date of Award
3-24-2016
Document Type
Thesis
Degree Name
Master of Science in Astronautical Engineering
Department
Department of Aeronautics and Astronautics
First Advisor
Christopher D. Geisel, PhD.
Abstract
Particle swarm optimization is used to generate an initial guess for designing fuel-optimal trajectories in multiple dynamical environments. Trajectories designed in the vicinity of Earth use continuous or finite low-thrust burning and transfer from an inclined or equatorial circular low-Earth-orbit to a geostationary orbit. In addition, a trajectory from near-Earth to a periodic orbit about the cislunar Lagrange point with minimized impulsive burn costs is designed within a multi-body dynamical environment. Direct transcription is used in conjunction with a nonlinear optimizer to find locally-optimal trajectories given the initial guess. The near-Earth transfers are propagated at low-level thrust where neither the very-low-thrust spiral solution nor the impulsive transfer is an acceptable starting point. The very-high-altitude transfer is designed in a multi-body dynamical environment lacking a closed-form analytical solution. Swarming algorithms excel given a small number of design parameters.When continuous control time histories are needed, employing a polynomial parameterization facilitates the generation of feasible solutions. For design in a circular restricted three-body system, particle swarm optimization gains utility due to a more global search for the solution, but may be more sensitive to boundary constraints. Computation time and constraint weighting are areas where a swarming algorithm is weaker than other approaches.
AFIT Designator
AFIT-ENY-MS-16-M-250
DTIC Accession Number
AD1028880
Recommended Citation
Zurita, Alfredo G. Jr., "Minimum-Fuel Trajectory Design in Multiple Dynamical Environments Utilizing Direct Transcription Methods and Particle Swarm Optimization" (2016). Theses and Dissertations. 456.
https://scholar.afit.edu/etd/456