Date of Award
Doctor of Philosophy (PhD)
Department of Aeronautics and Astronautics
Jonathan T. Black, PhD.
The growing congestion in space has increased the need for spacecraft to develop resilience capabilities in response to natural and man-made hazards. Equipping satellites with increased maneuvering capability has the potential to enhance resilience by altering their arrival conditions as they enter potentially hazardous regions. The propellant expenditure corresponding to increased maneuverability requires these maneuvers be optimized to minimize fuel expenditure and to the extent which resiliency can be preserved. This research introduces maneuvers to enhance resiliency and investigates the viability of metaheuristics to enable their autonomous optimization. Techniques are developed to optimize impulsive and continuous-thrust resiliency maneuvers. The results demonstrate that impulsive and low-thrust resiliency maneuvers require only meters per second of delta-velocity. Additionally, bi-level evolutionary algorithms are explored in the optimization of resiliency maneuvers which require a maneuvering spacecraft to perform an inspection of one of several target satellites while en-route to geostationary orbit. The methods developed are shown to consistently produce optimal and near-optimal results for the problems investigated and can be applied to future classes of resiliency maneuvers yet to be defined. Results indicate that the inspection requires an increase of only five percent of the propellant needed to transfer from low Earth orbit to geostationary orbit. The maneuvers and optimization techniques developed throughout this dissertation demonstrate the viability of the autonomous optimization of spacecraft resiliency maneuvers and can be utilized to optimize future classes of resiliency maneuvers.
DTIC Accession Number
Showalter, Daniel J., "Optimal Autonomous Spacecraft Resiliency Maneuvers Using Metaheuristics" (2014). Theses and Dissertations. 560.