Optimal station keeping strategies via parallel genetic algorithms

In an effort to overcome the limitations of more traditional methods this paper investigates the use of genetic algorithms in generating non-greedy, global, near-optimal station-keeping strategies. The orbit of an Ellipso(TM) Borealis satellite is constrained and the minimum-fuel optimal burn strategy is developed such that the orbit is maintained within the specified constraints over the entire Lime period of interest. The resulting fuel costs are shown to be lower than costs estimated via previous methods, specifically previous primer vector strategies. Operational and computational limitations of this method are also described.