Stochastic Advance ΔV99 Evolutionary Optimization - An Application to Europa Clipper

The Europa Clipper mission will investigate the habitability of Europa by conducting over 50 low-altitude flybys, each subject to stringent science constraints making it an operationally challenging mission. The design of the reference trajectory and navigation delivery requirements are coupled and are driven by science objectives. This work will introduce a capability of combining the design of the reference trajectory and the often decoupled stochastic analysis to conduct a robust trajectory optimization using an automated tool, called as Stochastic Advance ΔV99 Evolutionary Optimization (SAVE). The main goal is to minimize the stochastic fuel consumption while respecting operational constraints and probabilistic constraints like the probability of impact with the Galilean satellites. The statistical analysis of the nominal trajectory accounts for corrections due to expected maneuver execution and state knowledge errors, but lacks the mechanism of accommodating errors into the reference due to missed maneuvers or other large errors for robustness. SAVE also demonstrated the capability of modeling such errors and redesigning the nominal trajectory in case of such contingencies.