Stochastic Primer Vector for Robust Low-Thrust Trajectory Design Under Uncertainty

What is it about?

Any space trajectories are subject to state uncertainty due to imperfect state knowledge, random disturbances, and partially known dynamical environments. Ideally, such uncertainty and associated risks must be properly quantified and taken into account the process of trajectory design, ensuring a sufficiently low risk of causing hazardous events. To bridge the gap between the ideal goal and the current practice in mission design, this paper develops a solution method to solve the problem of low-thrust trajectory optimization under state uncertainty. The validity and effectiveness of the theoretical development are demonstrated in two illustrative examples, which confirm through Monte-Carlo simulations that the designed trajectories satisfy the imposed constraints under uncertainty with the prescribed confidence level.

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