The Maximum Initial Mass
Dario Izzo, Giacomo Acciarini
astro-ph.EP, astro-ph.IM
Submitted: 2026-06-28
License: http://creativecommons.org/licenses/by/4.0/
The gist: We introduce the maximum-initial-mass problem as a standalone optimal-control formulation for low-thrust trajectory design and analyze its structure within Pontryagin's framework.
Terminology
Abstract
We introduce the maximum-initial-mass problem as a standalone optimal-control formulation for low-thrust trajectory design and analyze its structure within Pontryagin's framework. For fixed transfer time and final state, the formulation seeks the largest initial mass from which the transfer is feasible, and its necessary conditions imply a full-throttle control law in the nondegenerate case together with the standard primer-vector steering direction. We then establish a correspondence between extremals of the maximum-initial-mass and minimum-time problems, showing that each minimum-time extremal induces a maximum-initial-mass extremal on the associated time interval, and conversely. This viewpoint also clarifies the role of the terminal Hamiltonian condition in indirect formulations of minimum-time problems, which we interpret as a gauge choice rather than an independent necessary condition in the setting considered. Finally, we show that the maximum-initial-mass framework provides a smooth and effective continuation strategy for multiple-revolution low-thrust transfers. Applied to a benchmark GTO-to-GEO transfer, the approach recovers the global minimum-time solution, reveals additional extremal branches, and makes explicit that some trajectories previously reported in the literature correspond to local maxima of transfer time along iso-M curves rather than to local minima.
Sources
- Reachability for Low-Thrust Trajectories via Maximum Initial Mass
- Pretrained Approximators for Low-Thrust Trajectory Cost and Reachability
- Rapid Determination of Low-Thrust Spacecraft Reachable Sets in Two-Body and Cislunar Problems
- Computing low-thrust transfers in the asteroid belt, a comparison between astrodynamical manipulations and a machine learning approach
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