Advancing Averaged Primer Vector Theory with Bang-Bang Control and Eclipsing
Noah Lifset

TL;DR
This paper enhances primer vector theory for low-thrust spacecraft trajectory optimization by integrating bang-bang control, eclipsing constraints, and multi-arc averaging, resulting in a practical, efficient, and more accurate modeling approach.
Contribution
It introduces a unified, practical formulation for minimum-fuel trajectory optimization that handles eclipsing constraints and bang-bang control efficiently using averaged dynamics.
Findings
Fixed a key singularity in eclipsing constraint handling.
Established an upper bound of six switching roots per revolution.
Demonstrated the model on a GTO to GEO transfer with up to 486 revolutions.
Abstract
Primer vector theory using averaged dynamics is well suited for optimizing low-thrust, many-revolution spacecraft trajectories, but is difficult to implement in a way that maintains both optimality and computational efficiency. An improved model is presented that combines advances from several past works into a general and practical formulation for minimum-fuel, perturbed Keplerian dynamics. The model maintains computational efficiency of dynamics averaging with optimal handling of the eclipsing constraint and bang-bang control through the use of the Leibniz integral rule for multi-arc averaging. A subtle, but important singularity arising from the averaged eclipsing constraint is identified and fixed. A maximum number of six switching function roots per revolution is established within the averaged dynamics. This new theoretical insight provides a practical upper-bound on the number of…
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