Autonomous orbital maintenance using a supervised-learning-based target point approach

Fu, Xiaoyu ORCID: 0000-0002-6405-5655 and Soldini, Stefania ORCID: 0000-0003-3121-3845 (2026) Autonomous orbital maintenance using a supervised-learning-based target point approach Acta Astronautica, 244. pp. 141-155. ISSN 0094-5765, 1879-2030

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Abstract

Autonomous orbital maintenance is a fundamental component of spacecraft autonomy and has become an active area of research. This study investigates the feasibility of implementing an autonomous onboard Target Point Approach (TPA) for the stationkeeping of periodic orbits, enabled by supervised learning. A stochastic optimization framework based on the TPA is first employed to generate optimal stationkeeping parameters from a range of initial state deviations. Based on these solutions, a large balanced dataset is constructed and used to train supervised learning models, including a multilayer perceptron (MLP) classifier to distinguish feasible from infeasible initial deviations, and MLP regressors to predict optimal stationkeeping parameters directly from initial deviations. The trained models are then integrated into an onboard TPA-based stationkeeping framework and evaluated through large-scale simulations involving 100,000 initial state deviations for a candidate Near Rectilinear Halo Orbit (NRHO). The simulation results demonstrate the effectiveness and robustness of the proposed approach. Furthermore, regularities observed from the large-scale stationkeeping analysis are identified and analysed, providing insight into the structure of the stationkeeping solution space and the learning-enabled decision process.

Item Type:	Article
Uncontrolled Keywords:	Spacecraft autonomy, Autonomous orbital maintenance, Supervised learning, Target point approach, Stochastic optimization
Divisions:	Faculty of Science & Engineering Faculty of Science & Engineering > School of Engineering Faculty of Science & Engineering > School of Engineering > Mechanical and Aerospace Engineering
Depositing User:	Symplectic Admin
Date Deposited:	13 Feb 2026 10:27
Last Modified:	28 Feb 2026 20:48
DOI:	10.1016/j.actaastro.2026.02.008
Related Websites:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3197015
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