ADP-Based Orbit Tracking Control for Deep Space Probe Flying Around Unknown Asteroid

This article investigates the orbit tracking control problem for the deep space probe flying around an unknown asteroid under completely unknown dynamics. First, an orbit tracking control model for the relative motion of the probe to the asteroid is established. Then, a model-based controller is designed for the optimal tracking control problem and the asymptotic stability of the closed-loop system is proved. Next, an adaptive dynamic programming (ADP) algorithm based on policy iteration is adopted to obtain a model-free suboptimal controller that approximates the previous model-based controller, followed by the convergence analysis. Specifically, by collecting some data online, a system of high-order linear equations is constructed and then solved to obtain parameters utilized in controller construction. Finally, numerical simulations are provided to validate the effectiveness and the performance of the proposed control method.

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Publication Details

Journal
IEEE Transactions on Neural Networks and Learning Systems
Published
2025-06-19
DOI
https://doi.org/10.1109/tnnls.2025.3578863
Primary Topic
Space Satellite Systems and Control
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
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article

ADP-Based Orbit Tracking Control for Deep Space Probe Flying Around Unknown Asteroid

Yanwei Ding, Hui‐Jie Sun, Wenjian Tao, Jinxiu Zhang et al.
IEEE Transactions on Neural Networks and Learning Systems
Space Satellite Systems and Control
article

ADP-Based Orbit Tracking Control for Deep Space Probe Flying Around Unknown Asteroid

Yanwei Ding, Hui‐Jie Sun, Wenjian Tao, Jinxiu Zhang, Zebin Chen
article en

Abstract

This article investigates the orbit tracking control problem for the deep space probe flying around an unknown asteroid under completely unknown dynamics. First, an orbit tracking control model for the relative motion of the probe to the asteroid is established. Then, a model-based controller is designed for the optimal tracking control problem and the asymptotic stability of the closed-loop system is proved. Next, an adaptive dynamic programming (ADP) algorithm based on policy iteration is adopted to obtain a model-free suboptimal controller that approximates the previous model-based controller, followed by the convergence analysis. Specifically, by collecting some data online, a system of high-order linear equations is constructed and then solved to obtain parameters utilized in controller construction. Finally, numerical simulations are provided to validate the effectiveness and the performance of the proposed control method.

IEEE Transactions on Neural Networks and Learning SystemsVol. 36(10)
Sun Yat-sen University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 81%
Space Satellite Systems and Control
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