Learning based Modelling of Throttleable Engine Dynamics for Lunar Landing Mission
Abstract
Typical lunar landing missions involve multiple phases of braking to achieve soft-landing. The propulsion system configuration for these missions consists of throttleable engines. This configuration involves complex interconnected hydraulic, mechanical, and pneumatic components each exhibiting non-linear dynamic characteristics. Accurate modelling of the propulsion dynamics is essential for analyzing closed-loop guidance and control schemes during descent. This paper presents a learning-based system identification approach for modelling of throttleable engine dynamics using data obtained from high-fidelity propulsion model. The developed model is validated with experimental results and used for closed-loop guidance and control simulations.
Cite
@article{arxiv.2511.08612,
title = {Learning based Modelling of Throttleable Engine Dynamics for Lunar Landing Mission},
author = {Suraj Kumar and Aditya Rallapalli and Bharat Kumar GVP},
journal= {arXiv preprint arXiv:2511.08612},
year = {2025}
}
Comments
5 pages, 9 figures, Global Space Exploration Conference 2025