@article{GUO2026, 
author = {Kang GUO and Huifeng LI and Weimin BAO},
title = {Hybrid guidance method for launch vehicle trans-lunar injection},
year = {2026},
journal = {Journal of Beijing University of Aeronautics and Astronautics},
volume = {52},
number = {10},
pages = {3592-3601},
keywords = {launch vehicle guidance, trans-lunar injection, real-time trajectory planning, second-order cone programming, neighboring optimal control},
url = {https://www.sciopen.com/article/10.13700/j.bh.1001-5965.2025.0353},
doi = {10.13700/j.bh.1001-5965.2025.0353},
abstract = {This paper addresses the critical guidance problem for launch vehicles performing trans-lunar injection missions with low thrust-to-weight ratios, where the extended flight duration and substantial multi-source uncertainties present formidable challenges to conventional closed-loop guidance methods. A novel hybrid guidance approach integrating second-order cone programming with neighboring optimal control is developed to overcome these challenges. The proposed methodology begins with establishing a comprehensive trans-lunar injection problem model that explicitly accounts for multi-source uncertainties. A hybrid guidance strategy based on real-time trajectory planning is formulated to handle these uncertainties effectively. The main innovation is the application of a real-time trajectory planning technique that uses second-order cone programming in conjunction with Gauss pseudospectral discretization. By synergistically applying the costate mapping theorem and exploiting the dual output of second-order cone programming, the method achieves high-precision costate estimation, which provides the essential foundation for the neighboring optimal control component. A trajectory correction method based on neighboring optimal control is developed to address situations where uncertainties cause significant trajectory deviations. This method generates high-quality initial references for the second-order cone programming solver, substantially improving convergence characteristics and computational efficiency. Extensive numerical experiments demonstrate the superiority of the proposed guidance method in trans-lunar injection missions. The computational performance shows remarkable improvement, with the average computation time reduced to 75.353 milliseconds per guidance cycle, representing a 30.67% reduction. In comparison to current methods, this hybrid guidance method’s successful demonstration offers a novel and feasible technical pathway for trans-lunar injection missions.}
}