Robust optimal powered descent guidance via model predictive convex programming

被引：0
作者：
Xiao, Yizheng [1 ]
Gong, Youmin [2 ]
Mei, Jie [2 ]
Ma, Guangfu [2 ]
Wu, Weiren [1 ,3 ]
机构：
[1] Harbin Inst Technol, Sch Aerosp Sci, Shenzhen 518055, Guangdong, Peoples R China
[2] Harbin Inst Technol, Sch Intelligence Sci & Engn, Shenzhen 518055, Guangdong, Peoples R China
[3] Deep Space Explorat Lab, Beijing 100089, Peoples R China
来源：
AEROSPACE SCIENCE AND TECHNOLOGY | 2025年 / 159卷
基金：
中国国家自然科学基金;
关键词：
Powered descent guidance; Convex programming; Trajectory optimization; Uncertainty propagation; Robust optimization; TRAJECTORY OPTIMIZATION; POLYNOMIAL CHAOS; MARS ENTRY; SMALL BODIES; DESIGN;
D O I：
10.1016/j.ast.2025.109999
中图分类号：
V [航空、航天];
学科分类号：
08 ; 0825 ;
摘要：
This paper investigates the robust fuel-optimal guidance problem for powered descent landing under uncertainty. A robust optimal control problem (OCP) with stochastic dynamics and constraints is first constructed to ensure both optimality and safety. The polynomial chaos expansion (PCE)-based uncertainty quantification technique is then employed to convert the stochastic OCP into a high-dimensional deterministic OCP, which, while tractable, involves a large number of decision variables and is computationally intensive. To mitigate this issue, the dynamics are convexified within the model predictive convex programming (MPCP) framework, reducing the number of decision variables by establishing the sensitivity relationship between state and control corrections. Furthermore, convexification techniques including lossless convexification and successive convexification are applied to convexify the nonlinear inequality constraints. To enhance computational efficiency, a dimension reduction method is also introduced. After solving the robust OCP through convex optimization, a closed-loop guidance algorithm based on receding horizon strategy is proposed to address navigational errors. Numerical simulations demonstrate the advantages of this guidance algorithm.
引用
收藏
页数：13
相关论文
共 47 条
  • [1] Malyuta D., Yu Y., Elango P., Acikmese B., Advances in trajectory optimization for space vehicle control, Annu. Rev. Control, 52, pp. 282-315, (2021)
  • [2] Acikmese B., Ploen S.R., Convex programming approach to powered descent guidance for Mars landing, J. Guid. Control Dyn., 30, 5, pp. 1353-1366, (2007)
  • [3] Scharf D.P., Acikmese B., Dueri D., Benito J., Casoliva J., Implementation and experimental demonstration of onboard powered-descent guidance, J. Guid. Control Dyn., 40, 2, pp. 213-229, (2017)
  • [4] Szmuk M., Acikmese B., Successive convexification for 6-dof Mars rocket powered landing with free-final-time, 2018 AIAA Guidance, Navigation, and Control Conference, (2018)
  • [5] Liu X., Shen Z., Lu P., Entry trajectory optimization by second-order cone programming, J. Guid. Control Dyn., 39, 2, pp. 227-241, (2016)
  • [6] Bernardini N., Baresi N., Armellin R., State-dependent trust region for successive convex programming for autonomous spacecraft, Astrodynamics, pp. 1-23, (2024)
  • [7] Liu X., Lu P., Pan B., Survey of convex optimization for aerospace applications, Astrodynamics, 1, pp. 23-40, (2017)
  • [8] Blackmore L., Acikmese B., Scharf D.P., Minimum-landing-error powered-descent guidance for Mars landing using convex optimization, J. Guid. Control Dyn., 33, 4, pp. 1161-1171, (2010)
  • [9] Bai C., Guo J., Zheng H., Optimal guidance for planetary landing in hazardous terrains, IEEE Trans. Aerosp. Electron. Syst., 56, 4, pp. 2896-2909, (2019)
  • [10] Szmuk M., Reynolds T.P., Acikmese B., Successive convexification for real-time six-degree-of-freedom powered descent guidance with state-triggered constraints, J. Guid. Control Dyn., 43, 8, pp. 1399-1413, (2020)
12345