Scholarlink

<p>This paper introduces a landing guidance strategy for reusable launch vehicles (RLVs) using a model predictive approach based on sequential convex programming (SCP). The proposed approach devises two distinct optimal control problems (OCPs): planning a fuel-optimal landing trajectory that accommodates practical path constraints specific to RLVs, and determining real-time optimal tracking commands. This dual optimization strategy, which refers to the definition of planning and tracking problems, allows for reduced computational load through adjustable prediction horizon lengths in the tracking task, achieving near closed-loop performance. Enhancements in model fidelity for the tracking task are achieved through an alternative rotational dynamics representation, enabling a more stable numerical solution of the OCP and accounting for vehicle transient dynamics. Furthermore, modifications of aerodynamic force in both planning and tracking phases are proposed, tailored for thrust-vector-controlled RLVs, to reduce the fidelity gap without adding computational complexity. Extensive 6-degree-of-freedom (6-DOF) simulation experiments validate the effectiveness and improved guidance performance of the proposed algorithm.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Optimal Landing Guidance of Reusable Launch Vehicles With Dual-convex Optimization

  • 期刊论文

  • 发表日期：

    2025年8月13日

查看全文
  • Ki-Wook Jung,
  • Sang-Don Lee,
  • Cheol-Goo Jung,
  • Chang-Hun Lee

摘要

This paper introduces a landing guidance strategy for reusable launch vehicles (RLVs) using a model predictive approach based on sequential convex programming (SCP). The proposed approach devises two distinct optimal control problems (OCPs): planning a fuel-optimal landing trajectory that accommodates practical path constraints specific to RLVs, and determining real-time optimal tracking commands. This dual optimization strategy, which refers to the definition of planning and tracking problems, allows for reduced computational load through adjustable prediction horizon lengths in the tracking task, achieving near closed-loop performance. Enhancements in model fidelity for the tracking task are achieved through an alternative rotational dynamics representation, enabling a more stable numerical solution of the OCP and accounting for vehicle transient dynamics. Furthermore, modifications of aerodynamic force in both planning and tracking phases are proposed, tailored for thrust-vector-controlled RLVs, to reduce the fidelity gap without adding computational complexity. Extensive 6-degree-of-freedom (6-DOF) simulation experiments validate the effectiveness and improved guidance performance of the proposed algorithm.