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Hauptverfasser: Jung, Ki-Wook, Lee, Sang-Don, Jung, Cheol-Goo, Lee, Chang-Hun
Format: Preprint
Veröffentlicht: 2024
Schlagworte:
Online-Zugang:https://arxiv.org/abs/2405.01264
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author Jung, Ki-Wook
Lee, Sang-Don
Jung, Cheol-Goo
Lee, Chang-Hun
author_facet Jung, Ki-Wook
Lee, Sang-Don
Jung, Cheol-Goo
Lee, Chang-Hun
contents 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 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-DOF simulation experiments validate the effectiveness and improved guidance performance of the proposed algorithm.
format Preprint
id arxiv_https___arxiv_org_abs_2405_01264
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Model Predictive Guidance for Fuel-Optimal Landing of Reusable Launch Vehicles
Jung, Ki-Wook
Lee, Sang-Don
Jung, Cheol-Goo
Lee, Chang-Hun
Systems and Control
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 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-DOF simulation experiments validate the effectiveness and improved guidance performance of the proposed algorithm.
title Model Predictive Guidance for Fuel-Optimal Landing of Reusable Launch Vehicles
topic Systems and Control
url https://arxiv.org/abs/2405.01264