Trajectory optimization for asteroid landing with two-phase free final time

Zhang, Yingying; Ji, Huang; Cui, Hutao

doi:10.1016/j.asr.2019.11.031

Cited by 14 publications

(1 citation statement)

References 26 publications

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“…Most small body landing work is 3-DoF in the sense that it considers point mass translational dynamics. However, recently (Zhang et al, 2020) studied a two-phase variable landing duration 6-DoF problem. The motivation was to impose a field of view constraint for a landing camera.…”

Section: Small Body Landingmentioning

confidence: 99%

Advances in Trajectory Optimization for Space Vehicle Control

Malyuta¹,

Yu²,

Elango³

et al. 2021

Preprint

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Space mission design places a premium on cost and operational efficiency. The search for new science and life beyond Earth calls for spacecraft that can deliver scientific payloads to geologically rich yet hazardous landing sites. At the same time, the last four decades of optimization research have put a suite of powerful optimization tools at the fingertips of the controls engineer. As we enter the new decade, optimization theory, algorithms, and software tooling have reached a critical mass to start seeing serious application in space vehicle guidance and control systems. This survey paper provides a detailed overview of recent advances, successes, and promising directions for optimization-based space vehicle control. The considered applications include planetary landing, rendezvous and proximity operations, small body landing, constrained attitude reorientation, endo-atmospheric flight including ascent and reentry, and orbit transfer and injection. The primary focus is on the last ten years of progress, which have seen a veritable rise in the number of applications using three core technologies: lossless convexification, sequential convex programming, and model predictive control. The reader will come away with a well-rounded understanding of the state-of-the-art in each space vehicle control application, and will be well positioned to tackle important current open problems using convex optimization as a core technology.

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Section: Small Body Landingmentioning

confidence: 99%