Small Body Precision Landing via Convex Model Predictive Control

Reynolds, Taylor P.; Mesbahi, Mehran

doi:10.2514/6.2017-5179

Cited by 13 publications

(3 citation statements)

References 31 publications

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“…In the same manner as Section 3.2, the small body is wrapped in an ellipsoid and a rotating hyperplane constraint is used (Dunham et al, 2016;Liao-McPherson et al, 2016;Sanchez et al, 2018). (Reynolds and Mesbahi, 2017) introduced an optimal separating hyperplane constraint that also generates auxiliary setpoints for MPC tracking that converge to the landing site. Once in close proximity to the landing site, the spacecraft enters the landing phase where constraint (68e) is enforced to facilitate pinpoint landing.…”

Section: Small Body Landingmentioning

confidence: 99%

“…Parameters of the small body, such as ω and g, are often subject to inevitable uncertainty, requiring judicious trajectory design. As a result, many aforementioned works use MPC to cope with the uncertainty in small body landing (Reynolds and Mesbahi, 2017;Sanchez et al, 2018). Application examples include tube MPC (Carson III and Açıkmeşe, 2006;Carson III et al, 2008) and input observers to compensate for gravity modeling errors (Dunham et al, 2016;Liao-McPherson et al, 2016).…”

Section: Small Body Landingmentioning

confidence: 99%

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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%

Section: Small Body Landingmentioning

confidence: 99%

Advances in Trajectory Optimization for Space Vehicle Control

Malyuta¹,

Yu²,

Elango³

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…However, mathematical and computational developments in recent years have enabled representative solutions to be determined online using onboard computers and applied in a closed-loop fashion [8]. This approach, where an optimal control input is computed based on the predicted trajectory, enables tackling the D&L problem in a model predictive control (MPC) setting [33][34][35].…”

Section: Improving Guidance Via Convex Optimisationmentioning

confidence: 99%

Guidance of Reusable Launchers: Improving Descent and Landing Performance

Simplicio

Marcos

Bennani

2019

Journal of Guidance, Control, and Dynamics

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The sizing and capability definition of reusable launchers during high-speed recovery are very challenging problems. In this article, a convex optimisation guidance algorithm for this type of systems is proposed based on performance improvements arising from the study of the coupled flight mechanics, guidance and control problem. In order to appreciate the obtained improvements, trade-off analyses of powered descent and landing scenarios are presented first using traditional guidance techniques. Subsequently, these results are refined by using the proposed online successive convex optimisation-based guidance strategy. The DESCENDO (Descending over Extended Envelopes using Successive Convexification-based Optimisation) algorithm has been designed as a middle-ground between efficiency and optimality. This approach contrasts with previous convexification algorithms that either aimed at increasing computational efficiency (by typically disregarding aerodynamic deceleration) or reaching trajectory design optimality (by using exhaustive convex approximations). More critically, the algorithm is not confined to the mild coverage conditions assumed by previous approaches and can successfully handle the incorporation of the operational dynamics of reusable launchers. Insights provided by DESCENDO operating in a closed-loop fashion over full recovery scenarios enable a computationally-efficient mission performance assessment.

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

Zhang

Cui

2020

Advances in Space Research

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Small Body Precision Landing via Convex Model Predictive Control

Cited by 13 publications

References 31 publications

Advances in Trajectory Optimization for Space Vehicle Control

Advances in Trajectory Optimization for Space Vehicle Control

Guidance of Reusable Launchers: Improving Descent and Landing Performance

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

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