Model Predictive Control of Spacecraft Relative Motion with Convexified Keep-Out-Zone Constraints

Zagaris, Costantinos; Park, Hyeongjun; Virgili-Llop, Josep; Zappulla, Richard; Romano, Marcello; Kolmanovsky, Ilya

doi:10.2514/1.g003549

Cited by 44 publications

(19 citation statements)

References 19 publications

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“…The above constraint is nonconvex, and hence not compatible with the formulation ( 6)-( 7) (X(k, N) is assumed to be convex). One way to convexify ( 9) is to employ the so-called rotating-hyperplane method [17]. Within this method, the hyperplane rotation rate is treated as a parameter to be tuned heuristically.…”

Section: A Rendezvous Constraintsmentioning

confidence: 99%

“…In order to facilitate online optimization, a great deal of research has been directed towards problem formulations which are inherently convex. Convex formulations are usually obtained by linearizing the spacecraft relative motion dynamics, exploiting suitable convex approximations of the RVD path constraints, and adopting a fixed planning horizon [16,17]. Most of the studies in this area focus on RVD to a cooperative target, assuming that the docking point is static, see, e.g., [18][19][20].…”

Section: Introductionmentioning

confidence: 99%

“…This is achieved by suitably approximating the RVD constraints. In particular, noncovex keep-out-zone constraints are approximated by a set of linear time-varying inequalities, using a variant of the so-called rotating hyperplane strategy (see, e.g., [17]). Then, the solution to the variable-horizon problem is obtained by solving a finite number of LPs.…”

Section: Introductionmentioning

confidence: 99%

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Variable-Horizon Guidance for Autonomous Rendezvous and Docking to a Tumbling Target

Leomanni¹,

Quartullo²,

Bianchini³

et al. 2021

Preprint

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In this paper, the trajectory planning problem for autonomous rendezvous and docking between a controlled spacecraft and a tumbling target is addressed. The use of a variable planning horizon is proposed in order to construct an appropriate maneuver plan, within an optimization-based framework. The involved optimization problem is nonconvex and features nonlinear constraints. The main contribution is to show that such problem can be tackled effectively by solving a finite number of linear programs. To this aim, a specifically conceived horizon search algorithm is employed in combination with a polytopic constraint approximation technique. The resulting guidance scheme provides the ability to identify favourable docking configurations, by exploiting the time-varying nature of the optimization problem endpoint. Simulation results involving the capture of the nonoperational En-viSat spacecraft indicate that the method is able to generate optimal trajectories at a fraction of the computational cost incurred by a state-of-the-art nonlinear solver.

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Section: A Rendezvous Constraintsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Variable-Horizon Guidance for Autonomous Rendezvous and Docking to a Tumbling Target

Leomanni¹,

Quartullo²,

Bianchini³

et al. 2021

Preprint

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“…It is worth acknowledging that alternative approaches to solve the system-wide translation exist. For example, inverse dynamic (Sternberg and Miller, 2018; Ventura et al, 2015; Virgili-Llop et al, 2018; Wilde et al, 2016), sampling-based (Starek et al, 2016; Zappulla et al, 2017), model predictive control (Park et al, 2017; Zagaris et al, 2018), or other convex optimization-based approaches (Szmuk and Acikmese, 2018; Watterson et al, 2016) may be able to solve the system-wide translation and be suitable for onboard implementation and real-time use. The advantage of the convex programming approach used here is that it can directly handle non-convex obstacles while retaining convergence guarantees.…”

Section: Step 1: System-wide Translation Optimizationmentioning

confidence: 99%

A convex-programming-based guidance algorithm to capture a tumbling object on orbit using a spacecraft equipped with a robotic manipulator

Virgili-Llop

Zagaris

Zappulla

et al. 2018

The International Journal of Robotics Research

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An algorithm to guide the capture of a tumbling resident space object by a spacecraft equipped with a robotic manipulator is presented. A solution to the guidance problem is found by solving a collection of convex programming problems. As convex programming offers deterministic convergence properties, this algorithm is suitable for onboard implementation and real-time use. A set of hardware-in-the-loop experiments substantiates this claim. To cast the guidance problem as a collection of convex programming problems, the capture maneuver is divided into two simultaneously occurring submaneuvers: a system-wide translation and an internal re-configuration. These two sub-maneuvers are optimized in two consecutive steps. A sequential convex programming procedure, overcoming the presence of non-convex constraints and nonlinear dynamics, is used on both optimization steps. A proof of convergence is offered for the system-wide translation, while a set of structured heuristics-trust regions-is used for the optimization of the internal re-configuration sub-maneuver. Videos of the numerically simulated and experimentally demonstrated maneuvers are included as supplementary material.

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“…For the missions employing these techniques, a trajectory or a set of way-points is assigned to the target spacecraft to follow. This trajectory does not respond to the changes such as the chaser diverging from its path or improper MPC has been studied thoroughly in the literature because of the compatibility with the rendezvous and docking problem while allowing constraint satisfaction [11,47,59,[100][101][102][103][104][105][106][107][108][109][110][111][112][113][114]. MPC typically implements a plan in a step by step manner.…”

Section: Model Predictive Controlmentioning

confidence: 99%

Model predictive control for spacecraft rendezvous and docking with uncooperative targets

Burak¹

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Firstly, I would like to sincerely thank my supervisor for his continuous support.Secondly, I would like to thank Mr. Luca Simonini and Dr. Vincent Dubanchet from Thales Alenia Space for being inspirer leaders who have always shown their faith in me and who continuously supported my dreams to come true. Next, the core part of my thesis is achieved in DLR/German facilities. Hence, I would like to thank the head of GNC/Bremen department Dr. Stephan Theil, head of G&C department Dr. David Seelbinder for providing me the opportunity to conduct my experiments. In DLR, Dr. Markus Schlotterer had always been supportive in the test, and verification phase of the embedded systems. That was remarkable and I appreciate to receive his support. Last but not the least, I am grateful to have Prof. Jan Maciejowski in my thesis advisory committee. I would like to thank Prof Jan. for his support and enthusiasm for my work. ix "If I had one hour to save the world, I would spend 55 minutes defining the problem and only five minutes finding the solution."

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Model Predictive Control of Spacecraft Relative Motion with Convexified Keep-Out-Zone Constraints

Cited by 44 publications

References 19 publications

Variable-Horizon Guidance for Autonomous Rendezvous and Docking to a Tumbling Target

Variable-Horizon Guidance for Autonomous Rendezvous and Docking to a Tumbling Target

A convex-programming-based guidance algorithm to capture a tumbling object on orbit using a spacecraft equipped with a robotic manipulator

Model predictive control for spacecraft rendezvous and docking with uncooperative targets

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