Concept of Operations for the Gateway

Coderre, Kathleen; Edwards, Christopher G.; Cichan, Tim; Richey, Danielle; Shupe, Nathan; Sabolish, David; Ramm, Steven; Perkes, Brent; Posey, Jerome; Pratt, William D.; Liu, Eileen

doi:10.1007/978-3-030-11536-4_4

Cited by 8 publications

(1 citation statement)

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“…A very challenging space mission scenario that has been brought into attention during the last decade is the Lunar Orbital Platform -Gateway (LOP-G) [10], which will be a human outpost in the cislunar environment. The lunar Gateway will fly a Near Rectlilinear Halo Orbit (NRHO) which has been deemed the most suitable environment for its extremely high performances in terms of stability.…”

Section: Introductionmentioning

confidence: 99%

Model Predictive Control for formation reconfiguration exploiting quasi-periodic tori in the cislunar environment

Capannolo

Zanotti

Lavagna

et al. 2022

Preprint

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Given the numerous possibilities that formation flying space missions can enable, being able to design and govern relative trajectories in this scenario is fundamental. Particularly interesting, due to the installation and operation of the Lunar Gateway, which will represent the next human outpost in the cislunar environment, will be the exploitation of formation flying missions in the vicinity of this lunar station. The nonlinear dynamics by which the Earth-Moon system is characterised offers the possibility to find bounded relative trajectories which can be used to design the formation. In order to best exploit the formation potential, some reconfiguration manoeuvres can be used, which by changing the relative geometry can increase the versatility and adaptation of the mission. In this paper, a Model Predictive Guidance and Control strategy is proposed and applied to perform rephasing manoeuvres in the harsh environment of the Near Rectilinear Halo Orbits. By including first a limited thrust constraint and then a collision avoidance, a more mission-oriented approach is provided to the system. To further increase the robustness of the on-board algorithms, an adaptive logic is provided to the different tuning weights involved in the Model Predictive Control scheme. In this way, a more flexible system is obtained, which is capable of optimally working also in the presence of a high-fidelity simulation scenario, including discrepancies with the simplified on-board dynamical model.

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Section: Introductionmentioning

confidence: 99%