TR2022-060
Local Eigenmotion Control for Near Rectilinear Halo Orbits
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- "Local Eigenmotion Control for Near Rectilinear Halo Orbits", American Control Conference (ACC), DOI: 10.23919/ACC53348.2022.9867672, June 2022, pp. 1822-1827.BibTeX TR2022-060 PDF
- @inproceedings{Elango2022jun,
- author = {Elango, Purnanand and Di Cairano, Stefano and Kalabic, Uros and Weiss, Avishai},
- title = {Local Eigenmotion Control for Near Rectilinear Halo Orbits},
- booktitle = {American Control Conference (ACC)},
- year = 2022,
- pages = {1822--1827},
- month = jun,
- doi = {10.23919/ACC53348.2022.9867672},
- issn = {2378-5861},
- isbn = {978-1-6654-5196-3},
- url = {https://www.merl.com/publications/TR2022-060}
- }
,
- "Local Eigenmotion Control for Near Rectilinear Halo Orbits", American Control Conference (ACC), DOI: 10.23919/ACC53348.2022.9867672, June 2022, pp. 1822-1827.
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MERL Contacts:
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Research Areas:
Abstract:
The upcoming deployment of the Lunar Orbital Platform-Gateway (LOP-G) on a Near Rectilinear Halo Orbit (NRHO) calls for reliable, low-cost strategies for station keeping and relative motion tailor-made for NRHO. This paper proposes a control approach which harnesses the eigenvectors of state transition matrices (STM) associated with a high-fidelity NRHO solution in the ephemeris model to design long-term station keeping and bounded relative motion. The proposed method effectively utilizes the natural motion of the spacecraft so that control actions are infrequent and fuel efficient. The performance of the proposed approach is demonstrated via simulations with a state estimator that uses simulated mea- surements from the Deep Space Network.
Related News & Events
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NEWS MERL researchers presented 9 papers at the American Control Conference (ACC) Date: June 8, 2022 - June 10, 2022
Where: Atlanta, GA
MERL Contacts: Scott A. Bortoff; Ankush Chakrabarty; Stefano Di Cairano; Christopher R. Laughman; Abraham P. Vinod; Avishai Weiss
Research Areas: Control, Machine Learning, OptimizationBrief- At the American Control Conference in Atlanta, GA, MERL presented 9 papers on subjects including autonomous-vehicle decision making and motion planning, realtime Bayesian inference and learning, reference governors for hybrid systems, Bayesian optimization, and nonlinear control.