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Title: Machine learning control for disruption and tearing mode avoidance

Authors:
ORCiD logo [1]; ORCiD logo [2];  [3];  [4]; ORCiD logo [1];  [3];  [2];  [5]; ORCiD logo [1]; ORCiD logo [6]
  1. Department of Astrophysical Science, Princeton University, Princeton, New Jersey 08544, USA
  2. General Atomics, PO Box 85608, San Diego, California 92186-5608, USA
  3. Princeton Plasma Physics Laboratory, Princeton, New Jersey, 08543-0451, USA
  4. Eindhoven University of Technology, 5612 AZ Eindhoven, The Netherlands
  5. Department of Physics, Yale University, New Haven, Connecticut 06516, USA
  6. Princeton Plasma Physics Laboratory, Princeton, New Jersey, 08543-0451, USA, Department of Mechanical and Aerospace Engineering, Princeton University, Princeton, New Jersey 08544, USA
Publication Date:
Sponsoring Org.:
USDOE
OSTI Identifier:
1596898
Grant/Contract Number:  
DE22 SC0015878; FC02-04ER54698; DC-AC02-09Ch11466; 633053
Resource Type:
Publisher's Accepted Manuscript
Journal Name:
Physics of Plasmas
Additional Journal Information:
Journal Name: Physics of Plasmas Journal Volume: 27 Journal Issue: 2; Journal ID: ISSN 1070-664X
Publisher:
American Institute of Physics
Country of Publication:
United States
Language:
English

Citation Formats

Fu, Yichen, Eldon, David, Erickson, Keith, Kleijwegt, Kornee, Lupin-Jimenez, Leonard, Boyer, Mark D., Eidietis, Nick, Barbour, Nathaniel, Izacard, Olivier, and Kolemen, Egemen. Machine learning control for disruption and tearing mode avoidance. United States: N. p., 2020. Web. doi:10.1063/1.5125581.
Fu, Yichen, Eldon, David, Erickson, Keith, Kleijwegt, Kornee, Lupin-Jimenez, Leonard, Boyer, Mark D., Eidietis, Nick, Barbour, Nathaniel, Izacard, Olivier, & Kolemen, Egemen. Machine learning control for disruption and tearing mode avoidance. United States. doi:10.1063/1.5125581.
Fu, Yichen, Eldon, David, Erickson, Keith, Kleijwegt, Kornee, Lupin-Jimenez, Leonard, Boyer, Mark D., Eidietis, Nick, Barbour, Nathaniel, Izacard, Olivier, and Kolemen, Egemen. Sat . "Machine learning control for disruption and tearing mode avoidance". United States. doi:10.1063/1.5125581.
@article{osti_1596898,
title = {Machine learning control for disruption and tearing mode avoidance},
author = {Fu, Yichen and Eldon, David and Erickson, Keith and Kleijwegt, Kornee and Lupin-Jimenez, Leonard and Boyer, Mark D. and Eidietis, Nick and Barbour, Nathaniel and Izacard, Olivier and Kolemen, Egemen},
abstractNote = {},
doi = {10.1063/1.5125581},
journal = {Physics of Plasmas},
number = 2,
volume = 27,
place = {United States},
year = {2020},
month = {2}
}

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