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RIS citation export for WEPV024: X-Ray Beamline Control with Machine Learning and an Online Model

AU  - Nash, B.
AU  - Abell, D.T.
AU  - Bruhwiler, D.L.
AU  - Carlin, E.G.
AU  - Du, Y.
AU  - Edelen, J.P.
AU  - Giles, A.
AU  - Keilman, M.V.
AU  - Lynch, J.
AU  - Maldonado, J.
AU  - Moeller, P.
AU  - Nagler, R.
AU  - Pogorelov, I.V.
AU  - Rakitin, M.S.
AU  - Walter, A.
AU  - Webb, S.D.
ED  - Furukawa, Kazuro
ED  - Yan, Yingbing
ED  - Leng, Yongbin
ED  - Chen, Zhichu
ED  - Schaa, Volker R.W.
TI  - X-Ray Beamline Control with Machine Learning and an Online Model
J2  - Proc. of ICALEPCS2021, Shanghai, China, 14-22 October 2021
CY  - Shanghai, China
T2  - International Conference on Accelerator and Large Experimental Physics Control Systems
T3  - 18
LA  - english
AB  - We present recent developments on control of x-ray beamlines for synchrotron light sources. Effective models of the x-ray transport are updated based on diagnostics data, and take the form of simplified physics models as well as learned models from scanning over mirror and slit configurations. We are developing this approach to beamline control in collaboration with several beamlines at the NSLS-II. By connecting our online models to the Blue-Sky framework, we enable a convenient interface between the operating machine and the model that may be applied to beamlines at multiple facilities involved in this collaborative software development.
PB  - JACoW Publishing
CP  - Geneva, Switzerland
SP  - 695
EP  - 699
KW  - simulation
KW  - controls
KW  - software
KW  - radiation
KW  - synchrotron
DA  - 2022/03
PY  - 2022
SN  - 2226-0358
SN  - 978-3-95450-221-9
DO  - doi:10.18429/JACoW-ICALEPCS2021-WEPV024
UR  - https://jacow.org/icalepcs2021/papers/wepv024.pdf
ER  -