JACoW logo

Journals of Accelerator Conferences Website (JACoW)

JACoW is a publisher in Geneva, Switzerland that publishes the proceedings of accelerator conferences held around the world by an international collaboration of editors.


RIS citation export for MOPA75: Machine Learning for Slow Spill Regulation in the Fermilab Delivery Ring for Mu2e

TY  - CONF
AU  - Narayanan, A.
AU  - Arnold, J.M.S.
AU  - Austin, M.R.
AU  - Berlioz, J.R.
AU  - Hanlet, P.M.
AU  - Hazelwood, K.J.
AU  - Ibrahim, M.A.
AU  - Jiang, J.
AU  - Liu, H.
AU  - Memik, S.
AU  - Nagaslaev, V.P.
AU  - Nicklaus, D.J.
AU  - Pradhan, G.
AU  - Prieto, P.S.
AU  - Saewert, A.L.
AU  - Schupbach, B.A.
AU  - Seiya, K.
AU  - Shi, R.
AU  - Thieme, M.
AU  - Thurman-Keup, R.M.
AU  - Tran, N.V.
AU  - Ulusel, D.
ED  - Biedron, Sandra
ED  - Simakov, Evgenya
ED  - Milton, Stephen
ED  - Anisimov, Petr M.
ED  - Schaa, Volker R.W.
TI  - Machine Learning for Slow Spill Regulation in the Fermilab Delivery Ring for Mu2e
J2  - Proc. of NAPAC2022, Albuquerque, NM, USA, 07-12 August 2022
CY  - Albuquerque, NM, USA
T2  - International Particle Accelerator Conference
T3  - 5
LA  - english
AB  - A third-integer resonant slow extraction system is being developed for the Fermilab’s Delivery Ring to deliver protons to the Mu2e experiment. During a slow extraction process, the beam on target is liable to experience small intensity variations due to many factors. Owing to the experiment’s strict requirements in the quality of the spill, a Spill Regulation System (SRS) is currently under design. The SRS primarily consists of three components - slow regulation, fast regulation, and harmonic content tracker. In this presentation, we shall present the investigations of using Machine Learning (ML) in the fast regulation system, including further optimizations of PID controller gains for the fast regulation, prospects of an ML agent completely replacing the PID controller using supervised learning schemes such as Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) ML models, the simulated impact and limitation of machine response characteristics on the effectiveness of both PID and ML regulation of the spill. We also present here nascent results of Reinforcement Learning efforts, including continuous-action soft actor-critic methods, to regulate the spill rate.
PB  - JACoW Publishing
CP  - Geneva, Switzerland
SP  - 214
EP  - 217
KW  - controls
KW  - extraction
KW  - quadrupole
KW  - experiment
KW  - target
DA  - 2022/10
PY  - 2022
SN  - 2673-7000
SN  - 978-3-95450-232-5
DO  - doi:10.18429/JACoW-NAPAC2022-MOPA75
UR  - https://jacow.org/napac2022/papers/mopa75.pdf
ER  -