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RIS citation export for TUP19: Neural Network Based Generalized Predictive Control for RFT-30 Cyclotron System

TY - CONF
AU - Kong, Y.B.
AU - Hur, M.G.
AU - Lee, E.J.
AU - Park, J.H.
AU - Park, Y.D.
AU - Yang, S.D.
ED - Chrin, Jan
ED - Schaa, Volker RW
TI - Neural Network Based Generalized Predictive Control for RFT-30 Cyclotron System
J2 - Proc. of Cyclotrons2016, Zurich, Switzerland, September 11-16, 2016
C1 - Zurich, Switzerland
T2 - International Conference on Cyclotrons and Their Applications
T3 - 21
LA - english
AB - Beamline tuning is time consuming and difficult work in accelerator system. In this work, we propose a neural generalized predictive control (NGPC) approach for the RFT-30 cyclotron beamline. The proposed approach performs system identification with the NN model and finds the control parameters for the beamline. Performance results show that the proposed approach helps to predict optimal parameters without real experiments with the accelerator.
PB - JACoW
CP - Geneva, Switzerland
SP - 212
EP - 214
KW - controls
KW - cyclotron
KW - network
KW - simulation
KW - target
DA - 2017/01
PY - 2017
SN - 978-3-95450-167-0
DO - 10.18429/JACoW-Cyclotrons2016-TUP19
UR - http://jacow.org/cyclotrons2016/papers/tup19.pdf
ER -