Cyclotrons2016 - List of Authors (Yang, S.D.)

Paper	Title	Page
TUP19	Neural Network Based Generalized Predictive Control for RFT-30 Cyclotron System	212
	Y.B. Kong, M.G. Hur, E.J. Lee, J.H. Park, S.D. Yang KAERI, Daejon, Republic of Korea Y.D. Park Advanced Radiation Technology Institute, Korea Atomic Energy Research Institute, Jeongup-si, Jeollabuk-do, Republic of Korea
	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.
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Paper

Title

Page

Neural Network Based Generalized Predictive Control for RFT-30 Cyclotron System

212

Y.B. Kong, M.G. Hur, E.J. Lee, J.H. Park, S.D. Yang
KAERI, Daejon, Republic of Korea
Y.D. Park
Advanced Radiation Technology Institute, Korea Atomic Energy Research Institute, Jeongup-si, Jeollabuk-do, Republic of Korea

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.

Export •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)