The Joint Accelerator Conferences Website (JACoW) is an international collaboration that publishes the proceedings of accelerator conferences held around the world.
TY - CONF AU - Edelen, A.L. AU - Biedron, S. AU - Chase, B.E. AU - Crawford, D.J. AU - Eddy, N. AU - Edstrom, D.R. AU - Harms, E.R. AU - Milton, S.V. AU - Ruan, J. AU - Santucci, J.K. AU - Stabile, P. ED - Henderson, Stuart ED - Akers, Evelyn ED - Satogata, Todd ED - Schaa, Volker R.W. TI - Initial Experimental Results of a Machine Learning-Based Temperature Control System for an RF Gun J2 - Proc. of IPAC2015, Richmond, VA, USA, May 3-8, 2015 C1 - Richmond, VA, USA T2 - International Particle Accelerator Conference T3 - 6 LA - english AB - Colorado State University (CSU) and Fermi National Accelerator Laboratory (Fermilab) have been developing a control system to regulate the resonant frequency of an RF electron gun. As part of this effort, we present experimental results for a benchmark temperature controller that combines a machine learning-based model and a predictive control algorithm for improved settling time, overshoot, and disturbance rejection relative to conventional techniques. Such improvements have implications for machine up-time and management of reflected power. This work is part of an on-going effort to develop adaptive, machine learning-based tools specifically to address control challenges found in particle accelerator systems. PB - JACoW CP - Geneva, Switzerland SP - 1217 EP - 1219 KW - controls KW - gun KW - cavity KW - monitoring KW - network DA - 2015/06 PY - 2015 SN - 978-3-95450-168-7 DO - 10.18429/JACoW-IPAC2015-MOPWI028 UR - http://jacow.org/ipac2015/papers/mopwi028.pdf ER -