We describe some of the challenges of particle accelerator control, highlight recent advances in neural network techniques, discuss some promising avenues for incorporating neural networks into particle accelerator control systems, and describe a neural network-based control system that is being developed for resonance control of an RF electron gun at the Fermilab Accelerator Science and Technology (FAST) facility, including initial experimental results from a benchmark controller.
@article{arxiv.1610.06151,
title = {Neural Networks for Modeling and Control of Particle Accelerators},
author = {A. L. Edelen and S. G. Biedron and B. E. Chase and D. Edstrom and S. V. Milton and P. Stabile},
journal= {arXiv preprint arXiv:1610.06151},
year = {2016}
}