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, J.P. AU - Keilman, M.V. AU - Moeller, P. AU - Nagler, R. ED - White, Karen S. ED - Brown, Kevin A. ED - Dyer, Philip S. ED - Schaa, Volker RW TI - A Cloud Based Framework for Advanced Accelerator Controls J2 - Proc. of ICALEPCS2019, New York, NY, USA, 05-11 October 2019 CY - New York, NY, USA T2 - International Conference on Accelerator and Large Experimental Physics Control Systems T3 - 17 LA - english AB - Modern particle accelerator facilities generate large amounts of data and face increasing demands on their operational performance. As the demand on accelerator operations increases so does the need for automated tuning algorithms and control to maximize uptime with reduced operator intervention. Existing tools are insufficient to meet the broad demands on controls, visualization, and analysis. We are developing a cloud based toolbox featuring a generic virtual accelerator control room for the development of automated tuning algorithms and the analysis of large complex datasets. This framework utilizes tracking codes combined with with algorithms for machine drift, low-level control systems, and other complications to create realistic models of accelerators. These models are directly interfaced with advanced control toolboxes allowing for rapid prototyping of control algorithms. Additionally, our interface provides users with access to a wide range of Python-based data analytics libraries for the study and visualization of machine data. In this paper, we provide an overview of our interface and demonstrate its utility on a toy accelerator running on EPICS. PB - JACoW Publishing CP - Geneva, Switzerland SP - 655 EP - 658 KW - controls KW - EPICS KW - interface KW - operation KW - framework DA - 2020/08 PY - 2020 SN - 2226-0358 SN - 978-3-95450-209-7 DO - doi:10.18429/JACoW-ICALEPCS2019-MOSH4002 UR - https://jacow.org/icalepcs2019/papers/mosh4002.pdf ER -