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BiBTeX citation export for THPV017: A cloud based toolbox for accelerator controls interfaces and optimization

  author       = {J.P. Edelen and E.G. Carlin and M.V. Keilman and P. Moeller and R. Nagler},
  title        = {{A cloud based toolbox for accelerator controls interfaces and optimization}},
  booktitle    = {Proc. ICALEPCS'21},
  language     = {english},
  intype       = {presented at the},
  series       = {International Conference on Accelerator and Large Experimental Physics Control Systems},
  number       = {18},
  venue        = {Shanghai, China},
  publisher    = {JACoW Publishing, Geneva, Switzerland},
  month        = {03},
  year         = {2022},
  note         = {presented at ICALEPCS'21 in Shanghai, China, unpublished},
  abstract     = {{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 have developed 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 control toolboxes allowing for rapid prototyping of tuning algorithms. In this paper, we will provide an overview of our interface and demonstrate its utility for building beamline controls displays directly from accelerator simulation lattices. We will also demonstrate the use of our interface for testing online optimization and control algorithms.}},