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BiBTeX citation export for TUPOGE03: Advanced Cryogenic Process Control and Monitoring for the SPIRAL2 Superconducting LINAC

@inproceedings{ghribi:linac2022-tupoge03,
  author       = {A. Ghribi and M. Aburas and P.-E. Bernaudin and P. Bonnay and F. Bonne and M. Di Giacomo and F. Millet and A.H. Trudel and Q. Tura},
% author       = {A. Ghribi and M. Aburas and P.-E. Bernaudin and P. Bonnay and F. Bonne and M. Di Giacomo and others},
% author       = {A. Ghribi and others},
  title        = {{Advanced Cryogenic Process Control and Monitoring for the SPIRAL2 Superconducting LINAC}},
  booktitle    = {Proc. LINAC'22},
% booktitle    = {Proc. 31st International Linear Accelerator Conference (LINAC'22)},
  pages        = {483--486},
  eid          = {TUPOGE03},
  language     = {english},
  keywords     = {cavity, controls, cryogenics, linac, cryomodule},
  venue        = {Liverpool, UK},
  series       = {International Linear Accelerator Conference},
  number       = {31},
  publisher    = {JACoW Publishing, Geneva, Switzerland},
  month        = {09},
  year         = {2022},
  issn         = {2226-0366},
  isbn         = {978-3-95450-215-8},
  doi          = {10.18429/JACoW-LINAC2022-TUPOGE03},
  url          = {https://jacow.org/linac2022/papers/tupoge03.pdf},
  abstract     = {{SPIRAL2 is a superconducting accelerator for protons, deuterons and heavy ions delivering a maximum beam power of 200 kW at 40 MeV (for deuteron beams). 26 superconducting quarter wave cavities are operated at 4.4 K, plunged in a liquid helium bath with a drastic phase separator pressure control. Previous years have seen the development of advanced process control for cryogenics allowing to cope with high heat load dynamics thanks to an automatic heat dissipation compensation and a model based control. The latter is based on models, using the Simcryogenics library, optimized and linearised in the Programmable Logic Controllers. The SPIRAL2 operation has demonstrated that such control allows to keep the specified conditions for RF and beam operation even at levels of heat load dissipation approaching the physical limits of the cryogenic system. These developments allowed to synthesise a virtual observer of the dynamic heat load dissipated by the cavities. The present paper summarises the development of such observer based on the physical thermodynamic model and on machine learning techniques.}},
}