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Title Advances in Automatic Performance Optimization at FERMI
  • G. Gaio, N. Bruchon, M. Lonza
    Elettra-Sincrotrone Trieste S.C.p.A., Basovizza, Italy
  • L. Saule
    University of Trieste, Trieste, Italy
Abstract Despite the large number of feedback loops running simultaneously at the FERMI Free Electron Laser (FEL), they are not sufficient to keep the optimal machine working point in the long term, in particular when the machine is tuned in such a way to be more sensitive to drifts of the critical parameters. In order to guarantee the best machine performance, a novel software application which minimizes the shot to shot correlation between these critical parameters and the FEL radiation has been implemented. This application, which keeps spatially and temporally aligned the seed laser and the electron beam, contrary to many algorithms that inject noise in the system to be optimized, run transparently during the experiment beam times. In this paper we will also present a newly developed method to calculate a beam 'quality factor' starting from the images provided by a photon spectrometer, which tries to mimic the evaluation of machine physicists, as well as the results obtained using two model-less algorithms to optimize the FEL performance through maximization of the quality factor.
Paper download TUMPA07.PDF [1.108 MB / 5 pages]
Slides download TUMPA07_TALK.PDF [0.846 MB]
Poster download TUMPA07_POSTER.PDF [1.124 MB]
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Conference ICALEPCS2017, Barcelona, Spain
Series International Conference on Accelerator and Large Experimental Control Systems (16th)
Proceedings Link to full ICALEPCS2017 Proccedings
Session Mini-Oral
Date 10-Oct-17   16:45–17:15
Main Classification Feedback Control and Process Tuning
Keywords ion, FEL, laser, electron, experiment
Publisher JACoW, Geneva, Switzerland
Editors Volker RW Schaa (GSI, Darmstadt, Germany); Isidre Costa (ALBA-CELLS, Cerdanyola del Vallès, Spain); David Fernández (ALBA-CELLS, Cerdanyola del Vallès, Spain); Óscar Matilla (ALBA-CELLS, Cerdanyola del Vallès, Spain)
ISBN 978-3-95450-193-9
Published January 2018
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