Speaker
Description
Power supply ripples at various frequencies - characteristic to the magnet circuits or from the electrical network - have always been an issue in accelerator operations, with several mitigation measures put in place over the years. This contribution summarises the efforts in the CERN SPS over the last years to compensate the ripple at 50 Hz and its harmonics in the main quadrupole circuits, using Machine Learning methods. The detrimental effects of the ripple at low energy for LHC-type beams and at top energy for slow extracted beams are introduced. For optimal conditions of slow extracted beams, a continuous control algorithm had to be conceived. The implementation required hardware modifications on the power converter electronics side, additional new controls infrastructure and the development of adaptive algorithms that can deal with changes in the electrical distribution network throughout the day. Continuous control with tailored adaptive Bayesian Optimisation has been implemented for slow extracted spill control throughout 2024 and 2025. The improved spill quality obtained over the years will be discussed. Finally, results from R&D towards one-shot correction algorithms for beams that are only played on-demand (i.e. LHC beams) will also be briefly summarised.
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