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تسجيل مستخدم جديدInitial experimental results of a machine learning-based temperature control system for an RF gun
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Colorado State University (CSU) and Fermi National Accelerator Laboratory (Fermilab) have been developing a control system to regulate the resonant frequency of an RF electron gun. As part of this effort, we present initial test results for a benchmark temperature controller that combines a machine learning-based model and a predictive control algorithm. This is part of an on-going effort to develop adaptive, machine learning-based tools specifically to address control challenges found in particle accelerator systems.
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