Keyword: resonance
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TUMBCMO14 Initial Test of a Machine Learning Based SRF Cavity Active Resonance Control cavity, controls, SRF, simulation 379
 
  • F.Y. Wang, J. Cruz
    SLAC, Menlo Park, California, USA
 
  We’ll introduce a high precision active motion controller based on machine learning (ML) technology and electric piezo actuator. The controller will be used for SRF cavity active resonance control, where a data-driven model for system motion dynamics will be developed first, and a model predictive controller (MPC) will be built accordingly. Simulation results as well as initial test results with real SRF cavities will be presented in the paper.  
DOI • reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-TUMBCMO14  
About • Received ※ 03 October 2023 — Revised ※ 14 November 2023 — Accepted ※ 27 November 2023 — Issued ※ 09 December 2023
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TUPDP005 Improvements on Kinematics and Control of Granite Benches at LNLS-Sirius controls, damping, real-time, timing 485
 
  • J.V.E. Matoso, J.P.S. Furtado, J.P.B. Ishida, T.R. Silva Soares
    LNLS, Campinas, Brazil
 
  At the Brazilian Synchrotron Light Laboratory, the radiation beam is conditioned by optical elements that must be positioned with high stability and precision. Many of the optical elements are positioned using granite benches that provide high coupling stiffness to the ground and position control in up to six degrees of freedom, using a set of stepper motors. The solution of the inverse kinematics was done numerically by the Newton Raphson method. By employing the property that these systems have small rotation angles, the Jacobian matrix used in this numerical method can be simplified to reduce computational execution time and allow high processing rates. This paper also shows the results of adding a notch filter to the position servo control loop of the granite benches to increase stability due to their mass-spring-damper characteristics. The kinematics and control of the granite benches are implemented in an Omron Power Brick LV controller, with the kinematics developed in MATLAB and the C-code generated by MATLAB C-Coder. Reducing the execution time of the kinematics improves the efficient use of the computational resources and allows the real-time clock rate to be increased.  
DOI • reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-TUPDP005  
About • Received ※ 05 October 2023 — Revised ※ 10 October 2023 — Accepted ※ 29 November 2023 — Issued ※ 04 December 2023
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