The Joint Accelerator Conferences Website (JACoW) is an international collaboration that publishes the proceedings of accelerator conferences held around the world.
TY - CONF AU - Shahriari, Z. AU - Dumont, G.A. AU - Fong, K. ED - Boland, Mark ED - Tanaka, Hitoshi ED - Button, David ED - Dowd, Rohan ED - Schaa, Volker RW ED - Tan, Eugene TI - Norm-optimal Iterative Learning Control to Cancel Beam Loading Effect on the Accelerating Field J2 - Proc. of IPAC2019, Melbourne, Australia, 19-24 May 2019 CY - Melbourne, Australia T2 - International Particle Accelerator Conference T3 - 10 LA - english AB - Iterative learning control (ILC) is an open loop control strategy that improves the performance of a repetitive system through learning from previous iterations. ILC can be used to compensate for a repetitive disturbance like the beam loading effect in resonators. In this work, we aim to use norm-optimal ILC to cancel beam loading effect. Norm-optimal ILC updates the control signal with the goal of minimizing a performance index, which results in monotonic convergence. Simulation results show that this controller improves beam loading compensation compared to a PI controller. PB - JACoW Publishing CP - Geneva, Switzerland SP - 3824 EP - 3826 KW - controls KW - beam-loading KW - cavity KW - simulation KW - feedback DA - 2019/06 PY - 2019 SN - 978-3-95450-208-0 DO - DOI: 10.18429/JACoW-IPAC2019-THPRB011 UR - http://jacow.org/ipac2019/papers/thprb011.pdf ER -