| Title |
Norm-optimal Iterative Learning Control to Cancel Beam Loading Effect on the Accelerating Field |
| Authors |
- Z. Shahriari, K. Fong
TRIUMF, Vancouver, Canada
- G.A. Dumont
UBC, Vancouver, Canada
|
| Abstract |
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.
|
| Paper |
download THPRB011.PDF [0.346 MB / 3 pages] |
| Export |
download ※ BibTeX
※ LaTeX
※ Text/Word
※ RIS
※ EndNote |
| Conference |
IPAC2019 |
| Series |
International Particle Accelerator Conference (10th) |
| Location |
Melbourne, Australia |
| Date |
19-24 May 2019 |
| Publisher |
JACoW Publishing, Geneva, Switzerland |
| Editorial Board |
Mark Boland (UoM, Saskatoon, SK, Canada); Hitoshi Tanaka (KEK, Tsukuba, Japan); David Button (ANSTO, Kirrawee, NSW, Australia); Rohan Dowd (ANSTO, Kirrawee, NSW, Australia); Volker RW Schaa (GSI, Darmstadt, Germany); Eugene Tan (ANSTO, Kirrawee, NSW, Australia) |
| Online ISBN |
978-3-95450-208-0 |
| Received |
14 May 2019 |
| Accepted |
19 May 2019 |
| Issue Date |
21 June 2019 |
| DOI |
doi:10.18429/JACoW-IPAC2019-THPRB011 |
| Pages |
3824-3826 |
| Copyright |
 Published by JACoW Publishing under the terms of the Creative Commons Attribution 3.0 International license. Any further distribution of this work must maintain attribution to the author(s), the published article's title, publisher, and DOI. |
|
