文章基本信息

标题：Direct Data-Driven Control of Cavity Tuners in Particle Accelerators
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作者：Andrea M. Zanchettin ; Simone Formentin ; Riccardo Loddo 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2018
卷号：51
期号：15
页码：138-143
DOI：10.1016/j.ifacol.2018.09.104
语种：English
出版社：Elsevier
摘要：AbstractX-Ray Free Electron Lasers (XFELs) are the next generation of X-rays sources delivering dramatical improvements over synchrotron radiation in terms of brilliance, pulse length and coherence. While obtaining such X-ray radiations, the high gradients of the accelerating electromagnetic field, external vibrations and pressure fluctuations may cause deformations of the cavities where the electrons are accelerated. This lowers the efficiency of the linear accelerator (linac) and degrades the beam quality. To contrast this phenomenon, known as "detuning", suitable mechanical compensators of cavity deformations are needed. In this paper, we propose a direct data-driven approach for the synthesis of such systems, as an alternative to the on-line iterative methods currently in use. The effectiveness of the proposed approach is shown on a complex linac simulator.
关键词：Keywordsdata-driven controlVRFTfeed-forward compensatorcorrelation approachparticle accelerator