17–22 May 2026
C.I.D
Europe/Zurich timezone

Neural Network-Based Amplitude Feedforward Control Algorithm for LLRF Systems

MOP6697
18 May 2026, 16:00
2h
C.I.D

C.I.D

Deauville, France
Poster Presentation MC6.T27: Instrumentation: Low Level RF Poster session

Speaker

Prof. Xiaofang Hu (University of Science and Technology of China)

Description

In free-electron laser facilities, the amplitude-phase stability of the microwave pulses driving the electron beam is a key factor determining beam energy spread. Aiming at the long bunch train operation mode, this paper proposes a neural network-based amplitude feedforward control for low-level radio frequency (LLRF) systems to suppress intra-pulse amplitude fluctuations. The algorithm has been validated at the output of a solid-state amplifier (SSA): under four randomly selected vector modulator (VM) output configurations, the average intra-pulse amplitude flatness (RMS) was reduced from 1.208% to 0.398%, and the average peak-to-peak variation was reduced from 4.683% to 1.353%, demonstrating a significant compensation effect.

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Authors

Yuchen Wang (University of Science and Technology of China) Prof. Xiaofang Hu (University of Science and Technology of China) Mr Shenghua Yang (University of Science and Technology of China) Jian Pang (University of Science and Technology of China) Fangfang Wu (University of Science and Technology of China) Kai Zhang (University of Science and Technology of China) Shancai Zhang (University of Science and Technology of China)

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