Journal Article

PUBDB-2024-07329

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Data-Driven Feedback Optimization for Particle Accelerator Application

Hespe, C. (Corresponding author)DESY* ; Kaiser, J.DESY* ; Luebsen, J.Extern* ; Mayet, F.DESY* ; Scholz, M.DESY* ; Eichler, A.XFEL.EU*DESY*

2025
De Gruyter Berlin

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Please use a persistent id in citations: doi:10.1515/auto-2024-0170  doi:10.3204/PUBDB-2024-07329

Abstract: For many engineering problems involving control systems, finding a good working point for steady-state operation is crucial. Therefore, this paper presents an application of steady-state optimization with feedback on particle accelerators, specifically the European X-ray free-electron laser. In simulation studies, we demonstrate that feedback optimization is able to reach a near-optimal steady-state operation in the presence of uncertainties, even without relying on a priori known model information but purely data-driven through input-output measurements. Additionally, we discuss the importance of including second-order information in the optimization to ensure a satisfactory convergence speed and propose an approximated Hessian representation for problems without second-order knowledge on the plant.

Note: EuXFEL R&D project “RP-513: Learning Based Methods”

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Contributing Institute(s):

1. Strahlkontrollen (MSK)
2. Koordination des XFEL-Beschleunigers (MXL)

Research Program(s):

1. 621 - Accelerator Research and Development (POF4-621) (POF4-621)

Experiment(s):

1. Facility (machine) XFEL

Appears in the scientific report 2025

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Database coverage:
; ; Clarivate Analytics Master Journal List ; Essential Science Indicators ; IF < 5 ; JCR ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection

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