This book systematically discusses the algorithms and principles for achieving stable and optimal beam (or products of the beam) parameters in particle accelerators. A four-layer beam control strategy is introduced to structure the subsystems related to beam controls, such as beam device control, beam feedback, and beam optimization. This book focuses on the global control and optimization layers. As a basis of global control, the beam feedback system regulates the beam parameters against disturbances and stabilizes them around the setpoints. The global optimization algorithms, such as the robust conjugate direction search algorithm, genetic algorithm, and particle swarm optimization algorithm, are at the top layer, determining the feedback setpoints for optimal beam qualities.

In addition, the authors also introduce the applications of machine learning for beam controls. Selected machine learning algorithms, such as supervised learning based on artificial neural networks and Gaussian processes, and reinforcement learning, are discussed. They are applied to configure feedback loops, accelerate global optimizations, and directly synthesize optimal controllers. Authors also demonstrate the effectiveness of these algorithms using either simulation or tests at the SwissFEL. With this book, the readers gain systematic knowledge of intelligent beam controls and learn the layered architecture guiding the design of practical beam control systems.

Describes the core systems and algorithms to achieve stable and optimal beam parameters in an accelerator Introduces the modern methods such as the multi-objective optimization and machine learning Provides recent research on using machine learning to train a nonlinear model to describe the input-output relation

Autorentext
Stefan Simrock is a Control System Coordinator at the ITER Organization located in southern France. He studied physics and microwave engineering at the Technical University of Darmstadt where he received his Ph.D. in engineering physics in 1988. From 1988 - 1996 he worked at the Thomas Jefferson National Accelerator Facility as RF controls group leader and deputy for the technical performance of the accelerator. He joined DESY in 1996 as leader of a multidisciplinary team responsible for the design, construction and commissioning of the control system for the superconducting linac at the TESLA Test Facility. In 2004 he was appointed group leader of beam controls group responsible for the timing, synchronisation, and beam feedback systems of all 10 accelerators at DESY. At the same time he was project leader for the RF Control System for FLASH and the European XFEL. Since 2010 he is responsible for the integration of ITER diagnostics with the central control system, machine protection system, safety system, and plasma control system. Zheqiao Geng is a senior electronic engineer at the Paul Scherrer Institute in Switzerland. He graduated with a bachelor's degree from Tsinghua University in Beijing, China, in 2002. In 2007 he received his Ph.D. degree in nuclear engineering from the Graduate School of Chinese Academy of Sciences. For more than ten years, he worked on accelerator RF and beam control systems in different labs, including IHEP (China), DESY (Germany), SLAC (USA) and PSI (Switzerland). He was the key developer of critical aspects of the LLRF systems for various accelerator projects such as the European XFEL, LCLS and SwissFEL. At SLAC, he led the system-level design of the LCLS-II LLRF system. Together with Dr. Stefan Simrock, he held a series of lectures on LLRF systems at the International Accelerator School for Linear Colliders. As an internationally acclaimed LLRF expert, he was appointed as a PSI Senior Expert in 2021.

Inhalt

Introduction.- Beam feedback control.- Beam optimizations.- Machine learning for beam control.