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.
This book begins with an overview of the RF control concepts and strategies. It then introduces RF system models for optimizing the system parameters to satisfy beam requirements and for controller design. In addition to systematically discussing the RF field control algorithms, it presents typical architecture and algorithms for RF signal detection and actuation. Further, the book addresses the analysis of the noise and nonlinearity in LLRF systems to provide a better understanding of the performance of the RF control system and to specify the performance requirements for different parts of the RF system. Today, accelerators require increased RF stability and more complex operation scenarios, such as providing beam for different beam lines with various parameters, and as a result LLRF systems are becoming more critical and complex. This means that LLRF system developers need have extensive knowledge of the entire accelerator complex and a wide range of other areas, including RF and digital signal processing, noise analysis, accelerator physics and systems engineering. Providing a comprehensive introduction to the basic theories, algorithms and technologies, this book enables LLRF system developers to systematically gain the knowledge required to specify, design and implement LLRF systems and integrate them with beam acceleration. It is intended for graduate students, professional engineers and researchers in accelerator physics.
The day after Beethoven’s death on March 26, 1827, his friends found, in a secret drawer of his desk, together with his will and two miniature portraits of two young women, a ten-page letter dated “July 6 in the morning,” that began with the intriguing incantation “My angel, my all, myself.” It included no address and no name of the addressee, except for the now famous my immortal beloved hyperbole, containing passionate declarations of love and was signed, “L., forever yours, forever mine, forever us.” Thus was born a biographical mystery of the artistic canon of the Western World, second only in tantalizing appeal to the identity of the person signing as William Shakespeare. Two hundred years later, biographers still have not come to a consensus on the mystery. Of the many candidates advanced in the meantime, only a few have survived in biographical literature. Stefan Romanó’s book brings the controversy to a close. It clarifies the existing evidence that has often been muddled, and at times reached the absurd, during almost two centuries of scholarly speculations. He also adds some new insights into the analysis of the evidence, thus making it easier for readers to draw their own conclusions, hopefully not different from his, namely, that only one of the candidates proposed so far fits the evidence. He also provides a substantially modified scenario from the one advanced by her proponents. Born in Romania during WWII and immigrated to the U.S.A. in 1989, Stefan Romanó is not a musician nor a musicologist. He is an engineer by formation, a man of exactitude and clear and logical thinking, qualities that served him thoroughly when he became an amateur Beethoven scholar. A long-time member of American Beethoven Society and of its French counterpart, Association Beethoven France et Francophonie, he has published in their professional journals, bringing valuable contributions to understanding Beethoven’s life and creation. His “Ending the Fifth” article answered a question that had puzzled musicians, scholars and music lovers alike for two hundred years: why does Beethoven’s Fifth Symphony end with that apparently interminable series of C major chords? He took up the pen by force of circumstance for his Beethoven’s Immortal Beloved when he realized that all the proposed solutions to the mystery relied on wild speculation and sometimes even falsifying the existing evidence.
Filling the need for a book bridging the effect of matter on X-ray radiation and the interaction of x-rays with plasmas, this monograph provides comprehensive coverage of the topic. As such, it presents and explains such powerful new X-ray sources as X-ray free-electron lasers, as well as short pulse interactions with solids, clusters, molecules, and plasmas, and X-ray matter interactions as a diagnostic tool. Equally useful for researchers and practitioners working in the field.
This book begins with an overview of the RF control concepts and strategies. It then introduces RF system models for optimizing the system parameters to satisfy beam requirements and for controller design. In addition to systematically discussing the RF field control algorithms, it presents typical architecture and algorithms for RF signal detection and actuation. Further, the book addresses the analysis of the noise and nonlinearity in LLRF systems to provide a better understanding of the performance of the RF control system and to specify the performance requirements for different parts of the RF system. Today, accelerators require increased RF stability and more complex operation scenarios, such as providing beam for different beam lines with various parameters, and as a result LLRF systems are becoming more critical and complex. This means that LLRF system developers need have extensive knowledge of the entire accelerator complex and a wide range of other areas, including RF and digital signal processing, noise analysis, accelerator physics and systems engineering. Providing a comprehensive introduction to the basic theories, algorithms and technologies, this book enables LLRF system developers to systematically gain the knowledge required to specify, design and implement LLRF systems and integrate them with beam acceleration. It is intended for graduate students, professional engineers and researchers in accelerator physics.
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.
This will help us customize your experience to showcase the most relevant content to your age group
Please select from below
Login
Not registered?
Sign up
Already registered?
Success – Your message will goes here
We'd love to hear from you!
Thank you for visiting our website. Would you like to provide feedback on how we could improve your experience?
This site does not use any third party cookies with one exception — it uses cookies from Google to deliver its services and to analyze traffic.Learn More.