001468110 000__ 04029cam\\22006257i\4500
001468110 001__ 1468110
001468110 003__ OCoLC
001468110 005__ 20230707003354.0
001468110 006__ m\\\\\o\\d\\\\\\\\
001468110 007__ cr\cn\nnnunnun
001468110 008__ 230524s2023\\\\sz\a\\\\ob\\\\001\0\eng\d
001468110 019__ $$a1379097790
001468110 020__ $$a9783031285974$$q(electronic bk.)
001468110 020__ $$a3031285972$$q(electronic bk.)
001468110 020__ $$z3031285964
001468110 020__ $$z9783031285967
001468110 0247_ $$a10.1007/978-3-031-28597-4$$2doi
001468110 035__ $$aSP(OCoLC)1380015790
001468110 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dYDX
001468110 049__ $$aISEA
001468110 050_4 $$aQC787.P3
001468110 08204 $$a539.73$$223/eng/20230524
001468110 1001_ $$aGeng, Zheqiao,$$eauthor.
001468110 24510 $$aIntelligent beam control in accelerators /$$cZheqiao Geng, Stefan Simrock.
001468110 264_1 $$aCham, Switzerland :$$bSpringer,$$c2023.
001468110 300__ $$a1 online resource (155 pages) :$$billustrations (black and white, and color).
001468110 336__ $$atext$$btxt$$2rdacontent
001468110 337__ $$acomputer$$bc$$2rdamedia
001468110 338__ $$aonline resource$$bcr$$2rdacarrier
001468110 4901_ $$aParticle acceleration and detection
001468110 504__ $$aIncludes bibliographical references and index.
001468110 5050_ $$aIntroduction -- Beam feedback control -- Beam optimizations -- Machine learning for beam control.
001468110 506__ $$aAccess limited to authorized users.
001468110 520__ $$aThis book systematically discusses the algorithms and principles for achieving stable and optimal beam (or products of the beam) parameters in particle accelerators. A four-layer beam control strategy is introduced to structure the subsystems related to beam controls, such as beam device control, beam feedback, and beam optimization. This book focuses on the global control and optimization layers. As a basis of global control, the beam feedback system regulates the beam parameters against disturbances and stabilizes them around the setpoints. The global optimization algorithms, such as the robust conjugate direction search algorithm, genetic algorithm, and particle swarm optimization algorithm, are at the top layer, determining the feedback setpoints for optimal beam qualities. In addition, the authors also introduce the applications of machine learning for beam controls. Selected machine learning algorithms, such as supervised learning based on artificial neural networks and Gaussian processes, and reinforcement learning, are discussed. They are applied to configure feedback loops, accelerate global optimizations, and directly synthesize optimal controllers. Authors also demonstrate the effectiveness of these algorithms using either simulation or tests at the SwissFEL. With this book, the readers gain systematic knowledge of intelligent beam controls and learn the layered architecture guiding the design of practical beam control systems.
001468110 588__ $$aDescription based on print version record.
001468110 650_0 $$aParticle accelerators$$xControl systems.
001468110 650_0 $$aParticle beams.
001468110 655_0 $$aElectronic books.
001468110 7001_ $$aSimrock, Stefan,$$eauthor.
001468110 77608 $$iPrint version:$$aGENG, ZHEQIAO. SIMROCK, STEFAN.$$tINTELLIGENT BEAM CONTROL IN ACCELERATORS.$$d[Place of publication not identified] : SPRINGER INTERNATIONAL PU, 2023$$z3031285964$$w(OCoLC)1370487859
001468110 830_0 $$aParticle acceleration and detection.
001468110 852__ $$bebk
001468110 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-28597-4$$zOnline Access$$91397441.1
001468110 909CO $$ooai:library.usi.edu:1468110$$pGLOBAL_SET
001468110 980__ $$aBIB
001468110 980__ $$aEBOOK
001468110 982__ $$aEbook
001468110 983__ $$aOnline
001468110 994__ $$a92$$bISE