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Feedback design for control of the micro-bunching instability based on reinforcement learning
The operation of ring-based synchrotron light sources with short electron bunches increases the emission of coherent synchrotron radiation in the THz frequency range. However, the micro-bunching instability resulting from self-interaction of the bunch with its own radiation field limits stable opera...
Autores principales: | , , , , , , , , , |
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Lenguaje: | eng |
Publicado: |
2020
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Materias: | |
Acceso en línea: | https://dx.doi.org/10.23732/CYRCP-2020-009.227 http://cds.cern.ch/record/2752631 |
_version_ | 1780969347584360448 |
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author | Boltz, T Brosi, M Bründermann, E Haerer, B Kaiser, P Pohl, C Schreiber, P Yan, M Asfour, T Müller, A -S |
author_facet | Boltz, T Brosi, M Bründermann, E Haerer, B Kaiser, P Pohl, C Schreiber, P Yan, M Asfour, T Müller, A -S |
author_sort | Boltz, T |
collection | CERN |
description | The operation of ring-based synchrotron light sources with short electron bunches increases the emission of coherent synchrotron radiation in the THz frequency range. However, the micro-bunching instability resulting from self-interaction of the bunch with its own radiation field limits stable operation with constant intensity of CSR emission to a particular threshold current. Above this threshold, the longitudinal charge distribution and thus the emitted radiation vary rapidly and continuously. Therefore, a fast and adaptive feedback system is the appropriate approach to stabilize the dynamics and to overcome the limitations given by the instability. In this contribution, we discuss first efforts towards a longitudinal feedback design that acts on the RF system of the KIT storage ring KARA (Karlsruhe Research Accelerator) and aims for stabilization of the emitted THz radiation. Our approach is based on methods of adaptive control that were developed in the field of reinforcement learning and have seen great success in other fields of research over the past decade. We motivate this particular approach and comment on different aspects of its implementation. |
id | oai-inspirehep.net-1847249 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2020 |
record_format | invenio |
spelling | oai-inspirehep.net-18472492021-02-25T20:02:00Zdoi:10.23732/CYRCP-2020-009.227http://cds.cern.ch/record/2752631engBoltz, TBrosi, MBründermann, EHaerer, BKaiser, PPohl, CSchreiber, PYan, MAsfour, TMüller, A -SFeedback design for control of the micro-bunching instability based on reinforcement learningAccelerators and Storage RingsThe operation of ring-based synchrotron light sources with short electron bunches increases the emission of coherent synchrotron radiation in the THz frequency range. However, the micro-bunching instability resulting from self-interaction of the bunch with its own radiation field limits stable operation with constant intensity of CSR emission to a particular threshold current. Above this threshold, the longitudinal charge distribution and thus the emitted radiation vary rapidly and continuously. Therefore, a fast and adaptive feedback system is the appropriate approach to stabilize the dynamics and to overcome the limitations given by the instability. In this contribution, we discuss first efforts towards a longitudinal feedback design that acts on the RF system of the KIT storage ring KARA (Karlsruhe Research Accelerator) and aims for stabilization of the emitted THz radiation. Our approach is based on methods of adaptive control that were developed in the field of reinforcement learning and have seen great success in other fields of research over the past decade. We motivate this particular approach and comment on different aspects of its implementation.oai:inspirehep.net:18472492020 |
spellingShingle | Accelerators and Storage Rings Boltz, T Brosi, M Bründermann, E Haerer, B Kaiser, P Pohl, C Schreiber, P Yan, M Asfour, T Müller, A -S Feedback design for control of the micro-bunching instability based on reinforcement learning |
title | Feedback design for control of the micro-bunching instability based on reinforcement learning |
title_full | Feedback design for control of the micro-bunching instability based on reinforcement learning |
title_fullStr | Feedback design for control of the micro-bunching instability based on reinforcement learning |
title_full_unstemmed | Feedback design for control of the micro-bunching instability based on reinforcement learning |
title_short | Feedback design for control of the micro-bunching instability based on reinforcement learning |
title_sort | feedback design for control of the micro-bunching instability based on reinforcement learning |
topic | Accelerators and Storage Rings |
url | https://dx.doi.org/10.23732/CYRCP-2020-009.227 http://cds.cern.ch/record/2752631 |
work_keys_str_mv | AT boltzt feedbackdesignforcontrolofthemicrobunchinginstabilitybasedonreinforcementlearning AT brosim feedbackdesignforcontrolofthemicrobunchinginstabilitybasedonreinforcementlearning AT brundermanne feedbackdesignforcontrolofthemicrobunchinginstabilitybasedonreinforcementlearning AT haererb feedbackdesignforcontrolofthemicrobunchinginstabilitybasedonreinforcementlearning AT kaiserp feedbackdesignforcontrolofthemicrobunchinginstabilitybasedonreinforcementlearning AT pohlc feedbackdesignforcontrolofthemicrobunchinginstabilitybasedonreinforcementlearning AT schreiberp feedbackdesignforcontrolofthemicrobunchinginstabilitybasedonreinforcementlearning AT yanm feedbackdesignforcontrolofthemicrobunchinginstabilitybasedonreinforcementlearning AT asfourt feedbackdesignforcontrolofthemicrobunchinginstabilitybasedonreinforcementlearning AT mulleras feedbackdesignforcontrolofthemicrobunchinginstabilitybasedonreinforcementlearning |