Predictive control modeling of ADS's MEBT using BPNN to reduce the impact of noise on the control system
文献类型：期刊论文
| 作者 | Zhou, Qingguo3; Wang, Jinqiang3; Li, Kuan-Ching2; He, Yuan1 ; Zhou, Rui3; Han, Lihong3; Yang, Xuhui3,4
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| 刊名 | ANNALS OF NUCLEAR ENERGY
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| 出版日期 | 2019-10-01 |
| 卷号 | 132页码:576-583 |
| ISSN号 | 0306-4549 |
| 关键词 | ADS injector II Beam commissioning Back propagation BPM offset Proton orbit calibrations |
| DOI | 10.1016/j.anucene.2019.06.034 |
| 通讯作者 | Zhou, Qingguo(zhouqg@lzu.edu.cn) |
| 英文摘要 | In the beam debugging of China ADS Injector 11, the mathematical matrix operation, software simulation or physical derivation methods are mainly used. These methods do not take into account noise conditions, so it is difficult to accurately control the deflection position of the beam. For this reason, this paper takes MEBT as an example to establish a function model of quadrupole magnet control parameter and beam position, and based on the BPNN to fit the function model to reduce the influence of noise on the control process, and then realizes control prediction model in beam debugging. The experiments results show that the prediction accuracy of the quadrupole magnet control voltages Q2 and Q3 are 0.9072 and 0.9352, respectively, and the MSE is 0.0064. This paper is the first attempt of deep neural network in China ADS injector 11, which provides a new method for beam debugging of the system. (C) 2019 Elsevier Ltd. All rights reserved. |
| WOS关键词 | DESIGN ; BUNCHER |
| 资助项目 | National Natural Science Foundation of China[61402210] ; National Natural Science Foundation of China[60973137] ; State Grid Corporation Science and Technology Project[SGGSKY00FJJS1700302] ; Program for New Century Excellent Talents in University[NCET-12-0250] ; Major National Project of High Resolution Earth Observation System[30-Y20A34-9010-15/17] ; Key R&D projects in Gansu Province[17YF1GA013] ; Gansu Academy of Sciences Application Development project[2017JK-06] ; Gansu Academy of Sciences Application Development project[2019QN-01] ; Ministry of Education China Mobile Research Foundation[MCM20170206] ; Fundamental Research Funds for the Central Universities[lzujbky-2018-k12] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDA03030100] ; Google Research Awards ; Google Faculty Award |
| WOS研究方向 | Nuclear Science & Technology |
| 语种 | 英语 |
| 出版者 | PERGAMON-ELSEVIER SCIENCE LTD |
| WOS记录号 | WOS:000482247600053 |
| 资助机构 | National Natural Science Foundation of China ; State Grid Corporation Science and Technology Project ; Program for New Century Excellent Talents in University ; Major National Project of High Resolution Earth Observation System ; Key R&D projects in Gansu Province ; Gansu Academy of Sciences Application Development project ; Ministry of Education China Mobile Research Foundation ; Fundamental Research Funds for the Central Universities ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Google Research Awards ; Google Faculty Award |
| 源URL | [http://119.78.100.186/handle/113462/132852]  |
| 专题 | 中国科学院近代物理研究所 |
| 通讯作者 | Zhou, Qingguo |
| 作者单位 | 1.Chinese Acad Sci, Inst Modern Phys, Beijing, Peoples R China 2.Providence Univ, Dept Comp Sci & Informat Engn, Taichung, Taiwan 3.Lanzhou Univ, Sch Informat Sci & Engn, Lanzhou, Peoples R China 4.Gansu Acad Sci, Inst Sensor Technol, Gansu Prov Key Lab Sensors & Sensing Technol, Lanzhou, Gansu, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhou, Qingguo,Wang, Jinqiang,Li, Kuan-Ching,et al. Predictive control modeling of ADS's MEBT using BPNN to reduce the impact of noise on the control system[J]. ANNALS OF NUCLEAR ENERGY,2019,132:576-583. |
| APA | Zhou, Qingguo.,Wang, Jinqiang.,Li, Kuan-Ching.,He, Yuan.,Zhou, Rui.,...&Yang, Xuhui.(2019).Predictive control modeling of ADS's MEBT using BPNN to reduce the impact of noise on the control system.ANNALS OF NUCLEAR ENERGY,132,576-583. |
| MLA | Zhou, Qingguo,et al."Predictive control modeling of ADS's MEBT using BPNN to reduce the impact of noise on the control system".ANNALS OF NUCLEAR ENERGY 132(2019):576-583. |
入库方式： OAI收割
来源：近代物理研究所
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