Jiles–Atherton model prediction and compensation of the hysteresis inside magnetic shields-Reference-Cited by-同舟云学术

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Jiles–Atherton model prediction and compensation of the hysteresis inside magnetic shields

Published:2019-03 Issue:3 Volume:9 Page:035222
ISSN:2158-3226
Container-title:AIP Advances
language:en
Short-container-title:AIP Advances

Author:

Peng Xiangkai¹²^ORCID,Li Lin¹,Ren Wei¹,Ji Jingwei¹,Xiang Jingfeng¹,Zhao Jianbo¹,Ye Meifeng¹,Zhao Xin¹,Wang Bin¹,Qu Qiuzhi¹,Li Tang¹,Liu Liang¹²,Lü Desheng¹²

Affiliation:

1. Key Laboratory for Quantum Optics and Center of Cold Atom Physics, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Science, Shanghai 201800, China

2. Center of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences, Beijing 100049, China

Funder

National Natural Science Foundation of China

Youth Innovation Promotion Association of the Chinese Academy of Sciences

Publisher

AIP Publishing

Subject

General Physics and Astronomy

Link

http://aip.scitation.org/doi/pdf/10.1063/1.5088766

Reference21 articles.

1. Magnetic field measurement on87Rb atomic fountain clock

2. Recent improvements on the pulsed optically pumped rubidium clock at SIOM

3. Space-borne Bose–Einstein condensation for precision interferometry

4. In-orbit operation of an atomic clock based on laser-cooled 87Rb atoms

5. Hysteresis prediction inside magnetic shields and application

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. State Space Representation of Jiles–Atherton Hysteresis Model and Application for Closed-Loop Control;Materials;2024-07-26

2. Space Cold Atomic Clock Technologies;CHIN J LASERS;2024

3. Dynamic stabilisation of magnetic fields measured inside a magnetically shielded room using an external coil system ^*;Journal of Physics D: Applied Physics;2024-03-15

4. Evolution of nonlinear magneto-elastic constitutive laws in ferromagnetic materials: A comprehensive review;Journal of Magnetism and Magnetic Materials;2022-03

5. Online learning method based on artificial neural network to optimize magnetic shielding characteristic parameters;Acta Physica Sinica;2019

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