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Optimal Spin Polarization Control for the Spin-Exchange Relaxation-Free System Using Adaptive Dynamic Programming

文献类型：期刊论文

作者Wang, Ruigang2,3; Wang, Zhuo2,3; Liu, Sixun2,3; Li, Tao1; Li, Feng2,3; Qin, Bodong2,3; Wei, Qinglai1
刊名IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
出版日期2022-12-26
页码13
ISSN号2162-237X
关键词3-D spin polarization control (3DSPC) adaptive dynamic programming (ADP) asymmetric input constraint multicritic multiaction neural networks (MCMANNs) multiphysics multiplayer nonzero-sum game (MP-NZSG) spin-exchange relaxation-free (SERF).
DOI10.1109/TNNLS.2022.3230200
通讯作者Wang, Zhuo(zhuowang@buaa.edu.cn)
英文摘要This work is the first to solve the 3-D spin polarization control (3DSPC) problem of atomic ensembles, which controls the spin polarization to achieve arbitrary states with the cooperation of multiphysics fields. First, a novel adaptive dynamic programming (ADP) structure is proposed based on the developed multicritic multiaction neural network (MCMANN) structure with nonquadratic performance functions, as a way to solve the multiplayer nonzero-sum game (MP-NZSG) problem in 3DSPC under the constraints of asymmetric saturation inputs. Then, we utilize the MCMANNs to implement the multicritic multiaction ADP (MCMA-ADP) algorithm, whose convergence is proven by the compression mapping principle. Finally, the MCMA-ADP is deployed in the spin-exchange relaxation-free (SERF) system to provide a set of control laws in 3DSPC that fully exploits the multiphysics fields to achieve arbitrary spin polarization states. Numerical simulations support the theoretical results.
WOS关键词ONLINE LEARNING CONTROL
资助项目Key Area Research and Development Program of Guangdong Province[2021B0101410005] ; National Natural Science Foundation of China[61673041]
WOS研究方向Computer Science ; Engineering
语种英语
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号WOS:001046423800005
资助机构Key Area Research and Development Program of Guangdong Province ; National Natural Science Foundation of China
源URL[http://ir.ia.ac.cn/handle/173211/53888]  
专题多模态人工智能系统全国重点实验室
通讯作者Wang, Zhuo
作者单位1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Beihang Univ, Sch Instrumentat Sci & Optoelect Engn, Beijing 100191, Peoples R China
3.Beihang Univ, Hangzhou Innovat Inst, Zhejiang Prov Key Lab Ultra Weak Magnet Field Spa, Hangzhou 310051, Peoples R China
推荐引用方式
GB/T 7714		 Wang, Ruigang,Wang, Zhuo,Liu, Sixun,et al. Optimal Spin Polarization Control for the Spin-Exchange Relaxation-Free System Using Adaptive Dynamic Programming[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2022:13.
APA Wang, Ruigang.,Wang, Zhuo.,Liu, Sixun.,Li, Tao.,Li, Feng.,...&Wei, Qinglai.(2022).Optimal Spin Polarization Control for the Spin-Exchange Relaxation-Free System Using Adaptive Dynamic Programming.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,13.
MLA Wang, Ruigang,et al."Optimal Spin Polarization Control for the Spin-Exchange Relaxation-Free System Using Adaptive Dynamic Programming".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2022):13.

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来源：自动化研究所

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