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Deep Learning Based Semi-Supervised Control for Vertical Security of Maglev Vehicle With Guaranteed Bounded Airgap
Sun, Yougang1,2; Xu, Junqi2; Wu H(吴晗)3; Lin, Guobin2; Mumtaz, Shahid4
通讯作者Xu, Junqi(xujunqi@tongji.edu.cn) ; Wu, Han(wuhan@imech.ac.cn)
发表期刊IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
2021-07-01
卷号22期号:7页码:4431-4442
ISSN1524-9050
摘要The vertical security problem of maglev train is challenging for nonlinearity, external disturbances, unmeasurable airgap velocity and constrained output. To solve this problem, a semi-supervised controller based on deep belief network (DBN) algorithm is proposed in the presence of unknown external disturbances. Firstly, the extended state observer (ESO) is designed to ensure fast convergence of observation errors with high enough estimation precision. An output-constrained controller is designed by backstepping method, and the estimated value of ESO is introduced to ensure that the output airgap is constrained within a bounded range. Then, the stability of this method is proved based on the symmetric Barrier Lyapunov function. Subsequently, a semi-supervised controller is presented based on DBN algorithm and the output-constrained controller. The numerical simulation results show that this method can effectively deal with unmeasurable airgap velocity and generalized external disturbances, and guarantee the vertical security with output airgap within a bounded range. Finally, experiments are implemented on a full-scale maglev vehicle and the experimental results demonstrate that the developed deep learning controller can ensure the vertical security.
关键词Extended state observer intelligent control nonlinear dynamics state constrains vertical security
DOI10.1109/TITS.2020.3045319
收录类别SCI ; EI
语种英语
WOS记录号WOS:000673518500048
关键词[WOS]BREATHING HYPERSONIC VEHICLES ; SLIDING MODE CONTROL ; NEURAL APPROXIMATION ; NONLINEAR-SYSTEMS ; NETWORKS ; OBSERVER
WOS研究方向Engineering ; Transportation
WOS类目Engineering, Civil ; Engineering, Electrical & Electronic ; Transportation Science & Technology
资助项目National Natural Science Foundation of China[51905380] ; National Natural Science Foundation of China[51805522] ; China Postdoctoral Science Foundation[2019M651582] ; China Postdoctoral Science Foundation[2020T130475]
项目资助者National Natural Science Foundation of China ; China Postdoctoral Science Foundation
论文分区一类
力学所作者排名1
RpAuthorXu, Junqi ; Wu, Han
引用统计
被引频次:97[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://dspace.imech.ac.cn/handle/311007/87068
专题流固耦合系统力学重点实验室
作者单位1.Tongji Univ, Inst Rail Transit, Shanghai 201804, Peoples R China;
2.Tongji Univ, Natl Maglev Transportat Engn R&D Ctr, Shanghai 201804, Peoples R China;
3.Chinese Acad Sci, Inst Mech, Key Lab Mech Fluid Solid Coupling Syst, Beijing 100190, Peoples R China;
4.Inst Telecomunicacoes, P-3810193 Aveiro, Portugal
推荐引用方式
GB/T 7714
Sun, Yougang,Xu, Junqi,Wu H,et al. Deep Learning Based Semi-Supervised Control for Vertical Security of Maglev Vehicle With Guaranteed Bounded Airgap[J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,2021,22,7,:4431-4442.
APA Sun, Yougang,Xu, Junqi,吴晗,Lin, Guobin,&Mumtaz, Shahid.(2021).Deep Learning Based Semi-Supervised Control for Vertical Security of Maglev Vehicle With Guaranteed Bounded Airgap.IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,22(7),4431-4442.
MLA Sun, Yougang,et al."Deep Learning Based Semi-Supervised Control for Vertical Security of Maglev Vehicle With Guaranteed Bounded Airgap".IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 22.7(2021):4431-4442.
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