| 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 | |
| Corresponding Author | Xu, Junqi([email protected]) ; Wu, Han([email protected]) |
| Source Publication | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
 |
| 2021-07-01 | |
| Volume | 22Issue:7Pages:4431-4442 |
| ISSN | 1524-9050 |
| Abstract | 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. |
| Keyword | Extended state observer intelligent control nonlinear dynamics state constrains vertical security |
| DOI | 10.1109/TITS.2020.3045319 |
| Indexed By | SCI ; EI |
| Language | 英语 |
| WOS ID | WOS:000673518500048 |
| WOS Keyword | BREATHING HYPERSONIC VEHICLES ; SLIDING MODE CONTROL ; NEURAL APPROXIMATION ; NONLINEAR-SYSTEMS ; NETWORKS ; OBSERVER |
| WOS Research Area | Engineering ; Transportation |
| WOS Subject | Engineering, Civil ; Engineering, Electrical & Electronic ; Transportation Science & Technology |
| Funding Project | National Natural Science Foundation of China[51905380] ; National Natural Science Foundation of China[51805522] ; China Postdoctoral Science Foundation[2019M651582] ; China Postdoctoral Science Foundation[2020T130475] |
| Funding Organization | National Natural Science Foundation of China ; China Postdoctoral Science Foundation |
| Classification | 一类 |
| Ranking | 1 |
| Contributor | Xu, Junqi ; Wu, Han |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://dspace.imech.ac.cn/handle/311007/87068 |
| Collection | 流固耦合系统力学重点实验室 |
| Affiliation | 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 |
| Recommended Citation 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.Rp_Au:Xu, Junqi, Wu, Han |
| 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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| Jp2021F251.pdf（2003KB） | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | View Download | |
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