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A Super-Twisting-Like Algorithm and Its Application to Train Operation Control With Optimal Utilization of Adhesion Force
Chen, Yao1; Dong, Hairong2; Lu, Jinhu3; Sun, Xubin4; Guo, Liang4
2016-11-01
Source PublicationIEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
ISSN1524-9050
Volume17Issue:11Pages:3035-3044
AbstractThe friction between wheel and track is usually called adhesion force, and it is the critical factor for the movement of trains. On one hand, excessive driving force of a train may lead to insufficient utilization of the adhesion effect and cause wasted energy; on the other hand, insufficient driving force of a train brings inefficient train operation. To balance the issues of energy consumption, operational efficiency, and security, it is necessary to control a train to obtain its maximal adhesion force, particularly in the cases of fast acceleration and emergency braking. However, since engineering experiments indicate a complex nonlinear relationship between the adhesion force and the slip ratio of a train, such a control problem is difficult and challenging, particularly when the optimal slip ratio is unknown. Facing this problem, this paper proposes a novel control method based on the modification of the famous super-twisting sliding mode algorithm, and rigorous mathematical analysis is given to guarantee the ultimate boundedness of the proposed algorithm. Furthermore, by considering four different control scenarios, detailed control and estimation algorithms are both proposed. Simulation result verifies that the proposed control strategy can control the train to obtain its maximum adhesion force.
KeywordTrain operation control super-twisting algorithm adhesion force
DOI10.1109/TITS.2016.2539361
Language英语
Funding ProjectNational Natural Science Foundation of China[61304157] ; National Natural Science Foundation of China[61322307] ; National Natural Science Foundation of China[61233001] ; National Natural Science Foundation of China[61304196]
WOS Research AreaEngineering ; Transportation
WOS SubjectEngineering, Civil ; Engineering, Electrical & Electronic ; Transportation Science & Technology
WOS IDWOS:000387902500004
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation statistics
Cited Times:12[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/24110
Collection系统科学研究所
Affiliation1.Hong Kong Polytech Univ, Dept Comp, Kowloon, Hong Kong, Peoples R China
2.Beijing Jiaotong Univ, State Key Lab Rail Traff Control & Safety, Beijing 100044, Peoples R China
3.Chinese Acad Sci, Acad Math & Syst Sci, Inst Syst Sci, Beijing 100190, Peoples R China
4.Beijing Jiaotong Univ, Sch Elect & Informat Engn, Beijing 100044, Peoples R China
Recommended Citation
GB/T 7714
Chen, Yao,Dong, Hairong,Lu, Jinhu,et al. A Super-Twisting-Like Algorithm and Its Application to Train Operation Control With Optimal Utilization of Adhesion Force[J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,2016,17(11):3035-3044.
APA Chen, Yao,Dong, Hairong,Lu, Jinhu,Sun, Xubin,&Guo, Liang.(2016).A Super-Twisting-Like Algorithm and Its Application to Train Operation Control With Optimal Utilization of Adhesion Force.IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,17(11),3035-3044.
MLA Chen, Yao,et al."A Super-Twisting-Like Algorithm and Its Application to Train Operation Control With Optimal Utilization of Adhesion Force".IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 17.11(2016):3035-3044.
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