A novel iterative learning approach for tracking control of high-speed trains subject to unknown time-varying delay

Chen, Yong, Huang, Deqing, Li, Yanan and Feng, Xiaoyun (2020) A novel iterative learning approach for tracking control of high-speed trains subject to unknown time-varying delay. IEEE Transactions on Automation Science and Engineering. pp. 1-9. ISSN 1545-5955

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Abstract

In this article, a novel iterative learning control scheme is proposed for high-speed trains, aiming to track the desired reference displacement and velocity, where the Krasovskii function is constructed to compensate for the negative influence of unknown time-varying speed delays. The main feature of the proposed approach is that the hyperbolic tangent function and the command filter are integrated into the learning controller to overcome the singularity problem that may occur during the control process and relax the requirement for the derivability of the desired velocity. The stability of control system is strictly proved through establishing the composite energy function, and the effectiveness is confirmed via numerical simulations. Compared with the existing works, the merits of the proposed control scheme lie in that more general nonlinear uncertainties are imposed on the dynamic model of train instead of the Lipschitz condition, and the reference acceleration assigned by the railway department is not required.

Item Type: Article
Schools and Departments: School of Engineering and Informatics > Engineering and Design
SWORD Depositor: Mx Elements Account
Depositing User: Mx Elements Account
Date Deposited: 01 Dec 2020 09:18
Last Modified: 11 Jan 2021 15:45
URI: http://sro.sussex.ac.uk/id/eprint/95416

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