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Interval Sliding Mode Observer Based Incipient Sensor Fault Detection with Application to a Traction Device in China Railway High-speed

Zhang, Kangkang, Jiang, Bin, Yan, Xing-gang, Shen, Jun (2019) Interval Sliding Mode Observer Based Incipient Sensor Fault Detection with Application to a Traction Device in China Railway High-speed. IEEE Transactions on Vehicular Technology, 68 (3). pp. 2585-2597. ISSN 0018-9545. E-ISSN 1939-9359. (doi:10.1109/TVT.2019.2894670) (KAR id:72476)

Abstract

This paper proposes an interval sliding mode observer (ISMO) and an incipient sensor faults detection method for a class of nonlinear control systems with observer unmatched uncertainties. The interval bounds for continuous nonlinear functions and new injection functions are constructed to design ISMOs. An incipient fault detection framework with newly designed residual and threshold generators is proposed. The detectability is then studied, and a set of sufficient detectable conditions are presented. Applications to an electrical traction device used in China Railway High-speed (CRH) are presented to verify the effectiveness of the proposed incipient sensor fault detection methodology.

Item Type: Article
DOI/Identification number: 10.1109/TVT.2019.2894670
Subjects: T Technology
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: Xinggang Yan
Date Deposited: 13 Feb 2019 17:14 UTC
Last Modified: 09 Dec 2022 01:23 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/72476 (The current URI for this page, for reference purposes)

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