title: Sliding mode observer based incipient sensor fault detection with application to high-speed railway traction device.
abstract: This paper considers incipient sensor fault detection issue for a class of nonlinear systems with "observer unmatched" uncertainties. A particular fault detection sliding mode observer is designed for the augmented system formed by the original system and incipient sensor faults. The designed parameters are obtained using LMI and line filter techniques to guarantee that the generated residuals are robust to uncertainties and that sliding motion is not destroyed by faults. Then, three levels of novel adaptive thresholds are proposed based on the reduced order sliding mode dynamics, which effectively improve incipient sensor faults detectability. Case study of on the traction system in China Railway High-speed is presented to demonstrate the effectiveness of the proposed incipient senor faults detection schemes.
authors.affiliation: College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China; Jiangsu Key Laboratory of Internet of Things and Control Technologies, Nanjing University of Aeronautics and Astronautics, China. Electronic address: KangZhang359@163.com.
authors.forename: Kangkang
authors.initials: K
authors.lastname: Zhang
authors.affiliation: College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China; Jiangsu Key Laboratory of Internet of Things and Control Technologies, Nanjing University of Aeronautics and Astronautics, China. Electronic address: binjiang@nuaa.edu.cn.
authors.forename: Bin
authors.initials: B
authors.lastname: Jiang
authors.affiliation: School of Engineering and Digital Arts, University of Kent, Canterbury, Kent CT2 7NT, United Kingdom. Electronic address: x.yan@kent.ac.uk.
authors.forename: Xing-Gang
authors.initials: XG
authors.lastname: Yan
authors.affiliation: College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China; Jiangsu Key Laboratory of Internet of Things and Control Technologies, Nanjing University of Aeronautics and Astronautics, China. Electronic address: zehuimao@nuaa.edu.cn.
authors.forename: Zehui
authors.initials: Z
authors.lastname: Mao
keywords: Adaptive threshold; Fault development detection; Incipient sensor fault; Sliding mode observer