Sliding mode observer based incipient sensor fault detection with application to high-speed railway traction device
Kangkang Zhang1, Bin Jiang1, Xing-Gang Yan2
1College 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.
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.
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