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基于滑模观测器的早期传感器故障检测及其在高速铁路牵引装置中的应用

Sliding mode observer based incipient sensor fault detection with application to high-speed railway traction device.

作者信息

Zhang Kangkang, Jiang Bin, Yan Xing-Gang, Mao Zehui

机构信息

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.

School of Engineering and Digital Arts, University of Kent, Canterbury, Kent CT2 7NT, United Kingdom.

出版信息

ISA Trans. 2016 Jul;63:49-59. doi: 10.1016/j.isatra.2016.04.004. Epub 2016 May 4.

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.

摘要

本文研究了一类具有“观测器不匹配”不确定性的非线性系统的早期传感器故障检测问题。针对由原系统和早期传感器故障构成的增广系统,设计了一种特殊的故障检测滑模观测器。利用线性矩阵不等式(LMI)和线性滤波器技术获得设计参数,以确保所产生的残差对不确定性具有鲁棒性,并且滑模运动不会因故障而被破坏。然后,基于降阶滑模动力学提出了三种新颖的自适应阈值,有效提高了早期传感器故障的可检测性。通过对中国高速铁路牵引系统的案例研究,验证了所提出的早期传感器故障检测方案的有效性。

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