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Mathematical Problems in Engineering
Volume 2013, Article ID 713560, 7 pages
Research Article

Nonlinear Robust Observer-Based Fault Detection for Networked Suspension Control System of Maglev Train

College of Mechatronics Engineering and Automation, National University of Defense Technology, Changsha 410073, China

Received 11 January 2013; Revised 22 April 2013; Accepted 26 April 2013

Academic Editor: Engang Tian

Copyright © 2013 Yun Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


A fault detection approach based on nonlinear robust observer is designed for the networked suspension control system of Maglev train with random induced time delay. First, considering random bounded time-delay and external disturbance, the nonlinear model of the networked suspension control system is established. Then, a nonlinear robust observer is designed using the input of the suspension gap. And the estimate error is proved to be bounded with arbitrary precision by adopting an appropriate parameter. When sensor faults happen, the residual between the real states and the observer outputs indicates which kind of sensor failures occurs. Finally, simulation results using the actual parameters of CMS-04 maglev train indicate that the proposed method is effective for maglev train.