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

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Yun Li ◽  
Guang He ◽  
Jie Li
Keyword(s):  
Control System ◽  
Time Delay ◽  
Fault Detection ◽  
External Disturbance ◽  
Maglev Train ◽  
Robust Observer ◽  
Suspension Control ◽  
Arbitrary Precision ◽  
Nonlinear Robust Observer ◽  
Nonlinear Robust

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.

CLPP: A User-Friendly Platform for Nonlinear Robust Observer Design

2010 ◽  
Vol 43 (5) ◽  
pp. 182-187
Author(s):  
M. Alamir ◽  
P. Bellemain ◽  
L. Boillereaux ◽  
I. Queinnec ◽  
M. Titica ◽  
...  
Keyword(s):  
Observer Design ◽  
Robust Observer ◽  
User Friendly ◽  
Nonlinear Robust Observer ◽  
Nonlinear Robust

scholarly journals Research on Siding Mode Controller of High-Speed Maglev Train Under Aerodynamic Load

2021 ◽  
Author(s):  
Meng-juan Liu ◽  
Han Wu ◽  
Xiao-Hui Zeng ◽  
Bo Yin ◽  
Zhan-zhou Hao
Keyword(s):  
High Speed ◽  
Vibration Suppression ◽  
Sliding Mode ◽  
Impact Load ◽  
External Disturbance ◽  
Aerodynamic Load ◽  
Suspension Stability ◽  
Maglev Train ◽  
Suspension Control ◽  
Dynamic Simulation Model

Abstract The high-speed maglev train will be subjected to extremely obvious aerodynamic load during operation, it will also be subjected to instantaneous aerodynamic impact load in the case of passing, which will bring extreme challenges to the suspension stability and safe operation of the train. It is necessary to consider the influence of aerodynamic load and shock wave in the design of suspension control algorithm. Traditional proportion integration differentiation (PID) control cannot follow the change of vehicle parameters or external disturbance, which is easy to cause suspension fluctuation and instability. In order to improve the suspension stability and vibration suppression of high-speed maglev train under aerodynamic load and impact, a controller based on sliding mode technique is designed in this paper, and in this controller, the deformation of the primary suspension is introduced to replace the aerodynamic load on the electromagnet. In order to verify the control performance of the designed controller, the dynamic simulation model of train with three vehicles is established, and the dynamic response of the train under the condition of passing in open air is calculated. Compared with the PID controller, it is verified that the sliding mode control (SMC) method proposed in this paper can effectively restrain the electromagnet fluctuation of the train under aerodynamic load.

A nonlinear robust observer design for SDINS in-flight alignment

2001 ◽  
Author(s):  
Chan Park ◽  
Jang Lee ◽  
Duk-Sun Shim ◽  
Myeong-Jong Yu
Keyword(s):  
Observer Design ◽  
Robust Observer ◽  
Nonlinear Robust Observer ◽  
Nonlinear Robust

scholarly journals T-S Fuzzy Model Based Control Strategy for the Networked Suspension Control System of Maglev Train

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Guang He ◽  
Jie Li ◽  
Peng Cui ◽  
Yun Li
Keyword(s):  
Control System ◽  
Control Strategy ◽  
State Feedback ◽  
Fuzzy Model ◽  
Maglev Train ◽  
Fuzzy Models ◽  
Physical Experiments ◽  
Suspension Control ◽  
The Stability ◽  
Takagi Sugeno

The control problem for the networked suspension control system of maglev train with random induced time delay and packet dropouts is investigated. First, Takagi-Sugeno (T-S) fuzzy models are utilized to represent the discrete-time nonlinear networked suspension control system, and the parameters uncertainties of the nonlinear model have also been taken into account. The controllers take the form of parallel distributed compensation. Then, a sufficient condition for the stability of the networked suspension control system is derived. Based on the criteria, the state feedback fuzzy controllers are obtained, and the controller gains can be computed by using MATLAB LMI Toolbox directly. Finally, both the numerical simulations and physical experiments on the full-scale single bogie of CMS-04 maglev train have been accomplished to demonstrate the effectiveness of this proposed method.

Simulation of Fault Detection in the Wireless Networked Control System

2013 ◽  
Vol 846-847 ◽  
pp. 778-781
Author(s):  
Hong Liang Guo ◽  
Shao Ying Kong
Keyword(s):  
Control System ◽  
Time Delay ◽  
Fault Detection ◽  
Wireless Network ◽  
Detection Method ◽  
State Space Model ◽  
Failure Detection ◽  
Networked Control System ◽  
Network Control ◽  
Network Control System

Wireless network control system is characterized by high uncertain delay time, thus the state of the system can not be fully observed. The fault characteristic is interfered by time delay so to be unstable, leading inaccurate fault detection. Traditional fault detection method of wireless network control system is usually based on the characteristics of the stability of the network status data. If the network has time delay fluctuations, it is unable to obtain accurate fault detection results. This paper presents a stochastic delay fault detection method. It builds a state space model of the system, analyzes the delay vector between the sensor end of the system and the controller end, depending on the delay residual signal of the system and the corresponding evaluation function to obtain the system failure detection result. The final simulation result shows that this method has high accuracy in the detection of Stability and randomness of the wireless network fault detection. Thus it is an effective wireless network control system fault detection method.

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