In this paper, an equivalent multi‐body dynamics model of high‐speed train with uncertain parameter is established. Based on this detailed model and neural network minimum parameter learning algorithm, an adaptive sliding mode control method is designed for speed and position tracking control of high‐speed train, and the stability of the proposed control method is proved strictly. Then an adaptive fuzzy sliding mode control method (AFSMC) is presented to avoid chattering caused by excessive robust switching gain. Finally, numerical tests are carried out on the proposed AFSMC under different scenarios and operation strategies, and model reference adaptive control (MRAC), PID control and sliding mode control are also tested under the same condition for performance comparison. The results show that the proposed control method is superior to the currently used method. More specifically, compared with MRAC and PID, the average speed tracking accuracy of AFSMC is improved by 0.25 km/h and 0.18 km/h, and the average position tracking accuracy is improved by 0.68 m and 0.7 m, respectively.
Adaptive fuzzy sliding mode control for high‐speed train using multi‐body dynamics model
IET Intelligent Transport Systems ; 17 , 2 ; 450-461
2023-02-01
12 pages
Article (Journal)
Electronic Resource
English
Adaptive fuzzy sliding mode control for high‐speed train using multi‐body dynamics model
DOAJ | 2023
|Automatic Stop Method for High Speed Train Based on Adaptive Fuzzy Sliding Mode Control
British Library Online Contents | 2015
|Adaptive Robust Control: Adaptive Fuzzy Sliding Mode Control Technique
Springer Verlag | 2021
|Automatic train operation based on adaptive terminal sliding mode control
British Library Online Contents | 2015
|