Research on high-speed train speed running curve tracking control based on compensating function observer
HOU Tao
ZHOU Wenqi
NIU Hongxia
Abstract:Aiming at the low estimation accuracy of the observer as well as the strong coupling,exter-nal perturbation,and time-varying parameters of the high-speed train system,a Fractional Order Non-singular Fast Terminal Sliding Mode Control(FONFTSMC)based on the Compensating Function Observer(CFO)is put forward to improve the robustness and control accuracy of the high-speed train speed control.Firstly,a longitudinal multi-mass dynamics model of the high-speed train is estab-lished,and a high-precision compensation function observer is designed to estimate and compensate the total perturbation of the system in real time;Secondly,a fractional-order non-singular fast terminal sliding mode control algorithm with state-negative exponential control law is designed for tracking and controlling the train's running curve,and the system's convergence is proved to be in finite time by the Lyapunov stability theory;Finally,the parameters of CRH3 high-speed train and the actual line of Hefei Station-Bengbu South Station are used as examples to track the ideal operation curve and the energy-saving optimized operation curve for experimental verification,respectively.The simulation results show that the average error of the proposed algorithm in tracking the ideal operating speed curve is 0.0137 7 km/h,and the average error in tracking the energy-saving optimized operating speed curve with interference is 0.036 4 km/h.Compared with the sliding mode and non-singular fast terminal sliding mode control methods based on dilated state observer,the proposed method has the smallest tracking error and higher tracking accuracy,which verifies its effectiveness and feasibility,and can provide a reference for the research in the field of train speed tracking control.
Keywords:high-speed trainmulti-mass modelcompensating function observerfractional-order non-singular fast terminal sliding modetracking control
Publication Date:2025-06-30
Online Publishing Date:2025-08-21(First online date of this platform, not the publication date of the document)
Pages:11( 100-110 )
