Finite-time Disturbance Observer based Distributed New Super-Twisting Sliding Mode Control for High-speed Train Systems

To solve the speed tracking problem of high-speed trains under complex operating conditions, including dynamic coupling forces between cars and external disturbances, this paper suggests a new super-twisting sliding mode control algorithm based on a finite-time disturbance observer for implementation. Firstly, a multi-mass model of high-speed train is established considering the train operation. Secondly, the traditional super-twisting algorithm is replaced by a new super-twisting algorithm that designs a nonlinear exponential function with a variable boundary layer instead of a switching function. The finite-time disturbance observer is used to estimate external disturbances acting on the system, and the estimated values are fed back to the output for compensate ion, to eliminate the effects of external disturbances on high-speed train operations. Through MATLAB simulations, the algorithm of this paper is compared with the conventional super-twisting sliding mode control algorithm and the algorithm without disturbance observer, respectively. The results show that the algorithm in this paper improves the tracking accuracy of the speed of each carriage, and at the same time ensures that the high-speed train is always within a safe distance during operation, and actively suppresses external interference.