Adaptive Backstepping Stopping Control of Urban Rail Vehicle

Stopping accuracy is an important index to measure the performance of Automatic Train Operation (ATO), as well as a significant guarantee of the safety of the train’s operation. However, during the process of braking, the stopping accuracy of the urban rail vehicle is affected by the line conditions, brake shoe friction coefficients and random noise. A braking model of the train reflecting these uncertain conditions and principle of braking system is derived in this paper. Based on this model, an adaptive backstepping control scheme is proposed to track ideal braking curve. Using Lyapunov stability theorem, the stability and the convergence of the adaptive algorithms are proved. Simulation results verify that this method not only overcomes the impact of uncertain parameters but also greatly improves the stopping accuracy of the train without loss of the comfort level of passengers.