Adaptive PIQ stopping control of urban rail vehicle

Stopping accuracy is an important index to measure the performance of Automatic Train Operation, as well as a significant guarantee of the safety of the train's operation. However, during the braking process, the stopping accuracy tends to be affected by line conditions and brake shoe friction coefficients. In this paper, a braking model of the train reflecting these uncertain conditions, also the principle and the dynamic characteristics of the braking system is derived. Based on this model, an adaptive PIQ control scheme is proposed to track ideal braking curve. Furthermore, we develop the backstepping technique to deal with the dynamic characteristics of the braking system. The stability and the convergence of the adaptive algorithms are proved by Lyapunov theorem. Simulation results verify that this method not only overcomes the impacts of unknown parameters and dynamic characteristics of the model but also achieves high stopping accuracy without any loss of riding comfort of the vehicle.