NMPC applied to operation of high-speed train

The operation of a high-speed train is a high-nonlinear process with uncertainties, which is one of challenges for Automatic Train Operation system. Thus this paper uses Nonlinear Model Predictive Control algorithm (NMPC). To the uncertainties of train caused by friction, slope of rails, strong wind, and so on, taking advantage of flexibility and adaptation of Model Predictive Control, an update strategy for model parameters is given. In the end, a simulation is conducted to test the effectiveness of this method with typical operation condition of a train on Beijing-Shanghai high-speed railway.