Optimal Prediction for Braking Speed of Urban Rail Vehicle

The accurate measurement of the speed of urban rail vehicle is the basis of normal operation of the train controlling. Since speed measuring devices of vehicle-borne is inevitably disturbed by the sensors or the external environment, the deviation between the measured speed and the actual value, which varies randomly, is impossible to eliminate. This paper utilizes the method of minimum variance prediction to predict the speed of the train. By this way, the variance of the deviation between the predicted value and the actual value of the speed can be minimized. The model of the speed of the train is also discretized, which overcomes the shortcomings that the transitional models and control theory are limited to theoretical analysis but cannot be used in the actual computer control systems. In the section of simulation, the article shows the actual simulation results, which prove that this method has strong practicability.