Model Reference Adaptive Algorithm Designed for Automatic Train Braking Control

Abstract

This paper investigates the automatic train braking control problem of ATC (Automatic Train Control) system under uncertain disturbances. An adaptive control algorithm is developed to ensure high precision tracking performance of the acceleration during the braking process, according to a standard reference model which has been widely used in the urban vehicles. The control parameter’s adaptive law is strictly deduced based on the Lyapunov Stability Theory. Rigorous analysis has shown that the train controlled by this method based ATO (Automatic Train Operation) system can effectively track the reference trajectory. Numerical simulation also verifies the effectiveness of this adaptive control algorithm.