Research on Automatic Train Operation System Based on Fuzzy Adaptive PID Algorithm

The traditional PID algorithm used in the currently existing automatic train operation system is limited due to fixed parameters, making it difficult to achieve excellent control effects in actual operation scenes featuring strong coupling and high nonlinearity, which is mainly attributed to difficulties in overcoming nonlinear disturbances.In light of this, this paper proposes an automatic train operation approach that relies on a fuzzy adaptive PID algorithm, which can adjust the PID parameters in real time according to the preset fuzzy rules, thus improving the PID controller's performance in speed tracking and leading to an improved train control effect. Based on the data from Changsha Rail Transit Line 4, the semi-physical simulation results show that the proposed algorithm resulted in the average root-mean-square error (RMSE) of 18.876 cm/s between the actual train speed and the recommended speed, which is less than the 35.200 cm/s of the traditional PID controller and the value of fitting degree is 1.6