Design of multi-objective optimal control algorithm for automatic driving of EMU based on PSO

With the acceleration of urbanization in China, the scale of cities is getting bigger and bigger, and the population of cities is increasing. The existing urban transportation network has been unable to meet the requirements of urban development. The application of automatic driving system ATO in urban rail trains can effectively ensure the safety and comfort of train operation, and it has more outstanding advantages than manual driving in automatically adjusting train speed, accurately stopping at stations on time and reducing energy consumption. Because of the complexity of the train running process, its running speed is usually affected by line conditions, speed limit conditions and driver proficiency, so there are many uncertain factors. The use of auto drive system instead of train driver driving can meet the requirements of various performance indicators during train operation, while avoiding arbitrary factors caused by human. Therefore, it is necessary to study auto drive system. Applying this algorithm to the optimization design of a large number of feature points, good linearization design results have been obtained, and the simulation results have been verified, which can also meet the simulation requirements. The simulation results show that the algorithm is effective and superior for control parameter optimization, and has certain engineering application value.