Research on Automatic Braking and Traction Control of High-speed Train Based on Neural Network

With the rapid development of economy and technology, people's quality of life has been continuously improved, which also makes people put forward higher requirements for the quality of transportation. As far as railway transportation is concerned, the running speed and route of trains in the past gradually failed to meet people's travel needs. Automatic train operation system (ATO), under the protection of automatic train protection system, realizes automatic train driving according to the instructions of automatic train supervision system, and can automatically control the starting, traction, cruising, idling and braking of trains. Traction drive system is the core part of high-speed train, and traction drive converter technology is one of the key technologies of high-speed train. In this paper, according to the different working mechanism of traction and braking, the dynamic model of train under traction and resistance braking is established by combining neural network algorithm, and the corresponding controller is designed by using nonlinear backstepping design method to realize automatic tracking of train speed and position.