A Strategy Based on LSTM Controller With Adaptive Proportional Compensation for High-Speed Train Operation Control

With the rapid development of high-speed railways, the issue of train speed tracking has become increasingly important. A controller based on a Long Short-Term Memory (LSTM) module was designed to meet the high-precision tracking requirements of trains, and its convergence analysis was analyzed. At the same time, in order to further improve the control performance on the basis of the original controller, an adaptive proportional compensation module was designed, and its effectiveness was theoretically proven. Finally, simulation validation was conducted on a multi-particle model with a large number of perturbations for both methods. The results show that the LSTM controller reaches good control results under external interference, and the adaptive proportional compensation module can further improve the control performance of the original controller.