Fault Tolerant Learning Control for High‐Speed Trains With Iteration‐Varying Parameters

High‐speed trains, one of the most modern means of transportation, always repeat the same tasks on a fixed route. However, the train operation environment varies, and actuator faults are inevitable, which makes the high‐speed train system a typical repetitive system with iteration‐varying parameters and actuator fault threats. To this end, a fault‐tolerant learning control scheme is proposed in this study for the train trajectory tracking problem. The iteration‐varying characteristics of parameters and actuator fault mechanisms are carefully analyzed and effectively compensated. By constructing an appropriate composite energy function, it is proved that the proposed control scheme can reach a practical error tracking to the reference speed trajectory even with the influence of iteration‐varying parameters and actuator faults. Numerical simulations verify the control effect.