Adaptive fault-tolerant automatic train operation using RBF neural networks

In order to accommodate actuator failures which are unknown in amplitude and time, adaptive fault-tolerant control schemes are proposed for automatic train operation system. Firstly a basic design scheme on the basis of direct adaptive control is considered. It is demonstrated that, when actuator failures occur, asymptotical speed and position tracking are guaranteed. Then a new user-friendly control scheme is proposed which can eliminate the undesirable chattering phenomenon, which is the defect of the previous method. Simulation results verify the effectiveness of established theoretical results that satisfactory speed tracking and position tracking can be guaranteed in the presence of uncertain actuator failures in automatic train operation systems.