关键词: 铁路运输, 列车自动驾驶, 自适应迭代学习控制, 高速列车, Lyapunov 函数, 跟踪误差

Abstract:

To study the automatic control of high-speed trains with time-varying exterior disturbances and state saturation, this paper proposes an adaptive iterative learning control algorithm. Based on Lyapunov function, the control law and the parameter of updating law are deduced by considering the state error during the operating process. Then the Lyapunov-like composite energy function is established. The differential negative definiteness and robustness of the proposed function are verified. The proposed adaptive iterative learning control algorithm has been applied to computational simulation and real case study to verify the tracking performance. The results show that the proposed algorithm improves tracking accuracy and convergence speed. It was able to accurately track the desired profile with less iterative times than before.

Key words: railway transportation, automatic train operation, adaptive iterative learning control, high- speed train, Lyapunov function, tracking error