Fuzzy adaptive automatic train operation control with protection constraints: A residual nonlinearity approximation-based approach

Abstract

In this study, we present fuzzy adaptive control based on residual nonlinearity approximation in the presence of protection constraints for the target trajectory tracking problem observed in automatic train operation. Herein, protection constraints refer to a condition wherein the speed and position of a controlled train are not allowed to surpass the boundaries imposed by automatic train protection and moving authority. By defining proper coordinate transformation, the protection constraints are converted to an error-prescribed performance control problem that facilitates operational efficiency by reducing the margin with respect to target trajectories. Based on the prescribed performance control methodology, we present an improved scheme using fuzzy residual nonlinearity approximation and establish the uniformly ultimately boundedness (UUB) property. A novel feature therein is that the ultimate boundary of the proposed scheme is simultaneously characterized by the prescribed performance functions and control parameters, with rigorous and analytically mathematical expressions; while pioneering the prescribed performance control methodology, the ultimate boundary is characterized solely by the prescribed performance functions. To verify the effectiveness and advantages of the proposed scheme, the controllers are applied to the automatic train operation on the Beijing Yizhuang line, which contains 13 operational intervals. Finally, comparative and simulation results are presented to validate the proposed method.