Composite model reference adaptive sliding mode controller for automatic train operation

Abstract

With the ever-increasing speed of trains, the passenger comfort, and the desired trajectory tracking play an important role in the design of automatic train operation. As the speed increases, the train experiences uncertainties, non-linearities, unknown disturbances and so on, due to the interaction among track-environment-disturbance-longitudinal train dynamics. Much attention has been drawn to design a suitable control scheme which can improve both longitudinal dynamic performance and operational robustness in view of automatic train operation. In this context, the authors propose a novel composite sliding mode control scheme with model reference adaptation scheme. The sliding surface of the composite control scheme is considered as a two-layer sliding surface to emulate the coupled vehicle dynamics. To derive the adaptive controller gains mathematically, the model reference adaptation framework is chosen that also helps to demonstrate the stability and the convergence using Lyapunov criterion. The effectiveness of the proposed composite algorithm is being tested by tracking a linear time-invariant stable reference model in the simulation under different environmental disturbances such as side wind, wet rail and model parameter uncertainties. The proposed scheme is found to improve passenger comfort with a least tracking error.