access icon free Composite model reference adaptive sliding mode controller for automatic train operation

© The Institution of Engineering and Technology
Received 10/01/2019, Accepted 22/07/2019, Revised 27/06/2019, Published 23/07/2019

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.

Inspec keywords: Lyapunov methods; uncertain systems; stability; railways; model reference adaptive control systems; variable structure systems; vehicle dynamics

Other keywords: track-environment-disturbance-longitudinal train dynamics; coupled vehicle dynamics; two-layer sliding surface; composite model reference; reference adaptive sliding mode controller; linear time-invariant stable reference model; longitudinal dynamic performance; adaptive controller gains; desired trajectory tracking; convergence; model reference adaptation framework; operational robustness; composite control scheme; passenger comfort; model parameter uncertainties; Lyapunov criterion; wet rail; stability; automatic train operation

Subjects: Rail-traffic system control; Multivariable control systems; Self-adjusting control systems; Vehicle mechanics; Stability in control theory

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