TS Model-based Composite Nonlinear Feedback Control Method for Heavy Haul Trains

As the mainstream method, heavy-haul-train-based transportation plays a significant role in bulk commodities' transportation. To reduce the drivers' workload and improve the control performance, the automatic control of heavy haul trains has come into being. In this paper, we propose a TS model-based composite nonlinear feedback (CNF) control method in which both the steady state and the dynamic process are considered simultaneously, which, however, differs from the existing results. The TS modeling method is introduced to address the nonlinearity of the dynamic model for heavy haul trains, while the corresponding CNF control is utilized to track the desired velocity and improve the transient control performance considering the input saturation. To facilitate the controller design, linear matrix inequalities (LMIs) are presented, which guarantees the tracking performance with a minimum disturbance attenuation level under a constraint input. Finally, simulation results show the effectiveness of the proposed method.