Adaptive guidance control of super-twisting sliding mode for virtual track train

In order to improve the robust performance of autonomous guidance control of virtual track trains subject to parameter uncertainties and unknown external disturbances, the multi-input and multi-output overdrive control problem during train operation was studied, a nonlinear guidance control model of multi-articulated virtual track train was established based on Lagrange's formula, and the equivalent lateral tire force was used as the control input. By employing discrete point coordinates of the virtual track and the speed of the train, a reference model was built to calculate the location, speed, and acceleration of the train, and an independent guidance controller and longitudinal speed controller of the train were designed. By applying Lyapunov method, based on the traditional sliding mode control (SMC) and adaptive super-twisting sliding mode (ASTSM), two guidance controllers of the train were designed, respectively, and the control command of a steer-by-wire system was calculated by an inverse tire model. Moreover, a wheel speed allocation model was established, in which the longitudinal train speed control was converted to the speed and electromagnetic torque control of each in-wheel motor on the basis of the reference velocity vector. A dynamics simulation model composed of seven carriages was constructed, and the responses of in-wheel motor speed and electromagnetic torque were analyzed by variable speed and compound path test. The distribution law of the articulated force between vehicle modules was revealed, and the robustnesses of SMC and ASTSM under uncertain parameters and unknown external disturbances were compared. Research results show that the proposed guidance control model, motion reference model, and wheel speed allocation model are effective. The tracking errors of longitudinal velocities of vehicle modules are less than 1.5 km·h^-1, and the tracking error rates of wheel speeds are not more than 1%. Compared with the SMC, the proposed ASTSM has better adaptive robustness in the presence of unmodeled dynamics, 50% load changes, and unknown disturbances, and the deviation of each axle center can gradually converge to around 0 in finite time. Under the lateral force interference, the root mean square deviation and maximum deviation of the ASTSM for all axis centers are 10 and 42 mm, and decrease by 82% and 61%, respectively. In addition, the steady-state deviation of the ASTSM on the curved section is not significant, and the articulated angles can consistently converge to a stable value, which guarantees the stability of the virtual track train.