Adaptive Tracking Control with Input Saturation and Asymmetrically Time-varying Full-State Constraints for Automatic Train Operation

The state feedback tracking control problem is investigated for the train with traction and braking saturation under asymmetrically time-varying full-state constraints. To reduce the influence of input constraint, the saturation function is approximated as the sum of a smooth function and a error term. Moreover, an asymmetrically time-varying Barrier Lyapunov function is adopted to deal with the state constraints. Meanwhile, RBF and adaptive control method have been used to approximate the unknown function and estimate the unknown parameters. Hence, the proposed control method can ensure that all the signals in the close-loop system are bounded and the asymmetrically time-varying state constraints have not been violated. At last, the simulation exmaple of the train operating in fast strategy and running in the wind zone demonstrates the effectiveness of the control method.