Adaptive Cooperative Control for Multiple High-Speed Trains with Uncertainties, Input Saturations and State Constraints

This paper investigates the adaptive cooperative control of multiple high-speed trains, where uncertainties, input saturations and state constraints are considered simultaneously. Within the multi-agent framework, the multi-train system cooperative operation problem is formulated, with the leader train tracks the desired operation trajectory, and the follower trains automatically operate according to the state information of the front train. In order to overcome the parameter uncertainties and unknown external disturbances of the system, a bounded-parameter robust adaptive control (BRAC) method is proposed for speed and position tracking of the leader train. Then a novel state-constraint bounded-parameter robust adaptive controller (SBRAC) is further designed in two steps to avoid the risk of overspeed and collision of the follower trains. The auxiliary dynamic system (ADS) with saturation compensation is introduced to solve input saturations, and the barrier Lyapunov function (BLF) is constructed to actively constrain the speed and position of the trains. Finally, numerical simulations are given for the multi-train system to demonstrate the effectiveness of the theoretical studies.