| Summary: | High-speed trains delay may happen due to the complicated and erratic operating circumstances of railway lines. In this paper, the problems of delayed recovery in high-speed train operations and the rapid acquisition of optimal trajectory for train offline operations are investigated. Firstly, taking on-time performance and energy saving as optimization objectives, an information communication topology model of train group is established. Then, a variable-parameter multi-objective particle swarm optimization algorithm is proposed to determine the best trajectory for train offline operation. The algorithm prevents decision variables from falling into a local optimum and effectively increases the speed of the overall search for an optimum. Secondly, consider the delay phenomenon in the dynamic process of online train operation, the idea of multi-agent consistent formation control is introduced, and an online train operation controller is designed to provide feedback regulation of the speed and position of trains deviating from the offline operation trajectory. The stability of train operation control system is demonstrated by Lyapunov’s method. The controller can improve the immunity of disturbance and delay recovery for train operation. Finally, using actual data from the Wuhan to Changsha South line, the validity of the proposed theoretical results is further verified.
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