Research On Control Algorithm For Tracking Operation Of High-Speed Trains Under Moving Block

The control for tracking operation is critical to the high-speed trains under moving block. Various automatic train protection algorithms are proposed for this difficult problem. But there are lots of shortcomings of these algorithms, such as low line utilization, the ripple speed in high amplitude range and frequent braking. The use of potential function in control can raise the line utilization rate. Furthermore, cooperative control is a good choice to stabilize the train speed and adjust the distance from neighbors. This paper studies two control strategies for the tracking operation of the high-speed trains under Quasi-moving block and moving block respectively:the potential function based control strategy and the cooperative control strategy, with the aim of safety, efficiency, and stability of high-speed trains.Firstly, key technologies and control algorithms of racking interval for block system are investigated by analyzing the structure and principle of CTCS-3system. Then a cooperative control method for tracking operation of high-speed trains under moving block is proposed to solve the problem of failure to satisfy the train’s behavioral evaluation criteria in existed tracking algorithms.Secondly, a potential function based train tracking control algorithm is proposed to solve the problem of low line utilization rate existed in the Quasi-moving block case. The dynamic networked topology of multi-rail is set up on the basis of the graph theory and the rail module. And a finite energy potential function is designed by using the information of distance between trains, which can be used for avoiding rail collision and rising line utilization rate. The simulation results show the superiority of the algorithms proposed in this paper in contrast with the existing algorithms.Finally, a tracking cooperative control algorithm for High-speed trains under the moving block is proposed by synthesizing the potential function and the own dedicated virtual leader following strategy, which can overcome the shortcoming of the potential function based tracking algorithm in the Quasi-moving block case. The speed and location error between the trains and its own dedicated virtual leader could be used to emerge the track force or the brake force to make sure the train runs at the desired speed and keeps away from its neighbours at the necessary distance. Simulation results show that the algorithms proposed in this paper can adjust the train’s state automatically to achieve the goal of minimum distance and permitted speed according to the practical operation environment and criteria.