Iterative Learning Control For High-speed Trains With Velocity And Displacement Constraints

With the development of economy and society,the requirements for high-speed,highefficiency,safety and comfort of modern trains continue to grow,and precise tracking of train operation control has become a research hotspot.The automatic train control system is the basis of the research on train operation control.It has developed from the track circuit-based train control to the communication-based train control which is now widely used.In this paper,the characteristics of high-speed train running process,such as line repeatability,model structure invariance are fully used to study the reliable operation control strategy with autonomous learning ability.It should be emphasized that the project not only realizes the tracking of displacement and speed,but also ensures the safety of train operation.From the perspective of single train,the speed must always be kept under the maximum safe speed,and the displacement should be constrained in a safe interval.Iterative learning control is suitable for a class of controlled objects with repetitive operation in a finite time interval.When it is applied to high-speed train operation control,with the increase of iteration times,the train tracking effect is significantly improved.The main work of this paper is as follows:Firstly,mechanical analysis of high-speed train is analysed,and the train dynamics model is established.In the process of train operation,the train is mainly affected by the resistance,traction force and braking force.Combining with Newton’s second law,the train dynamics model with parametric and non-parametric uncertainties is established to better describe the actual condition of high-speed train.Then,according to the control theory and dynamics model in the previous chapters,the barrier Lyapunov function(BLF)is introduced into the composite energy function(CEF)to form the barrier composite energy function(BCEF),and ILC controller is designed by backstepping method.In addition,its convergence is proved with the help of the barrier composite energy function.Finally,the effectiveness of the proposed control algorithm is verified by simulation.According to the actual situation,set the additional resistance when the train is running on a certain line.The speed reference curve set in the simulation involves traction,cruise and braking,which verifies the effectiveness of the ILC algorithm more intuitively.Combined with the traction / braking characteristic curve of CRH2-A,the control input curve is analyzed to meet the requirements of maximum traction force and braking force of the train and the basic criteria of high-speed train operation comfort.