Iterative Learning Operation Control Of High-speed Trains With Adhesion Dynamics

China's high-speed railway is shifting from independent innovation period(2004-2008)to comprehensive independent innovation period(2012-present),in which the common goal of public transportation development has gradually become intelligentization,network integration,synergy and integration.Basic theories and key technology researches based on high-speed train operation safety are vigorously supposed to be carry out to solve the problem.Simultaneously,providing theoretical support and technical support is of great significance for the development of China's modernization and informatization high-speed railway and minimizing most incidence of train safety accidents.The studies for the high-speed trains' adhesion problem between the wheel and rail as well as the train operation control process are as follows.First of all,the research is conducted on the wheel-rail adhesion mechanism and the repeatability of the train.Although the operation of entire train will be affected by the adhesion dynamics which even pose the train in a dangerous situation,the existed work on high-speed train operation control is still very limited.Based on the theory of wheel-rail adhesion and creep reasons for the formation,it is reasonable to learn several calculation methods of adhesion force which lays a foundation for the establishment of the high-speed train model for the next chapter.At the same time,since the running process of high-speed trains is repeated in the spatial domain in the operational level,which satisfied the application conditions of the iterative learning control(ILC)algorithm,the intelligent control algorithm can be designed.Then,according to the theoretical basis of the previous chapter and the understanding of the basis of the train dynamics modeling,a dynamic model of high-speed train operation including adhesion dynamics is established.This model is built in the time domain.However,in order to apply the spatial iterative learning scheme,the running dynamics of the train can be converted from the time domain to the spatial domain to realize the proposed control scheme by describing the relationship between the time domain and the spatial domain.Next,based on the space dynamic model of the high-speed train,a new spatial domain iterative learning control(ILC)algorithm is proposed,which realizes the target speed trajectory tracking of high-speed train operation control in the basis of the time-varying adhesion dynamic between wheel and rail.At the same time,the convergence of the new ILC algorithm is guaranteed with the help of the new composite energy function.It is worth noting that the dynamic system has no require of global Lipschitz continuity in the analysis process of composite energy function,which is one of the common assumptions in the ILC convergence analysis.Finally,based on the proposed spatial ILC algorithm,the MATLAB software is used to establish a complete simulation of the starting-to-stopping operation of a CRH380 A train on the dry rail surface.The tracking result of the processes of traction,sliding,acceleration and braking is a good proof for the effectiveness of the spatial ILC algorithm.