Cooperative Multi-train Control Algorithms Under Restricted States

Recent years have witnessed tremendous developments of urban rail transit in aspects such as the coverage area,the network scale,the train numbers and density,the line crossings and the transfer stations,etc.Consequently,the influences of both internal restrictive factors and external interrupting factors are aggravated.Numerous factors may interrupt the normal operation order of urban rail transit,and the delay caused by the interruptions would decrease passenger service quality or even influence the whole network operation order.Therefore,the studies on train operation control strategies under multiple state constraints and various stochastic nonlinear disturbances are with significant practical meanings.This work studies the key issues in urban rail transit train operation control strategies considering the state constraints.Main issues of this work include:Firstly,the problem of train trajectory tracking control under nonlinear constrains is studied.Taking the speed limit and input saturation into consideration,a back-stepping control strategy with over-speed restriction and saturation cutoff is designed to realize the active restraint control.Aiming at the threshold of motor traction power and the speed restriction,this work introduces a saturated truncation function and speed constraint function,and puts forward a control strategy that reduces the tracking error via active running speed constraints and error transforms.Secondly,the problem of train speed curve tracking control under stochastic disturbance is studied.Considering the external disturbance in obtaining train position and speed information,the problem of train trajectory tracking control is transformed into a problem of optimal states estimation in discrete-time nonlinear systems with uncertain parameters.A weighted filtering algorithm based on the Kalman filter observer is designed to estimate the velocity of the discrete-time nonlinear system in the sensor network,while reducing the dependence of the controller design on the accuracy of sensors.Meanwhile,as the train dynamics contains uncertain parameters and additional resistance which is difficult to be modeled,the accurate target tracking under uncertain train model is realized by designing controllers based on the fuzzy logic system,with the aim to solve the parameter adaptive estimation problems.Finally,the adaptive control problem of multi-train cooperative operation with restricted minimum interval distance is studied.Considering the minimum tracing distance constraint between the previous train position and the following train position in multi-train cooperative operations,novel auxiliary tracking error variables are introduced through the state information of the coupled train and the adjacent train.Then,a collaborative operation control approach for the active tracking control of minimum tracing distance is designed to achieve the train platoon stability in tracking distance.In this method,the tracking distance between adjacent trains is maintained at the minimum safety distance and the tracking errors of each train decrease with the train numbers successively,which would contribute to enhancing safety under high-density operation conditions.