Application Of Intelligent Algorithm In Traction Control Of Unmanned Urban Rail Transit

Urban rail trains have become one of the ways to solve traffic congestion in many cities,in order to improve operation efficiency,the control level of the urban rail ATO must be transited from traditional manual driving to the completely unmanned system.The design of a high efficiency ATO control system can ensure the train running smoothly and safely in different environment,improve the parking accuracy,passenger comfort and punctual probability,and save energy consumption,increase departure frequency of passenger peak hours.The mathematical modeling method,running distance,the optimization of speed target curve and the tracking accuracy of ATO speed controller will have a direct impact on the performance indicators.Therefore,this thesis will start from the above aspects,the main contents are as follows:Firstly,This thesis introduces the relationship between the ATO system and the related systems,the working principle of the ATO speed controller and the performance indicators required for the safe and smooth operation of the train;analyzes the force analysis of the train in different traction conditions and establishes a single particle model of train operation.Secondly,This thesis analyzes the composition of train energy consumption,based on the single particle model and the mode transition principle of the operation,the objective function of minimizing the train traction energy consumption is established as the fitness function of the genetic algorithm,The distance between the train operating condition conversion points is coded as the chromosome,and the target curve is optimized by genetic algorithm.Thirdly,According to the method and principle of the sliding mode control,setting up the ATO speed controller.In the case of an accurate control model for train operation and no interference conditions,carrying out the numerical simulation in a straight line,the tracking position and speed are consistent with the target position and speed of the train,the result shows that the tracking effect is good.Fourthly,The actual train control model is difficult to establish accurately,and there are uncertainties and internal and external interferences in the operation.Aiming at the above situation,based on the principles of robust control and adaptive control,a robust ATO speed controller based on sliding mode robust and sliding mode adaptive is established.The simulation results show that tracking effect of the speed controller based on the sliding mode robust method is better than tracking effect of the speed controller based on the sliding mode method in the identified external interference.In the interference of uncertainty,the ATO speed controller based on the sliding mode adaptive robust method can meet the basic requirements of train operation and ensure accurate parking,punctual arrival and better ride comfort of the train.Fifthly,In this thesis,the relationship between the longitudinal and vertical in the running process of the train is discussed preliminary,Through the establishment of vertical vibration model and longitudinal dynamic model of 6-DOF urban rail train,the simulation results show that the one-way coupling of the longitudinal vertical running relationship of the train is relatively weak.