Research And Simulation Of Traction Control Strategy Of Urban Rail Train Based On Fuzzy Adaptive Control

In recent years,with the rapid development of economy,the demand for transportation is increasing.To ease traffic congestion,the construction of a green and new type of transportation system has become the development direction of rail transportation,and the urban rail trains have gradually changed from the traditional manual driving to driverless operation mode.The automatic train system of the urban rail train controls the traction and braking of the train,to achieve the purpose of adjusting the train operating speed,so that the train can operate on a punctual basis automatically and safely,and at the same time,the smoothness of the train operation and the comfort are improved.The key technologies to achieve automatic safety and efficient operation of trains are the optimization of the speed target curve and the design of speed controllers.Under this background,the paper mainly focuses on the structure,principle and achievable functions of the train autopilot system(ATO).The performance of each operating condition,principle and control strategy was introduced.Based on this,the operating environment of the urban rail train,as well as the traction,braking force and resistance of the train were analyzed.The characteristics of the automatic operation of the urban rail train were established.Based on the multi-objective model of energy-efficiency,comfort,punctuality of parking,and parking alignment,the weighted values of each index were obtained by using the method of mean square error,and the established multi-objective model was optimized by using genetic algorithm in MATLAB.Under the environment,the target curve of the train operation is obtained for a certain section of line simulation;by using the classic control theory(PID),a PID speed controller is established,and the target curve is tracked and simulated.The simulation finds that when the train operation conditions are converted,PID control the speed curve will appear relatively large fluctuations,and the recovery time will be longer than the target.The expected tracking effect of the curve,PID control can not be adjusted according to the changes in the train operating environment on the control parameters,combined with fuzzy inference and adaptive control strategy,the establishment of a fuzzy adaptive PID controller,to achieve the dynamic adjustment of the train speed.Through the simulation of the target curve,the simulation results of energy consumption,comfort,safety,trackability,stopping accuracy,and punctuality during train operation are analyzed.Under consideration of the conditions of the train operating environment and other disturbance factors,the train running curve controlled by the fuzzy adaptive PID speed controller is closer to the target curve,the speed-distance error is smaller,and it has stronger anti-interference ability,and the control effect is ideal.