Research On Multi-objective Optimal Control Strategy Of Automatic Train Operation For Urban Rail Transit

The capacity of the existing urban rail transit system has become saturated,which affects the daily travel of the general public.In the case that the new line cannot be built immediately to expand the capacity of urban rail transit system,by changing the operation mode of the existing line,the urban rail train controlled by train crew will be upgraded to automatic train operation and ATO system will replace the locomotive crew to control the train to operate safely on the line.Upgrading from manual driving to automatic driving of train is not only the embodiment of improvement of scientific and technological,but also the general trend of the operation mode of urban rail transit system in the future.The operation of urban rail train on the line controlled by ATO system needs to meet the five performance indicators of safety,punctuality,parking accuracy,comfort and energy saving.However,most of the current research on ATO control strategy is focused on the single performance indicator of energy saving,without the complete consideration of the five performance indicators.In view of the above problems,the thesis will solve them from the following aspects.Firstly,the automatic train operation system needs to be understood.Then the operation environment of urban rail train is to be analyzed with the establishment of the corresponding dynamic model.Finally,five performance indicators are considered comprehensively and the multi-objective optimization model of urban rail train of ATO system is established through multi-objective optimization technology.By solving the model with genetic algorithm,the ideal speed curve of urban rail of ATO system can be generated in the aspect of ATO speed controller design,combined with the characteristics of grey predictive control and fuzzy adaptive PID control,an integrated intelligent speed controller based on the core of Grey Prediction Fuzzy Adaptive PID control method is formed.The speed controller can track the generated ideal speed curve of the train well.Finally,appropriate simulation line and vehicles are to be selected,the genetic algorithm program is to be written and the simulation platform of urban rail train automatic driving is to be built in MATLAB software for simulation verification.From the simulation results,it can be seen that the optimized ideal speed curve of train after the optimization of the genetic algorithm meets the requirements of various performance indexes,which indicates the effectiveness and superiority of the optimization method.ATO system takes the ideal speed curve of train generated by multi-objective optimization technology as the target speed curve of automatic train operation,which makes the integrated intelligent speed controller control the train to operate according to the target speed curve.It can be seen that the integrated intelligent speed controller can track the train target running curve well in the range of small tracking error and safety,which makes the controlled train more stable and punctual in the operation to improve the comfort of passengers,reduce energy consumption,and reduce the parking error.To sum up,the application of intelligent control algorithm in ATO system can control the train during operation to meet five performance indexes,so as to realize the research purpose of automatic driving of urban rail train.