Research On Intelligent Algorithm Of PID Controller For Urban Rail Trains

In recent years,the urban rail transit system has been developed rapidly in our country.It plays an important role in solving important problems such as traffic congestion,environmental pollution,and excessive energy consumption.With the increasing demand for urban railways,the systems need to be safer,more punctual,and more efficient.At present,the operation control system of urban rail trains is mainly based on traditional PID controllers.Problems as the parameters determined based on experience,and controller parameters cannot be adjusted in real time still exist in researches and reality.This not only leads to a large consumption of manpower and time,but also makes it difficult for the train operation controller to cope with changing environment.Therefore,it is necessary to explore the adaptive adjustment methods of PID controllers.According to the above problems,combined with the specific application requirements of urban rail transit systems,the real-time self-tuning scheme of PID controller parameters in ATO system is given in the paper.Based on the actual running data of the train and the characteristics of the train control command,a more accurate train dynamics model is proposed as the controlled object of the PID controller.The dynamic model includes five train running stages:the coasting stage,the start-up stage,the re-traction stage,the traction removal stage,and the braking stage.At the same time,16 parameters of the model are given,which can be fitted according to the data online.In order to achieve the accurate PID controller parameters in real time,a Double Subgroups Fruit Fly Optimization Algorithm with fusion mechanism is proposed.The algorithm has been improved in both population partitioning and population fusion.The running time of the algorithm has not changed much,but the optimization precision has been greatly improved.Compared with other intelligent algorithms,the algorithm has great advantages in stability,running time and optimization accuracy.In our paper,it takes the Yizhuang line in Beijing subway as an example,the algorithm is applied to accurately fit the PID controller parameters and the train dynamics model.In the paper,a simulation software is developed according to the algorithm.The simulation software provides the function of fitting the train dynamics model parameters and the PID controller parameters,and provides users with a friendly and convenient software interface.The running data of the stations inside and outside the tunnel and in different weather of the Yizhuang line in Beijing subway are simulated by the software.The simulation results verify the influence of external conditions on the PID controller parameters,and prove that the algorithm has good convergence accuracy,stability and adaptability.The results further show that the scheme has a high application value for the parameter adjustment of the PID controller in urban rail trains.