Research On Energy-saving Operation Control Of Maglev Train Based On Active Disturbance Rejection Controller

The maglev train has the characteristics of zero friction,less operation and maintenance,strong climbing ability,and high degree of intelligence.Further improving my China’s independent intellectual property rights related to magnetic levitation technology is an important strategic starting point for promoting the popularization and application of magnetic levitation technology,accelerating the construction of a transportation power,and building a modern,high-quality comprehensive three-dimensional transportation network.Aiming at the problems in the design of the speed tracking control algorithm for the maglev train,this paper carries out the following research work:(1)The maglev train’s traction characteristic curve is corrected by data fitting method,and the dynamic model,resistance model and traction calculation model of the maglev train are summarized,optimized and perfected to provide a research foundation for simulation analysis and academic research in related fields.(2)On the basis of the existing research results,in accordance with the idea of modular design,a simulation model of the train speed tracking control system is designed based on the theory of active disturbance rejection control.Firstly,builds a speed tracking controller based on the auto-disturbance-rejection control algorithm;secondly,in view of the numerous parameters,wide range,and complex internal change rules of the auto-disturbance-rejection controller,particle swarm optimization is used for parameter search and optimization,and adaptives weight method to improve the inertia weight coefficient of the particle swarm optimization to achieve better search results;finally,compares and studies the control effect of the auto disturbance rejection control algorithm based on the optimized parameters of the particle swarm optimization,PID control algorithm and the auto disturbance rejection control algorithm based on the optimized parameters of the artificial bee colony algorithm.Through simulation experiment analysis,the simulation model of maglev train speed tracking control system designed in this paper is simple and practical;the train speed tracking control algorithm based on active disturbance rejection control algorithm has the advantages of low model dependence,strong anti-disturbance performance and high tracking accuracy;Combined with the improved particle swarm optimization to optimize the parameters of the auto disturbance rejection controller,the stability,rapidity and energy saving of the entire control system are further improved.This article has important engineering application value to the study of energy-saving operation control of maglev trains.The active disturbance rejection control algorithm described in this article is not only suitable for the speed tracking control of maglev trains,but also has a good reference value for other speed tracking control and motion control.