Design Of Speed Control Scheme For High Speed Train Based On Active Disturbance Rejection Control

In recent years,with the rapid development of high-speed train technology,China’s large-scale eight vertical and eight horizontal railway plans are gradually being realized.High-speed trains have excellent riding comfort,low carbon,environmental protection,low pollution,high speed and high efficiency.High-speed trains are becoming more and more important in people’s lives,and the safety problems of high-speed trains should not be underestimated,so the reliability of the speed control system of high-speed trains is particularly important.In view of the nonlinearity,variability and complexity of the highspeed train system,this paper studies and designs a reliable control strategy to ensure the normal operation of the high-speed train.The main research contents and results of this paper include the following aspects:Firstly,based on the parameter uncertainty and nonlinearity of the high-speed train model,the train dynamics model is established.In order to fully reflect the real operation of high-speed trains,various unknown disturbances encountered in the complex operation process are introduced into the train operation model.This paper introduces the working principle of high-speed train speed control system,analyzes the longitudinal dynamic model of the train,and builds the running model of the high-speed train through simulation software.Secondly,the high-speed train speed control system is designed by active disturbance rejection control(ADRC),the disturbance inside and outside the system is estimated and compensated by using the extended state observer,and the tracking differentiator is introduced to solve the overshoot problem of the input signal.The parameter tuning method of ADRC is analyzed in detail,and the stability analysis of ADRC at steady-state point is given by partial derivative method.Thirdly,considering the shortcoming that traditional ADRC has too many parameters and is difficult to adjust,a new parameter optimization control scheme of RBF-ADRC controller is proposed by using the approximation of radial basis function neural network(RBFNN).This scheme not only inherits the advantage that ADRC can estimate and compensate disturbance without detailed model,but also eliminates the peak value of control signal and reduces the peak impact of control signal on actuator.Compared with other control schemes,the advantages of RBF-ADRC controller are verified by detailed theoretical analysis and rigorous simulation results.Fourthly,considering the running model of high-speed train with actuator failure,a composite ADRC is designed,which introduces the adaptive law of ADRC gain,further combines neural network to approach the observation error of the observer,and analyzes the stability of the composite controller.In order to verify the robustness of the composite ADRC more effectively,white noise interference and step interference are introduced into the controller.The simulation results show that the performance of ADRC is optimized by the composite controller,which effectively eliminates the internal and external interference of the system,protects the safety of the executive system and ensures the steady-state characteristics of the system output.