Research On Speed Adaptive Control Of SRM

Due to the strong coupling and nonlinear characteristics of switched reluctance motor(SRM),the general linear control method for switched reluctance motor has great limitations.As the main controller of the motor control system,the speed regulator plays an important role in the stable and efficient operation of the whole drive system.Aiming at this key technical problem,this paper takes the vehicle SRM as the research object,focuses on the optimization and improvement of the speed regulator in the switched reluctance motor drive system,and proposes two speed adaptive control methods of fuzzy auto disturbance rejection and single neuron PID.At the same time,combined with the torque inner loop,it aims to improve the robustness and anti-interference ability of the switched reluctance motor drive system.Firstly,this paper analyzes the development prospect of SRM for electric vehicles,introduces the basic structure and working principle of switched reluctance motor,the common modeling methods and conventional control methods and their application scope.Secondly,the speed torque double closed-loop system is constructed.The direct instantaneous torque hysteresis control method is used in the inner torque loop,which can effectively reduce the torque ripple of the motor.Thirdly,two kinds of adaptive speed regulators are built.Firstly,according to the characteristics of ADRC,an ADRC speed regulator composed of tracking differentiator,extended state observer and nonlinear feedback control rate is built for switched reluctance motor(SRM).However,due to the many control parameters of ADRC,it is difficult to adjust.In this paper,combined with the idea of fuzzy control,it is applied to the parameter self-tuning of ADRC speed regulator,which reduces the parameter adjustment and improves the adaptive ability of the regulator;at the same time,according to the characteristics of neural network for nonlinear control object,combined with the control requirements of motor itself,a single neuron PID speed regulator is constructed,which can self-learning neural network The combination of self-tuning and PID control ensures the timeliness of motor control and improves the adaptive ability.Finally,according to the above simulation model,the control system of switched reluctance motor drive system with STM32 chip as the core is designed,mainly focusing on circuit design and device selection...