Research On Control Technology Of Switched Reluctance Motor For Robot Joints

The switched reluctance motor(SRM),as a new type of speed-regulating motor,has a wide range of application prospects in the field of robot joints due to its high torque,wide speed range,low starting current,low cost,and simple structure.Since the robot joints have high requirements on the response speed and output stability of the servo system,simultaneously,the SRM has the problem of large nonlinearity of the motor model caused by its own structure,it is necessary to establish a suitable SRM model and optimize the control algorithm to make the SRM’s response speed and output stability meet the servo system requirements of robot joints.The specific research work is as follows:Firstly,to solve the problem of inaccurate servo system control results caused by the low accuracy of the existing SRM simulation model,this thesis uses the Motor Solve’s finite element analysis to simulate the operation data of the SRM,and utilize the Cerebellar Model Articulation Controller(CMAC)to obtain the nonlinear model of the current-position angle-inductance and current-position angle-torque of the motor by using the simulation data and actual measurement data of the motor as training samples.Then,based on nonlinear models,a speed control simulation model of 12/8 SRM is built on the MATLAB/Simulation platform.By comparing the simulation results with the actual operation results of the motor,it shows that the current value of each phase winding and its change trend obtained by the simulation operation are consistent with the actual operation of the motor,which verifies the feasibility of this method for nonlinear modeling of SRM.The SRM model are used in the follow-up servo control research.Secondly,based on the speed control simulation of SRM,a Current chopping control(CCC)-cascade Proportional Integral Derivative(PID)SRM servo control simulation system is built.To improve the control effect of the SRM servo control system,based on fuzzy control theory,this thesis designs a fuzzy controller whose input is the SRM position and position change rate,and the output is the expected torque.And a servo system is built in Matlab/Simulink whose position loop is fuzzy control,and current loop is CCC.To reduce the torque ripple and improve the output stability of the servo control system,a predictive control model of the current change rate is designed based on the predictive control theory.This method improves the current following accuracy by predictively controlling the PWM duty cycle of each phase.The results show that this system is better than the CCC control system,the adjustment time is shortened by 0.03 s,the overshoot is reduced by 2.96%,and the torque fluctuation coefficient is reduced by4.45%.Finally,an experimental platform which uses the digital signal processor(DSP)as controller unit is built to verify the applicability of the above simulation model.The performance of the servo control system of SRM in different control modes is compared.It verifies the feasibility of position fuzzy control servo system based on predictive current control in robot joints.