Research On Parameter Identification And Control Of Permanent Magnet Synchronous Motor For Industrial Robot

The parameter identification and control of permanent magnet synchronous motor(PMSM)is a hot spot in the motion control technology of industrial robot servo system.This paper firstly analyzes the background and significance of the research,compares the performance of common servo motors,expounds the advantages of the PMSM and the trend of the development of the servo system.Then introduces the status of the research of PMSM parameter identification and the research of the sensorless sensor control,and introduces the composition and main contents of this paper.This paper introduces the principle of common coordinate transformation under the vector control of PMSM,gives the mathematical model of the motor under different coordinate systems,expounds the principle of vector control of PMSM and the common control method,introduces the principle of voltage feed-forward decoupling control,and builds the voltage feed-forward decoupling vector control simulation,the simulation results are given and analyzed.The parallel chaotic optimization algorithm(PCOA)is introduced in this paper.Then,the multi parameter identification of PMSM based on PCOA is studied.The effect of parameter identification is analyzed by two indexes of absolute error and relative error,and the effect of identification is analyzed by comparing the actual PMSM model and identifying PMSM model.Finally,change the relevant parameters,identify and contrast again,prove the usability of the scheme.Aiming at the demand of PMSM sensorless control performance,an improved model reference adaptive(MRAS)sensorless control is used to expand the speed range and the simulation is carried out.Firstly,the MRAS theory of motor is briefly introduced.The PMSM sensorless control based on MRAS is designed by Popov super stability theory.Secondly,the real-time estimation speed is introduced to adjust the parameters of PI to optimize the estimation effect when changing the given speed.Finally,The effectiveness and feasibility of the improved algorithm is verified by comparing the results of simulation.