Study On Performance Optimization Of Six-axis Industrial Robot Servo System

When the six-axis industrial robot is disturbed by external load in the running process,the motor of each axis will occasionally oscillate and resonate,which affects the normal operation of the robot and the production quality of the whole product.The results of the experiment show that the main problem is that the performance of the servo system can not meet the performance of the robot.Firstly,the control model of PMSM is established,and the principle of vector control is introduced to build the load inertia model of PMSM.When the robot run,due to the changes of the attitude and position at the end,make robot moment of inertia of the axial load and real-time change,if a robot in the movement process of the external disturbance,will cause the robot's axis servo system can't fast and accurate identification load moment of inertia,the parameters of the servo control system and the actual motor load parameters cannot be accurately match,prone to lead to robots each axis motor range,resonance phenomenon.Then,a particle swarm optimization algorithm based on nonlinear dynamic learning factor is proposed to identify the moment of inertia of the servo system.This algorithm takes the speed controller in the servo control model as the core,identifies the load moment of inertia in real time,and makes the internal control parameters of the servo system adjust according to the actual conditions.By using the identification value,the velocity control PI parameter value is calculated,and the velocity loop controller PI parameter value is corrected in real time.MATLAB/SIMULINK simulation results show that,compared with the traditional particle swarm optimization algorithm,the servo system using the improved method has faster response speed,higher control accuracy and stronger anti-interference ability,whether in the motor startup process or under load disturbance.Finally,based on the industrial robot platform,the performance of the servo drive device is verified,the improved algorithm is transplanted to the servo drive hardware platform,and the improved servo system is applied to the robot servo control system.Based on the experimental platform built by industrial robots,the uniaxial variable load experiment and the terminal variable load walking trajectory experiment were designed.The feasibility of the improvement scheme of servo system was verified through experiments,which reduced the momentum of the maximum wave of position error of the robot's walking trajectory from ±10mm to ±3mm.In other words,the improved servo system enables the robot to have better stability,stronger anti-disturbance ability and higher trajectory precision when running under variable load disturbance.