PID参数对机器人在线力补偿的影响
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摘要
工业串联机器人的定位精度尤其是绝对定位精度较低,使其在高精度制造领域受到较大的限制,因此设计机器人受力在线补偿系统以提高其绝对定位精度。该系统基于KUKA机器人的RSI接口,通过测量机器人末端受力值,结合机器人的刚度矩阵计算误差,对机器人进行在线补偿,为了改善性能,将基于PID算法的补偿算法加入控制系统中。最后分别分析了比例环节、积分环节、微分环节的补偿效果。实验结果表明,比例环节有较好的补偿效果,而积分、微分环节对补偿效果没有改善;同时,调节比例系数,可以得到最好的补偿效果,在本系统中,当比例系数为4.0时为最优,此时,补偿效果达到40.5%。
The positioning accuracy,especially the absolute positioning accuracy of the industrial serial robot,is low,so it is limited in the field of high precision manufacturing. Therefore,an online force compensation system is designed to improve its absolute positioning accuracy. The system is based on the robot sensor interface( RSI) of KUKA robot. It can calculate the error by measuring the force value of robot end and using the stiffness matrix of robot,and compensate robot online. In order to improve the performance,an algorithm based on PID algorithm is added to the control system. Finally,the effect of proportional component,integration component and differentiation component is analyzed respectively. The result shows that the proportional component is effective,while the other two is ineffective. Besides,the better compensation effect can be gotten by adjusting proportional coefficient. In this system,when P = 4. 0,the effect is the best and it can be up to 40. 5%.
The positioning accuracy,especially the absolute positioning accuracy of the industrial serial robot,is low,so it is limited in the field of high precision manufacturing. Therefore,an online force compensation system is designed to improve its absolute positioning accuracy. The system is based on the robot sensor interface( RSI) of KUKA robot. It can calculate the error by measuring the force value of robot end and using the stiffness matrix of robot,and compensate robot online. In order to improve the performance,an algorithm based on PID algorithm is added to the control system. Finally,the effect of proportional component,integration component and differentiation component is analyzed respectively. The result shows that the proportional component is effective,while the other two is ineffective. Besides,the better compensation effect can be gotten by adjusting proportional coefficient. In this system,when P = 4. 0,the effect is the best and it can be up to 40. 5%.
引文
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[17]王智源,朱刚.测定工业机器人位置特性的误差不确定度分析[J].电子测量技术,2016,39(9):8-11.WANG ZH Y,ZHU G.Study on uncertainty evaluation of industrial robot position characteristic[J].Electronic Measurement Technology,2016,39(9):8-11.
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[2]史晓佳,张福民,曲兴华,等.KUKA工业机器人位姿测量与在线误差补偿[J].机械工程学报,2017,53(8):1-7.SHI X J,ZHANG F M,QU X H,et al.Position and attitude measurement and online errors compensation for KUKA industrial robots[J].Journal of Mechanical Engineering,2017,53(8):1-7.
[3]李睿,曲兴华.工业机器人运动学参数标定误差不确定度研究[J].仪器仪表学报,2014,35(10):2192-2199.LI R,QU X H.Study on calibration uncertainly of industrial robot kinematic parameters[J].Chinese Journal of Scientific Instrument,2014,35(10):2192-2199.
[4]SHI X J,ZHANG F M,QU X H,et al.An online realtime path compensation system for industrial robots based on laser tracker[J].International Journal of Advanced Robotic System,2016,13(5):1-14.
[5]NUBIOLA A,BONEV I A.Absolute calibration of an ABB IRB 1600 robot using a laser tracker[J].Robotics and Computer-Integrated Manufacturing,2013,29(1):236-245.
[6]刘本德.基于D-H参数精确标定的工业机器人关节刚度辨识[D].天津:天津大学,2014:39-43.LIU B D.Joint stiffness identification of industrial robot based on accurate calibration of D-H parameters[D].Tianjin:Tianjin University,2014:39-43.
[7]ZHANG H,WANG J J,ZHANG G,et al.Machining with flexible manipulator:toward improving robotic machining performance[C].International Conference on Advanced Intelligent Mechatronics,2005:1127-1132.
[8]刘柏灵.基于在线位姿测控系统的工业机器人定位精度优化[D].天津:天津大学,2016:25-40.LIU B L.Research on improving the accuracy of industrial robot based on online pose measurement system[D].Tianjin:Tianjin University,2016:25-40.
[9]QIN J N,LEONARD F,ABBA G.Real-time trajectory compensation in robotic friction stir welding using state estimators[J].IEEE Transactions on Control Systems Technology,2016,24(6):2207-2214.
[10]朱坚民,沈正强,李孝茹,等.基于神经网络反馈补偿控制的磁悬浮球位置控制[J].仪器仪表学报,2014,35(5):976-986.ZHU J M,SHEN ZH Q,LI X R,et al.Magnetic levitation ball position control based on neural network feedback compensation control[J].Chinese Journal of Scientific Instrument,2014,35(5):976-986.
[11]张召瑞,张旭,郑泽龙,等.融合旋转平移信息的机器人手眼标定方法[J].仪器仪表学报,2015,36(11):2443-2450.ZHANG ZH R,ZHANG X,ZHENG Z L,et al.Handeye calibration method fusing rotational and translationalconstraint information[J].Chinese Journal of Scientific Instrument,2015,36(11):2443-2450.
[12]谢宏,杨鹏,陈海滨,等.遗传优化模糊PID融合算法的5自由度机械手控制[J].电子测量与仪器学报,2015,29(1):21-30.XIE H,YANG P,CHEN H B,et al.Fuzzy PID control system optimized by genetic algorithm for 5-freedom robot arm[J].Journal of Electronic Measurement and Instrumentation,2015,29(1):21-30.
[13]侯鹏辉.机器人加工系统刚度性能优化研究[D].杭州:浙江大学,2013:39-45.HOU P H.Study on the stiffness performance optimization for robot machining system[D].Hangzhou:Zhejiang University,2013:39-45.
[14]周美丽,白宗文.基于2D-PSD的激光位移测量系统设计[J].国外电子测量技术,2015,34(2):64-66.ZHOU M L,BAI Z W.Design of the laser displacement measurement system based on 2 D-PSD[J].Foreign Electronic Measurement Technology,2015,34(2):64-66.
[15]CHEN T C,CHANG C J,HUNG J P,et al.Real-time compensation for thermal errors of the milling machine[J].Applied Sciences,2016,6(4):1-13.
[16]郑红梅,刘正士.机器人六维腕力传感器动态性能标定系统的研究[J].电子测量与仪器学报,2006,20(3):88-92.ZHENG H M,LIU ZH SH.Research on the dynamic performance calibration system for robot’s 6-axis wrist force sensor[J].Journal of Electronic Measurement and Instrument,2006,20(3):88-92.
[17]王智源,朱刚.测定工业机器人位置特性的误差不确定度分析[J].电子测量技术,2016,39(9):8-11.WANG ZH Y,ZHU G.Study on uncertainty evaluation of industrial robot position characteristic[J].Electronic Measurement Technology,2016,39(9):8-11.
[18]YOSHIOKA T,PHUONG T T,YABUKI A,et al.Highperformance load torque compensation of industrial robot using Kalman-filter-based instantaneous state observer[J].Journal of Industry Applications,2015,4(5):589-590.