机器人曲面抛光末端VCM力迭代学习控制研究

Research on Iterative Learning Control of VCM Force at the End of Robot Surface Polishing

针对曲面元件机器人抛光过程中的柔顺控制和响应速度问题,研究一套机器人抛光柔顺控制系统。采用切片算法完成抛光轨迹规划以控制机器人顺应曲面元件表面低频段轮廓与曲率变化,设计一种力控末端执行器达到主动力输出和高速响应要求,提出基于迭代学习控制的电流迭代优化控制策略使执行器中音圈电机输出力以高精度跟随目标力,减小元件表面中高频段波纹度与表面粗糙度。搭建以机器人、力控执行器、六维力传感器、运动控制卡为核心部件的实验平台。仿真与实验结果证明所设计柔顺控制系统力控性能良好,力平均响应时间为55.4 ms,力跟踪误差小于3 N,能够满足曲面元件抛光加工需求。

Aiming at the problem of compliance control and response speed in robot polishing of curved surface components,a set of compliance control system for robot polishing was studied.The slicing algorithm was used to complete the polishing trajectory planning to control the robot to comply with the low-frequency profile and curvature changes of the surface of curved components.A force controlled end effector was designed to meet the requirements of active force output and high-speed response.The current iterative optimization control strategy based on iterative learning control was proposed to make the output force of voice coil motor in the actuator follow the target force with high accuracy,reducing the waviness and surface roughness of the high-frequency segment of the surface of components.An experimental platform with robots,force control actuators,six dimensional force sensors and motion control cards as the core components was built.The simulation and experimental results show that the designed compliance control system has good force control performance,the average force response time is 55.4 ms,and the force tracking error is less than 3 N,which can meet the needs of surface component polishing.