直角坐标机器人轮廓误差补偿算法设计

Design of Contour Error Compensation Algorithm for Cartesian Coordinate Robot

为提高直角坐标机器人控制精度,结合迭代学习控制和交叉耦合控制设计了一种轮廓误差补偿算法。在单轴数学模型的基础上,搭建了直角坐标机器人轮廓误差模型。根据不同控制方法的特点,结合反馈控制、单轴迭代学习控制、双轴交叉耦合控制和轮廓误差迭代学习控制设计了一种控制器。直角坐标机器人的控制系统以ARM和FPGA为核心,其中,ARM主要用于传感器信号采集、上位机通信、故障检测和机器人运动轨迹规划等;FPGA则可实现伺服电机的控制。实验结果表明:轮廓误差平均值、最大值和标准偏差均大幅降低;迭代学习交叉耦合控制能够大幅降低轮廓误差,有效提高直角坐标机器人运动精度。

In order to improve the control accuracy of cartesian coordinate robot,a contour error compensation algorithm is designed combining iterative learning control and cross coupling control.Based on the uniaxial mathematical model,the contour error model of cartesian coordinate robot is established.According to the characteristics of different control methods,a controller is designed by combining feedback control,uniaxial iterative learning control,biaxial cross coupling control and contour error iterative learning control.The control system of cartesian coordinate robot takes ARM and FPGA as the core.ARM is mainly used for sensor signal acquisition,upper computer communication,fault detection,robot trajectory planning,etc.FPGA can realize servo motor control.The experimental results show that the mean value,maximum value and standard deviation of contour error are greatly reduced.Iterative learning cross coupling control can greatly reduce the contour error and effectively improve the motion accuracy of cartesian coordinate robot.