工业机器人的小脑模型控制

本文为动力学控制工业机器人提出了一种综合学习算法,这种学习算法可将以前所学的信息用于新的控制输入.这种控制方法不需要事先知道机器人动力学,它易于应用于特殊的控制问题或修改以适应实际系统中的变化,控制方法在时间上是有效的,且很适合于定点实现.学习控制算法的有效性通过4自由度的直接驱动机器人前两个关节在重复运动中的计算机仿真实验得到了验证.

In this paper,a general learning algorithm for dynamic control of robot manipulator is proposed.In this al-gorithm,information learned previously can be applied to new control objectives as long as similar regions ofthe system state space are involved.The control scheme requires no prior knowledge of the robot dynamics sothat it is easy to be used to solve a particular control problem or to be modified to accommodate changes inthe physical system.The control scheme is computationally efficient and well suited to fixed-point implemen-tation.The effectiveness of the learning algorithm is verified by the computer simulation experiment of repet-itive movements of two fore arms of 4 DOFs direct drive robot manipulator.