Computer Engineering and Applications ›› 2021, Vol. 57 ›› Issue (3): 261-265.DOI: 10.3778/j.issn.1002-8331.1911-0243

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Iterative Learning Control of Industrial Robot with Arbitrary Initial State

XI Xiaojian   

  1. School of Science, Xijing University, Xi’an 710123, China
  • Online:2021-02-01 Published:2021-01-29

任意初态下的工业机器人迭代学习控制

惠小健   

  1. 西京学院 理学院,西安 710123

Abstract:

A nonlinear iterative learning control algorithm based on sliding surface is proposed for the trajectory tracking control system of industrial robot with arbitrary initial value, which enables the robot trajectory to track the desired trajectory quickly and accurately. Based on the principle of finite time convergence, an iterative sliding surface about the trajectory tracking error is constructed. In the sliding surface, the trajectory tracking error of robot converges to zero in a predetermined time. An iterative learning control algorithm based on the sliding surface is designed. It is proved that with the increase of iteration times, the trajectory in arbitrary initial state will converge to the sliding surface uniformly, and arbitrary initial value problem is solved in learning. The effectiveness and anti-jamming ability of the algorithm are verified by numerical simulation.

Key words: robot, trajectory tracking, iterative learning control, sliding mode control, finite time control

摘要:

对迭代初值为任意值的工业机器人轨迹跟踪控制系统,提出了一种基于滑模面的非线性迭代学习控制算法,使机器人轨迹能快速、精确跟踪上期望轨迹。基于有限时间收敛原理,构建了关于机器人轨迹跟踪误差的迭代滑模面,在滑模面内,机器人轨迹跟踪误差在预定时间内收敛到零。设计了基于滑模面的迭代学习控制算法,理论证明了随着迭代次数的增加,处于任意初态的轨迹将一致收敛到滑模面内,解决了迭代学习中的任意初值问题。数值仿真验证了该算法的有效性和抗干扰能力。

关键词: 机器人, 轨迹跟踪, 迭代学习控制, 滑模控制, 有限时间控制