计算机工程

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基于预测型间接迭代学习的SCARA机器人轨迹跟踪控制

严浩,白瑞林,朱朔   

  1. (江南大学 轻工过程先进控制教育部重点实验室,江苏 无锡 214122)
  • 收稿日期:2016-08-01 出版日期:2017-10-15 发布日期:2017-10-15
  • 作者简介:严浩(1992—),男,硕士研究生,主研方向为机器人控制技术;白瑞林,教授、博士生导师;朱朔,硕士研究生。
  • 基金项目:
    江苏省产学研前瞻性联合研究项目(BY2015019-38);江苏高校优势学科建设工程项目(PAPD)。

Trajectory Tracking Control of SCARA Robot Based on Anticipatory-type Indirect Iterative Learning

YAN Hao,BAI Ruilin,ZHU Shuo   

  1. (Key Laboratory of Advanced Process Control for Light Industry,Ministry of Education,Jiangnan University,Wuxi,Jiangsu 214122,China)
  • Received:2016-08-01 Online:2017-10-15 Published:2017-10-15

摘要: SCARA机器人是一个强耦合、多输入多输出的非线性系统,运行时较易受外界干扰的影响,而且传统比例-积分-微分(PID)反馈控制器的轨迹跟踪精度较低。针对上述问题,设计具有前馈作用的预测型迭代学习控制器(A-ILC)。利用运行批次在采样时刻t+Δ处的误差输出信息,优化调整下次运行在采样时刻t处双闭环PID反馈控制器的角度。仿真结果表明,与仅采用双闭环PID反馈控制器相比,采用所设计的控制器能明显减小机器人末端的轨迹跟踪误差。

关键词: 机器人, 双闭环, 反馈控制器, 迭代学习, 轨迹跟踪

Abstract: SCARA robot is a strong coupling,multi-input and multi-output nonlinear system,which is easy to be affected by outside interference when running,and the traditional Proportional-Integra-Derivative(PID) feedback controller leads to low trajectory tracking accuracy.To solve this problem,an Anticipatory-type Iterative Learning Controller(A-ILC) with feedforward function is designed,which utilizes the previous cycle output tracking error at moment t+Δ to adjust the angle reference of the double-loop PID feedback controller in next cycle at moment t.Simulation results show that compared with the double closed loop PID feedback controller,the designed controller can significantly reduce the trajectory tracking error at the end of the robot.

Key words: robot, double closed loop, feedback controller, iterative learning, trajectory tracking

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