吉林大学学报(工学版) ›› 2012, Vol. 42 ›› Issue (02): 469-475.

• 论文 • 上一篇    下一篇

可重构机械臂分散自适应迭代学习控制

李元春1, 朱路2, 董博2, 刘克平1   

  1. 1. 长春工业大学 控制工程系, 长春 130012;
    2. 吉林大学 汽车仿真与控制国家重点实验室, 长春 130022
  • 收稿日期:2010-12-06 出版日期:2012-03-01 发布日期:2012-03-01
  • 通讯作者: 朱路(1985-),男,硕士研究生.研究方向:模块机器人运动学、动力学和控制方法. E-mail:zhulu08@mails.jlu.edu.cn E-mail:zhulu08@mails.jlu.edu.cn
  • 作者简介:李元春(1962-),男,教授,博士生导师.研究方向:复杂系统建模与优化,机器人控制. E-mail:liyc@mail.ccut.edu.cn
  • 基金资助:

    国家自然科学基金项目(60974010,60674091);吉林省科技发展计划项目(20110705).

Decentralized adaptive iterative learning control for reconfigurable manipulators

LI Yuan-chun1, ZHU Lu2, Dong Bo2, LIU Ke-ping1   

  1. 1. Department of Control Engineering, Changchun University of Technology, Changchun 130012, China;
    2. State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China
  • Received:2010-12-06 Online:2012-03-01 Published:2012-03-01

摘要: 基于Lyapunov稳定性理论和Backstepping技术,提出了一种可重构机械臂分散自适应迭代学习控制方法。将可重构机械臂动力学系统描述为一个交联子系统的集合,基于Backstepping技术,给出自适应迭代学习控制方法。为了补偿系统模型不确定项和子系统之间交联项,采用自适应神经网络进行逼近。最后,通过数值仿真验证了所提方法的有效性。

关键词: 自动控制技术, 可重构机械臂, 神经网络, 迭代学习控制, Backstepping技术

Abstract: Based on Lyapunov stability theory and Backstepping technology, a decentralized adaptive iterative learning control algorithm for reconfigurable manipulators was proposed. The dynamics of the reconfigurable manipulators was represented as a set of interconnected subsystems. An adaptive iterative learning control method based on backstepping technology was proposed. Adaptive neural network was introduced to compensate the unknown term and the interconnection term of each subsystem. Simulation examples were presented to demonstrate the effectiveness of the proposed decentralized controller.

Key words: automatic control technology, reconfigurable manipulator, neural network, iterative learning control, Backstepping design

中图分类号: 

  • TP273
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