机器人系统非线性分散重复学习轨迹跟踪控制

田慧慧; 苏玉鑫

doi:10.3724/SP.J.1004.2011.01264

机器人系统非线性分散重复学习轨迹跟踪控制

doi: 10.3724/SP.J.1004.2011.01264

田慧慧^,,
苏玉鑫

1.
西安电子科技大学机电工程学院西安 710071

详细信息

通讯作者:
田慧慧西安电子科技大学机电工程学院博士研究生. 主要研究方向为机器人控制和重复学习控制. E-mail: yezifairy@163.com

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出版历程
- 收稿日期: 2011-03-04
- 修回日期: 2011-05-17
- 刊出日期: 2011-10-20

Nonlinear Decentralized Repetitive Control for Global Asymptotic Tracking of Robot Manipulators

TIAN Hui-Hui^,,
SU Yu-Xin

1.
School of Electro-Mechanical Engineering, Xidian University, Xi'an 710071

摘要

摘要: 采用一类具有"小误差放大、大误差饱和"功能的非线性饱和函数来改进传统重复学习控制(Repetitive control, RC)机器人系统动力学控制, 形成一类新的非线性分散重复学习控制(Nonlinear decentralized repetitive control, NRC),使得在不增加驱动力矩的条件下获得了更快的响应速度和更高的轨迹跟踪精度. 应用Lyapunov直接稳定性理论和LaSalle不变性原理证明了闭环系统的全局渐近稳定性. 三自由度机器人系统数值仿真结果表明了所提出的非线性分散重复学习控制具有良好的控制品质.
- 机器人控制 /
- 轨迹跟踪 /
- 重复学习控制 /
- 分散控制 /
- 全局渐近稳定性
Abstract: A new kind of nonlinear decentralized repetitive control (NRC) for robot manipulators is proposed to give faster response and higher tracking precision over the commonly used repetitive control (RC) without increased torque. The proposed NRC is formulated with a class of nonlinear saturated functions with the characteristics of "enlargement of small error and saturated in large error". The global asymptotic stability of the resulting closed-loop system is proved by the Lyapunov's direct method and LaSalle invariance principle. The simulation results on a three degree-of-freedom robot illustrate the effectiveness and improved performance of the proposed controller.
- Robot control /
- tracking control /
- repetitive control (RC) /
- decentralized control /
- global asymptotic stability

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参考文献(1)

[1]

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