[1]郭一,刘金琨.带执行器饱和的柔性关节机器人位置反馈动态面控制[J].智能系统学报,2013,8(01):21-27.[doi:10.3969/j.issn.1673-4785.201204012]
 GUO Yi,LIU Jinkun.Position feedback dynamic surface control for flexible joint robots with actuator saturation[J].CAAI Transactions on Intelligent Systems,2013,8(01):21-27.[doi:10.3969/j.issn.1673-4785.201204012]
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带执行器饱和的柔性关节机器人位置反馈动态面控制(/HTML)
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第8卷
期数:
2013年01期
页码:
21-27
栏目:
出版日期:
2013-03-25

文章信息/Info

Title:
Position feedback dynamic surface control for flexible joint robots with actuator saturation
文章编号:
1673-4785(2013)01-0021-07
作者:
郭一刘金琨
北京航空航天大学 自动化科学与电气工程学院,北京 100191
Author(s):
GUO Yi LIU Jinkun
School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
关键词:
柔性关节机器人动态面控制执行器饱和神经网络观测器
Keywords:
flexible joint robots dynamic surface control actuator saturation neural network observer
分类号:
TP24
DOI:
10.3969/j.issn.1673-4785.201204012
文献标志码:
A
摘要:
针对带有执行器饱和的柔性关节机器人系统,提出一种位置反馈动态面控制,以实现机器人连杆的角位置跟踪.在一般动态面控制的设计框架下,设计观测器重构系统未知速度状态,利用径向基函数神经网络学习饱和非线性特性,结合“最小参数学习”算法减轻计算负担.通过Lyapunov方法证明得出闭环系统所有信号半全局一致有界,跟踪误差可以通过调节控制器参数达到任意小.仿真结果表明,控制系统能够克服外界干扰,有效补偿系统存在的执行器饱和,实现柔性关节机器人的准确跟踪控制.该方法避免了传统反演设计存在的“微分爆炸”现象,简化了设计过程.
Abstract:
The research explored the compensation of flexiblejoint robot′s actuator saturation using a dynamic surface controller for tracking control of link position. Under the design of a general dynamic surface control, an observer was designed to aid in the estimation of unknown velocity states. Radical basis function (RBF) neural network was used to examine saturation nonlinearity and “minimal learning parameter”technique for the reduction of computational burden. Based on the Lyapunov stability analysis, it was shown that the control strategy could guarantee the semi global stability of the closed loop system and arbitrarily small tracking error by adjusting the controller parameters. The simulation results indicated that the proposed control system may overcome the external disturbances, compensate for the existing actuator saturation of systems effectively, and realize more accurate tracking control for flexible joint robots. The proposal eliminates the problem of “explosion of complexity” existing in traditional backstepping approaches and simplifies controller design procedures plainly.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2012-04-18.
网络出版日期:2013-01-15.
基金项目:教育部高等学校博士学科点专项科研基金资助项目(20121102110008).
通信作者:郭一.
E-mail: guoyiandy@yahoo.cn.
作者简介:
郭一,男,1988年生,硕士研究生,主要研究方向为动态面控制与智能控制.
刘金琨,男,1965年生,教授,博士生导师.主要研究方向为智能控制、机器人控制和电机控制等.曾主持国家自然科学基金、航空基金等项目12项.发表学术论文90余篇,其中被EI检索20余篇,出版专著4部.
更新日期/Last Update: 2013-04-12