Robotic manipulators with double encoders: accuracy improvement based on advanced stiffness modeling and intelligent control

被引：27
作者：
Klimchik, A. [1 ]
Pashkevich, A. [1 ,2 ]
机构：
[1] Innopolis Univ, Univ Skaya 1, Innopolis 420500, Republic Of Tat, Russia
[2] IMT Atlantique, Lab Sci Numer Nantes LS2N, 4 Rue Alfred Kastler, F-44307 Nantes, France
来源：
IFAC PAPERSONLINE | 2018年 / 51卷 / 11期
基金：
俄罗斯科学基金会;
关键词：
Robotic manipulator; double encoders; stiffness modeling; parameter identification; compliance error compensation; IDENTIFICATION; PARAMETERS;
D O I：
10.1016/j.ifacol.2018.08.407
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The paper deals with advanced stiffness modeling and intelligent control of industrial robots with double encoders. In contrast to previous works that concentrate on the actuator compliance compensation, this work is aimed at reduction of the compliance errors produced by all manipulator components. Particular attention is paid to the identifiability of the stiffness model parameters using a combination of the tool location measurements and information from double encoders integrated into the actuated joints. For the considered architecture, new strategies for intelligent compliance error compensation are proposed. The developed techniques were applied to the stiffness modeling and accuracy improvement of a typical industrial robotic manipulator, for which the impact of external loading and gravity on the positioning accuracy was essentially reduced. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
引用
收藏
页码：740 / 745
页数：6
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