Improving experiment design for frequency-domain identification of industrial robots

被引:2
|
作者
Zimmermann, S. A. [1 ]
Enqvist, M. [1 ]
Gunnarsson, S. [1 ]
Moberg, S. [2 ]
Norrlof, M. [2 ]
机构
[1] Linkoping Univ, Dept Elect Engn, S-58183 Linkoping, Sweden
[2] ABB Robot, S-72136 Vasteras, Sweden
来源
IFAC PAPERSONLINE | 2022年 / 55卷 / 37期
关键词
Closed-loop identification; frequency-domain; nonlinear systems; industrial robots; optimal experiment design; covariance matrices;
D O I
10.1016/j.ifacol.2022.11.228
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
For accurate control of industrial robots, a fast and easy-to-use method to estimate the model parameters based on experimental data is desired. This publication is about optimal experiment design in terms of short experiment times and an accurate parameter estimate. An optimization problem that is based on information matrices is solved for finding the optimal robot configurations for the identification experiment. A simulation study shows that the experiment time can be reduced significantly and the accuracy of the parameter estimate can be increased if experiments are conducted only in the optimal manipulator configurations. Furthermore, it is shown that a realistic estimate of the uncertainty in the frequency response function is crucial for successful experiment design. Copyright (c) 2022 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0)
引用
收藏
页码:475 / 480
页数:6
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