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Songthumjitti et al. Intell Robot 2023;3(3):306-36 Intelligence & Robotics
DOI: 10.20517/ir.2023.20

Research Article Open Access

Stability compensation of an admittance-controlled carte-
sian robot considering physical interaction with a hu-

man operator

1
Narawich Songthumjitti , Takeshi Inaba 2
1 Course of Electrical and Electronic Engineering, Graduate School of Tokai University, Kanagawa 259-1292, Japan.
2 Department of Applied Computer Engineering, School of Information Science and Technology, Tokai University, Kanagawa 259-1292,
Japan.
Correspondence to: Prof. Takeshi INABA, Department of Applied Computer Engineering, School of Information Science and
Technology, Tokai University, Kanagawa 259-1292, Japan. E-mail: inaba@tokai.ac.jp
How to cite this article: Songthumjitti N, Inaba T. Stability compensation of an admittance-controlled cartesian robot considering
physical interaction with a human operator. Intell Robot 2023;3(3):306-36. http://dx.doi.org/10.20517/ir.2023.20

Received: 29 Mar 2023 First Decision: 30 May 2023 Revised: 13 Jun 2023 Accepted: 3 Jul 2023 Published: 25 Jul 2023

Academic Editors: Simon X. Yang, Jinhua She Copy Editor: Yanbin Bai Production Editor: Yanbin Bai

Abstract
In human-machine systems, admittance control is widely used for controlling robots. However, the problem with this
method is that the stability can be impacted by the stiffness of the machine and the human operator. In order to
minimize the oscillation issue that is caused by insufficient structure stiffness, this study used compensation meth-
ods, specifically feed-forward and acceleration feedback. Simulation results show that both compensation methods
can expand the stability region of the system. Nevertheless, feedback compensation is more appropriate than feed-
forward when taking into account uncertainties in the structure parameters of the system. Even when the system is
not perfectly implemented, feedback compensation can keep the system stable, whereas feed-forward compensation
causes a significantly reduced stability region. From the experiment, it is also confirmed that the feedback system
has an advantage over the feed-forward system, and this simple feedback using an accelerometer can compensate
for the insufficient stiffness of the robot structure and greatly enhance the stability of the human-machine system.

Keywords: Human-machine system, admittance model, system stability, compensator, feed-forward, feedback

© The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0
International License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, shar-
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