Frequency-Shaped Impedance Control for Safe Human-Robot Interaction in Reference Tracking Application

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In the control of industrial robots, both safety and reference tracking performance are required. For safe human-robot interaction, robots should exhibit low mechanical (or controlled) impedance so that they react to the interaction forces in a compliant manner. On the other hand, the reference tracking requires for the robots to reject exogenous disturbances, which results in an increased impedance. In order to achieve these two conflicting objectives, a frequency-shaped impedance control (FSIC) method is proposed in this paper. The proposed method utilizes the two different functionalities of the disturbance observer (DOB): a disturbance estimation function as an observer and a disturbance rejection function as a feedback controller. Namely, the DOB is utilized as an observer at the frequencies where the robots interact with humans, while it is used as a feedback controller (i.e., disturbance rejection controller) at the frequencies where the reference tracking is required. The proposed approach is realized by shaping a filter of the DOB in the frequency domain so that the impedance is manipulated to achieve both the compliant interaction and reference tracking. The compromised reference tracking performance in the frequency range, where the impedance is set low, can also be supplemented by feedforward control. A typical feedback controller and a feedforward controller are designed in addition to the DOB-controlled system as the whole control system to enhance reference tracking performance and the betterment of stability robustness. The proposed method is verified by experimental results in this paper.
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date
2014-12
Language
English
Article Type
Article
Citation

IEEE-ASME TRANSACTIONS ON MECHATRONICS, v.19, no.6, pp.1907 - 1916

ISSN
1083-4435
DOI
10.1109/TMECH.2014.2309118
URI
http://hdl.handle.net/10203/250048
Appears in Collection
ME-Journal Papers(저널논문)
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