Adaptive fractional-order admittance control for force tracking in highly dynamic unknown environments
ISSN: 0143-991x
Article publication date: 1 February 2023
Issue publication date: 13 April 2023
Abstract
Purpose
With the increasing demands of industrial applications, it is imperative for robots to accomplish good contact-interaction with dynamic environments. Hence, the purpose of this research is to propose an adaptive fractional-order admittance control scheme to realize a robot–environment contact with high accuracy, small overshoot and fast response.
Design/methodology/approach
Fractional calculus is introduced to reconstruct the classical admittance model in this control scheme, which can more accurately describe the complex physical relationship between position and force in the interaction process of the robot–environment. In this control scheme, the pre-PID controller and fuzzy controller are adopted to improve the system force tracking performance in highly dynamic unknown environments, and the fuzzy controller is used to improve the trajectory, transient and steady-state response by adjusting the pre-PID integration gain online. Furthermore, the stability and robustness of this control algorithm are theoretically and experimentally demonstrated.
Findings
The excellent force tracking performance of the proposed control algorithm is verified by constructing highly dynamic unstructured environments through simulations and experiments. In simulations and experiments, the proposed control algorithm shows satisfactory force tracking performance with the advantages of fast response speed, little overshoot and strong robustness.
Practical implications
The control scheme is practical and simple in the actual industrial and medical scenarios, which requires accurate force control by the robot.
Originality/value
A new fractional-order admittance controller is proposed and verified by experiments in this research, which achieves excellent force tracking performance in dynamic unknown environments.
Keywords
Acknowledgements
This research was funded by the Ministry of Science and Technology xx Project: “High-performance Artificial Intelligence-driven Digital Twin System for Industry 4.0” (Grant number G2022165013L).
Citation
Li, K., He, Y., Li, K. and Liu, C. (2023), "Adaptive fractional-order admittance control for force tracking in highly dynamic unknown environments", Industrial Robot, Vol. 50 No. 3, pp. 530-541. https://doi.org/10.1108/IR-09-2022-0244
Publisher
:Emerald Publishing Limited
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