A Lyapunov-Based Step-by-Step Sliding-Mode Observer Algorithm With Application to Joint Torque Estimation of Robot Manipulators

Force control strategies are crucial for robot manipulators to effectively adapt to diverse tasks. However, employing force sensors to measure force/torque information significantly increases the cost of robotic systems. Hence, it is crucial to delve into sensorless force/torque estimation techniques. Given the low precision of traditional force estimation algorithms, this article presents a novel algorithm to improve the torque estimation precision of robot manipulators' joints. First, based on the dynamic model, a finite-time sliding-mode torque observer is designed for the robot manipulators via a step-by-step method. A new Lyapunov function is constructed to prove the finite-time convergence of the closed-loop system. Second, in the presence of sampling noise, the robustness of the proposed finite-time torque observer is analyzed. Finally, simulation and experimental results validate the effectiveness of the proposed algorithm.

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Publication Details

Journal
IEEE Transactions on Industrial Informatics
Published
2024-12-12
DOI
https://doi.org/10.1109/tii.2024.3507208
Citations
3
Primary Topic
Iterative Learning Control Systems
Type
article
Field-Weighted Citation Impact
0.98

Funders

Controls
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article

A Lyapunov-Based Step-by-Step Sliding-Mode Observer Algorithm With Application to Joint Torque Estimation of Robot Manipulators

Haibo Du, Yongzheng Cong, Weile Chen, Guanghui Wen et al.
3 citations
IEEE Transactions on Industrial Informatics
Iterative Learning Control Systems
0.98
article

A Lyapunov-Based Step-by-Step Sliding-Mode Observer Algorithm With Application to Joint Torque Estimation of Robot Manipulators

Haibo Du, Yongzheng Cong, Weile Chen, Guanghui Wen, Wenwu Zhu
article en
3 citations

Abstract

Force control strategies are crucial for robot manipulators to effectively adapt to diverse tasks. However, employing force sensors to measure force/torque information significantly increases the cost of robotic systems. Hence, it is crucial to delve into sensorless force/torque estimation techniques. Given the low precision of traditional force estimation algorithms, this article presents a novel algorithm to improve the torque estimation precision of robot manipulators' joints. First, based on the dynamic model, a finite-time sliding-mode torque observer is designed for the robot manipulators via a step-by-step method. A new Lyapunov function is constructed to prove the finite-time convergence of the closed-loop system. Second, in the presence of sampling noise, the robustness of the proposed finite-time torque observer is analyzed. Finally, simulation and experimental results validate the effectiveness of the proposed algorithm.

IEEE Transactions on Industrial InformaticsVol. 21(3)
Hefei University of Technology (CN), Southeast University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Anhui Province
Affordable and clean energy
Openalex Percentile: Top 22%
Iterative Learning Control Systems
0.98
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