Robust approximate constraint following control design for collaborative robots system and experimental validation

Abstract The paper presents a novel control method aimed at enhancing the trajectory tracking accuracy of two-link mechanical systems, particularly nonlinear systems that incorporate uncertainties such as time-varying parameters and external disturbances. Leveraging the Udwadia–Kalaba equation, the algorithm employs the desired system trajectory as a servo constraint. First, the system’s constraints to construct its dynamic equation and apply generalized constraints from the constraint equation to an unconstrained system. Second, we design a robust approximate constraint tracking controller for manipulator control and establish its stability using Lyapunov’s law. Finally, we numerically simulate and experimentally validate the controller on a collaborative platform using model-based design methods.

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Publication Details

Journal
Robotica
Published
2024-11-01
DOI
https://doi.org/10.1017/s0263574724001760
Citations
16
Primary Topic
Advanced Control Systems Optimization
Type
article
Field-Weighted Citation Impact
5.25
Controls
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article

Robust approximate constraint following control design for collaborative robots system and experimental validation

Ye‐Hwa Chen, Haohua Liu, Shengchao Zhen, Lihua Gao et al.
16 citations
Robotica
Advanced Control Systems Optimization
5.25
article

Robust approximate constraint following control design for collaborative robots system and experimental validation

Ye‐Hwa Chen, Haohua Liu, Shengchao Zhen, Lihua Gao, Hongmei Zheng, Xiaoli Liu
article en
16 citations

Abstract

Abstract The paper presents a novel control method aimed at enhancing the trajectory tracking accuracy of two-link mechanical systems, particularly nonlinear systems that incorporate uncertainties such as time-varying parameters and external disturbances. Leveraging the Udwadia–Kalaba equation, the algorithm employs the desired system trajectory as a servo constraint. First, the system’s constraints to construct its dynamic equation and apply generalized constraints from the constraint equation to an unconstrained system. Second, we design a robust approximate constraint tracking controller for manipulator control and establish its stability using Lyapunov’s law. Finally, we numerically simulate and experimentally validate the controller on a collaborative platform using model-based design methods.

RoboticaVol. 42(11)
Georgia Institute of Technology (US), Anhui University (CN), Hefei University of Technology (CN)
Peace, Justice and strong institutions
Openalex Percentile: Top 4%
Advanced Control Systems Optimization
5.25
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