Composite Finite-Time ADRC for Flexible-Joint Manipulators with Frequency-Domain Separation

Flexible-joint manipulators suffer from severe performance degradation due to the coupling of joint elasticity and varying loads. To address this, we propose a composite finite-time active disturbance rejection control (CFT-ADRC) strategy utilizing a frequency-domain separation architecture. A recursive least squares (RLS) algorithm identifies slow-varying load parameters, while an extended state observer (ESO) compensates for high-frequency unmodeled dynamics and external disturbances, effectively preventing loop interference. A finite-time control law guarantees rapid tracking error convergence. Comprehensive simulations confirm that this approach significantly outperforms standard ADRC and neural network-based methods (RBFNN-ASMC). Under 50% load variations, it achieves an RMS tracking error of 2×10−3 rad and maintains robust stability during 200% instantaneous load mutations. The strategy presents a strong theoretical framework for future hardware implementation while maintaining an optimal balance of precision, robustness, and computational simplicity.

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Publication Details

Journal
Processes
Published
2026-03-08
DOI
https://doi.org/10.3390/pr14050863
Primary Topic
Dynamics and Control of Mechanical Systems
Type
article
Field-Weighted Citation Impact
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article

Composite Finite-Time ADRC for Flexible-Joint Manipulators with Frequency-Domain Separation

Zhongbo Shao, Ming Wu
Processes
Dynamics and Control of Mechanical Systems
article

Composite Finite-Time ADRC for Flexible-Joint Manipulators with Frequency-Domain Separation

Zhongbo Shao, Ming Wu
article en

Abstract

Flexible-joint manipulators suffer from severe performance degradation due to the coupling of joint elasticity and varying loads. To address this, we propose a composite finite-time active disturbance rejection control (CFT-ADRC) strategy utilizing a frequency-domain separation architecture. A recursive least squares (RLS) algorithm identifies slow-varying load parameters, while an extended state observer (ESO) compensates for high-frequency unmodeled dynamics and external disturbances, effectively preventing loop interference. A finite-time control law guarantees rapid tracking error convergence. Comprehensive simulations confirm that this approach significantly outperforms standard ADRC and neural network-based methods (RBFNN-ASMC). Under 50% load variations, it achieves an RMS tracking error of 2×10−3 rad and maintains robust stability during 200% instantaneous load mutations. The strategy presents a strong theoretical framework for future hardware implementation while maintaining an optimal balance of precision, robustness, and computational simplicity.

ProcessesVol. 14(5)
Hankou University (CN), KU Leuven (BE)
Peace, Justice and strong institutions
Openalex Percentile: Top 31%
Dynamics and Control of Mechanical Systems
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