Adaptive Terminal Control of n-DOF Robot Manipulators With Enhanced Nonlinear Model-Based Synergetic Manifold

This paper presents an Adaptive Terminal Model-Based Synergetic Control (ATMB-SC) framework for n-DOF robot manipulators, addressing critical limitations of conventional synergetic control. The proposed strategy integrates a nonlinear model-based manifold function for robotic manipulators, ensuring robust trajectory tracking while eliminating the coupling effect inherent in the conventional synergetic control method. By establishing a linear relationship between the torque input and both position error and its rate of change, the method simplifies control design without compromising robustness or accuracy. An adaptive strategy based on the MIT rule dynamically adjusts the convergence matrix in real-time is implemented, enhancing precision and responsiveness to uncertainties and external disturbances. Additionally, a terminal term is incorporated into the manifold, guaranteeing finite-time convergence of error trajectories, which is critical for high-precision, time-sensitive applications. Experimental validation on a 4-DOF robot demonstrates the strategy’s effectiveness, with input torque variation improved by 10% to 112.67% and the least mean square error achieved across all axes, ranging from 1.63<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">e</i> − 4 to 9.15<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">e</i> − 5, compared to other controllers.

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Publication Details

Journal
IEEE Transactions on Automation Science and Engineering
Published
2025-01-01
DOI
https://doi.org/10.1109/tase.2025.3558961
Citations
3
Primary Topic
Neural Networks and Applications
Type
article
Field-Weighted Citation Impact
7.44
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article

Adaptive Terminal Control of n-DOF Robot Manipulators With Enhanced Nonlinear Model-Based Synergetic Manifold

Maâmar Bettayeb, Raouf Fareh, Saif Sinan, M. Nasir et al.
3 citations
IEEE Transactions on Automation Science and Engineering
Neural Networks and Applications
7.44
article

Adaptive Terminal Control of n-DOF Robot Manipulators With Enhanced Nonlinear Model-Based Synergetic Manifold

Maâmar Bettayeb, Raouf Fareh, Saif Sinan, M. Nasir, Sofiane Khadraoui
article en
3 citations

Abstract

This paper presents an Adaptive Terminal Model-Based Synergetic Control (ATMB-SC) framework for n-DOF robot manipulators, addressing critical limitations of conventional synergetic control. The proposed strategy integrates a nonlinear model-based manifold function for robotic manipulators, ensuring robust trajectory tracking while eliminating the coupling effect inherent in the conventional synergetic control method. By establishing a linear relationship between the torque input and both position error and its rate of change, the method simplifies control design without compromising robustness or accuracy. An adaptive strategy based on the MIT rule dynamically adjusts the convergence matrix in real-time is implemented, enhancing precision and responsiveness to uncertainties and external disturbances. Additionally, a terminal term is incorporated into the manifold, guaranteeing finite-time convergence of error trajectories, which is critical for high-precision, time-sensitive applications. Experimental validation on a 4-DOF robot demonstrates the strategy’s effectiveness, with input torque variation improved by 10% to 112.67% and the least mean square error achieved across all axes, ranging from 1.63<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">e</i> − 4 to 9.15<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">e</i> − 5, compared to other controllers.

IEEE Transactions on Automation Science and EngineeringVol. 22
University of Sharjah (AE), École de Technologie Supérieure (CA)
Openalex Percentile: Top 4%
Neural Networks and Applications
7.44
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