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    Volume 1, Issue 2, IECE Transactions on Sensing, Communication, and Control
    Volume 1, Issue 2, 2024
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    Aradhana Misra
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    IECE Transactions on Sensing, Communication, and Control, 2024, Volume 1, Issue 2: 126-135

    Free to Read | Research Article | 18 December 2024
    Adaptive Tunable Predefined-Time Backstepping Control for Uncertain Robotic Manipulators
    by
    IECE Author Huihui Shi 1
    IECE Author Shuzong Xie 2 *
    IECE Author Qiang Chen 1
    IECE Author Shuangyi Hu 1
    IECE Author Shenglun Yi 3
    1 Zhejiang University of Technology, Hangzhou 310023, China
    2 Zhejiang University of Science and Technology, Hangzhou 310023, China
    3 University of Padova, 35131 Padova, Italy
    * Corresponding Author: Shuzong Xie, [email protected]
    DOI: https://doi.org/10.62762/TSCC.2024.672831
    Received: 17 October 2024, Accepted: 05 December 2024, Published: 18 December 2024  
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    Abstract
    In engineering applications, high-precision tracking control is crucial for robotic manipulators to successfully complete complex operational tasks. To achieve this goal, this study proposes an adaptive tunable predefined-time backstepping control strategy for uncertain robotic manipulators with external disturbances and model uncertainties. By establishing a novel practical predefined-time stability criterion, a tunable predefined-time backstepping controller is systematically presented, allowing the upper bound of tracking error settling time to be precisely determined by adjusting only one control parameter. To accurately address lumped uncertainty, two updating laws are designed: a fuzzy weight updating law and a boundary adaptive updating law, which together reduce dependence on system model knowledge. In addition, the singularity problem in the predefined-time design process is effectively avoided by constructing the hyperbolic tangent function. The efficacy of the proposed control strategy is verified through numerical simulations.
    Graphical Abstract
    Adaptive Tunable Predefined-Time Backstepping Control for Uncertain Robotic Manipulators
    Keywords
    predefined-time control
    adaptive fuzzy control
    backstepping design
    robotic manipulators
    Funding
    This work was supported in part by the National Natural Science Foundation of China under Grant 62203384, Grant 62222315 and Grant 62403426; in part by the Zhejiang Provincial Nature Science Foundation of China under Grant MS25F030011 and LZ22F030007.
    Cite This Article
    APA Style
    Shi, H., Xie, S., Chen, Q., Hu, S., & Yi, S. (2024). Adaptive Tunable Predefined-Time Backstepping Control for Uncertain Robotic Manipulators. IECE Transactions on Sensing, Communication, and Control, 1(2), 126–135. https://doi.org/10.62762/TSCC.2024.672831
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    IECE Transactions on Sensing, Communication, and Control

    IECE Transactions on Sensing, Communication, and Control

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