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Adaptive Super-Twisting Tracking for Uncertain Robot Manipulators Based on the Event-Triggered Algorithm

文献类型： 外文期刊

作者： Ma, Yajun 1 ; Zhao, Hui 3 ; Li, Tao 4 ;

作者机构： 1.Tianjin Univ, Sch Elect & Informat Engn, Tianjin 300072, Peoples R China

2.Beijing Inst Precis Mechatron & Controls, Beijing 100076, Peoples R China

3.Tianjin Univ Technol, Sch Elect Engn & Automat, Tianjin 300384, Peoples R China

4.Beijing Acad Agr & Forestry Sci, Beijing Res Ctr Intelligent Equipment Agr, Beijing 100097, Peoples R China

关键词： event-triggered control; adaptive super-twisting; robot manipulator; Zeno free execution

期刊名称：SENSORS （ 影响因子：3.5； 五年影响因子：3.7 ）

ISSN：

年卷期： 2025 年 25 卷 5 期

页码：

收录情况： SCI

摘要： In this study, the authors present an event-triggered control scheme for uncertain robot manipulators combined with an adaptive super-twisting algorithm to handle uncertain robot manipulator systems with unknown external uncertainties and disturbances. The proposed controller can ensure the system-tracking performance while also guaranteeing the robust stability of the system. First, an event-triggered adaptive super-twisting control (ETASTC) method for multivariable second-order nonlinear systems is proposed. In addition, unlike the implementation of periodic control, in the event-triggered method, the control signal is updated by the requirement of system stability, thus avoiding the frequent periodic execution of control tasks. Furthermore, through rigorous proof, the Zeno free execution of the triggering sequence is also ensured. Lastly, the proposed method is illustrated through numerical simulation and experimental study, and the results show that the computational cost is saved while also ensuring the desired performance of the robot system.

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