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Volume 11 Issue 5
May  2024

IEEE/CAA Journal of Automatica Sinica

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Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2024  >  11(5): 1190-1201
X. Yao, H. Sun, Z. Zhao, and  Y. Liu,  “Event-triggered bipartite consensus tracking and vibration control of flexible Timoshenko manipulators under time-varying actuator faults,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 5, pp. 1190–1201, May 2024. doi: 10.1109/JAS.2024.124266
Citation: X. Yao, H. Sun, Z. Zhao, and  Y. Liu,  “Event-triggered bipartite consensus tracking and vibration control of flexible Timoshenko manipulators under time-varying actuator faults,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 5, pp. 1190–1201, May 2024. doi: 10.1109/JAS.2024.124266
shu

Event-Triggered Bipartite Consensus Tracking and Vibration Control of Flexible Timoshenko Manipulators Under Time-Varying Actuator Faults

doi: 10.1109/JAS.2024.124266
Funds:  This work was supported in part by the National Key R&D Program of China (2021YFB3202200), the Natural Science Foundation of China (62203141), and the Guangdong Basic and Applied Basic Research Foundation (2021B1515120017)
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    Abstract

  • For bipartite angle consensus tracking and vibration suppression of multiple Timoshenko manipulator systems with time-varying actuator faults, parameter and modeling uncertainties, and unknown disturbances, a novel distributed boundary event-triggered control strategy is proposed in this work. In contrast to the earlier findings, time-varying consensus tracking and actuator defects are taken into account simultaneously. In addition, the constructed event-triggered control mechanism can achieve a more flexible design because it is not required to satisfy the input-to-state condition. To achieve the control objectives, some new integral control variables are given by using back-stepping technique and boundary control. Moreover, adaptive neural networks are applied to estimate system uncertainties. With the proposed event-triggered scheme, control inputs can reduce unnecessary updates. Besides, tracking errors and vibration states of the closed-looped network can be exponentially convergent into some small fields, and Zeno behaviors can be excluded. At last, some simulation examples are given to state the effectiveness of the control algorithms.

     

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    Highlights

    • Vibration control and bipartite consensus tracking of multiple Timoshenko manipulators
    • Time-varying actuator fault and event-based control are considered together
    • Novel boundary control terms and trigger functions are designed

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