Further Results on Event‐Triggered Impulsive Control of Nonlinear Systems Against Disturbance

ABSTRACT This article investigates the event‐triggered impulsive control of nonlinear systems with external disturbance by using a dynamic gain method. In the existing works, the dynamic gain method is often utilized to handle unknown parameters of nonlinear systems without external disturbances. In this article, the disturbance rejection problem is solved by introducing a sliding‐variable‐based method to the designs of the event‐triggered impulsive controller and adaptive dynamic gain laws. Under the proposed control method: (i) the systems states converge to a region around the origin; (ii) the system states are globally asymptotically convergent. It is proved that the Zeno phenomenon can be avoided. Finally, the proposed control schemes are applied to the electromechanical system, which shows the effectiveness and advantages of the results.

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Publication Details

Journal
International Journal of Robust and Nonlinear Control
Published
2025-11-26
DOI
https://doi.org/10.1002/rnc.70313
Primary Topic
Neural Networks Stability and Synchronization
Type
article
Field-Weighted Citation Impact
0.00
Controls
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article

Further Results on Event‐Triggered Impulsive Control of Nonlinear Systems Against Disturbance

Zhengrong Xiang, Xingwen Liu, Min Li, Feng Shu
International Journal of Robust and Nonlinear Control
Neural Networks Stability and Synchronization
article

Further Results on Event‐Triggered Impulsive Control of Nonlinear Systems Against Disturbance

Zhengrong Xiang, Xingwen Liu, Min Li, Feng Shu
article en

Abstract

ABSTRACT This article investigates the event‐triggered impulsive control of nonlinear systems with external disturbance by using a dynamic gain method. In the existing works, the dynamic gain method is often utilized to handle unknown parameters of nonlinear systems without external disturbances. In this article, the disturbance rejection problem is solved by introducing a sliding‐variable‐based method to the designs of the event‐triggered impulsive controller and adaptive dynamic gain laws. Under the proposed control method: (i) the systems states converge to a region around the origin; (ii) the system states are globally asymptotically convergent. It is proved that the Zeno phenomenon can be avoided. Finally, the proposed control schemes are applied to the electromechanical system, which shows the effectiveness and advantages of the results.

International Journal of Robust and Nonlinear ControlVol. 36(5)
Nanjing University of Science and Technology (CN), Southwest Minzu University (CN)
Openalex Percentile: Top 58%
Neural Networks Stability and Synchronization
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