Bipartite Synchronization of Complex Dynamical Networks via Hybrid Triggering Reliable Control

ABSTRACT This work concerns the acquisition of bipartite synchronization for the multi‐weighted complex dynamical networks associated with coupling delays and nonlinearities against external disturbances and actuator faults. The goal of this study is achieved by adopting the reliable adaptive hybrid triggering mechanism, which is a more flexible control strategy. In particular, the adaptive hybrid triggering mechanism combines two effective control schemes, that is, the time‐triggered and the adaptive event‐triggered scheme in order to reinforce the procurement of the required objective. Precisely, the undesirable impacts of exogenous disturbances in the addressed networks are dealt with by attempting the mixed and passivity performance. As a part of this process, by fabricating a proper Lyapunov‐Krasovskii functional, the sufficient conditions that ensure the stability of the closed‐loop error system are obtained as linear matrix inequalities. Ultimately, the verification of the produced results is performed with the numerical simulations.

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Publication Details

Journal
Asian Journal of Control
Published
2026-07-28
DOI
https://doi.org/10.1002/asjc.70203
Primary Topic
Neural Networks Stability and Synchronization
Type
article
Field-Weighted Citation Impact
0.00
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article

Bipartite Synchronization of Complex Dynamical Networks via Hybrid Triggering Reliable Control

Yong Ren, Rathinasamy Sakthivel, Nallamuthu Birundha Devi
Asian Journal of Control
Neural Networks Stability and Synchronization
article

Bipartite Synchronization of Complex Dynamical Networks via Hybrid Triggering Reliable Control

Yong Ren, Rathinasamy Sakthivel, Nallamuthu Birundha Devi
article en

Abstract

ABSTRACT This work concerns the acquisition of bipartite synchronization for the multi‐weighted complex dynamical networks associated with coupling delays and nonlinearities against external disturbances and actuator faults. The goal of this study is achieved by adopting the reliable adaptive hybrid triggering mechanism, which is a more flexible control strategy. In particular, the adaptive hybrid triggering mechanism combines two effective control schemes, that is, the time‐triggered and the adaptive event‐triggered scheme in order to reinforce the procurement of the required objective. Precisely, the undesirable impacts of exogenous disturbances in the addressed networks are dealt with by attempting the mixed and passivity performance. As a part of this process, by fabricating a proper Lyapunov‐Krasovskii functional, the sufficient conditions that ensure the stability of the closed‐loop error system are obtained as linear matrix inequalities. Ultimately, the verification of the produced results is performed with the numerical simulations.

Asian Journal of Control
Bharathiar University (IN), Anhui University (CN), Hefei University (CN), Karpagam Academy of Higher Education (IN)
Openalex Percentile: Top 6%
Neural Networks Stability and Synchronization
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