Adaptive Passivity Based Output Synchronization of Complex Dynamical Networks with Unknown Time-varying Periodic Coupling Strength

In this paper, the passivity and synchronization of complicate dynamical nets are addressed, the dimension of in-and-output vector are different and the coupling strength is unknown time-varying. First, the passivity of complex dynamical networks with the designed adaptive law is derived based on the extended passivity definitions. Second, an adaptive output synchronization scheme is proposed where the coupling intensity is updated with a periodic law. And a sufficient condition in term of linear matrix inequality of output synchronization for the complex dynamical networks is derived based on passivity theory. Numerical simulations are provided to demonstrate the correctness of the proposed theory.

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Published
2025-05-09
DOI
https://doi.org/10.1109/ddcls66240.2025.11064967
Primary Topic
Neural Networks Stability and Synchronization
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article
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article

Adaptive Passivity Based Output Synchronization of Complex Dynamical Networks with Unknown Time-varying Periodic Coupling Strength

Junmin Li, Jianguo Cui, Yueying Li
Neural Networks Stability and Synchronization
article

Adaptive Passivity Based Output Synchronization of Complex Dynamical Networks with Unknown Time-varying Periodic Coupling Strength

Junmin Li, Jianguo Cui, Yueying Li
article en

Abstract

In this paper, the passivity and synchronization of complicate dynamical nets are addressed, the dimension of in-and-output vector are different and the coupling strength is unknown time-varying. First, the passivity of complex dynamical networks with the designed adaptive law is derived based on the extended passivity definitions. Second, an adaptive output synchronization scheme is proposed where the coupling intensity is updated with a periodic law. And a sufficient condition in term of linear matrix inequality of output synchronization for the complex dynamical networks is derived based on passivity theory. Numerical simulations are provided to demonstrate the correctness of the proposed theory.

Xidian University (CN), Taiyuan University of Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 82%
Neural Networks Stability and Synchronization
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Adaptive Passivity Based Output Synchronization of Complex Dynamical Networks with Unknown Time-varying Periodic Coupling Strength — Junmin Li, Jianguo Cui, et al. · (2025) | TGRS Research Map | TGRS