Synchronization Control of Complex Spatio-Temporal Networks Based on Fractional-Order Hyperbolic PDEs with Delayed Coupling and Space-Varying Coefficients

This paper studies synchronization behaviors of two sorts of non-linear fractional-order complex spatio-temporal networks modeled by hyperbolic space-varying PDEs (FCSNHSPDEs), respectively, with time-invariant delays and time-varying delays, including one delayed coupling. One distributed controller with space-varying control gains is firstly designed. For time-invariant delayed cases, sufficient conditions for synchronization of FCSNHSPDEs are presented via LMIs, which have no relation to time delays. For time-varying delayed cases, synchronization conditions of FCSNHSPDEs are presented via spatial algebraic LMIs (SALMIs), which are related to time delay varying speeds. Finally, two examples show the validity of the control approaches.

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Publication Details

Journal
Fractal and Fractional
Published
2024-09-09
DOI
https://doi.org/10.3390/fractalfract8090525
Citations
2
Primary Topic
Neural Networks Stability and Synchronization
Type
article
Field-Weighted Citation Impact
0.70
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article

Synchronization Control of Complex Spatio-Temporal Networks Based on Fractional-Order Hyperbolic PDEs with Delayed Coupling and Space-Varying Coefficients

Muwei Jian, Jiashu Dai, Jin Wang, Chengyan Yang
2 citations
Fractal and Fractional
Neural Networks Stability and Synchronization
0.70
article

Synchronization Control of Complex Spatio-Temporal Networks Based on Fractional-Order Hyperbolic PDEs with Delayed Coupling and Space-Varying Coefficients

Muwei Jian, Jiashu Dai, Jin Wang, Chengyan Yang
article en
2 citations

Abstract

This paper studies synchronization behaviors of two sorts of non-linear fractional-order complex spatio-temporal networks modeled by hyperbolic space-varying PDEs (FCSNHSPDEs), respectively, with time-invariant delays and time-varying delays, including one delayed coupling. One distributed controller with space-varying control gains is firstly designed. For time-invariant delayed cases, sufficient conditions for synchronization of FCSNHSPDEs are presented via LMIs, which have no relation to time delays. For time-varying delayed cases, synchronization conditions of FCSNHSPDEs are presented via spatial algebraic LMIs (SALMIs), which are related to time delay varying speeds. Finally, two examples show the validity of the control approaches.

Fractal and FractionalVol. 8(9)
Universiti Putra Malaysia (MY), Linyi University (CN), Shandong University of Finance and Economics (CN), Anhui Polytechnic University (CN)
Openalex Percentile: Top 28%
Neural Networks Stability and Synchronization
0.70
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