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<p>In this paper, a hybrid controller with a sampled data control is investigated to achieve finite-time master–slave synchronization of delayed fractional-order neural networks (DFONNs). A Lyapunov-Krasovskii functional is constructed to obtain the sufficient conditions that incorporate delay information. For the first time, the asymptotic stability of the error system is guaranteed in a finite-time using the inequality technique and a sampled-data hybrid controller. The obtained conditions are expressed via linear matrix inequality. Notably, the proposed approach outperforms existing methods, demonstrating improved results in a comparative analysis. An explicit formula is utilized to calculate the settling time, which is significantly influenced by the fractional order <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11063_2025_11733_Article_IEq1.gif" Format="GIF" Height="17" Rendition="HTML" Resolution="72" Type="Linedraw" Width="74" /> </InlineMediaObject> <EquationSource Format="TEX">\(0&lt;\beta \le 1\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mn>0</mn> <mo>&lt;</mo> <mi>β</mi> <mo>≤</mo> <mn>1</mn> </mrow> </math></EquationSource> </InlineEquation>. The superior performance of the proposed control method is evident, showcasing its effectiveness through numerical simulations and addressing the synchronization problem in DFONNs.</p>

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Master–Slave Finite-Time Synchronization of Chaotic Fractional-Order Neural Networks under Hybrid Sampled-Data Control: An LMI Approach

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年2月7日

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  • R. Kiruthika,
  • A. Manivannan

摘要

In this paper, a hybrid controller with a sampled data control is investigated to achieve finite-time master–slave synchronization of delayed fractional-order neural networks (DFONNs). A Lyapunov-Krasovskii functional is constructed to obtain the sufficient conditions that incorporate delay information. For the first time, the asymptotic stability of the error system is guaranteed in a finite-time using the inequality technique and a sampled-data hybrid controller. The obtained conditions are expressed via linear matrix inequality. Notably, the proposed approach outperforms existing methods, demonstrating improved results in a comparative analysis. An explicit formula is utilized to calculate the settling time, which is significantly influenced by the fractional order \(0<\beta \le 1\) 0 < β ≤ 1 . The superior performance of the proposed control method is evident, showcasing its effectiveness through numerical simulations and addressing the synchronization problem in DFONNs.