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Research Article | Open Access

Numerical simulation of chaotic dynamics in a fractional-order vibration model with Grünwald-Letnikov fractional derivative

Jiaxin Zhang1Wei Zhang2( )Xiaoyu Li3( )
School of Information and Network Engineering, Anhui Science and Technology University, Bengbu 233030, China
Institute of Economics and Management, Jining Normal University, Ulanqab 012000, China
College of Date Science and Application, Inner Mongolia University of Technology, Hohhot 010080, China
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Abstract

This paper investigates the chaotic dynamics in a fractional-order vocal fold vibration (VCV) model based on the Grünwald-Letnikov fractional derivative (GLFD). Studying the characteristics of vocal fold vibration is of great significance for revealing its vibration mechanism, the etiology of abnormal vibrations, and natural speech synthesis. Traditional vocal fold vibration models are based on integer-order systems and are unable to describe the memory effects present in real physical systems. To overcome this limitation, this paper introduces fractional derivatives and develops a high-precision numerical method to simulate the fractional-order VCV model. By incorporating nonlinear elastic and damping forces, the model can more accurately describe the complex dynamic characteristics of vocal fold vibrations, including memory effects and non-locality. The numerical simulation results reveal novel chaotic behaviors in the fractional-order VCV model, which have not been observed in integer-order models. These findings provide new insights into the possible dynamic states of vocal fold vibrations and lay the foundation for further theoretical and experimental studies on the vocal cord vibration mechanism.

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Networks and Heterogeneous Media
Pages 625-647

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Cite this article:
Zhang J, Zhang W, Li X. Numerical simulation of chaotic dynamics in a fractional-order vibration model with Grünwald-Letnikov fractional derivative. Networks and Heterogeneous Media, 2025, 20(2): 625-647. https://doi.org/10.3934/nhm.2025027

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Received: 01 March 2025
Revised: 01 May 2025
Accepted: 16 May 2025
Published: 03 June 2025
©2025 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)