Analysis and Applications of the Chaotic Hyperbolic Memristor Model with Fractional Order Derivative

Authors

  • Ghada Ahmed AL Baha University

DOI:

https://doi.org/10.29020/nybg.ejpam.v17i2.5131

Keywords:

Fractional model, Lorenz-Stenflo model,, Hyperchaotic behavior, Nonlinear dynamical systems,, Fractional derivative, Simulation.

Abstract

This work presents a new five-dimensional fractional-order chaotic system that includes a feedback memristor. A Lorenz-Stenflo-based fractional-order chaotic system with five dimensions that contains feedback memristor dynamics is used to do this. This work focuses on chaotic models through the ABC fractional derivative, a concept we rigorously examine. We designed and used
sophisticated numerical algorithms to model fractional-order dynamics with the utmost precision to understand this system’s complex characteristics. These numerical approaches excel at non-integer order differentiation, which standard numerical methods struggle with. Our research uses fractional calculus to increase the system’s complexity and robustness, revealing its hyperchaotic nature. We demonstrate that the system is chaotic and stable over fractional orders using eigenvalues, Lyapunov exponents, Kaplan-Yorke dimensions, maximal exponents, phase portraits, and equilibrium points. Our conclusions are strengthened by using these numerical systems, intended for this work, and analytical tools. We improve our understanding of fractional-order chaotic systems with our research. It illuminates how to improve electrical integrations and create more sophisticated nonlinear dynamical systems. This work establishes the approach and insights for future research, guiding the development of new systems with enhanced dynamical features

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Published

2024-04-30

Issue

Section

Nonlinear Analysis

How to Cite

Analysis and Applications of the Chaotic Hyperbolic Memristor Model with Fractional Order Derivative. (2024). European Journal of Pure and Applied Mathematics, 17(2), 835-851. https://doi.org/10.29020/nybg.ejpam.v17i2.5131

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