ANALYSIS OF THE DYNAMICS OF PERTURBED AND UNPERTURBED LORENZ SYSTEMS

Chaotic behavior is a fundamental feature of many nonlinear deterministic systems, leading to a sensitive dependence on initial conditions and unpredictable dynamics. This study investigates chaos in unperturbed and perturbed Lorenz systems using phase portraits, time series analysis, and Lyapunov exponents. The systems were analyzed for parameters σ = 10, ρ = 25, β = 2.667, and perturbation ε = 0.1. Numerical simulations were performed using MATLAB with the fourth-order Runge–Kutta method. Stability analysis of fixed points was conducted alongside graphical and quantitative evaluations. The results show that both systems exhibit at least one positive Lyapunov exponent, confirming the chaotic behavior. However, an increase in the perturbation parameter ε indicates a gradual transition from chaotic dynamics toward more stable behavior. These findings provide insight into the sensitivity and evolution of chaotic systems under perturbations

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-08-17
DOI
https://doi.org/10.5281/zenodo.21981083
Primary Topic
Chaos control and synchronization
Type
article
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article

ANALYSIS OF THE DYNAMICS OF PERTURBED AND UNPERTURBED LORENZ SYSTEMS

M. O. Oyeleye, Q. O. Adewuyi, O. M. Falola
Zenodo (CERN European Organization for Nuclear Research)
Chaos control and synchronization
article

ANALYSIS OF THE DYNAMICS OF PERTURBED AND UNPERTURBED LORENZ SYSTEMS

M. O. Oyeleye, Q. O. Adewuyi, O. M. Falola
article en

Abstract

Chaotic behavior is a fundamental feature of many nonlinear deterministic systems, leading to a sensitive dependence on initial conditions and unpredictable dynamics. This study investigates chaos in unperturbed and perturbed Lorenz systems using phase portraits, time series analysis, and Lyapunov exponents. The systems were analyzed for parameters σ = 10, ρ = 25, β = 2.667, and perturbation ε = 0.1. Numerical simulations were performed using MATLAB with the fourth-order Runge–Kutta method. Stability analysis of fixed points was conducted alongside graphical and quantitative evaluations. The results show that both systems exhibit at least one positive Lyapunov exponent, confirming the chaotic behavior. However, an increase in the perturbation parameter ε indicates a gradual transition from chaotic dynamics toward more stable behavior. These findings provide insight into the sensitivity and evolution of chaotic systems under perturbations

Zenodo (CERN European Organization for Nuclear Research)
Crescent University (NG), Lead City University (NG), University of Missouri–Kansas City (US)
Openalex Percentile: Top 10%
Chaos control and synchronization
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