Approximating hidden chaotic attractors via parameter switching
Marius-F. Danca, Nikolay Kuznetsovc, Guanrong Chen
TL;DR
This paper introduces a parameter switching method to approximate hidden chaotic attractors in nonlinear systems, demonstrated on Lorenz and Rabinovich-Fabrikant systems, offering a new approach to studying complex dynamics.
Contribution
The paper presents a novel parameter switching algorithm for approximating hidden chaotic attractors, extending the ability to analyze complex nonlinear systems.
Findings
Successfully approximated hidden attractors in Lorenz and Rabinovich-Fabrikant systems
Demonstrated the effectiveness of parameter switching in capturing complex dynamics
Provided a numerical method for analyzing hidden chaotic attractors
Abstract
In this paper, the problem of approximating hidden chaotic attractors of a general class of nonlinear systems is investigated. The Parameter Switching (PS) algorithm is utilized, which switches the control parameter within a given set of values with the initial value problem numerically solved. The PS-generated generated attractor approximates the attractor obtained by averaging the control parameter with the switched values, which represents the hidden chaotic attractor. The hidden chaotic attractors of a generalized Lorenz system and the Rabinovich-Fabrikant system are simulated for illustration
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