Current Trends on Fractional-Order Systems: Bifurcations, Synchronization, and Chaos

A special issue of Fractal and Fractional (ISSN 2504-3110). This special issue belongs to the section "Complexity".

Deadline for manuscript submissions: closed (15 January 2025) | Viewed by 5418

Special Issue Editors


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Guest Editor
Applied Physics Division, Center for Scientific Research and Higher Education at Ensenada, CICESE. Carr. Ensenada-Tijuana, 3918 Zona Playitas, Ensenada 22860, Mexico
Interests: robust control; chaotic dynamics; fractional calculus; nonlinear dynamics

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Guest Editor
Applied Physics Division, Center for Scientific Research and Higher Education at Ensenada, CICESE. Carr. Ensenada-Tijuana, 3918 Zona Playitas, Ensenada 22860, Mexico
Interests: synchronization; complex networks; nonlinear phenomena; chaos theory; bifurcations; arbitrary order calculus

Special Issue Information

Dear Colleagues,

Fractional calculus is an exciting and powerful tool for addressing problems involving non-integer order integration and differentiation. Since the pioneering work of the Norwegian mathematician Niels Henrik Abel (1802-1829)—who introduced a rather general framework for fractional calculus while solving the tautochrone problem—many researchers have been attracted by this branch of mathematics and its applications in science and technology. In fact, from a Dynamical Systems perspective, fractional calculus has helped us to understand and to model nonlinear phenomena, for example, chaotic behavior, synchronization, bifurcations, and population dynamics, among others. Hence, nowadays, the following words of H. T. Davis, a former professor at the University of New Mexico, are more valid than ever: “The great elegance that can be secured by the proper use of fractional operators and the power which they have in the solution of complicated functional equations should more than justify a more general recognition and use”.

This Special Issue aims to provide a forum for presenting state-of-the-art theoretical, numerical, and experimental results regarding the modeling, analysis, and implementation of dynamical systems described by fractional order differential equations as well as the study of nonlinear phenomena, for example, chaos, bifurcations, and synchronization, occurring in (networks of) fractional order systems, emerging either as a consequence of the interaction among them or due to a variation in the fractional order of the derivative.

The topics covered in this Special Issue include but are not limited to the following:

  • Modeling of nonlinear phenomena via fractional order differential equations;
  • Fractional-order chaotic systems;
  • Synchronization of (networks of) fractional-order dynamical systems;
  • Emergent behavior;
  • Bifurcations;
  • Integer and fractional-order dynamic couplings;
  • Periodic solutions and fractional order oscillators;
  • Stability and multi-stability;
  • Complex networks;
  • Fractional order neural networks;
  • Applications of fractional order ordinary differential equations;
  • Influence of the fractional-order of a system on the onset of bifurcations and chaos.

Dr. Joaquin Alvarez
Dr. J. Pena-Ramirez
Guest Editors

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Keywords

  • stability
  • oscillators
  • complex networks
  • chaos
  • bifurcation
  • synchronization
  • emergent behavior
  • fractional order neural networks

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Published Papers (4 papers)

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Research

26 pages, 2372 KiB  
Article
Bifurcation Analysis and Chaos Control of a Discrete Fractional-Order Modified Leslie–Gower Model with Nonlinear Harvesting Effects
by Yao Shi, Xiaozhen Liu and Zhenyu Wang
Fractal Fract. 2024, 8(12), 744; https://doi.org/10.3390/fractalfract8120744 - 16 Dec 2024
Viewed by 1153
Abstract
This paper investigates the dynamical behavior of a discrete fractional-order modified Leslie–Gower model with a Michaelis–Menten-type harvesting mechanism and a Holling-II functional response. We analyze the existence and stability of the nonnegative equilibrium points. For the interior equilibrium points, we study the conditions [...] Read more.
This paper investigates the dynamical behavior of a discrete fractional-order modified Leslie–Gower model with a Michaelis–Menten-type harvesting mechanism and a Holling-II functional response. We analyze the existence and stability of the nonnegative equilibrium points. For the interior equilibrium points, we study the conditions for period-doubling and Neimark–Sacker bifurcations using the center manifold theorem and bifurcation theory. To control the chaos arising from these bifurcations, two chaos control strategies are proposed. Numerical simulations are performed to validate the theoretical results. The findings provide valuable insights into the sustainable management and conservation of ecological systems. Full article
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16 pages, 3723 KiB  
Article
Numerical Simulation and Solutions for the Fractional Chen System via Newly Proposed Methods
by Mohamed Elbadri, Mohamed A. Abdoon, D. K. Almutairi, Dalal M. Almutairi and Mohammed Berir
Fractal Fract. 2024, 8(12), 709; https://doi.org/10.3390/fractalfract8120709 - 29 Nov 2024
Cited by 1 | Viewed by 1001
Abstract
This study presents two methods: a novel numerical scheme that utilizes the Atangana–Baleanu–Caputo (ABC) derivative and the Laplace New Iterative Method (LNIM). Furthermore, some complex dynamic behavior of fractional-order Chen is observed. The NABC method illustrates chaotic systems. We used the LNIM method [...] Read more.
This study presents two methods: a novel numerical scheme that utilizes the Atangana–Baleanu–Caputo (ABC) derivative and the Laplace New Iterative Method (LNIM). Furthermore, some complex dynamic behavior of fractional-order Chen is observed. The NABC method illustrates chaotic systems. We used the LNIM method to find analytical solutions for fractional Chen systems. The method stands out for its user-friendliness and numerical stability. The proposed methods are effective and yield analytical solutions and detection of chaotic behavior. Simultaneously, this results in a more precise understanding of the system. As a result, we may apply the approach to different systems and achieve more accurate findings. Furthermore, it has been demonstrated to be effective in accurately identifying instances through the exhibition of attractor chaos. Future applications in science and engineering can utilize these two methods to find numerical simulations and solutions to a variety of models. Full article
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20 pages, 1612 KiB  
Article
Does a Fractional-Order Recurrent Neural Network Improve the Identification of Chaotic Dynamics?
by José Luis Echenausía-Monroy, Daniel Alejandro Magallón-García, Luis Javier Ontañón-García, Raul Rivera Rodriguez, Jonatan Pena Ramirez and Joaquín Álvarez
Fractal Fract. 2024, 8(11), 632; https://doi.org/10.3390/fractalfract8110632 - 26 Oct 2024
Cited by 2 | Viewed by 1485
Abstract
This paper presents a quantitative study of the effects of using arbitrary-order operators in Neural Networks. It is based on a Recurrent Wavelet First-Order Neural Network (RWFONN), which can accurately identify several chaotic systems (measured by the mean square error and the coefficient [...] Read more.
This paper presents a quantitative study of the effects of using arbitrary-order operators in Neural Networks. It is based on a Recurrent Wavelet First-Order Neural Network (RWFONN), which can accurately identify several chaotic systems (measured by the mean square error and the coefficient of determination, also known as R-Squared, r2) under a fixed parameter scheme in the neural algorithm. Using fractional operators, we analyze whether the identification capabilities of the RWFONN are improved, and whether it can identify signals from fractional-order chaotic systems. The results presented in this paper show that using a fractional-order Neural Network does not bring significant advantages in the identification process, compared to an integer-order RWFONN. Nevertheless, the neural algorithm (modeled with an integer-order derivative) proved capable of identifying fractional-order dynamical systems, whose behavior ranges from periodic and multi-stable to chaotic oscillations. That is, the performances of the Neural Network model with an integer-order derivative and the fractional-order network are practically identical, making the use of fractional-order RWFONN-type networks meaningless. The results deepen the work previously published by the authors, and contribute to developing structures based on robust and generic neural algorithms to identify more than one chaotic oscillator without retraining the Neural Network. Full article
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16 pages, 1071 KiB  
Article
Dynamics Analysis and Adaptive Synchronization of a Class of Fractional-Order Chaotic Financial Systems
by Panhong Zhang and Qingyi Wang
Fractal Fract. 2024, 8(10), 562; https://doi.org/10.3390/fractalfract8100562 - 27 Sep 2024
Viewed by 888
Abstract
It is of practical significance to realize a stable and controllable financial system by using chaotic synchronization theory. In this paper, the dynamics and synchronization are studied for a class of fractional-order chaotic financial systems. First, the stability and dynamics of the fractional-order [...] Read more.
It is of practical significance to realize a stable and controllable financial system by using chaotic synchronization theory. In this paper, the dynamics and synchronization are studied for a class of fractional-order chaotic financial systems. First, the stability and dynamics of the fractional-order chaotic financial system are analyzed by using the phase trajectory diagram, time series diagram, bifurcation diagram, and Lyapunov exponential diagram. Meanwhile, we obtain the range of each parameter that puts the system in a periodic state, and we also reveal the relationship of the derivative order and the chaotic behaviors. Then, the adaptive control strategy is designed to achieve synchronization of the chaotic financial system. Finally, the theoretical results and control method are verified by numerical simulations. Full article
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