Lyapunov Exponent Diagrams Research Articles

Nonlinear performance of aerospace face gear-planetary gear transmission system under multi-factors including the effect of temperature

Face gear-planetary gear transmission system combines the advantages of both planetary and face gears. And has enormous advantages in the aerospace field. The meshing of gear teeth generates heat through friction, resulting in thermal deformation and affects nonlinear dynamic characteristics. Exploring the temperature effect on the nonlinear dynamics of the transmission system of face gear-planetary gear is of great significance. Considering the temperature variations effect and time-varying meshing stiffness, tooth side clearance as well as meshing error, a nonlinear dynamic model of the face gear-planetary gear system is established. The nonlinear dynamic characteristics of the system were described by maximum Lyapunov exponent diagram, phase diagram, bifurcation diagram et al. The findings indicate that the effect of temperature variations on the gear system is related to the values of the time-varying mesh stiffness coefficient and mesh damping ratio. When the mesh damping ratio is small, the influence of temperature changes on the bifurcation characteristics of the system is more obvious. As the time-varying mesh stiffness value increases, the temperature rise gradually stabilizes in the range of 15°C to 42°C; Under certain temperature changes, as the meshing damping ratio and time-varying meshing stiffness coefficient increase, the face gear planetary gear system gradually tends to stabilize.

The chaotic behavior and traveling wave solutions of the conformable extended Korteweg–de-Vries model

Abstract In this article, the phase portraits, chaotic patterns, and traveling wave solutions of the conformable extended Korteweg–de-Vries (KdV) model are investigated. First, the conformal fractional order extended KdV model is transformed into ordinary differential equation through traveling wave transformation. Second, two-dimensional (2D) planar dynamical system is presented and its chaotic behavior is studied by using the planar dynamical system method. Moreover, some three-dimensional (3D), 2D phase portraits and the Lyapunov exponent diagram are drawn. Finally, many meaningful solutions are constructed by using the complete discriminant system method, which include rational, trigonometric, hyperbolic, and Jacobi elliptic function solutions. In order to facilitate readers to see the impact of fractional order changes more intuitively, Maple software is used to draw 2D graphics, 3D graphics, density plots, contour plots, and comparison charts of some obtained solutions.

Complex dynamical behaviors of a honeybee-mite model in parameter plane

The honeybee has a significant impact on ecosystem stability, biodiversity conservation, and pollinating crops. However, during the past few years, there has been a sharp reduction in both the honeybee population and their colonies. It has been found that the parasitic mite Varroa destructor is responsible for the decline in honeybee colonies around the world, which in turn immensely affects the economic growth of a country. To investigate how the dynamics of a system is influenced by the growth of honeybees and the parasitism of mites, we study a nonlinear honeybee-mite population model in a discrete-time setup. We observe that an increase in the value of the queen’s egg-laying rate drives the system towards chaos. However, chaos can be controlled as well if the parasite attachment effect is increased. The intrinsic dynamical properties of the proposed system are investigated with the simultaneous variation of the queen’s egg-laying rate and the mite’s parasite attachment effect by constructing several largest Lyapunov exponent and isoperiodic diagrams. The investigation reveals the existence of several periodic structures in the quasiperiodic and chaotic regimes of the parameter plane, including Arnold tongues, saddle area, spring area, connected shrimp-shaped structure, and connected saddle area. We also find the appearance of a novel ‘jellyfish’-shaped periodic structure. One of the most fascinating findings of this study is the appearance of Arnold tongues along the inner boundary region of another Arnold tongue. In addition, this work also reveals different types of multistability, e.g., the coexistence of two, three, and even four attractors. What is more interesting is that the current analysis unveils the coexistence of five attractors as well, more specifically, four different periodic attractors coexist with the trivial fixed point attractor, which is quite rare in ecological systems. The structures of the basins of these coexisting attractors are either smooth or very complex in nature. Furthermore, the present study also discloses the fact that variation in the initial condition of the system can significantly change the appearance of the periodic structures in the parameter plane.

Complex dynamic behaviors in a small network of three ring coupled Rayleigh-Duffing oscillators: Theoretical study and circuit simulation

This work focuses on the dynamics of a small network of three ring-coupled unidirectional Rayleigh-Duffing oscillators. The equations governing the Rayleigh-Duffing oscillator, containing a cubic term, make this study a more interesting and complex case to analyze. Coupling is achieved by perturbing the amplitude of each oscillator with a signal proportional to the amplitude of the other. The sixth-order self-driven nonlinear system obtained after coupling is analyzed, and presents up to twenty seven equilibrium points. Amongst these equilibrium points, we determined which can present the Hopf bifurcation. Also, the effects of the coupling coefficients and damping coefficients are analyzed. It is shown that varying these different coefficients leads to the appearance of extremely complex dynamic phenomena such as: instability and bifurcations (i.e coexistence of bifurcation branches), coexistence of up to fifteen attractors (heterogeneous multistability) and eight spiral chaotic attractor. The investigation of the coupled system is carried out by using to both analytical and numerical tools such as Hopf bifurcation theorem, the phase portraits, bifurcation diagrams, Lyapunov exponent diagram, frequency spectrum, to name but a few. The Routh-Hurwitz criterion is also used to analyze the stability of equilibrium points. We compute basins of attraction to highlight different zones corresponding to coexisting attractors. The implementation of an analog circuit of coupled Rayleigh-Duffing oscillators has enabled us to confirm the analytical and numerical results.

Dynamics and Implementation of FPGA for Memristor-Coupled Fractional-Order Hopfield Neural Networks

The coupling between neurons can lead to diverse neural network architectures, with the Hopfield neural network (HNN) being particularly noteworthy for its resemblance to human brain function and its potential in modeling chaotic systems. This paper introduces a novel approach: a fractional-order HNN coupled with a hyperbolic tangent-type memristor. Initially, we propose a new model for the hyperbolic tangent-type memristor and fingerprints. Subsequently, we construct a memristor-coupled fractional-order Hopfield neural network (mFOHNN) and explore its dynamic behavior using various analytical tools, including phase diagrams, bifurcation diagrams, Lyapunov exponent diagrams, Poincaré maps, and attractor basins. Our findings reveal rich coexisting bifurcation behavior in the neural network model, influenced by different initial values of coexisting attractors. Finally, we validate the model through analysis and implementation using Multisim circuit simulation software and FPGA hardware, respectively.

Cap like trajectories in 5D chaotic tangent hyperbolic memristive model: fractional calculus and encryption

This research aims to investigate the influence of model parameters and fractional order on a novel mathematical model with tangent hyperbolic memristor. This investigation conducted by applying Lyapunov exponents and bifurcation analysis. We utilize the Lyapunov exponent theory to understand and characterize these chaotic behaviors under fractional indices. The Lyapunov exponent, bifurcation, and phase diagrams have been depicted to explore the intricate dynamics of the chaotic system governed by the chaotic equation. A novel approach termed Atangana-Baleanu-Caputo (ABC) fractional derivative (FD) to generate phase portraits and gain insights into the system’s behavior. The random numbers generated by the chaotic system are employed to distort the image through an amalgamated image encryption (AIE) algorithm. Subsequently, the integrity of the scrambled image has been assessed using various image security evaluation methods to reinforce the notion that combining the chaotic system and image can constitute a valuable encryption key. Finally, the chaotic model circuit realization uses active and passive components, and the outcomes are compared with the numerical simulations.

Dynamics and non-integrability of the double spring pendulum

This paper investigates the dynamics and integrability of the double spring pendulum, which has great importance in studying nonlinear dynamics, chaos, and bifurcations. Being a Hamiltonian system with three degrees of freedom, its analysis presents a significant challenge. To gain insight into the system’s dynamics, we employ various numerical methods, including Lyapunov exponents spectra, phase-parametric diagrams, and Poincaré cross-sections. The novelty of our work lies in the integration of these three numerical methods into one powerful tool. We provide a comprehensive understanding of the system’s dynamics by identifying parameter values or initial conditions that lead to hyper-chaotic, chaotic, quasi-periodic, and periodic motion, which is a novel contribution in the context of Hamiltonian systems. In the absence of gravitational potential, the system exhibits S1 symmetry, and the presence of an additional first integral was identified using Lyapunov exponents diagrams. We demonstrate the effective utilization of Lyapunov exponents as a potential indicator of first integrals and integrable dynamics. The numerical analysis is complemented by an analytical proof regarding the non-integrability of the system. This proof relies on the analysis of properties of the differential Galois group of variational equations along specific solutions of the system. To facilitate this analysis, we utilized a newly developed extension of the Kovacic algorithm specifically designed for fourth-order differential equations. Overall, our study sheds light on the intricate dynamics and integrability of the double spring pendulum, offering new insights and methodologies for further research in this field.

Backstepping synchronization control for four-dimensional chaotic system based on DNA strand displacement

Backstepping control is an important nonlinear control design method, which realizes the control of complex systems by constructing control law step by step, and has significant advantages for dealing with complex nonlinear systems. This article proposes a synchronization technique for four-dimensional chaotic systems using a combination of backstepping control method and DNA strand displacement technology. By relying on theoretical knowledge of DNA molecules, five basic chemical reaction modules such as trigger reaction, reference reaction, catalytic reaction, annihilation reaction and degradation reaction are given to construct a four-dimensional DNA chaotic system. On the basis of the relevant theory of chaotic dynamics, the constructed system is analyzed by Lyapunov exponent diagram and spectral entropy complexity algorithm, and the results come to the conclusion that the system reveals extremely complex and varied dynamic behaviors. Combining DNA strand displacement technology with backstepping control method, four controllers are developed to ensure that the trajectories of two homogeneous chaotic systems are synchronized. The numerical simulation results validate the feasibility and applicability of the proposed method. The method proposed in this paper may provide some references in the field of DNA molecular chaos synchronization control.

A Lie symmetry approach to traveling wave solutions, bifurcation, chaos and sensitivity analysis of the geophysical Korteweg–de Vries equation

Strong waves known as tsunamis are caused by earthquakes, landslides, or volcanic eruptions that traverse oceans. This article examines the geophysical Korteweg–de Vries (GPKdV) equation, which controls the propagation of tsunami waves in seas. The study involves exploring symmetry diminution exerted Lie group analysis, examining the properties of the dynamical structure with the help of bifurcation phase pictures, and researching the dynamic demeanor of the perturbed dynamical system utilizing chaos theory. Techniques such as 3D and 2D phase portraits, time series analysis, poincaré maps, looking into the existence of multistability in the autonomous structure under diverse beginning circumstances, lyapunov exponent, and bifurcation diagram are applied to identify chaotic demeanor. Furthermore, the study establishes general forms of solitary wave results, containing periodic, trigonometric, and singular soliton results, by using the unified Riccati equation expansion approach to address the examined problem analytically. These results are visually represented as 2D and 3D graphs with cautiously chosen parameters, along with their accompanying constraint conditions. Moreover, the sensitivity evaluation of the investigated equation is discussed and demonstrated pictorially. The discoveries revealed are intriguing, novel, and potentially helpful in understanding a wide range of physical events in engineering and science.

Multiple scroll attractors and multistability in the collective dynamics of a four chain coupled hopfield inertial neuron network: analysis and circuit design investigations

This work deals with the chain bidirectional coupling of four inertial Hopfield neurons. Each of our cells taken alone is modeled by a second order differential equation having three resting points. Coupling these neurons helps increasing the number of fixed points that is related to the amount of memory assigned to the network. The system having a hyperbolic tangent as nonlinearity is investigated with the help of suitable nonlinear dynamical tools like bifurcation diagrams, Lyapunov exponent diagrams and phase portraits to resort the richness of the model. As the coupling adds the amount of equilibriums, it also helps in generating multiple scroll attractors. The system that was unable of oscillation presents firing patterns such as parallel branches, coexistence of up to sixteen attractors in the phase plane, extreme events and Hopf bifurcation to name a few. All these features are discovered when observing the coupling strengths, the dissipation coefficient and when programming initial states around sensitive equilibriums. The electronic version of the four-chain coupled inertial neurons system is provided and simulated on Pspice with the aim to confirm the results obtained in the numerical scheme.

Complex Dynamics of a Discrete-Time Food Chain Model

In a food chain, the role of intake patterns of predators is very influential on the survival and extinction of the interacting species as well as the entire dynamics of the ecological system. In this study, we investigate the affluent and intricate dynamics of a simple three-species food chain model in a discrete-time framework by analyzing the parameter plane of the system with simultaneous changes of two crucial parameters, the predation rates of middle and top predators. From the theoretical viewpoint, we study the model by determining the fixed points’ biological feasibility and local asymptotic stability criteria, and performing some analyses of local bifurcations, namely, transcritical, flip, and Neimark–Sacker bifurcations. Here, we initiate the numerical simulation by plotting the changes of the prey population density in terms of a vital parameter of the system, and we observe the switching among different dynamical behaviors of the system. We also draw some phase portraits and plot the time series solutions to show the diverse characteristics of the system dynamics. Further, we move one step ahead to explore the intricate dynamical scenarios appearing in the parameter plane by forming Lyapunov exponent and isoperiodic diagrams. In the parameter plane of the system, we see the emergence of innumerable Arnold tongues. All these Arnold tongues are organized along a particular direction, and the beautiful arrangement of these tongues forms several kinds of period-adding sequences. The study sheds more light on various types of multistability occurring in the model system. We see the coexistence of three periodic attractors in the parameter plane. In this study, the most striking observation is the coexistence of four periodic attractors, which occurs infrequently in ecological systems. We draw the basins of attraction for the tristable and tetrastable attractors, which are complex Wada basins. A system with Wada basin is very sensitive to initial conditions and more erratic in nature than a system with fractal basin. Also, we plot the density of all interacting species in terms of the predation rates of middle and top predators and observe the variation in the population densities of all species with the variability of these two key parameters. In the parameter plane created by the simultaneous changes of two parameters, the system exhibits a variety of intricate and subtle dynamics, which cannot be found by changing only a single parameter.

Nonlinear vibration characteristics of axially moving anisotropic membrane with gas-thermal-elastic coupling

In the actual printing production process, the printing electronic motion membrane is susceptible to transverse vibration caused by interference from air drag, temperature changes, and other external conditions, resulting in membrane wrinkles, slippage, and other phenomena in the transmission process. We studied the bifurcation and chaos movement properties of anisotropic membranes under air drag and temperature. According to D’Alembert’s theory and von Kármán’s principle, the nonlinear dynamic differential formulas of axially moving anisotropic membranes with gas-thermal-elastic coupling are established. The Galerkin method is applied to discretize the formulas to obtain the state equation of the system. Finally, numerical simulations are performed by applying the fourth-order Runge–Kutta method to analyze the bifurcation and chaos of the system in terms of orthotropic coefficient, dimensionless air drags, and dimensionless temperature. The bifurcation diagrams, Lyapunov exponent diagrams, displacement time-history diagrams, phase-trajectory plane diagrams, and Poincaré diagrams of the membrane system are obtained. The results show that the anisotropic coefficient, dimensionless air drag, and dimensionless temperature significantly impact the investigated nonlinear dynamic of the anisotropic membrane, which provides a theoretical basis for production efficiency and high-quality printing equipment.

Influence of Raman gain on dynamics of spatiotemporal chaos in optical ring microresonators

We theoretically investigate on the evolution of spatiotemporal chaos under the influence of Raman gain, in an optical ring microresonator. The dynamics of the system is shown to be governed by the Lugiator–Lefever equation, with an additional real and imaginary Raman gain term. In the absence of pump field intensity and Raman gain, we observe an increase in the amplitude and frequency of the traveling optical field as the pump detuning frequency increases. However this field gradually vanishes as time increases, owing to the intra-cavity loss. By exploring an appropriate ansatz which incorporate a chirping parameter, the modified Lugiator–Lefever equation is transformed to a set of four coupled first-order nonlinear ordinary differential equations. Fixed point stability analysis strongly suggest that variation in Raman gain has the propensity of inducing the co-existence of bright and dark solitons in the anomalous dispersion regime. Results of numerical simulations underscore that the structural profiles of the optical field amplitude are greatly modified by the Raman effects. Variation in Raman gain equally leads to a bifurcation analysis of the system, in which the Lyapunov exponent diagrams reveal regions of period doubling and chaos. We finally observe that for a fixed value of the real part of Raman gain coefficient, an increase in the effects of soliton self-frequency shift generally drives the system to chaotic regime.

Dynamical analysis of the FitzHugh–Nagumo model with memristive synapse

Understanding the transition mechanism between different activity patterns in realistic neuron models brings forward fundamental challenges for the dynamical systems theory. The knowledge about the mechanisms can present precious predictions and intuitions for determining fundamental principles of neuron functioning. This paper aims to present a dynamic analysis of the FitzHugh–Nagumo neuron model with a memristive synapse. In this article, the effects of memristive synapse's conductance gain, applied current, and the speed of electrical signal propagation along axons and dendrites on the system's behavior and the neuron's membrane potential are investigated. Analyzes are performed by investigating bifurcation and Lyapunov exponent diagrams versus various model parameters. The physiological role of some parameters and the effect of parameter changes on the model behaviors are discussed. The results demonstrate that when no current is applied to the system, the maximum value of membrane potential is larger, and also, a lower memristive synapse conductance gain leads to a larger maximum value of membrane potential. So, it can be concluded that the neuron in an amplitude death state may be triggered and start firing by decreasing the conductance gain or not applying current.

Dynamical behavior of q-deformed logistic map in superior orbit

In this paper, we study the q-deformed logistic map in Mann orbit (superior orbit) which is a two-step fixed-point iterative algorithm. The main aim of this paper is to investigate the whole dynamical behavior of the proposed map through various techniques such as fixed-point and stability approach, time-series analysis, bifurcation plot, Lyapunov exponent and cobweb diagram. We notice that the chaotic behavior of q-deformed logistic map can be controlled by choosing control parameters carefully. The convergence and stability range of the map can be increased substantially. Moreover, with the help of bifurcation diagrams, we prove that the stability performance of this map is larger than that of existing other one dimensional chaotic maps. This map may have better applications than that of classical logistic map in various situations as its stability performance is larger. Mathematics Subject Classification (2010): 34H10, 37M10, 37B25, 37F45. Received 09 April 2021; Accepted 08 October 2021

Bifurcation analysis in a discrete toxin-producing phytoplankton–zooplankton model with refuge

This paper concerns a discrete-time phytoplankton–zooplankton model in which the effects of toxin produced by phytoplankton and refuges provided for phytoplankton on the interactions between phytoplankton and zooplankton are considered. We first discuss the existence and stability of fixed points. When two parameters change, it is shown that there exist some codimension-two bifurcations, including fold-flip bifurcation and strong resonance bifurcations. Moreover, we give the corresponding bifurcation diagrams, phase diagrams and maximum Lyapunov exponent diagrams. The results show that phytoplankton toxin and refuges play important roles in the occurrence and termination of algal blooms in freshwater lakes.

Effects of Josephson junction synapse on coupled Morris-Lecar neurons

Recently, various artificial synapses have been examined in neural networks for obtaining different dynamical characteristics of neurons. The Josephson junction can be used for constructing an artificial synapse that incorporates the external magnetic field effects. Using the Josephson junction for coupling the neurons involves the phase error between the junctions. This paper uses the Josephson junction and a linear resistor to connect two Morris-Lecar neuron models. The effects of Josephson junction parameters are investigated on the dynamical properties of neurons. The obtained bifurcation and Lyapunov exponent diagrams represent that the Josephson junction synapse significantly affects the neurons’ dynamics. Rich dynamics are observed by varying the junction parameters. Moreover, the multistability properties are reported. Finally, the synchronization of coupled neurons is studied under different junction's parameters.

Speech encryption algorithm based on two newly designed chaotic maps

Two new integrated chaotic maps are designed. The sine and logistic maps are used to create a sine-logistic integrated map (SLIM). The sine and cubic maps are used to design a sine-cubic integrated map (SCIM). Their dynamical analyses are done using time series plots, 0–1 tests, bifurcations, sample entropy, and Lyapunov exponent diagrams. The newly designed chaotic maps exhibit their dynamical properties of a period-two cycle, period-four cycle, and chaos. The speech signal is compressed first, and encryption is performed based on the new integrated chaotic maps. The two keys, such as key-A and key-B, are generated using SLIM and SCIM, respectively. Key-A is used for the shifting operation, while the bitwise XOR operation is carried out between the compressed-shifted speech signal and key-B. After that, the encrypted speech is sent across a public channel, and the original speech is recovered by performing reverse operations on the receiving end. The degree of security is measured using various speech security and attack analysis tools. It is found that the proposed strategy is more secure than some existing methods described in the literature and can withstand several attacks.

Chaotic Neural Network with Nonlinear Delayed Self-feedback and Applications

We propose a novel transient chaotic neural network model with a nonlinear delayed self-feedback term, aiming to leverage its complex dynamical behavior for algorithm optimization. To avoid the influence of chance, we conduct experiments using randomly generated data and analyze the model’s chaotic dynamical behavior by visualizing the stability of the neurons through inverse bifurcation diagrams and maximum Lyapunov exponent diagrams. The simulation results demonstrate the remarkable effectiveness of this new model in network optimization, with a success rate even reaching 100%, surpassing previous chaotic neural network models. Notably, in the following sections, all nonlinear terms are represented using trigonometric functions.

An investigation of the parameter space in a tri-trophic food chain model with refuge

Aside from humans, the instinct to run and hide from dangerous situations is ingrained in individuals of many other species. Taking refuge is a very common precautionary strategy among prey species to avoid direct contact with their predators. In this article, we investigate a three-species food chain model where the logistically growing basal prey seeks refuge to avoid the middle predator. To assess the impact of varying levels of refuge, we explore the system dynamics in the biparametric space of refuge and another important system parameter related to the half-saturation constant of the basal prey. The isospike diagrams along with the largest Lyapunov exponent diagrams show a stabilizing role of refuge. Apart from this, we observe an abundance of organized periodic structures embedded inside the chaotic zone of the biparametric space. The most notable ones include the shrimp-shaped structures and an “elliptic disc” shaped structure. The article also explores the coexistence between multiple pairs of coexisting attractors and one instance of spike-bubbling phenomena. The basins of attraction for the coexisting attractors also have a self-similar pattern. We also modify the present model by replacing the density-dependent prey refuge with constant proportion of prey refuge, and then explore the dynamics of the modified model within the same biparametric space and find similar complexity in its dynamics. We compare the effects of both types of refuge on the density variations of all three species when they show stable coexistence and observe that density-dependent refuge is more beneficial to the system from the standpoint of species conservation.