A New Hyperchaotic Attractor with Complex Patterns

Similar documents
Basins of Attraction Plasticity of a Strange Attractor with a Swirling Scroll

A 3D Strange Attractor with a Distinctive Silhouette. The Butterfly Effect Revisited

A Novel Three Dimension Autonomous Chaotic System with a Quadratic Exponential Nonlinear Term

A Novel Hyperchaotic System and Its Control

GLOBAL CHAOS SYNCHRONIZATION OF HYPERCHAOTIC QI AND HYPERCHAOTIC JHA SYSTEMS BY ACTIVE NONLINEAR CONTROL

Hyperchaos and hyperchaos control of the sinusoidally forced simplified Lorenz system

ADAPTIVE CONTROL AND SYNCHRONIZATION OF A GENERALIZED LOTKA-VOLTERRA SYSTEM

Dynamical analysis and circuit simulation of a new three-dimensional chaotic system

SIMPLE CHAOTIC FLOWS WITH ONE STABLE EQUILIBRIUM

HYBRID CHAOS SYNCHRONIZATION OF HYPERCHAOTIC LIU AND HYPERCHAOTIC CHEN SYSTEMS BY ACTIVE NONLINEAR CONTROL

Generating hyperchaotic Lu attractor via state feedback control

Coexisting Hidden Attractors in a 4-D Simplified Lorenz System

THE ACTIVE CONTROLLER DESIGN FOR ACHIEVING GENERALIZED PROJECTIVE SYNCHRONIZATION OF HYPERCHAOTIC LÜ AND HYPERCHAOTIC CAI SYSTEMS

Recent new examples of hidden attractors

MULTISTABILITY IN A BUTTERFLY FLOW

Generating a Complex Form of Chaotic Pan System and its Behavior

CONTROLLING IN BETWEEN THE LORENZ AND THE CHEN SYSTEMS

Multistability in the Lorenz System: A Broken Butterfly

Complete Synchronization, Anti-synchronization and Hybrid Synchronization Between Two Different 4D Nonlinear Dynamical Systems

ADAPTIVE CONTROL AND SYNCHRONIZATION OF HYPERCHAOTIC NEWTON-LEIPNIK SYSTEM

ADAPTIVE STABILIZATION AND SYNCHRONIZATION OF HYPERCHAOTIC QI SYSTEM

Constructing a chaotic system with any number of equilibria

ADAPTIVE DESIGN OF CONTROLLER AND SYNCHRONIZER FOR LU-XIAO CHAOTIC SYSTEM

International Journal of PharmTech Research CODEN (USA): IJPRIF, ISSN: Vol.8, No.3, pp , 2015

A new four-dimensional chaotic system

ADAPTIVE CHAOS CONTROL AND SYNCHRONIZATION OF HYPERCHAOTIC LIU SYSTEM

GLOBAL CHAOS SYNCHRONIZATION OF UNCERTAIN SPROTT J AND K SYSTEMS BY ADAPTIVE CONTROL

Construction of four dimensional chaotic finance model and its applications

ADAPTIVE CHAOS SYNCHRONIZATION OF UNCERTAIN HYPERCHAOTIC LORENZ AND HYPERCHAOTIC LÜ SYSTEMS

A New Chaotic Behavior from Lorenz and Rossler Systems and Its Electronic Circuit Implementation

Constructing Chaotic Systems with Total Amplitude Control

HX-TYPE CHAOTIC (HYPERCHAOTIC) SYSTEM BASED ON FUZZY INFERENCE MODELING

ADAPTIVE CONTROLLER DESIGN FOR THE ANTI-SYNCHRONIZATION OF HYPERCHAOTIC YANG AND HYPERCHAOTIC PANG SYSTEMS

On Universality of Transition to Chaos Scenario in Nonlinear Systems of Ordinary Differential Equations of Shilnikov s Type

Controlling a Novel Chaotic Attractor using Linear Feedback

A New Circuit for Generating Chaos and Complexity: Analysis of the Beats Phenomenon

A New Dynamic Phenomenon in Nonlinear Circuits: State-Space Analysis of Chaotic Beats

Dynamical Behavior And Synchronization Of Chaotic Chemical Reactors Model

Crisis in Amplitude Control Hides in Multistability

Multi-Scroll Chaotic Attractors in SC-CNN via Hyperbolic Tangent Function

Using Artificial Neural Networks (ANN) to Control Chaos

Adaptive Control of Rikitake Two-Disk Dynamo System

Anti-synchronization of a new hyperchaotic system via small-gain theorem

Introduction Knot Theory Nonlinear Dynamics Topology in Chaos Open Questions Summary. Topology in Chaos

FUZZY STABILIZATION OF A COUPLED LORENZ-ROSSLER CHAOTIC SYSTEM

HYBRID CHAOS SYNCHRONIZATION OF UNCERTAIN LORENZ-STENFLO AND QI 4-D CHAOTIC SYSTEMS BY ADAPTIVE CONTROL

Adaptive Synchronization of Rikitake Two-Disk Dynamo Chaotic Systems

A Memristive Diode Bridge-Based Canonical Chua s Circuit

COMPLEX DYNAMICS IN HYSTERETIC NONLINEAR OSCILLATOR CIRCUIT

A simple spatiotemporal chaotic Lotka Volterra model

Research Article Adaptive Control of Chaos in Chua s Circuit

Electronic Circuit Simulation of the Lorenz Model With General Circulation

CHAOS ENTANGLEMENT: A NEW APPROACH TO GENERATE CHAOS

Experimental and numerical realization of higher order autonomous Van der Pol-Duffing oscillator

DIFFERENTIAL GEOMETRY APPLIED TO DYNAMICAL SYSTEMS

Generalized projective synchronization of a class of chaotic (hyperchaotic) systems with uncertain parameters

Computers and Mathematics with Applications. Adaptive anti-synchronization of chaotic systems with fully unknown parameters

6.2 Brief review of fundamental concepts about chaotic systems

Time-delay feedback control in a delayed dynamical chaos system and its applications

Chaos synchronization of complex Rössler system

Simplest Chaotic Flows with Involutional Symmetries

GLOBAL CHAOS SYNCHRONIZATION OF PAN AND LÜ CHAOTIC SYSTEMS VIA ADAPTIVE CONTROL

Mechanisms of Chaos: Stable Instability

Finite-time hybrid synchronization of time-delay hyperchaotic Lorenz system

International Journal of PharmTech Research

ANALYSIS AND CONTROLLING OF HOPF BIFURCATION FOR CHAOTIC VAN DER POL-DUFFING SYSTEM. China

A Generalization of Some Lag Synchronization of System with Parabolic Partial Differential Equation

GLOBAL CHAOS SYNCHRONIZATION OF UNCERTAIN LORENZ-STENFLO AND QI 4-D CHAOTIC SYSTEMS BY ADAPTIVE CONTROL

A GALLERY OF LORENZ-LIKE AND CHEN-LIKE ATTRACTORS

THREE DIMENSIONAL SYSTEMS. Lecture 6: The Lorenz Equations

Simple Chaotic Flows with a Curve of Equilibria

International Journal of PharmTech Research CODEN (USA): IJPRIF, ISSN: Vol.8, No.6, pp 01-11, 2015

DIFFERENTIAL EQUATIONS, DYNAMICAL SYSTEMS, AND AN INTRODUCTION TO CHAOS

DIFFERENTIAL EQUATIONS, DYNAMICAL SYSTEMS, AND AN INTRODUCTION TO CHAOS

Multistability in symmetric chaotic systems

3. Controlling the time delay hyper chaotic Lorenz system via back stepping control

Amplitude-phase control of a novel chaotic attractor

BIFURCATIONS AND SYNCHRONIZATION OF THE FRACTIONAL-ORDER SIMPLIFIED LORENZ HYPERCHAOTIC SYSTEM

Dynamical Systems and Chaos Part I: Theoretical Techniques. Lecture 4: Discrete systems + Chaos. Ilya Potapov Mathematics Department, TUT Room TD325

State Regulation of Rikitake Two-Disk Dynamo Chaotic System via Adaptive Control Method

Chaos. Dr. Dylan McNamara people.uncw.edu/mcnamarad

ARTICLE IN PRESS. JID:PLA AID:17118 /SCO Doctopic: Nonlinear science [m5+; v 1.73; Prn:2/08/2007; 12:08] P.1 (1-7)

Simple conservative, autonomous, second-order chaotic complex variable systems.

Numerical Simulations in Jerk Circuit and It s Application in a Secure Communication System

ANTI-SYNCHRONIZATON OF TWO DIFFERENT HYPERCHAOTIC SYSTEMS VIA ACTIVE GENERALIZED BACKSTEPPING METHOD

International Journal of PharmTech Research CODEN (USA): IJPRIF, ISSN: Vol.8, No.7, pp , 2015

Function Projective Synchronization of Fractional-Order Hyperchaotic System Based on Open-Plus-Closed-Looping

Backstepping synchronization of uncertain chaotic systems by a single driving variable

Chaos Control of the Chaotic Symmetric Gyroscope System

Solving Zhou Chaotic System Using Fourth-Order Runge-Kutta Method

An Image Encryption Scheme Based on Hyperchaotic Rabinovich and Exponential Chaos Maps

Introduction to Dynamical Systems Basic Concepts of Dynamics

CONTROLLING HYPER CHAOS WITH FEEDBACK OF DYNAMICAL VARIABLES

Construction of a New Fractional Chaotic System and Generalized Synchronization

ADAPTIVE SYNCHRONIZATION FOR RÖSSLER AND CHUA S CIRCUIT SYSTEMS

TWO DIMENSIONAL FLOWS. Lecture 5: Limit Cycles and Bifurcations

CONTROLLING CHAOTIC DYNAMICS USING BACKSTEPPING DESIGN WITH APPLICATION TO THE LORENZ SYSTEM AND CHUA S CIRCUIT

Bifurcation and chaos in simple jerk dynamical systems

International Journal of PharmTech Research CODEN (USA): IJPRIF, ISSN: Vol.8, No.8, pp , 2015

Unit Ten Summary Introduction to Dynamical Systems and Chaos

Transcription:

A New Hyperchaotic Attractor with Complex Patterns Safieddine Bouali University of Tunis, Management Institute, Department of Quantitative Methods & Economics, 41, rue de la Liberté, 2000, Le Bardo, Tunisia Safieddine.Bouali@isg.rnu.tn The paper introduces a new dynamical system which equation s specification ensures full hyperchaotic attractor patterns. Its focal statement appears in its self-sufficiency from previous 3D nonlinear systems. It is mathematically not an extension of a 3D nonlinear system into the fourth dimension but it is built as a new system integrating a small set of nonlinear terms. To explore the basic behavior of the new 4D dynamical model, we selected an arrangement of simple parameters to display the phase portraits of the related strange attractor projected onto the 3D representation spaces. The computation of the Lyapunov exponents establishes presence of hyperchaos since two positive exponents are found. Indexes of stability of the equilibrium points corresponding to the typical 4D strange attractor are also examined. A collection of Poincaré Maps highlights the intricate dynamics of the system. Key words: 4D system; Phase Portraits; Lyapunov exponents; Poincaré Map; Hyperchaos; 1

1. Introduction Hyperchaos concept was firstly introduced in the seminal paper of Rössler [1] to assert the dynamical patterns of dynamical systems when more than one positive Lyapunov exponent is found [2]. Some of hyperchaotic systems are thereafter discovered mainly by the extension of established 3D chaotic to the four-dimension. These hyperchaotic applications start from a fully 3d chaotic system adding a state feedback controller [see for example, 3-9]. Such 4D models are only expanded editions in the phase hyperspace. This paper introduces a new hyperchaotic system not derived from previous 3d models since we do not apply hyperchaotification techniques. Indeed, all the 3D sub-models of the system are not sustainable. However, the present system retains a modified 2D Lotka-Volterra oscillator [10-11] integrated in the block of the first two equations. Purposefully creating hyperchaos can be a nontrivial task to focus a new kind of dynamical patterns as shown by several 4D models recently discovered [12-18, and references therein]. Section 2 investigates the basic characteristics of the introduced autonomous fourdimensional system of first order differential equations. Section 3 points chiefly to the intricate patterns of the hyperchaotic attractor generated by the system. Concluding remarks reports the singularity of the model and its novel contribution to the chaos literature. 2. The hyperchaotic 4D model The new system is governed by four nonlinear differential equations: dx/dt = x (1 y) + α z dy/dt = β (x ² -1) y dz/dt = γ (1 y) v (1) dv/dt = η z where x, y, z and v the state variables of the model, and α, β, γ, and η real parameters. Equations embed only height terms on the right-hand side, three of them are nonlinear, i.e. two quadratic terms xy, and vy, and a unique cubic cross-term yx 2. One would expect the emergence of hyperchaotic patterns in our application. 2

We notice that the system is not derived from a previous 3d chaotic model. Any configuration of systems carried out by three state variables amongst the four is not sustainable. Indeed, the introduced 4D model is not an expanded version adding a state feedback loop formulated in a supplementary equation. In fact, the core of the system is constituted by the 2D sub-model representing a modified version of the well-established 2D Lotka-Volterra oscillator, dx/dt = x (1 y) dy/dt = ( x ² - 1) y and composing previously the core of typical three dimensional chaotic systems. Indeed, this basic oscillator was applied as the fundamental mechanism of two chaotic models [19-20]. The exploration of the widest dynamical behaviors leads us to choose specific values of the parameters between several specifications to simplify the analysis. Let P0 (α, β, γ, η) = (-2, 1, 0.2, 1), the equilibria of the system (1) are found by setting dx/dt = dy/dt = dz/dt = dv/dt = 0, expressed as follow: 0 = x (1 y) - 2 z 0 = ( x ² - 1) y 0 = 0.2 (1 - y) v (1.1) 0 = z The coordinates of the equilibria are the origin S 0, (0, 0, 0, 0) and two sets of parametric solutions: S 1 (1, 1, 0, v) and S 2 (-1, 1, 0, v). The eigenvalues λi and stability features of the related solutions are determined from the characteristic equation J λi = 0, where I, the unit matrix and J, the Jacobian of the model: 1 y - x -2 0 J = 2xy (x ² -1) 0 0 0-0.2 v 0 0.2 (1 y) 0 0 1 0 The volume contraction of the flot is given by: V = Tr (J) = x ² - y. 3

However, the dissipativity in the phase hyperspace is enclosed in the domain: x ² - y < 0, and thus the system is a dissipative system. In this domain, the orbits converge to a specific subset of zero volume as t exponentially, i.e. dv/ dt = e (x ² - y). Indeed, for P0, all solutions are unstable (Table 1) and distinguished with different indexes of stability. Coordinates of the Equilibrium The corresponding characteristic equation, J λi = 0, and eigenvalues Index (1) and Instability S 0 (x 0, y 0, z 0, v 0 ) = (0, 0, 0, 0) Det (J 0 ) = 0.2 > 0 (λ 2 1)(λ 2-0.2) = 0 λ 1 = - 1 λ 2 = - 0.2 λ 3 = 0.2 λ 4 = 1 Index-2: saddle focus Set S 1 of equilibria: S 1 (x 1, y 1, z 1, v 1 ) = (1, 1, 0, v) for v R Det (J 1 ) = 0 For V 0 Re (λ 1 ) > 0 Re (λ 2, λ 3, λ 4 ) 0 ifor V < 0 Re (λ 1, λ 2 ) > 0 Re (λ 3, λ 4 ) 0 Index-1 Saddle points Index-2: saddle foci Set S 2 of equilibria: S 2 (x 2, y 2, z 2, v 2 ) = (-1, 1, 0, v) for v R Det (J 2 ) = 0 For V > 0 Re (λ 1, λ 2 ) > 0 Re (λ 3, λ 4 ) 0 For V 0 Re (λ 1 ) > 0 Re (λ 2, λ 3, λ 4 ) 0 Index-2: saddle foci Index-1 Saddle points (1) Index reports the number of eigenvalues with real parts Re (λ) > 0. From 1 to 4, it indicates the degree of instability. Index-0: null or negative real parts of all eigenvalues of the equilibrium characterize its stability. Table 1. Stability of the Equilibria 3. Global Behavior of the hyperchaotic Attractor To substitute the unfeasibility of the four-dimensional representation, four projections in 3D phase portraits are exhibited, respectively the x-y-z, the x-y-v, the z-y-v, and z-v-x spaces (Fig. 1). The orbits have intricate paths following butterfly wings and scrolls. The trajectories are extremely abundant and dense taking relatively regular and simple forms. However, does the new system have explicitly and globally a hyperchaotic nature? 4

It is known that the spectrum of Lyapunov exponents is the most useful diagnostic to quantify chaos. When the nearby trajectories in the phase space diverge at exponential rates, giving positive Lyapunov exponents, the dynamics become unpredictable. Any system containing at least two positive Lyapunov exponents is defined to be hyperchaotic. The computed Lyapunov exponents LEi are the follows: LE1= 1.85 LE2=.36 LE3 0 LE4= - 34.2 The system (1) can be classified hyperchaotic since: LE1 > LE2 > 0, LE3 = 0, LE4 < 0 and LE1 + LE2 + LE4 < 0. The Kaplan-Yorke dimension of the attractor reaches D 3.064. Fig.1. Projections of the 4D hyperchaotic system into the 3D phase portraits. (a) Projection on x-y-z space, (b) Projection on x-y-v space, (c) Projection on z-y-v space, and (d) Projection on z-v-x space To describe the folding properties of chaos, we apply the technique of the Poincaré map. Take = {(x, y, z, v) R 4 y = 2} as a crossing section. We select the mapping on from the 4D space not to the 3D phase space but on 2D surfaces. 5

Fig.2. Poincaré maps of the System (1) for Y = 2. (a) Projection on v z of the Poincaré map, (b) Projection on x z of the Poincaré map, and (c) Projection on x v of the Poincaré map. 6

The associated Poincaré map on the three phase planes show that the system has extremely rich and intricate dynamics (fig. 2). Branches and twigs unravel the complex folding of the hyperchaotic attractor. In fact, such mapping can exhibit nine other 2D maps for x, z and v as crossing sections. Similar dynamical patterns are also found indicating complex envelops of the orbits. 4. Concluding Remarks The prevailing feature of the system emerges in its independency from previous 4D chaotic systems. Reaching chaos through a relatively simple algebraic structure is still a challenging task. The new hyperchaotic system embedding a modified 2D Lotka-Volterra oscillator depicts a complex scroll butterfly-shaped attractor and exhibiting elegant contours. On the other hand, several specifications of P have been experimented. The simplest one, P0, inducing the widest range of dynamical behaviors, had been selected. This intentionally constructed 4d chaotic system doesn t reincarnate known hyperchaotic patterns. The appearance and also the characteristics of the new 4D attractor are utterly distinct from the other existing hyperchaotic systems (4D Lorenz Haken system, 4D hyperchaotic Chua s circuit, 4D hyperchaotic Chen, etc.). The new system could be suitable for the financial modelization of the macroeconomic sphere. It could be also suitable for digital signal encryption in the communication field when its variants provide a very large set of encryption keys. Further developments and extended analysis related to the set of parameters, and the diagram of bifurcations, will be investigated in a future work. References [1] Rössler O. E. (1979). An Equation for Hyperchaos. Physics Letters, vol. 71A, n o 2, 3, 155 157. [2] Pecora, L. (1996). Hyperchaos harnessed. Phys. World 9, 51, 17. [3] Kapitaniak, T. & Chua, L.O. (1994). Hyperchaotic attractor of unidirectionally coupled Chua s circuit. International Journal of Bifurcation & Chaos, Vol. 4, 477-482. [4] Thamilmaran K., Lakshmanan M., & Venkatesan A. (2004). A hyperchaos in a modified canonical Chua's circuit. International Journal of Bifurcation and Chaos, 14, 221-243. [5] Li Y.X., Tang W.K.S., & Chen G. (2005). Generating hyperchaos via state feedback control. International Journal of Bifurcation and Chaos, Vol. 10, 3367-3375. 7

[6] Chen A, Lu J., Lü J, & Yu S. (2006). Generating Hyperchaotic Lü Attractor via State Feedback Control, Physica A; Statistical Mechanics and its Applications, Vol. 364, 103-110. [7] Jia, Q. (2007). Hyperchaos generated from Lorenz chaotic system and its control. Phys. Lett. A, Vol. 366, 217-222. [8] Tam L., Chen J., Chen H., & Tou W. (2008). Generation of hyperchaos from the Chen Lee system via sinusoidal perturbation. Chaos, Solitons and Fractals, Vol. 38, 826-839. [9] Sun K., Liu X., Zhu C., & Sprott J. C. (2012). Hyperchaos and hyperchaos control of the sinusoidally forced simplified Lorenz system, Nonlinear Dynamics, vol. 69, no. 3, 1383 1391. [10] Volterra, V. (1926). Variazioni e fluttuazioni del numero d individui in specie animali conviventi. Mem. R. Accad. Naz. dei Lincei, Ser. VI 2. [11] Lotka, A.J. (1925). Elements of Physical Biology. Williams &Wilkins, Baltimore. [12] Wu W., Chen Z., & Yuan Z. (2009). The evolution of a novel fourdimensional autonomous system: among 3-torus, limit cycle, 2- torus, chaos and hyperchaos. Chaos, Solitons and Fractals, vol. 39, 2340 2356. [13] Yong C., & Yun-Qing Y. (2010). A new four-dimensional chaotic system, Chin. Phys. B, Vol. 19, No. 12 120510, 1-5. [14] Zhang J., & Tang W. (2012). A novel bounded 4D chaotic system. Nonlinear Dynamics, 67, 4, 2455-2465. [15] Yu H., Cai G., & Li Y. (2012). Dynamic analysis and control of a new hyperchaotic finance system. Nonlinear Dynamics, vol. 67, 3, 2171 2182. [16] Wang Z., Cang S., Ochola E.O., & Sun Y. (2012). A hyperchaotic system without equilibrium. Nonlinear Dynamics, vol. 69, no. 1-2, 531 537. [17] Shu Y., Zhang F. & Mu C. (2014). Dynamical behaviors of a new hyperchaotic system. Mathematical Methods in the Applied Sciences. Wiley online Library. DOI: 10.1002/mma.3287. [18] Shen C., Yu S., Lü J., & Chen G. (2015). Constructing hyperchaotic systems at will. International Journal of Circuit Theory and Applications, Wiley online Library, DOI: 10.1002/cta.2062. [19] Bouali S. (2012). A novel strange attractor with a stretched loop. Nonlinear Dynamics, 70, 2375 2381. [20] Bouali S. (2013-v1, 2014-v2). A 3D Strange Attractor with a Distinctive Silhouette. The Butterfly Effect Revisited. http://arxiv.org/ftp/arxiv/papers/1311/1311.6128.pdf March 2015 8