Research Article  Open Access
Huijian Zhu, "Harmonic Balance Method for Chaotic Dynamics in FractionalOrder Rössler Toroidal System", Discrete Dynamics in Nature and Society, vol. 2013, Article ID 593856, 6 pages, 2013. https://doi.org/10.1155/2013/593856
Harmonic Balance Method for Chaotic Dynamics in FractionalOrder Rössler Toroidal System
Abstract
This paper deals with the problem of determining the conditions under which fractional order Rössler toroidal system can give rise to chaotic behavior. Based on the harmonic balance method, four detailed steps are presented for predicting the existence and the location of chaotic motions. Numerical simulations are performed to verify the theoretical analysis by straightforward computations.
1. Introduction
The concept of fractional calculus has been known since the development of the regular calculus, with the first reference probably being associated with Leibniz and L’Hôspital in 1695. In the past three decades or so, fractional calculus gained considerable popularity and importance, due mainly to its demonstrated applications in numerous seemingly diverse and widespread fields of science and engineering [1–3]. In particular, by utilizing fractional calculus technique, many investigations were devoted to the chaotic behaviors and chaotic control of dynamical systems involving the fractional derivative, called fractionalorder chaotic system [4–8]. For example, it has been shown that Chua circuit of the order as low as 2.7 can behave in chaotic manner [4]. In [5], the nonautonomous Duffing systems of the order less than 2 can still produce a chaotic attractor. In [6], chaotic behavior of the fractionalorder Lorenz system was further studied. In [7], chaos and hyperchaos in the fractionalorder Rössler equations were also studied, in which the authors showed that chaos can exist in the fractionalorder Rössler equation with the order as low as 2.4, and hyperchaos can exist in the fractionalorder Rössler hyperchaos equation with the order as low as 3.8. Later on, the chaotic behavior and its control in the fractionalorder Chen system were investigated in [8]. And recently, more dynamic behaviors of fractional order chaotic systems were analyzed by using different approaches; we refer the readers to [9–12].
However, to our knowledge, the conditions for chaos existence in dynamical systems (including integerorder system and fractionalorder system) are still incomplete. For a given dynamical system, can we decide (without invoking numerical simulations) whether and in what parameter ranges, chaotic behavior might exist? It is still an open problem [13]. Even though some theorems such as Melnikov’s criteria [14] and Shil’nikov’s theorem [15] may be helpful in some special cases, it seems that a powerful tool is not generally available to determine the accurate parameter ranges for chaos existence in a given dynamical system. Moreover, the fact that fractionalorder system possess long memory characteristics makes the system behave in more complicated manner. This means that chaos analysis in fractionalorder systems is more complicated than that in integerorder systems. Recently, based on harmonic balance method (or describing function method), predicting chaotic dynamics in fractionalorder GenesioTesi system was investigated [16]. Later on, two describing functionbased techniques were proposed to predict chaos in a class of fractionalorder differential equations [17]. Therefore, harmonic balance method can give another way to detect the conditions for chaos existence in fractionalorder systems. Following them, the subject of this paper is predicting conditions for chaos existence in fractionalorder Rössler toroidal system.
The paper is organized as follows. In Section 2, some basic concepts of fractional calculus are briefly introduced. Sections 3 and 4 are about predicting chaos in fractionalorder Rössler toroidal system by utilizing harmonic balance method. In Section 5, numerical simulations are further presented to confirm the obtained results of Section 4. Finally, the brief conclusions are drawn in Section 6 and close the paper.
2. Preliminaries
2.1. Basic Definitions
In what follows, the definitions of fractional derivative are introduced in brief. For an arbitrary real number , the RiemannLiouville and Caputo fractional derivatives are defined, respectively, as wherestands for the integer part of; that is,is the first integer which is not less than.
Note that the main advantage of Caputo approach is that the initial conditions for fractional differential equations with Caputo derivatives take on the same form as for integerorder differential equations. Some other important properties of the fractional derivatives and integrals can be found in [1–3].
2.2. Numerical Method
According to [18, 19], the predictorcorrector scheme for fractionalorder system is derived. This scheme is the generalization of AdamsBashforthMoulton scheme. First, the following fractionalorder differential equation involving Caputo derivative is equivalent to the Volterra integral equation (see [18, Lemma 2.1]) Set, , , and system (4) can be discretized as where The error estimate is (), in which.
3. Fractional Rössler Toroidal System
The Rössler toroidal system, which was firstly introduced in [20], is defined by where and are real parameters.
For what follows, it is useful to transform this system in the equivalent thirdorder differential equation: Now we introduce fractional order into the system (8) and obtain the corresponding fractionalorder Rössler toroidal model: where , , , and is in sense of the Caputo fractional derivative defined in (2) with the initial time .
According to the PoincareBendixson theorem [21], ifis very close to zero, then system (9) behaves like a twodimensional system and cannot be chaotic. However, iftends to 1, system (9) dynamically approaches a thirdorder ordinary differential equation which can be chaotic. So, it is interesting to analyze the conditions under which chaos can occur in system (9) when.
First, system (9) can be represented as a nonlinear feedback structure, made of a linear dynamic partand a nonlinear dynamic part(shown in Figure 1).
The linear subsystemis modeled by the following transfer function: and the nonlinear subsystemis described by a real function Suppose that the hypothetical solution of system (9) is represented by whereand. Also, the nonlinear subsystemcan be approximated by whereandare represented by Note that this approximation can be satisfied, if the linear parthas the property of a low pass filter. From Figure 1, it follows Thus, the following equations are obtained:
4. The Conditions for Chaos to Occur
Based on the GenesioTesi conjecture [22], the predicted existence of chaos can be synthesized, with the following four conditions satisfied: (i) existence of a stable limit cycle, (ii) existence of an unstable equilibrium pointwhich is different from the fixed point that originates the predicted limit cycle in (i), (iii) an interaction between the observed limit cycleand equilibrium point; that is,for some, (iv) suitable filtering effect in the GenesioTesi conjecture. So, the following four steps must be performed.
4.1. A Stable Limit Cycle
Suppose that the predicted limit cycle is denoted by. Substituting (15) into (18) and letting the real and imaginary parts be equal to zero, respectively, their solutions can be expressed as follows: From (14) and (17), it follows which implies that Sinceand, the necessary condition [17] for existence of a limit cycle is Based on the approximate Loeb criterion [23], the stability of the predicted limit cycle depends on the relative location ofwith respect toand the locus ofwith respect to, whereis considered as a function of, that is,. The predicted limit cycle is stable if the locus ofenters in a stable interval of the real axis by increasingfrom and, vice versa, by decreasing(see Figurein [24]). From [17], it is sufficient to check.
According to (14)–(18), it follows Thus, from inequalities (22) and (23), it can be calculated that Therefore, the predicted limit cycle is stable according to the Loeb criterion [23].
4.2. An Unstable Equilibrium Point
By solving the equation, the equilibrium points of system (9) can be derived as follows: The equilibrium pointis the equilibrium point of interest in this step of the described function method because the equilibrium pointoriginates the limit cycle described by (19)–(21). Moreover, the characteristic equation of linearized system of the system (9) around the equilibrium pointis given by Sinceand, it is easy to check thatand. This means that there at least exists a positive real numberbetweenand, which satisfies. Hence, the equilibrium pointis unstable according to the stability theorem proved in [25].
4.3. Interaction between the Limit Cycle and Equilibria
In this section, an interaction between the observed limit cycleand equilibrium pointshould be verified. This condition can be restated by the following inequality: Because of heuristic nature of the method, condition (28) should be considered in the more indefinite form such as whereis a number close to[22]. According to (20) and (21), condition (29) can be verified if which is stronger than the necessary condition (23). Hence, an interaction between the observed limit cycleand equilibrium pointis certain.
4.4. Filter Effect
Since the reliability of the stable limit cycle is based on the filtering hypothesis, the higher harmonic terms ofare discarded. The amount of the neglected higher harmonics concerning the predicted limit cycle withof frequencycan be expressed by the socalled distortion index where the symbolstands for thenorm with the period anddenotes the steadystate periodic output of the system [26]. But, it is too difficult to calculate the undistorted signalin the fractionalorder system. As suggested in [16], the limitsandare used to replaceand. Based on the final value theorem of Laplace transform, it follows Substituting relations (32) and (33) into (31), the distortion indexcan be obtained for different values,, and. Indeed, small value ofimplies that the predicted limit cycle is reliable.
5. Numerical Simulations
By fixing, the possible chaotic parameter region for fractionalorder Rössler toroidal system based on the GenesioTesi conjecture in theplane is shown in Figure 2. In the shaded region of Figure 2, it is possible for chaos to occur.
Next consider the filter effect for different parameter values. Based on the above expressions (31)–(33), an interesting thing has been found that different valuesandcannot affect the value of distortion index. Moreover, the values of distortion indexfor different valuesare shown in Table 1.

According to Table 1, the filtering effect of the system decreases by increasing. It means that the possibility of existence of chaos increases by choosing larger in the possible chaotic region (shown in Figure 2). To confirm the existence of chaotic behavior in fractionalorder Rössler toroidal system (9), numerical simulations are carried out by applying the numerical method in Section 2.2. For instance, the pairis selected as a paradigm to confirm the existence of chaos (shown in Figure 3).
6. Conclusions
In this paper, harmonic balance based method is applied to detect the conditions indicating a chaotic behavior of fractionalorder Rössler toroidal system. Based on the four steps of GenesioTesi conjecture, the possible chaotic parameter region is obtained. Also, numerical simulations are carried out to verify the accuracy and effectiveness of the obtained results. Finally, the finding in present paper indicates that harmonic balance method can give a useful approach to find rather simple conditions indicating a chaotic behavior of nonlinear fractionalorder dynamical systems.
Acknowledgment
This work was supported by the Science and Technology Innovation Projects of Education Bureau of Guangdong Province (no. 2012KJCX0073).
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Copyright
Copyright © 2013 Huijian Zhu. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.