Limit Cycles of a Class of Hilbert's Sixteenth Problem Presented by Fractional Differential Equations
© G. H. Erjaee et al. 2010
Received: 21 June 2009
Accepted: 15 March 2010
Published: 26 April 2010
The second part of Hilbert's sixteenth problem concerned with the existence and number of the limit cycles for planer polynomial differential equations of degree n. In this article after a brief review on previous studies of a particular class of Hilbert's sixteenth problem, we will discuss the existence and the stability of limit cycles of this class in the form of fractional differential equations.
where and are polynomial of degree with real coefficients. The general form of this problem, even for , is yet an open problem that has attracted more researches but it is remarkably inflexible. With the development of computer's and graphical software, many recent new improvement results have been obtained. Some survey articles can be found in [1–5] and references therein. One of the classical methods to produce and study limit cycles in such system (1.1) is by perturbing a system which has a centre (e.g., see [6, 7]). In such methods the limit cycles are produced in the perturbed system from the periodic orbits of the periodic annulus of the unperturbed system. As we can see in  by perturbing the linear centre , using arbitrary polynomials and of degree n, limit cycles bifurcated with the bifurcation parameter of order one. Almost the same argument can be seen in  by perturbing the system with maximum n limit cycles. By perturbing the Hamiltonian centre given by in the polynomial differential systems of odd degree n, we can obtain limit cycles . Several other similar investigations have been done using the perturbed polynomial differential systems of second, third, or even more degree. For example, see [11–13] and references therein.
In system (1.2) is a real polynomial of degree n, and and are two real polynomial of degree m. Moreover, system (1.2) contains at least a family of closed orbits for any level curve with and . A full investigation of this planar system for the number of limit cycles and their stabilities can be found in . In this article we study the existence of limit cycles and their stabilities for such system in the form of Fractional Differential Equations (FDEs). Recently great considerations have been made to the systems of FDE. The most essential property of these systems is their nonlocal property which does not exist in the integer-order differential operators. We mean by this property that the next state of a system depends not only upon its current state but also upon all of its historical states. This is a more realistic and is one reason why fractional calculus has become more and more popular. On the other hand, the integer-order differential operator is indifferent to its history. Furthermore, there have been several recent mathematical discoveries that have helped to unlock the power of the fractional derivative . One such discovery is that of fractal functions. Indeed, most of the functions that we are familiar with are smooth. This means that locally they can be approximated by a straight line segment. For example, the function is well approximated by at the point . The derivative of the function at a particular point provides the slope of the straight line approximation or tangent to the curve. Fractal functions are not smooth. They have details on all scales and they cannot be approximated locally by straight line segments. An example is the Weierstrass function which can be written as the infinite sum of cosine functions, . For this function at the point , the tangent changes orientation under increasing magnification. Functions such as the Weierstrass function cannot be differentiated (a whole number of times). But it turns out that these fractal functions can be differentiated a fractional number of times, and the fractional calculus is important for studying these differentiability properties. Fractals are characterized by scaling laws and the fractional derivative at a point can reveal this law. In recent research, scientists at the Mount Sinai School of Medicine have shown that the surfaces of breast cells are fractals and they have found clear differences in the scaling laws for benign cells and malignant cells. The different scaling laws have enabled accurate diagnosis of breast cancers. Another important new discovery that has brought fractional calculus into prominence is that many physical processes are modeled by fractional differential equations. Obviously, the importance of a mathematical model is that it can be used to make predictions and to give insight into the physical process that underlies the behavior. One area where mathematical models have been employed extensively is that of diffusion and transport processes. For example, the dispersion of pollutants in the ocean and the motion of electronic charges in conductors are diffusion processes. Here, a probabilistic description leads to a (whole number) differential equation which can be solved to predict average properties of the system. Similar types of equations are used by financial analysts to model stock prices. It has recently been discovered that processes governed by diffusion which is enhanced or hindered in some fashion are better modeled by FDEs than by integer-order differential equations. These FDEs are finding numerous applications in areas ranging from financial mathematics to ocean-atmosphere dynamics to mathematical biology .
These and the other applications of FDEs provide a good motivation for study such Hilbert's 16th problem of system (1.2) in the form of FDE. So, in the next section we will consider system (1.2) in the form of FDEs and to be more specific we will take , as polynomials of degree 1 and , as polynomials of degrees 3 and 5, respectively. Due to the existence of Riemann-Liouville integral operator in the definition of FDE in the Caputo sense , direct analytical solution for FDE is too rare, and so using the numerical methods is inevitable. In order to use a reliable numerical method we should first discretized the given FDE. However, discretization schemes that produce difference equations whose dynamics resemble that of their continuous counterparts are a major challenge in numerical analysis. To this end we will apply the Mickens nonstandard discretization scheme  to the Grunwald-Letnikov discretization process for our system of FDE. As we will see in Section 3 this discretization scheme leads to the fast convergence with more accurate results in solving the original system (1.2) with integer-order derivative one. Therefore, we are expecting the same accurate results for system (1.2) in the form of FDE with different noninteger-order derivative. Then in Section 4 we will discuss the stability of limit cycle which exists in our system and illustrate the numerical results. We will summarize the results with some final comments in Section 5.
2. Specific Case of the Weakened Hilbert's 16th Problem
For the proof of this theorem, as discussed above, we need to find the zero of the Abelian integral (2.4) which leads to a polynomial of degree 3 with respect to . Then it is straight forward to see that this polynomial has no positive root for and at least one positive real root for . That is, in the first case system (2.1) has no limit cycle and in the former case there is one limit cycle. For the detail proof of this theorem refer to .
3. System (2.1) in the Form of Fractional Differential Equations and Its Discretization
We assert that nonstandard discretization method is a numerical attempt which can be used in discretization process of FDE to get the better results and preserves their crucial property, that is, nonlocal property. In order to do this, we apply the Mickens nonstandard discretization scheme  to the Grunwald-Letnikov discretization process for FDE system (3.4). Indeed, the derivative term, , in the Mickens schemes is replaced by , where is a continuous function of step size . In addition the nonlinear terms such as are either replaced by , or left untouched depending upon the context of the differential equation. There is no appropriate general method for choosing the function , but some special techniques may be found in [18, 21].
Here, we replaced and by and , respectively. Later on, following Mickens' method in the next section, for finding the better results we replace the nonlinear terms in system (3.5) by appropriate combination of the variables in different levels of times.
4. Stability of the Limit Cycles in System (3.5) and Numerical Results
Without losing our generality, we suppose here to be positive. Now, from theory of dynamical systems, the limit cycle exists in system (3.5) whenever the characteristic equation of matrix, , has two solutions with module one.
In addition, for the stability of this limit cycle we can use the stability analysis which is thoroughly investigated by Matignon in . To utilize this theorem for our problem, first we consider the linearization of system (2.1) in the form of FDE with the derivative order in both equations around a given stationary point . This linearized system can be written as where matrix is similar to matrix in (4.1) with and . Now the Matignon stability theorem for our problem can be stated as the following theorem.
5. Final Comments
Another difficulty exists in choosing and for conditions in (4.4) to be satisfied. That is, whenever by choosing small positive values for and conditions (4.4) are satisfied, but the numerical limit cycle cannot be found in system (3.5) even in unstable form. Nevertheless, as we saw the limit cycles exist for the values and with different signs. In particular these limit cycles are stable, easy to find for values , and agreed with the stability condition in Theorem 4.1.
This work is supported by Qatar National Research Fund under the Grant no. NPRP08-056-1–014.
- Gaiko VA: Hilbert's sixteenth problem and global bifurcations of limit cycles. Nonlinear Analysis: Theory, Methods & Applications 2001,47(7):4455-4466. 10.1016/S0362-546X(01)00559-4MATHMathSciNetView ArticleGoogle Scholar
- Gasull A, Giacomini H: A new criterion for controlling the number of limit cycles of some generalized Liénard equations. Journal of Differential Equations 2002,185(1):54-73. 10.1006/jdeq.2002.4172MATHMathSciNetView ArticleGoogle Scholar
- Chen F, Li C, Llibre J, Zhang Z:A unified proof on the weak Hilbert 16th problem for . Journal of Differential Equations 2006,221(2):309-342. 10.1016/j.jde.2005.01.009MATHMathSciNetView ArticleGoogle Scholar
- Giné J: On some open problems in planar differential systems and Hilbert's 16th problem. Chaos, Solitons & Fractals 2007,31(5):1118-1134. 10.1016/j.chaos.2005.10.057MATHMathSciNetView ArticleGoogle Scholar
- Du C, Liu Y: The problem of general center-focus and bifurcation of limit cycles for a planar system of nine degrees. Journal of Computational and Applied Mathematics 2009,223(2):1043-1057. 10.1016/j.cam.2008.03.037MATHMathSciNetView ArticleGoogle Scholar
- Blows TR, Perko LM: Bifurcation of limit cycles from centers and separatrix cycles of planar analytic systems. SIAM Review 1994,36(3):341-376. 10.1137/1036094MATHMathSciNetView ArticleGoogle Scholar
- Chow S-N, Li CZ, Wang D: Normal Forms and Bifurcation of Planar Vector Fields. Cambridge University Press, Cambridge, UK; 1994:viii+472.MATHView ArticleGoogle Scholar
- Giacomini H, Llibre J, Viano M: On the nonexistence, existence and uniqueness of limit cycles. Nonlinearity 1996,9(2):501-516. 10.1088/0951-7715/9/2/013MATHMathSciNetView ArticleGoogle Scholar
- Llibre J, Pérez del Río JS, Rodríguez JA: Averaging analysis of a perturbated quadratic center. Nonlinear Analysis: Theory, Methods & Applications 2001,46(1):45-51. 10.1016/S0362-546X(99)00444-7MATHMathSciNetView ArticleGoogle Scholar
- Li C, Li W, Llibre J, Zhang Z: Polynomial systems: a lower bound for the weakened 16th Hilbert problem. Extracta Mathematicae 2001,16(3):441-447.MATHMathSciNetGoogle Scholar
- Coll B, Gasull A, Prohens R: Bifurcation of limit cycles from two families of centers. Dynamics of Continuous, Discrete & Impulsive Systems. Series A 2005,12(2):275-287.MATHMathSciNetGoogle Scholar
- Llibre J, Zhang X: On the number of limit cycles for some perturbed Hamiltonian polynomial systems. Dynamics of Continuous, Discrete & Impulsive Systems. Series A 2001,8(2):161-181.MATHMathSciNetGoogle Scholar
- García B, Llibre J, Pérez del Río JS: On the number of limit cycles surrounding a unique singular point for polynomial differential systems of arbitrary degree. Nonlinear Analysis: Theory, Methods & Applications 2008,69(12):4461-4469. 10.1016/j.na.2007.11.004MATHMathSciNetView ArticleGoogle Scholar
- Atabaigi A, Nyamoradi N, Zangeneh HRZ: The number of limit cycles of a quintic polynomial system. Computers & Mathematics with Applications 2009,57(4):677-684. 10.1016/j.camwa.2008.10.079MATHMathSciNetView ArticleGoogle Scholar
- Atabaigi A, Nyamoradi N, Zangeneh HRZ: The number of limit cycles of a quintic Hamiltonian system with perturbation. Balkan Journal of Geometry and Its Applications 2008,13(2):1-11.MATHMathSciNetGoogle Scholar
- Borredon L, Henry B, Wearne S: Differentiating the non-differentiable fractional calculus. Parabola 1999,35(2):8-17.Google Scholar
- Caputo M: Linear models of dissipation whose Q is almost frequency independent-II. Geophysical Journal of the Royal Astronomical Society 1967, 13: 529-539. 10.1111/j.1365-246X.1967.tb02303.xView ArticleGoogle Scholar
- Mickens RE: Nonstandard Finite Difference Models of Differential Equations. World Scientific, River Edge, NJ, USA; 1994:xii+249.MATHGoogle Scholar
- Ye YQ, Cai SL, Chen LS, et al.: Theory of Limit Cycles, Translations of Mathematical Monographs. Volume 66. 2nd edition. American Mathematical Society, Providence, RI, USA; 1986:xi+435.Google Scholar
- Meerschaert MM, Tadjeran C: Finite difference approximations for fractional advection-dispersion flow equations. Journal of Computational and Applied Mathematics 2004,172(1):65-77. 10.1016/j.cam.2004.01.033MATHMathSciNetView ArticleGoogle Scholar
- Liu P, Elaydi SN: Discrete competitive and cooperative models of Lotka-Volterra type. Journal of Computational Analysis and Applications 2001,3(1):53-73. 10.1023/A:1011539901001MATHMathSciNetView ArticleGoogle Scholar
- Matignon D: Stability results of fractional differential equations with applications to control processing. Proceeding of the IMACS-IEEE Multiconference on Computational Engineering in Systems Applications (CESA '96), July 1996, Lille, France 963:Google Scholar
This article is published under license to BioMed Central Ltd. 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.