Research Article | Open Access
Yingjia Guo, "The Stability of Solutions for a Fractional Predator-Prey System", Abstract and Applied Analysis, vol. 2014, Article ID 124145, 7 pages, 2014. https://doi.org/10.1155/2014/124145
The Stability of Solutions for a Fractional Predator-Prey System
We study a class of fractional predator-prey systems with Holling II functional response. A unique positive solution of this system is obtained. In order to prove the asymptotical stability of positive equilibrium for this system, we study the Lyapunov stability theory of a fractional system.
We consider the following fractional predator-prey model with Holling Type II functional response: where and represent the population densities of prey and predator at time , respectively. The parameters , , , , , and are positive constants that stand for prey intrinsic growth rate, carrying capacity, the maximum ingestion rate, half-saturation constant, predator death rate, and the conversion factor, respectively. One of the most popular predator-prey models with Holling Type II functional response is established in [1, 2]. The asymptotic behavior of a stochastic predator-prey system with Holling Type II functional response is studied in . The existence and asymptotical stability of equilibria and limit cycles for predator-prey systems with Holling II are obtained in . A more complicated case about predator-prey systems is studied in [5, 6]. White noise is always present in natural world; Liu et al. studied the asymptotic behavior of a stochastic predator-prey system with Holling II functional response.
However, in the real world, there are still many problems that cannot be solved by usual prey-predator model. Some complexity on multiscale analysis can be simplified by the fractional order calculus. Fractional differential equations have been studied in many other fields, for example, economic , physics [8–10], material , and so forth. In this paper, we present a fractional prey-predator model (1) to describe the ecosystem which performs well in the practical problem.
We will study long time behavior of system (1). If , then system (1) has a unique positive equilibrium: The positive equilibrium is asymptotically stable, which is proved in Section 5. The fractional derivative of (1) is modified Riemann-Liouville derivative, which is established in [12, 13]. There are some good properties on the fractional derivative to study fractional system, such as the chain rule and fractional Taylor series. The details of modified Riemann-Liouville derivative are given in Section 2. We show that there is a unique nonnegative solution of (1) in Section 3. In order to prove that the positive equilibrium is stable, we give a Lyapunov stability theorem of the fractional system in Section 4.
2.1. Fractional Derivative via Fractional Difference
Definition 1. Let , , be a continuous function, and let be a constant discretization span. Define the forward operator ; that is, (the symbol := means that the left side is defined by the right one) Then the fractional difference of order , , of is defined by the expression and its derivative of fractional order is defined by the expression
2.2. Modified Riemann-Liouville Derivative
Definition 2 (Riemann-Liouville definition revisited). Refer to the function of Definition 1. Then its fractional derivative of order is defined by the expression
For positive , one will set
2.3. Useful Relations
Here we give some properties of the modified Riemann-Liouville derivative (see ) which are used further in this paper.(i)Consider (ii)Useful differential relation: (iii)Consider (iv)The chain rule:
2.4. Integration with respect to
The solution of the equation is defined by the following result (see ).
Lemma 3. Let denote a continuous function; then the solution of (12) is defined by the equality
3. Existence and Uniqueness of the Nonnegative Solution
Theorem 4. For any initial value , there is a unique global solution of system (1) on .
Proof. Note that the coefficients of system (1) are locally Lipschitz continuous for the given initial value ; there is a unique local solution on , where is the explosion time. Hence, we know that , is a unique positive local solution of system (1). To show that this solution is global, we need to show that . Let be sufficiently large so that , all lie within the interval . For each integer , define
Clearly, is increasing as . Set , where . If we can show that , then and for all . In other words, to complete the proof all we need to show is that . If this statement is false, then there is a constant such that Hence there is an integer such that Define a -function by where is a positive constant to be determined later. Using the chain rule, we get Choose such that ; then where is a positive constant. Then
Therefore, on the one hand, Using the equality (13), we have which implies that
On the other hand, using the differential relation (9), Therefore, Set for . Note that there is at least one of and that equals either or ; then Hence, Let lead to the contradiction that , . So we must therefore have .
4. Lyapunov Stability Theory
Consider the equation Here, and are -dimensional column vectors. Suppose that and is continuous in and satisfies local Lipschitz condition.
Definition 5 (Lyapunov Stability). is said to be stable (or Lyapunov stable) if, given , there exists a such that, for any satisfying , the solution of (28) is defined for and has the following inequality:
We remark that a solution which is not stable is said to be unstable.
Definition 6 (asymptotic stability). is said to be asymptotically stable if it is Lyapunov stable and there exists such that, for any satisfying , .
Define a -scalar function in
Using the chain rule, we have
Theorem 7. Let be function satisfying , .(i)If , then system (28) has a stable null solution;(ii)if , then system (28) has an asymptotically stable null solution;(iii)the null solution of system (28) is unstable provided that .
Proof. Consider the following.
Case 1 . Consider Obviously, Let ; then .
Let ; the right maximal interval of existence of for (30) is .
That is to say, for , Then .
Using (9), Therefore, Thus, from (32), we obtain
Case 2. We can easily know that the system (28) has a stable null solution. We will consider that there exists such that for any satisfying then .
Let ; then for , . is bounded for ; then there exists increasing which converges to such that Suppose . One obtains Since , then Using (9) yields Therefore, we have Besides, for any satisfying , which implies that Then according to (38), It is easy to verify that, for any , Note that when , which implies that Let and note that is continuous and is continuous for initial value; we have which contradicts (45).
Case 3 . Suppose system (28) has a stable null solution; then , , ; we have , .
Let , ; according to condition (iii) in Theorem 7, we know Then there exists satisfying .
Next, we show ; then there exists , such that Thus, Noting that is bounded and is unbounded when , this contradiction shows that the null solution of system (28) is unstable when .
Example 8. Consider the stability of the null solution of system: where . Define a function . Then , , , . Here by Theorem 7 the system has a stable solution.
Example 9. Consider the stability of the null solution of system: Define a function , where . Obviously, , , , ; we can choose the constants such that , . Then and by Theorem 7 the system has an asymptotically stable null solution.
5. The Stability of the Solution
Since , then there is a positive equilibrium of system (1), and Let where is a positive constant to be determined later. Then using the chain rule, we have Choose such that yields
Note that Then Note that Then
Hence, from these arguments, we get the following result.
Conflict of Interests
The author declares that there is no conflict of interests regarding the publication of this paper.
The author thanks Professor Y. Li for his valuable discussion.
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