Research Article  Open Access
Bifurcation and Feedback Control of an Exploited PreyPredator System
Abstract
This paper makes an attempt to highlight a differential algebraic model in order to investigate the dynamical behavior of a preypredator system due to the variation of economic interest of harvesting. In this regard, it is observed that the model exhibits a singularity induced bifurcation when economic profit is zero. For the purpose of stabilizing the proposed model at the positive equilibrium, a state feedback controller is therefore designed. Finally, some numerical simulations are carried out to show the consistency with theoretical analysis and to illustrate the effectiveness of the proposed controller.
1. Introduction and Model Description
Biological resources in the preypredator ecosystem are commercially harvested and sold with the aim of achieving economic interest. For this reason, harvesting plays an important role in the study of biological resources. Furthermore, the harvest effort is usually influenced by the variation of economic interest of harvesting. To formulate a biological economic system from an economic point of view and to investigate the dynamical behavior of the model, many scientists use differentialalgebraic equations. The differential equations investigate the dynamics of prey and predators and the algebraic equation studies the harvest effort on prey from an economic perspective.
Differentialalgebraic system has been applied widely in power system, aerospace engineering, chemical process, social economic systems, biological systems, network analysis, and so on. With the help of the differential algebraic model for power systems and bifurcation theory, the complex dynamical behavior of power systems, specially the bifurcation phenomena which can reveal instability mechanisms of power systems, has been extensively studied by Marszalek and Trzaska [1], Ayasun et al. [2], Yue and Schlueter [3], and others. Again, the application of differential algebraic model has an immense impact on the analysis of biological system.
I am aware that harvesting has a strong impact on the dynamics of populations. Depending on the applied harvesting strategy, the long run stationary density of a population may be significantly smaller than the long run stationary density of a population without harvesting. Harvesting can lead to the incorporation of a positive extinction probability, even if in the absence of harvesting, a population can be free from extinction risk. If a population is subjected to a positive extinction rate, then harvesting can drive the population density to a dangerously low level at which extinction becomes sure no matter how the harvest affects the population afterwards. Some works on predatorprey species with harvesting can be found in Das et al. [4], Kar et al. [5], Clark [6], and Song and Chen [7]. Kar and Pahari [8], Kar and Ghosh [9], and Kumar et al. [10] have studied the dynamics in preypredator models with harvesting and have obtained complex dynamics behavior, such as stability of equilibria, Hopf bifurcation, limit cycle, and heteroclinic bifurcation. Zhang and Q.L. Zhang [11] systematically studied a hybrid predator prey economic model, which is formulated by differentialdifferencealgebraic equations. They proved that this model exhibits two bifurcations phenomena at the intersampling instants. Kar and Chakraborty [12] have discussed a bioeconomic model with harvesting and removed the singularity induced bifurcation as well as the instability behavior towards the positive economic profit by means of feedback control theory.
However, in this context of the above studies, this paper tries to examine the dynamical behavior of a biological economic prey predator model where the prey population is harvested using differential algebraic equation and bifurcation theory. I consider the model with zero economic profit, and singularity induced bifurcation is obtained at the interior equilibrium of the model. To reduce the singularity induced bifurcation, a state feedback controller is designed.
In this paper, I develop a twospecies predatorprey model. I consider a logistic growth function of the prey and a Holling type III response function. Thus the growth rate of the prey is formulated as where and represent the prey and predator populations, respectively, at time is the carrying capacity of the prey, is the intrinsic growth rate of the prey, is the predation coefficient, and is the half saturation constant.
The growth rate of the predator population is taken in the following form: where is the conversion factor (I assume that , since the whole biomass of the prey is not transferred to the biomass of the predator), is the death rate of predator, and is the coefficient of intraspecific competition of the predator population. Here are positive constants.
For considering the exploited prey system, I introduce a scaled harvesting effort for the prey and then the equations governing my model become
For system (3), the supply amount of harvested prey into the market is [6], where is the catchability coefficient of the prey population. Simultaneously, an algebraic equation is also developed by considering the economic interest of harvesting according to Gordon’s economic theory of a common property resource [13]. He established the economic interest of the yield of harvest effort as net economic revenue is equal to total revenue (TR) − total cost (TC). In my problem, total revenue (TR) and total cost (TC) in system (3) are given by and .
Since the net economic revenue ; therefore, where is the price per unit harvested biomass, is the cost per unit harvest effort, and is the economics interest of harvesting.
Based on (3) and (4), a differential algebraic system consisting of two differential equations and one algebraic equation is established as
The advantage of the differential algebraic system is that it offers a simpler (than ordinary differential systems) way to study the dynamical behaviour of the system due to the variation of economic interest of harvesting.
The differentialalgebraic model (5) can be expressed in the following form: where
2. The Model with Zero Economic Profit
When the economic profit is zero, system (5) takes the following form:
2.1. The Interior Equilibrium: Existence
The interior equilibrium exists provided that and where
The Jacobian matrix for the differential algebraic equations (DAE’s) (8) at an arbitrary point is given by
2.2. Singular Point and Singularity Induced Bifurcation in a Differential Algebraic Equations (DAEs) System
The DAEs system [14] can be put in the following form: where , , with , , and which are all positive integers. In this particular section, is the dynamic state vector whose time evaluation is directly connected by the equation (12a), is the instantaneous state vector which satisfies the constraint equation (12b), and the parameter set defines a specific system configuration and operating condition.
Then according to Venkatasubramanian et al. [15], denote the set of all equilibria of the DAEs system (12a)(12b) to be and the set of all stable equilibria as where is the set of all eigenvalues corresponding to the Jacobian matrix of the system (12a)(12b). Also denote the singular surface , and corresponding point on is known as singular point which plays an important role in differential algebraic system. In a DAEs system the singularity induced bifurcation (SIB) occurs if equilibrium crosses the singular surface at bifurcation point. Trajectories cross the singularity in a finite time with an infinite speed and the system may change its stability due to an eigenvalue diverging to infinity. This type of bifurcation can be analyzed with the help of the following theorem.
Theorem 1 (singularity induced bifurcation theorem). Suppose that the system (12a)(12b) satisfies the following conditions at the singular equilibrium . : has a simple zero eigenvalue and trace is nonzero. : is nonsingular. : is also nonsingular.
Then according to Venkatasubramanian et al. [15], there exists a smooth curve of the equilibrium in which passes through and is transversal to the singular surface at . When increases through , one eigenvalue of the Jacobian matrix of the system (12a)(12b) moves from to if (resp., from to if ) along the real axis by diverging through infinity. The rest of the eigenvalues remain bounded and stay away from the origin. The constants and can be computed by evaluating the following:
Theorem 2. The differentialalgebraic model (5) has a singularity induced bifurcation at the interior equilibrium , and the economic parameter ( is the economic interest of harvesting) is a bifurcation value. Furthermore, a stability switch occurs as increases through 0.
Proof. Let
where and is a bifurcation parameter.
It can be calculated that
Furthermore, it can also be calculated that
According to the part A of Venkatasubramanian et al. [15], can be defined as follows:
Now,
Based on the above analysis, three items can be obtained as follows.(i) has an algebraically simple zero eigenvalue and trace .(ii)
is nonsingular at .(iii)It can be shown that
is nonsingular at .
It is observed from (i) to (iii) that all the conditions for singularity induced bifurcation (Venkatasubramanian et al. [15]) are satisfied. Hence the differentialalgebraic model system (5) has a singularity induced bifurcation at the positive equilibrium and the bifurcation value is . Again it is noted that
The inequality (23) satisfies Theorem 3 in Venkatasubramanian et al. [15]. According to Theorem 3 [15] when increases through 0, one eigenvalue (denoted by ) of the differentialalgebraic model (5) moves from along the real axis by diverging through infinity. Consequently, the movement behavior of this eigenvalue influences the stability of the differentialalgebraic model (5).
Other eigenvalues of the differentialalgebraic model (5) at can be calculated as follows. The Jacobian of the differentialalgebraic model (5) evaluated at takes the following form:
According to the leading matrix in the model (6) and , I obtain the characteristic equation of the differentialalgebraic model (5) at as det, which can be expressed as follows: . Consequently, it can calculate that another eigenvalue of the differentialalgebraic model (5) at is . It shows that the eigenvalue is negative. And hence the eigenvalue is continuous, nonzero, and cannot jump from one halfopen complex plane to another as increases through 0. Therefore they are continuous and bounded in the half plane as increases through 0 and their movement behaviors has no influence on the stability of the differentialalgebraic model (5) at the positive equilibrium .
Table 1 shows the change in the sings of the real parts of the eigenvalues and due to variation of economics interest of harvest effort.
According to Table 1 and the stability theory, it can be concluded that the differentialalgebraic model (5) is stable at as and it is unstable at as . Consequently, a stability switch occurs as increases through 0. This completes the proof.

3. State Feedback Control for Singularity Induced Bifurcation
In consequence to the above theorem, it is clear that the differential algebraic model (5) becomes unstable when the economic interest of harvesting is considered to be positive. A state feedback controller is designed to eliminate the singularity induced bifurcation and stabilize the differentialalgebraic model (5) at the interior equilibrium of the model (8).
According to the leading matrix in the model and in (24), it can be calculated that rank . By using Theorem 22.1 in Dai [16], it is shown that the differentialalgebraic model (5) is locally controllable at . Consequently, a state feedback controller can be applied to stabilize the differentialalgebraic model (5) at the interior equilibrium of the model (5).
By using the Theorem 31.2 in Dai [16], a state feedback controller ( is a feedback gain and is the component of the interior equilibrium ) can be applied to stabilize the differentialalgebraic model (5) at the interior equilibrium .
Apply the controller into the differentialalgebraic model (5) and then a controlled differentialalgebraic model is as follows:
Theorem 3. If the feedback gain satisfies the inequality then the differentialalgebraic model (26) is stable at of the model (8).
Proof. The Jacobian of the differentialalgebraic model (26) evaluated at the interior equilibrium takes the following form:
The characteristic equation of the matrix is given by
where
By using the RouthHurwitz criteria (Kot, [17]), it can be concluded that the model (26) is stable at the equilibrium , of the system (8), if the feedback gain satisfies the following condition:
Therefore, applying the feedback controller into the model (5), the system can be stabilized around the interior equilibrium and the impulsive phenomenon due to singularity induced bifurcation can be eliminated. This elimination of singularity induced bifurcation implies that the ecological balance in the preypredator system is restored.
4. Numerical Simulation
With the help of Matlab 7.0, and Mathematica 5.2, a numerical simulation is provided to substantiate the theoretical result which has been established in the previous sections of this paper. The parameters values are set in appropriate units as follows: , , , , , , , , , and . By virtue of these given parameters, the differentialalgebraic model (5) takes the following form:
When economic interest is zero (i.e., ), the system (32) has a positive equilibrium . When , the eigenvalues are −0.0692, −973.5813 and then they become −0.0691, 967.2611 when . It is obvious that one eigenvalue remains almost constant and another one moves from along the real axis by diverging through .
A state feedback controller can be applied to stabilize the differentialalgebraic model (32) at , and then the differentialalgebraic model (32) with the state feedback controller takes the following form:
By using Theorem 3, if the feedback gain satisfies , then the differentialalgebraic model (33) is stable at and the singularity induced bifurcation of the differentialalgebraic model (32) is also eliminated. Now considering the feedback gain , which is greater than 1.44998, I find that an interior equilibrium of the differential algebraic model (33) is (0.808079, 2.303551, 0.332081), when , and the eigenvalues are −0.0691, −169298.8247, and consequently the system is stable (see Figure 1). Also when and , an interior equilibrium of the differential algebraic model (33) becomes (0.808011, 2.303309, 0.332203) and the eigenvalues are −0.0691, −4222.0930, and consequently the system is stable (see Figure 2) in this case also.
5. Concluding Remarks
In this paper, I proposed a harvested differentialalgebraic preypredator model, which is governed by two differential equations and an algebraic equation. The differential equations investigate the dynamics of prey and predator and the algebraic equation studies the harvest effort on prey from an economic perspective. Dynamical behavior of the model is investigated due to the variation of the economic interest of harvesting. It is found that singularity induced bifurcation takes place when the net economic revenue is zero. In consequence to the aforesaid bifurcation, an impulsive phenomenon occurs and the system becomes unstable around the interior equilibrium. A state feedback controller is designed to eliminate the singularity induced bifurcation and stabilize the differentialalgebraic model around the interior equilibrium. Numerical simulation is used to show the effectiveness of the state feedback controller. The biological meaning of the proposed controller is that enhancing the harvest effort on preys can not only prevent the stability switch of the preypredator model, but also drive the model to a stable equilibrium.
However the model and its dynamical behavior are studied mainly on the deterministic framework. In this regard, I can say that it will be more realistic to consider the model in a stochastic environment due to either ecological or economic fluctuations. This needs further future work in this context.
Conflict of Interests
The author declares that there is no conflict of interests regarding the publication of this paper.
Acknowledgment
The author is very thankful to his supervisor Dr. Tapan Kumar Kar, Department of Mathematics, Bengal Engineering and Science University, Shibpur, for his valuable comments and suggestions in the preparation of this paper.
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Copyright
Copyright © 2014 Uttam Das. 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.