Discrete Dynamics in Nature and Society

Discrete Dynamics in Nature and Society / 2019 / Article
Special Issue

Stability and Bifurcations Analysis of Discrete Dynamical Systems

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Research Article | Open Access

Volume 2019 |Article ID 7254121 | 17 pages | https://doi.org/10.1155/2019/7254121

Double Delayed Feedback Control of a Nonlinear Finance System

Academic Editor: Douglas R. Anderson
Received16 Sep 2018
Revised16 Nov 2018
Accepted26 Nov 2018
Published05 Feb 2019

Abstract

In this paper, a class of chaotic finance system with double delayed feedback control is investigated. Firstly, the stability of equilibrium and the existence of periodic solutions are discussed when delays change and cross some threshold value. Then the properties of the branching periodic solutions are given by using center manifold theory. Further, we give an example and numerical simulation, which implies that chaotic behavior can be transformed into a stable equilibrium or a stable periodic solution. Also, we give the local sensitivity analysis of parameters on equilibrium.

1. Introduction

Chaos applied to various disciplines of natural science and social science is a complex dynamic phenomenon. Chaotic systems with nonlinearity have been extensively investigated by many communities [15], and so on. In 1985, chaos was first discovered in the economic field, which had great impact imposed on the prominent economies. In economic field, chaos means that the economic operation has its intrinsic uncertainty.

Nonlinear methods are an important research method that has been widely used to explain complex economic phenomena [610]. In economic field, financial risks mean the possibilities of suffering losses caused by uncertainly endogenous factors in financial or investment activities, which displays irregularly fluctuations. The source of risks derives from the strange attractor, while the key of risk management is to control the chaotic attractor. In fact, one of the features of chaos in the economic system is financial crisis. In the passed few decades, a lot of ways to control or synchronize chaos have been proposed, such as OGY method [11], PC method [12], fuzzy control [13], impulsive control [1418], linear feedback control [1923], delayed feedback method [2429], multiple delayed feedback control [3035], and so on. Nowadays, the delayed dynamic systems occupy a central position in many fields, such as biology, transport control, and chemistry [3639]. Since many economic processes have time-delay characteristics [4044], they are unsuitable using ordinary differential equations (ODEs) to describe. Some authors concluded that the chaotic behavior of a microeconomic system could be stabilized to periodic orbits by using delayed feedback control, which seemed more applicable to experimental systems and avoided heavy data processing. In [6, 7], the authors proposed a financial system including four parts (production, money, stock, and labor force). Furthermore, they proposed a simplified model which is described using three variables: represents the interest rate, represents the investment demand, and represents the price index. The three-dimensional model is given as follows:where is the saving amount, is the cost per investment, and is the elasticity of demand of commercial markets. For system (1), the feedback control with one delay had been studied by many authors [4547]. In 2008, Chen [48] firstly prevented the feedback control with three delays in system (1) as follows:where represent the feedback strengths and represent delays, . In [47], by the numerical simulations, Chen firstly gave the dynamic behavior of system (2) with only one and then gave the dynamic behavior when all and . After that, Woo-Sik Son et al. [49] gave the theory analysis for the above results. We find that system (2) with one delay has obtained complete results and the delayed feedback control method is valid. But system (2) with multiple different delays has not completely been investigated. Therefore, our objective is to study system (2) with two different delays. Next, we assume that and , the other cases are similar to analyze, then system (2) becomes and the delayed feedback control graph is shown in Figure 1, where is the state vector of the system.

We consider system (3) with the parameters , and [50]. When , system (3) has a chaotic attractor (see Figure 2).

We choose the initial conditions for system (3) as where and denotes the Banach space .

This paper is arranged as follows. In Section 2, the stability of equilibrium and existence of Hopf bifurcations are obtained by investigating the distribution of roots of characteristic equation. In Section 3, an algorithm is derived for deciding the properties of the branching periodic solutions by computing center manifold. In Section 4, some numerical simulations are given for verifying the theoretical analyses. In Section 5, the local sensitivity analyses of parameters on equilibrium are given. At last, we give a brief conclusion and discussion.

2. Stability of Equilibrium and Local Hopf Bifurcation

The existence and uniqueness of solutions and stability of equilibrium have always been an important issue for differential and difference systems [5154]. Let the right sides of system (3) be zero; it can obtain the equilibrium as follows.

Lemma 1. (i) If the condition holds, then system (3) has a unique boundary equilibrium .
(ii) If the condition holds, then system (3) has three equilibria: and

Remark 2. If the cost per investment is smaller than some value , then is feasible.

In this paper, it always assumes that holds and only considers the stability of and the other one can be analyzed in the same way.

Let , where , , and , then system (3) becomeswhose characteristic equation iswhereNow we analyze the distribution of roots of (7) by using the method in [55, 56].

When , (7) becomesIt has if .

Let Then and under . By using Routh-Hurwitz criterion, all roots of (9) have negatively real parts if holds.

Next, let and use as parameter, then (7) becomes

Let be the root of (10), then satisfiesSquaring and adding in the both sides of (11), it haswhere

Let , then (12) becomesHence Let and , from Ruan and Wei [55], it knows that (14) has at least one positive root if ; (14) has no positive roots if and ; if , then (14) has positive roots iff Hence, under the condition , it has the following lemma.

Lemma 3. (i) Equation (14) has at least one positive root if .
(ii) Equation (14) has no positive root if and .
(iii) If and , then (14) has one positive roots iff and , where

It assumes that (14) has three positive roots, denoted by . Then (12) has three positive roots . Substituting into (11) yields and furthermore, it haswhere is determined by the sign of . Define

Let be the root of (10) satisfying

Lemma 4. It assumes that . Then

Proof. Substituting into (10) and taking the derivative of both sides with respect to , it has Hence, using and (10), it has where . Since and , then it has

By Lemmas 3 and 4 and applying the Hopf bifurcation theorem for FDE [5761], it has the following theorem.

Theorem 5. When , suppose that is satisfied.
(i) If and , then, for any , all roots of (10) has negatively real parts and is locally asymptotically stable.
(ii) If either or and hold, then has at least a positive root , for , all roots of (10) have negatively real parts, and is locally asymptotically stable.
(iii) If conditions (ii) and hold, then system (3) undergoes Hopf bifurcations at when ,

Remark 6. When and hold, Theorem 5 tells us that, through adjusting the cost per investment, the system will tend to or vibrates around . Under this situation, the state of system goes from order to order, that is, the macroeconomic operation is definite.

It has known that guarantees that all roots of (9) have negatively real parts. Now we assume that is violated. For convenience, denote then (9) becomes

Let , then (23) becomeswhere and

Define From Cardano’s formula, it has the following theorem.

Theorem 7. If , then (24) has a real root and a pair of complex roots , that is to say, (23) has a real root , and a pair of complex roots .
(ii) If , then (24) has three real roots and (23) has also three real roots.

Furthermore, it assumes that

Theorem 8. When , suppose that the condition is satisfied.
(i) If and , then, for any , (10) has at least one root with positively real parts and is unstable.
(ii) If either or and hold, then has at least one positive root , for , (10) has at least one root with positively real parts, and is unstable. In addition, if , then is locally asymptotically stable when , where is the second bifurcating value.
(iii) If conditions (ii) and hold, then system (3) undergoes Hopf bifurcations at when , ,

Remark 9. When and hold, Theorem 8 tells us that it can still adjust the cost per investment , such that the system tends to or vibrates around under some conditions. Under this situation, the state of system goes from chaos to order; that is, the financial crisis may be eliminated.

From the above discussions, it knows that system (3) possibly makes stability switches as varying when . Define is stable interval of . Let and be the root of (7), then it haswhere We know that (26) has finite positive roots . For every fixed , there exists a sequence satisfying (26). Define , . When , are a pair of roots of (7). Hence, by Hopf bifurcation theorem [57], it has the next result.

Theorem 10. Suppose that either or is satisfied and .
(i) If (26) has no positive roots, then for any , all roots of (7) have negatively real parts and is locally asymptotically stable.
(ii) If (26) has positive roots, then all roots of (7) have negatively real parts when and is locally asymptotically stable. In addition, if   holds, then system (3) undergoes Hopf bifurcation at when

Remark 11. When and or hold, Theorem 10 tells us that, through adjusting the parameters (), the system will tend to or vibrates around . Under this situation, the state of system goes from order to order or from chaos to order.

3. Property of Hopf Bifurcation

In the above section, the sufficient conditions that system (3) undergoes a Hopf bifurcation at when have already been obtained. In this section, it assumes that Theorem 10 (ii) is satisfied and establishes the explicit formula for determining the properties of Hopf bifurcation at by using the method developed in [62].

For convenience, it assumes that and lets and drops the bar for simplifying. Then is the Hopf bifurcation value. Since , the phase space , system (3) is transformed into the following FDE in :where and are given, respectively, by where where .

By Riesz representation theorem, there exists a bounded variation function for , such that For , define and

For , it has and system (28) becomes

For and , define and the inner product where It knows that and are adjoint operators, then are eigenvalues of and when

By computations, it can obtain that is the eigenvector of corresponding to the eigenvalue , and is the eigenvector of corresponding to the eigenvalue . Therefore, it has that where

Let be the solution of system (28) at . Define , thenwhere Rewrite (39) aswhere

Substituting (3) and (39) into , it has where

By comparing the coefficients, it can obtain where

Substituting and into and , then can be expressed. Thus we may compute the following important quantities:

Theorem 12. If , Hopf bifurcation is supercritical (subcritical). If , periodic solution is stable (unstable). If , the period of periodic solution is increase (decrease).

4. Numerical Simulations

In this section, we give an example:With these parameters, it can obtain and is satisfied. When , by computation, it can obtain that (12) has two positive roots , . Substituting them into (16) gives, respectively, Furthermore, , . By Theorem 8, is asymptotically stable when and unstable for , which means that the stability switches occur. These results are illustrated in Figures 35.

Let ; we obtain . By Theorem 10, it knows that is asymptotically stable for and . Furthermore, it has and . Therefore, at , the periodic solution is orbitally asymptotically stable, and the Hopf bifurcation is forward (see Figures 6 and 7).

Next, we investigate the effect of two different delays. Firstly, we choose and find system (3) has chaos phenomenon (see Figure 8). When choosing and , we find that chaos phenomenon disappears and the solutions of system (48) approach stable equilibrium (see Figure 9). When choosing and , chaos phenomenon disappears and appears stable periodic solutions (see Figure 10). The above results show that double delayed feedback control is superior to delayed feedback control. Hence, we improve the results in [48].

Using the same methods, it can also obtain the similar results in the following systems by choosing suitable : and

In [48], Chen investigated the dynamics of system (2) with three delays by numerical simulations with and , and Chen found that the dynamics of this case have become more complex (the inverse period doubling, period doubling routes, and chaos). Next, we further consider system (2) with three delays by numerical simulations with , , and . System (2) becomes