Mathematical Problems in Engineering

Volume 2016 (2016), Article ID 7068479, 14 pages

http://dx.doi.org/10.1155/2016/7068479

## Effective Control and Bifurcation Analysis in a Chaotic System with Distributed Delay Feedback

^{1}Department of Mathematics and Information Science, Beifang University of Nationalities, Yinchuan, Ningxia 750021, China^{2}Department of Mathematics and Statistics, Zhoukou Normal University, Zhoukou, Henan 466001, China

Received 21 September 2015; Accepted 26 November 2015

Academic Editor: Ivanka Stamova

Copyright © 2016 Wei Tan et al. 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.

#### Abstract

We discuss the dynamic behavior of a new Lorenz-like chaotic system with distributed delayed feedback by the qualitative analysis and numerical simulations. It is verified that the equilibria are locally asymptotically stable when and unstable when ; Hopf bifurcation occurs when crosses a critical value by choosing as a bifurcation parameter. Meanwhile, the explicit algorithm for determining the direction of the Hopf bifurcation and the stability of the bifurcating periodic solutions is derived by normal form theorem and center manifold argument. Furthermore, regarding as a bifurcation parameter, we explore variation tendency of the dynamics behavior of a chaotic system with the increase of the parameter value .

#### 1. Introduction

As one of the important discoveries in 21st century, chaos has been extensively investigated in many fields over the last several decades, which has been widely applied in secure communication, signal processing, radar, image processing, power system protection, flow dynamics, and so on. As is known chaos is undesirable and needs to be controlled in many practical applications. Therefore, the investigation of controlling chaos is of great significance. Many schemes have been presented to carry out chaos control [1–17] of which using time-delayed controlling forces proves to be a simple and viable method for a continuous dynamical system.

Recently, a new Lorenz-like system has been introduced in [18, 19] as follows:where , , , , , and . System (1) exhibits bifurcation and period orbits by taking as the bifurcation parameter and putting , , , , and . In particular, when , there appears to be chaotic attractor in [19] (see Figure 3). The conditions of Hopf bifurcation occurring and the stability analysis of the equilibrium points have been studied in detail in [19].

In order to reveal the forming mechanism of the chaotic attractor structure, its controlled system is proposed in [18] as follows: where , , , , , and . The system exhibits the period-doubling bifurcations taking as the bifurcation parameter and fixing , , , , , and (see Figure 2). See [18] for more details. In the controller, one can see that when is large enough, chaos attractor disappears and the stable family of limit cycles appears; when is small enough, a complete chaos attractor appears.

With purpose of reflecting and controlling the complex and unpredictable dynamical behavior of the model depending on the past information of the system, it is necessary to incorporate time delay into this system. The signal error of current state and past state of the continuous time system will be given distributed delay feedback to the system itself.

As compared with the former method, a chaotic model with distributed delay feedback is more general than that with discrete delay feedback [10–13], because the distributed delay becomes a discrete delay when the delay kernel is a delta function at a certain time. The distributed delay has found widespread applications in many fields such as neural network [14, 16], complicated real models [15], and the modeling of aggregative processes involving the flow of entities with random transit times through a given process [17]. Therefore, it is of considerable significance to propose distributed delays as control input to control the chaotic system.

Many studies have been made in [18, 19] about the Lorenz-like system. In this paper, we present the Hopf bifurcation of a Lorenz-like system with the distributed delay. We not only display numerical simulation of Hopf bifurcation in delayed feedback Lorenz-like system, but also give the theoretical proof. The stability of the equilibrium point will vary complicatedly setting different values of the feedback intensity coefficient . Regarding the delay variable as a branch of parameters, when passes through a critical value, the stability of the equilibrium point will change from instability to stability, and then the chaos phenomenon of the system disappears. Finally, the stable periodic solution emerges. Furthermore, flat malicious point of the original system will not change and retain some features of the original system.

Motivated by the above works, we, in this paper, add a time-delayed force to the third equation of system (1); then system (1) takes the form where , , , , , , , and .

The rest of this paper is organized as follows. In Section 2, the stability and the existence of Hopf bifurcation are determined. In Section 3, based on the normal form method and the center manifold theorem presented in Hassard et al. [20], the direction, stability, and the period of the bifurcating period solutions are analyzed. In Section 4, numerical simulations are given to verify the theorem analysis. Finally, Section 5 concludes some discussions.

#### 2. Bifurcation Analysis of Lorenz-Like System

In this section, we will study the stability of the equilibria and the existential conditions of local Hopf bifurcations. As the Lorena-like system (3) is symmetric about the -axis, and have the same stability. It is sufficient to discuss the stability of equilibrium .

By the linear transform system (3) becomesThe linearization of (5) near is given by The Jacobian matrix of (6) at is written as whose characteristic equation is given byIn this paper, we focus on considering the weak kernel case; that is, , where . As to the general gamma kernel case, we can make a similar analysis. We give the initial condition of system (6) asThe characteristic equation (8) with the weak kernel case takes the form whereIn view of the well known Routh-Hurwitz criterion, we can conclude that all the roots of (10) have negative real parts if the following conclusions hold: Based on the analysis above, we can easily obtain the following result.

Theorem 1. *The equilibrium of system (3) with the weak kernel is locally asymptotically stable if the following conditions are fulfilled:Let () be the roots of (10); then we have If there exists , such that and , then, by Routh-Hurwitz criterion, there exists a pair of purely imaginary roots and that are satisfied: if and are real, then and ; if and are complex conjugate, then . It is easy to calculate that and thus the Hopf bifurcation occurs near when passes through .*

Theorem 2. *Suppose (13) for (10) is satisfied; then system (3) admits the following results:*(i)*If , system (3) undergoes a Hopf bifurcation at the equilibria , respectively.*(ii)*If , the equilibria of system (3) are locally asymptotically stable.*(iii)*If , the equilibria of system (3) are unstable.*

*Remark 3. *It is shown that if (13) is fulfilled, then the states , and of system (1) will tend to , , and , when If (13) is satisfied, then the states , and of system (1) may coexist and remain in an oscillatory model near the equilibrium Thus, chaos vanishes, which means that chaos can be controlled.

*3. Direction and Stability of Hopf Bifurcation Period Solution*

*In this section, we will establish the explicit formulae determining the direction, the stability, and the period of these periodic solutions bifurcating from the equilibrium at the critical value of by using the normal form theory and the center manifold reduction developed by Hassard et al. [20]. Let ; then system (3) undergoes the Hopf bifurcation at the equilibrium for . And then are purely imaginary roots of the characteristic equation at the equilibrium . System (3) can be written as a functional differential equation (FDE) in aswhere and .*

*Definewhere and , *

*For , define and define the bilinear inner productwhere Obviously and are adjoint operator. By the discussion in Section 2, we know that are eigenvalues of . Thus they are eigenvalues of . We need to calculate the eigenvectors of and corresponding to and , respectively. Let be the eigenvalues of ; that is, , and then we have We can obtain where Similarly, assume that is the eigenvector of corresponding to From the definition of , we have where*

*Since , we can have where is a constant such that ; by (18), we get Therefore, we can choose as *

*Next, we employ the idea of Hassrd et al. in [20] to compute the coordinates describing the center manifold coat . Let be the solution of (3) when .*

*Definingon the center manifold , we get wherewhere and are local coordinates for center manifold in the direction of and .*

*Note that is also real if is real. For the solution , because , we have That is,whereLet ; we have *

*Comparing the coefficients of (33) with (34), we getSince , , , , and in are unknown, we still need to compute them, so we have We can rewritewhereComparing the coefficients, we getFor ,comparing the coefficients of (38) with (40), gives By (39) and (41) and the definition of , we obtainSince , we get where is a constant vector.*

*Similarly, in view of (39) and (41) and the definition of we get where is a constant vector.*

*Next, we will seek appropriate in (43) and (45), respectively; by the definition of and (41),*

*we have where By (41), we get For is the eigenvalues of and is the corresponding eigenvector, we obtain Substituting (43) and (48) into (46), we obtain which is equivalent to It follows that whereSimilarly, substituting (44) and (49) into (47), we have Consequently, we can determine and . Thus, all can be determined by [7]. Following the basic idea of [7] and the method in [20], one can draw the conclusion about the bifurcation direction and the stability of the Hopf bifurcation, which are determined by the following parameters: which determines the quantities of bifurcating periodic solutions on the center manifold ; namely, we have the following result.*

*Theorem 4. determines the direction of the Hopf bifurcation, if ; determines the stability of the bifurcating period solutions: the bifurcation period solutions are orbitally stable (unstable) if , and determines the period of the bifurcating periodic solutions: the period increases (decreases) if .*

*4. Computer Simulations*

*In this section, we give numerical simulation result of system (3) to certify our theoretical analysis. Let us consider the following system: where , . By simple calculation, we know (57) has three equilibrium points , , and . For equilibrium point will be stable. Furthermore, we conclude that the bifurcating periodic solution is also stable in the phase space even though it is stable in the center manifold. From the equilibria , all the conditions indicated in Theorem 4 are satisfied. By means of Matlab 7.8.0, we get . Thus the equilibria , are asymptotically stable when which is illustrated by the computer simulations (see Figures 1, 3, 4, and 5). When passes through the critical value , the equilibria , lose their stability and Hopf bifurcation occurs (see Figure 6) and quasi-periodic solutions appear (see Figure 7). With increasing of , the bifurcation numerical simulations show the bifurcating quasi-periodic solutions disappear when , and chaos occurs again (see Figures 1 and 8).*