Research Article | Open Access
Changjin Xu, Peiluan Li, Maoxin Liao, Zixin Liu, Qimei Xiao, Shuai Yuan, "Control Scheme for a Fractional-Order Chaotic Genesio-Tesi Model", Complexity, vol. 2019, Article ID 4678394, 15 pages, 2019. https://doi.org/10.1155/2019/4678394
Control Scheme for a Fractional-Order Chaotic Genesio-Tesi Model
In this paper, based on the earlier research, a new fractional-order chaotic Genesio-Tesi model is established. The chaotic phenomenon of the fractional-order chaotic Genesio-Tesi model is controlled by designing two suitable time-delayed feedback controllers. With the aid of Laplace transform, we obtain the characteristic equation of the controlled chaotic Genesio-Tesi model. Then by regarding the time delay as the bifurcation parameter and analyzing the characteristic equation, some new sufficient criteria to guarantee the stability and the existence of Hopf bifurcation for the controlled fractional-order chaotic Genesio-Tesi model are derived. The research shows that when time delay remains in some interval, the equilibrium point of the controlled chaotic Genesio-Tesi model is stable and a Hopf bifurcation will happen when the time delay crosses a critical value. The effect of the time delay on the stability and the existence of Hopf bifurcation for the controlled fractional-order chaotic Genesio-Tesi model is shown. At last, computer simulations check the rationalization of the obtained theoretical prediction. The derived key results in this paper play an important role in controlling the chaotic behavior of many other differential chaotic systems.
As is known to us, chaos control issue has been widely studied in the last decades because of its potential practical value in various areas. How to control the chaotic phenomenon to serve human beings has become a hot issue in today’s world. Chaos control has attracted much attention of researchers from various fields. In recent years, many chaos control techniques (for example, delayed feedback approach , Ott–Grebogi–York (OGY) technique , variable structure control , observer-based control , backstepping design technique , and active control ) have been proposed. Many excellent fruits have been reported. For example, Kocamaz et al.  investigated the chaos control by applying the sliding mode control technique; Chen  proposed an adaptive feedback control technique for chaos and hyperchaos control; Din  studied the chaos control of a discrete-time prey-predator system by using three different types of feedback control strategies; Singh and Gakkhar  controlled the chaos of a food chain model with a time-delayed feedback controller; Yan et al.  discussed the chaos control of continuous unified chaotic systems applying discrete rippling sliding mode control. For more knowledge on chaos control, readers can refer to [12–19, 34–44].
In 1992, Genesio and Tesi  put up the chaotic Genesio-Tesi system:where denote different voltage of electronic components and are all negative coefficients. Genesio and Tesi  investigated the chaotic behavior of model (1) by applying harmonic balance approaches. In 2012, Guan et al.  discussed the chaos control of model (1) by designing distributed delay feedback controller. By analyzing the characteristic equation of the controlled Genesio-Tesi model, the sufficient conditions to ensure the stability of the equilibrium point and the existence of Hopf bifurcation for the controlled Genesio-Tesi model are established. In addition, the stability and the direction of bifurcating periodic solution are determined by the centre manifold theorem and normal form theory. In 2009, Sun  proposed a tracking control to realize chaos synchronization for the Genesio-Tesi chaotic system (1) based on the time-domain approach. In 2007, Park  designed a novel feedback controller to realize exponential synchronization of the Genesio-Tesi chaotic system (1). In 2009, Park  further considered the functional projective synchronization problem for the Genesio-Tesi chaotic system (1) and Zhou and Chen  dealt with the Hopf bifurcation and Si’lnikov chaos of Genesio model (1).
It is worth mentioning that all the above papers focus only on the integer-order differential models. In recent years, many researchers argue that fractional-order differential equations play a key role in describing the real phenomena and are found to have potential applications in various areas such as physics, economics, physics, heat transfer, and chemical engineering [26–28]. Thus, it is important to deal with the fractional-order differential models. Based on discussion above, we revise model (1) in the following fractional-order form:where denote different voltage of electronic components, are all negative coefficients, and denotes the fractional order. Model (2) is the commensurate fractional-order system. Let and , then the chaotic phenomenon will occur in model (2). The fact is shown in the following (see Figures 1 and 2).
This paper mainly focuses on two aspects: (a) designing two appropriate controllers to control the chaotic phenomenon of model (2) and (b) revealing the impact of time delay on the stability and bifurcation behavior of the controlled fractional-order Genesio-Tesi chaotic model. The superiority of this paper can be summarized as follows:(a)A new fractional-order Genesio-Tesi chaotic model is proposed(b)Two controllers are designed to control the chaotic phenomenon of the fractional-order Genesio-Tesi chaotic model(c)The advantages and disadvantages of two controllers are compared
The outline of this paper is organized as follows: In Section 2, some elementary knowledge on fractional-order differential is prepared. In Section 3, two different control techniques are designed to control the chaotic phenomenon of the fractional-order chaotic Genesio-Tesi model. In Section 4, two examples are given to illustrate the theoretical analysis. In Section 5, we end this manuscript with conclusion.
2. Elementary Knowledge
In this section, we list several basic results about fractional-order differential equations.
Definition 1 (see ). The Caputo fractional-order derivative is defined as follows:where , , and m is a positive integer such that . If , then
Lemma 1 (see ). Denote the root of the characteristic equation of the autonomous systemwhere Then, system (6) is asymptotically stable and also stable , and those critical eigenvalues that satisfy have geometric multiplicity one.
Lemma 2 (see ). For the systemwhere , the characteristic equation takes the following form:
Remark 1. In Lemma 1 and Lemma 2, we say that system (6) (or system (7)) is asymptotically stable (or stable), implying that the fixed point E of system (6) (or system (7)) is asymptotically stable (or stable).
3. Chaos Control via Time-Delayed Feedback Controllers
It is easy to see that system (2) has two unique equilibrium points:
A long time ago, there were many publications that handle the chaos control issue of integer-order differential models by applying time-delayed feedback controllers. But the studies on the chaos control of fractional-order chaotic models via time-delayed feedback controllers are very rare. To make up the deficiency, in this paper, we will design two time-delayed feedback controllers to eliminate the chaotic behavior of system (2). In this paper, we are concerned only with the equilibrium point . The other equilibrium point is easily analyzed in a similar way.
3.1. Adding Time-Delayed Feedback Controller to the First Equation of Model (2)
In this section, we add a time-delayed feedback controller to the first equation of model (2), and then system (2) takes the following form:where is the gain coefficient and ϱ is the time delay. The linear system of system (10) near the equilibrium point reads
The corresponding characteristic equation of (11) takes the following form:
Suppose that is the root of (13), then we getwhere
In view of (15), we have
By (19), we have
By (20), we havewhere
Proof of Lemma 3(i). According to (25), we haveIn view of , we have , . In view of , we know that (26) does not possess positive real roots. Furthermore, is not the root of (13). This proves Lemma 3(i).
Proof of Lemma 3(ii). According to , and , and such that Hence, (26) possesses at least two positive real roots and (13) possesses at least two pairs of purely imaginary roots. This proves Lemma 3 (ii).
Next, the hypothesis is given: where
Lemma 4. Suppose that is the root of (13) around such that , then
Proof of Lemma 4. In view of (13), we getSincewe obtainwhereThus,It follows from thatThis proves Lemma 4.
Next, the hypothesis is given:
Lemma 5. If and holds true, then system (13) is locally asymptotically stable.
The following results are established by above discussion.
Theorem 1 (under the condition of Lemma 3(ii)). Suppose that and hold true, then (i) the equilibrium point of system (10) at the origin is locally asymptotically stable if and (ii) a Hopf bifurcation will happen near the equilibrium point if .
3.2. Adding Time-Delayed Feedback Controller to the Second Equation of Model (2)
In this section, we add a time-delayed feedback controller to the second equation of model (2), and then system (2) becomeswhere is the gain coefficient and ρ is the time delay. The linear equation of equation (39) around is
The characteristic equation of (40) takes the following form:
Assume that is the root of (42), then we havewhere
According to (44), we get
By (46), we have
In view of (49), we havewhere
By (52), we have
Proof of Lemma 6(i). In view of (55), we haveIn view of , we have , . In view of , we know that (56) does not possess positive real roots. Furthermore, is not the root of (42). This proves Lemma 6(i).
Next, we give the hypothesis as follows: where
Lemma 7. Assume that is the root of (42) around