Discrete Dynamics in Nature and Society

Volume 2018, Article ID 2950357, 8 pages

https://doi.org/10.1155/2018/2950357

## On the – Chaos Synchronization of Fractional-Order Discrete-Time Systems: General Method and Examples

^{1}Mathematics and Computer Science Department, Tebessa University, 12062, Algeria^{2}Department of Mathematics and Computer Sciences, University of Larbi Ben M’hidi, Oum El Bouaghi, Algeria^{3}Universita del Salento, Dipartimento Ingegneria Innovazione, 73100 Lecce, Italy^{4}Department of Electrical Engineering, College of Engineering, Yanbu, Taibah University, Saudi Arabia

Correspondence should be addressed to Samir Bendoukha; as.ude.uhabiat@ahkuodnebs

Received 19 May 2018; Accepted 6 August 2018; Published 10 September 2018

Academic Editor: Allan C. Peterson

Copyright © 2018 Adel Ouannas 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

In this paper, we propose two control strategies for the – synchronization of fractional-order discrete-time chaotic systems. Assuming that the dimension of the response system is higher than that of the drive system , the first control scheme achieves -dimensional synchronization whereas the second deals with the -dimensional case. The stability of the proposed schemes is established by means of the linearization method. Numerical results are presented to confirm the findings of the study.

#### 1. Introduction

Since the concept of chaos synchronization was first proposed nearly three decades ago, dynamical systems exhibiting chaotic behavior have attracted considerable attention in a number of fields. In addition to the original continuous-time chaotic systems such as Lorenz and Chen systems, discrete-time chaotic systems or maps have been proposed and studied. Among the most widely used 2-component discrete systems of these are the Hénon map [1], the Lozi map [2], and the flow model [3]. Higher-dimensional systems have also been studied such as the generalized Hénon map [4] and the Stefanski map [5]. All of these maps are classified as integer–order signifying that the difference order is integer.

Although fractional calculus was studied by mathematicians as early as the nineteenth century, it wasn’t until recently that it gained popularity in applied science and engineering. For the longest time, the study and application of fractional calculus was limited to continuous time. However, most recently, researchers have diverted their attention to the discrete-time case and attempted to put together a complete theoretical framework for the subject. Perhaps one of the earliest works is that of [6]. Among the most interesting and relevant works on fractional discrete calculus in the last decade is that of [7] where the authors introduce a backward fractional difference operator. In [8], the author discusses the discrete-time difference counterparts of conventional Riemann and Caputo derivatives. More on the general notation of fractional discrete-time calculus can be found in [9, 10]. Furthermore, the numerical formulas corresponding to a fractional difference systems can be found in [11]. Recent studies have examined the stability conditions for fractional discrete-time systems including [12]. Most recently, some advances have been made in relation to chaotic fractional discrete-time systems and their applications. A number of fractional difference maps including the fractional logistic map [13], the fractional sine map [14], fractional Hénon map [15], and fractional cubic logistic map [16].

Chaos synchronization in its simplest form refers to the control of a response chaotic system to force its trajectory towards that of a drive [17]. In this case, the error defined as the difference between the states of the drive and those of the response towards zero as . Numerous other types of synchronization have been proposed in the literature, whereby a general function of the two state vectors is forced to zero instead. The synchronization of integer–order discrete-time systems subject to different definitions of the error has been studied in the literature such as hybrid synchronization [18], generalized synchronization [19], and inverse full state hybrid projective synchronization [20]. As for fractional-order discrete systems, the literature related to their synchronization is still very limited including synchronization of the logistic map [21], synchronization based on the stability condition [22], synchronization of linearly coupled fractional Hénon maps [23], and impulsive synchronization of fractional-order discrete-time hyperchaotic systems [24].

In this paper, we are concerned with the – synchronization of fractional-order discrete-time chaotic systems with different dimensions and non–identical orders. In this scheme, two functions and are used to condition the response and drive states, respectively, such that different values for and lead to different types of synchronization. – synchronization was first proposed by Yan in 2005 [25] for continuous–time dynamical systems. The author developed a backstepping approach with a strict feedback form to synchronize two identical systems. The author, then, extended the – scheme to discrete-time systems [26]. In the years that followed, several algorithms were proposed for the – synchronization of integer-order continuous-time systems including [27–29]. Several studies also looked at the fractional continuous-time case such as [30]. Finally, in [31, 32], the authors investigated – synchronization between integer-order and fractional-order continuous-time systems with different dimensions.

In the next section of this paper, we will present the notation adopted in our study and formulate the – synchronization problem for a fractional-order discrete-time chaotic drive-response pair. We denote the number of states for the drive and response by and , respectively. Sections 3 and 4 present the control laws for the –dimensional and –dimensional cases, respectively. Section 5 presents some numerical results related to two particular examples. Finally, Section 6 provides a general summary of the main findings of this study.

#### 2. Problem Formulation

Consider the following drive and response maps described aswhere and denote the drive and response state vectors, respectively, , , , are nonlinear functions and is a vector controller to be determined by the control laws of the synchronization scheme. Note that denotes the set of natural numbers starting from and .

The notation denotes the Caputo type delta difference of defined over [8]. This operator can be defined asfor , , and . The operator denotes the –th fractional sum of defined in [7] aswith , , and is given in terms of the Gamma function as

For the purpose of this study, we will assume and thus the subscript may be ignored. With these notations in mind, we can go ahead and define the synchronization of our drive-response pair. The following definition is consistent with the literature reviewed earlier in this paper.

*Definition 1. *The drive-response pair (1) is synchronized in the dimension if there exist a controller and two functions and such that

It is easy to observe from Definition 1 that, depending on our choice of the pair , we may end up with one of many synchronization types, namely,

For reasons that will become clear later on, suppose that can be divided into two parts:where is an invertible matrix and is a nonlinear function. In the following two sections, we will present two distinct synchronization schemes of dimensions and , respectively.

#### 3. Synchronization in Dimension

The – synchronization error defined in (5) can be written in the following form:where is an invertible matrix, , and . The order Caputo fractional difference of (8) is of the following form:This can be further simplified towhere is an appropriately chosen control matrix andThe following remark is important.

*Remark 2. *Note that our aim in synchronization is to find a suitable controller that forces the synchronization error to zero asymptotically. Since is part of the response system, the function hinders our process. To overcome this problem, we assumed that can be decomposed into a linear part (matrix ) and some other nonlinear function . The reasoning behind this is that matrix is constant and thus may be factored out of the fractional difference operator.

Before stating the proposed control law and establishing its stability, it is important to state the following theorem, which is essential for our proof. Interested readers are referred to [33] for the proof of this result.

Theorem 3. *The zero equilibrium of the linear fractional-order discrete-time system:where , , and , is asymptotically stable, iffor all the eigenvalues of .*

With this stability result, we are now ready to present our synchronization scheme.

Theorem 4. *The drive-response pair (1) is globally – synchronized in dimension subject towhere is the inverse of and the control matrix is selected such that all the eigenvalues of satisfy*

*Proof. *By substituting (14) into (10), we obtain a new formulation for the error system:Now, it is easy to see that subject to (15), all eigenvalues of matrix satisfy andTherefore, by means of Theorem 3, we establish the global asymptotic stability of the zero solution. Consequently, the drive-response maps (1) are globally synchronized in dimension .

#### 4. Synchronization in Dimension

Let us now move to establish synchronization in dimension . In this section, we assume . We define the following notations: We set the last controller components to zero, i.e., Then, the error system reduces towhere is an invertible matrix and . This can be further simplified towhere is an appropriate control matrix and

To achieve – synchronization between the drive-response maps (1) in dimension , we propose choosingSubstituting (24) into (22) yields the error dynamicsThe following theorem can be proven in the exact same way as Theorem 4.

Theorem 5. *By selecting control matrix such that all the eigenvalues of matrix satisfy , the drive and response maps (1) are globally – synchronized in dimensions subject to (20) and (24).*

#### 5. Numerical Examples

In order to show the validity of the proposed control strategies, let us consider some numerical examples. The 2D fractional Hénon map given byis chosen as the driving map. The fractional Hénon map (26) was proposed in [34]. The authors showed that this map has a chaotic attractor, for instance, when and . In order to unify the notation, (26) can be rewritten aswhereThe chaotic behavior of the drive map is depicted in Figure 1.