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Sandwich synchronization of memristorbased hyperchaos systems with time delays
Advances in Difference Equations volumeÂ 2018, ArticleÂ number:Â 19 (2018)
Abstract
In this paper, a memristorbased hyperchaotic system is introduced. Considering time delays between the drive system and the response system in the process of synchronization, this paper designs one kind of flexible sandwich controller, which includes a rest in the sandwich structure, to realize the synchronization between two memristorbased hyperchaotic systems. Based on Lyapunov stability theory, matrix inequality, sandwich control and considering time delays, the exponential synchronization conditions for the memristorbased hyperchaotic systems with time delays via sandwich control are given. Finally, simulation results are displayed to verify the effectiveness and feasibility of this method.
1 Introduction
Memristor as the fourth fundamental circuit element was first proposed by Chua [1] in 1971 based on logical symmetry arguments, and it was realized by HewlettPackard [2] research team in 2008. This passive electronic device has generated unprecedented worldwide interest because of its potential applications in signal processing, programmable logic, control system, neural network, braincomputer interface [3], etc.
Recently, the research on memristorbased circuits is becoming a hot topic. A lot of memristor oscillator systems have been used in generating signals which are found in satellite communications, radio, switching power supply, etc. [4â€“10]. With the potential memristor applications, it is necessary to do some deep research on the related nonlinear memristorbased oscillator systems [11â€“13]. Itoh and Chua [14] derived several nonlinear oscillators from Chuaâ€™s oscillators by replacing Chuaâ€™s diodes with memristors. Bao et al. [15, 16] studied the complicated dynamical behaviors of the memristor oscillators. Although various memristorbased chaotic systems have been researched in recent years [17â€“19], the research of synchronization between two memristorbased hyperchaotic systems is rarely reported. Because the synchronization of the memristorbased chaotic systems is a challenging problem [20â€“23], chaotic behavior, especially the hyperchaotic behavior that has more than one positive Lyapunov exponent, may be uncoordinated and unpredictable.
Sandwich control is one kind of discontinuous control. It can be used in many industrial fields [24]. It could include many subsystems that are continuous. Feng et al. [25] studied the sandwich structure control system that includes two continuous controls and an impulsive control in each period and applied it to control Chuaâ€™s oscillator. While this paper will talk about another kind of flexible sandwich structure, which is different from [25]. In each period of this sandwich control system, the first and third parts of the control system are continuous controls, which may be continuous controls with different control gains. Between these two parts, there is a rest. This kind of sandwich control structure is very suitable for these systems that cannot be controlled continuously all the time.
In this paper, we apply this kind of sandwich control to ensure the synchronization between two memristorbased hyperchaotic systems. We pay attention to time delays between the drive system and the response system when we control the error system [26â€“29], because there are always some transmission time delays between the drive system and the response system in the real environment. Based on Lyapunov stability theory, matrix inequality, sandwich control and considering time delays, the exponential synchronization conditions for the memristorbased hyperchaotic systems with time delays via sandwich control are given.
2 The fourthorder memristorbased hyperchaotic system
Memristor is a nonlinear circuit element, and its value is not unique. Assume that the fluxcontrolled memristor is characterized by the mathematical model of a smooth continuous cubic monotoneincreasing nonlinearity [15]
where a and b are parameters. From equation (1), the memductance \(W(\varphi )\) is obtained as follows:
Consider one kind of fourthorder memristorbased hyperchaotic oscillator system as FigureÂ 1 shows. It is directly extended from Chuaâ€™s oscillator by replacing Chuaâ€™s diode with a smooth fluxcontrolled memristor and a negative conductance [14, 30, 31]. In this memristorbased hyperchaotic circuit, these two parts, passive memristor (fluxcontrolled memristor) and negative conductance, can be considered an active memristor.
According to KCL and KVL, this circuit can be described by the following differential equations.
where C refers to capacitor, V denotes voltages, \(W(\varphi )\) is memductance, R denotes resistors, Ï†, L, i, G are magnetic flux, inductor, current and conductance, respectively. From equations (2) and (3), it follows that
If we let \(x_{1}=V_{1}\), \(x_{2}=V_{2}\), \(x_{3}=i\), \(x_{4}=\varphi \), \(\gamma_{1}=\frac{1}{C_{1}R_{1}}\), \(\gamma_{2}=\frac{1}{C_{1}R_{1}}\frac{G}{C _{1}}+\frac{a}{C_{1}}\), \(\gamma_{3}=\frac{3b}{C_{1}}\), \(\gamma_{4}=\frac{1}{C _{2}R_{1}}\), \(\gamma_{5}=\frac{1}{C_{2}}\), \(\gamma_{6}=\frac{1}{L}\) and \(\gamma_{7}=\frac{R_{2}}{L}\), system (4) can be further expressed as follows:
If we set \(\gamma_{1}=15\), \(\gamma_{2}=3.2\), \(\gamma_{3}=19.7\), \(\gamma _{4}=1\), \(\gamma_{5}=1\), \(\gamma_{6}=15\), \(\gamma_{7}=0.52\) for the initial states \((10^{4}, 10^{4}, 10^{4}, 10^{4})^{T}\), by means of a computer program with MATLABÂ 7.0, computer simulation shows that system (5) has hyperchaotic attractors as shown in FigureÂ 2.
Remark 1
Although various memristorbased chaotic systems have been researched extensively in recent years, the research of memristorbased hyperchaotic systems is rarely reported and investigated directly. Thus the hyperchaotic system (5) is important for understanding of memristorbased hyperchaotic systems.
3 Synchronization of the memristorbased hyperchaotic systems with time delays
In this section, system (5) is taken as two parts, that is,
where \(x(t)={{({{x}_{1}}(t), {{x}_{2}}(t), {{x}_{3}}(t), {{x}_{4}}(t))} ^{T}}\),
Because \(g(x)\) satisfies the Lipschitz condition, for any \(x, x' \in \Omega \), we have
where L is the Lipschitz coefficient.
If we take system (6) as the drive system, the response system is described by
where y is the state variable, \(y(t)=({{y}_{1}}(t), {{y}_{2}}(t), {{y}_{3}}(t), {{y}_{4}}(t))^{T}\). \(u(t)\) is the sandwich controller, which might be with two different control gains. Considering time delays between the drive system and the response system, \(u(t)\) can be described as the following equations:
where \(I_{1}\) and \(I_{2}\) refer to control gains, \(\theta_{1}\) and \(\theta_{2}\) are the percentages of each period T, \(\theta_{1}+ \theta_{2}<1\). Let \(e(t)=y(t)x(t\tau )\), then \(e(t)\) is the synchronization error between system (6) and system (8) with time delays. The error system can be described by the following equation:
If we apply sandwich control to system (10), then the error system can be redescribed as three subsystems:
Remark 2
In the real environment, there are always some time delays between the drive system and the response system. Thus considering time delays between the drive system and the response system in the process of synchronization is of great practical significance.
Remark 3
The sandwich control put forward by this paper is a general model, which can be used as a prototype of other discontinuous controls that include more than two continuous controls with different control gains in each period.
Lemma 1
([32])
Given any real matrices \(\Sigma_{1}\), \(\Sigma_{2}\), \(\Sigma_{3}\) of appropriate dimensions and a scalar \(\varepsilon > 0\) such that \(0 < \Sigma_{3} = \Sigma_{3}^{T}\), the following inequality holds:
Next, we will find the proper T, \(I_{1}\), \(I_{2}\), \(\theta_{1}\), \(\theta _{2}\), \(s_{1}\), \(s_{2}\), \(s_{3}\) to ensure the synchronization between drive system (6) and response system (8). In other words, if the stability of error system (11) can be guaranteed, drive system (6) and response system (8) can realize synchronization.
Theorem 1
Suppose there are three positive scalars (\(s_{1}>0, s_{2}>0\), \(s_{3}>0\), \(\varepsilon_{1}>0\), \(\varepsilon_{2}>0\) and \(\varepsilon _{3}>0\)) and the following conditions hold:

(1)
\(A+A^{T}+2I_{1}E+\varepsilon_{1} BB^{T}+\varepsilon_{1}^{1} \tilde{L}^{2}E+s_{1}E\le 0\),

(2)
\(A+A^{T}+\varepsilon_{2}BB^{T}+\varepsilon_{2}^{1}\tilde{L}^{2}Es _{2}E\le 0\),

(3)
\(A+A^{T}+2I_{2}E+\varepsilon_{3} BB^{T}+\varepsilon_{3}^{1} \tilde{L}^{2}E+s_{3}E\le 0\),

(4)
\({{s}_{1}}{{\theta }_{1}}{{s}_{2}}{{\theta }_{2}}+{{s}_{3}}(1 {{\theta }_{1}}{{\theta }_{2}})>0\), where LÌƒ is the largest Lipschitz coefficient, then error system (11) is exponentially stable. That is, the exponential synchronization between system (6) and system (8) with time delays will be realized.
Proof
Define a Lyapunov function \(V(e(t))=e(t)^{T}e(t)\). When \(nT\le t< nT+ {{\theta }_{1}}T\), the derivative of \(V(e(t))\) with respect to time t of the first subsystem is calculated and estimated as follows:
Through LemmaÂ 1, we get
So that the value of \(\dot{V}(e(t))\) should satisfy
Similarly, when \(nT+{{\theta }_{1}}T\le t< nT+({{\theta }_{1}}+{{\theta } _{2}})T\), the derivative of \(V(e(t))\) with respect to time t of the second subsystem is as follows:
When \(nT+({{\theta }_{1}}+{{\theta }_{2}})T\le t<(n+1)T\), the \(\dot{V}(e(t))\) of the third subsystem is as follows:
Therefore, we get that
Case 1. When \(n=0\), then
Subcase 1. If \(0\le t < \theta_{1}T\), then we have that
Subcase 2. If \(\theta_{1}T \le t <(\theta_{1}+\theta_{2})T\), then we have that
Subcase 3. If \((\theta_{1}+\theta_{2})T\leq t< T\), then we have that
Similarly, we get that
Case 2. When \(n=1\), then
Subcase 1. If \(T \le t < T+\theta_{1}T\), then we have that
Subcase 2. If \(T+\theta_{1}T\le t < T+(\theta_{1}+\theta_{2})T\), then we have that
Subcase 3. If \(T+(\theta_{1}+\theta_{2})T \leq t<2T\), then we have that
By induction, we get the following.
Case \(m+1\). When \(n=m\), then
Subcase 1. If \(mT\leq t< mT+\theta_{1}T\), then we have that
Because \((t\theta_{1}T)/T < m \leq t/T\), then
Subcase 2. If \(mT+\theta_{1}T\leq t< mT+(\theta_{1}+\theta_{2})T\), then we have that
Because \((t+T\theta_{1}T\theta_{2}T)/T < m+1 \leq (t+T\theta_{1}T)/T\), then
Subcase 3. If \(mT+(\theta_{1}+\theta_{2})T \leq t<(m+1)T\), similarly, then we have that
Therefore, in this situation, for any \(t>0\), if \({{s}_{1}}{{\theta } _{1}}{{s}_{2}}{{\theta }_{2}}+{{s}_{3}}(1{{\theta }_{1}}{{\theta } _{2}})>0\), error system (11) is exponentially stable, which implies system (6) and system (8) with time delays can realize exponential synchronization.â€ƒâ–¡
Corollary 1
If there are positive scalars \(\theta_{1}\), \(\theta_{2}\), \({{s}_{1}}\), \({{s}_{2}}\) and \({{s}_{3}}\) that satisfy the condition
where \(0<\theta_{1}+\theta_{2}<1\), \(s_{1} \leq s_{1}^{\prime} =\lambda_{\min}(A ^{T}+A)\lambda_{\min}(BB^{T})2I_{1}\tilde{L}^{2}\), \(s_{2} \geq s_{2} ^{\prime}=\lambda_{\min}(A^{T}+A)+\lambda_{\min}(BB^{T})+\tilde{L}^{2}\), and \(s_{3} \leq s_{3}^{\prime}=\lambda_{\min}(A^{T}+A)\lambda_{\min}(BB^{T})2I _{2}\tilde{L}^{2}\), then the memristorbased hyperchaotic systems (6) and (8) with time delays can realize exponential synchronization.
4 Simulation results
In this section, the simulation results will be displayed. Set \(\gamma_{1}=15\), \(\gamma_{2}=3.2\), \(\gamma_{3}=19.7\), \(\gamma_{4}=1\), \(\gamma_{5}=1\), \(\gamma_{6}=15\), \(\gamma_{7}=0.52\), and let these two systems get their initial values:
According to the boundaries of state variables, we get \(\tilde{L}=4.1794\). When \(I_{1}=8, I_{2}=7\), if we choose \(T=1\), \(\theta_{1}=0.3\), \(\theta_{2}=0.2\), \(s_{1}=5\), \(s_{2}=4\), \(s_{3}=5\) and \(\tau =0.3\), then by TheoremÂ 1 and CorollaryÂ 1, we know that system (11) is exponentially stable. Synchronization between two memristorbased systems with \(\tau =0.3\) is shown in FigureÂ 3.
5 Conclusions
In this paper, the characteristics of a memristorbased hyperchaotic system have been discussed. Based on Lyapunov stability theory, matrix inequality, sandwich control and considering time delays, this paper designed one type of sandwich controller and applied it to realize the exponential synchronization between two memristorbased hyperchaotic systems with transmission time delays. Simulation results were given to verify the effectiveness of this method.
6 Competing interests
The authors declare that they have no competing interests.
References
Chua, LO: Memristor  the missing circuit element. IEEE Trans. Circuit Theory 18(5), 507519 (1971)
Strukov, DB, Snider, GS, Stewartand, DR, Williams, RS: The missing memristor found. Nature 453, 8083 (2008)
Guckert, L, Swartzlander, EE: Optimized memristorbased multipliers. IEEE Trans. Circuits Syst. I, Regul. Pap. 64(2), 373385 (2017)
Bao, B, Liu, Z, Xu, J: Transient chaos in smooth memristor oscillator. Chin. Phys. B 19(3), Article ID 030510 (2010)
Corinto, F, Ascoli, A, Gilli, M: Nonlinear dynamics of memristor oscillators. IEEE Trans. Circuits Syst. I, Regul. Pap. 58(6), 13231336 (2011)
Li, C, Ge, J, Tian, Y: Associative learning of memristive synapses circuits based on spiking neural networks. J.Â Chongqing Univ. 37(7), 115124 (2014) (in Chinese)
Li, Z, Zeng, Y: A memristor oscillator based on a twinT network. Chin. Phys. B 22(4), Article ID 040502 (2013)
Riaza, R: First order memcircuits: modeling, nonlinear oscillations and bifurcations. IEEE Trans. Circuits Syst. I, Regul. Pap. 60(6), 15701583 (2013)
Talukdar, A, Radwan, AG, Salama, KN: Generalized model for memristorbased Wien family oscillators. Microelectron. J. 42(9), 10321038 (2011)
Talukdar, A, Radwan, AG, Salama, KN: Nonlinear dynamics of memristor based 3rd order oscillatory system. Microelectron. J. 43(3), 169175 (2012)
Wu, A, Wen, S, Zeng, Z: Synchronization control of a class of memristorbased recurrent neural networks. Inf. Sci. 183(1), 106116 (2012)
Wu, A, Zeng, Z: Dynamic behaviors of memristorbased recurrent neural networks with timevarying delays. Neural Netw. 36, 110 (2012)
Wu, A, Zeng, Z: Exponential stabilization of memristive neural networks with time delays. IEEE Trans. Neural Netw. Learn. Syst. 23(12), 19191929 (2012)
Itoh, M, Chua, LO: Memristor oscillators. Int. J.Â Bifurc. Chaos 18(11), 31833206 (2008)
Bao, B, Liu, Z, Xu, J: Steady periodic memristor oscillator with transient chaotic behaviours. Electron. Lett. 46(3), 237238 (2010)
Bao, B, Xu, J, Liu, Z: Initial state dependent dynamical behaviors in memristor based chaotic circuit. Chin. Phys. Lett. 27(7), Article ID 070504 (2010)
Zhang, B, Deng, F, Zhao, X, Zhang, C: Hybrid control of stochastic chaotic system based on memristive Lorenz system with discrete and distributed timevarying delays. IET Control Theory Appl. 10(13), 15131523 (2016)
Min, G, Duan, S, Wang, L: A doublewing chaotic system based on ion migration memristor and its sliding mode control. Int. J.Â Bifurc. Chaos Appl. Sci. Eng. 26(8), Article ID 1650129 (2016)
Ding, D, Qian, X, Hu, W, Wang, N, Liang, D: Chaos and Hopf bifurcation control in a fractionalorder memristorbased chaotic system with time delay. Eur. Phys. J.Â Plus 132, Article ID 447 (2017). https://doi.org/10.1140/epjp/i2017116999
Shen, W, Zeng, Z, Wang, G: Feedback stabilization of memristorbased hyper chaotic systems. In: Third International Conference on Information Science and Technology, 2325 March, Yangzhou, Jiangsu, China (2013)
Wu, H, Li, R, Yao, R, Zhang, X: Weak, modified and function projective synchronization of chaotic memristive neural networks with time delays. Neurocomputing 149, 667676 (2015)
Wu, H, Li, R, Wei, H, Zhang, X, Yao, R: Synchronization of a class of memristive neural networks with time delays via sampleddata control. Int. J.Â Mach. Learn. Cybern. 6(3), 365373 (2015)
Huang, J, Li, C, He, X: Stabilization of a memristorbased chaotic system by intermittent control and fuzzy processing. Int. J.Â Control. Autom. Syst. 11(3), 643647 (2013)
Feng, Y, Li, C, Huang, T: Sandwich control systems with impulse time windows. Int. J.Â Mach. Learn. Cybern. 8, 20092015 (2017). https://doi.org/10.1007/s1304201605805
Feng, Y, Li, C, Huang, T: Sandwich control systems. In: Sixth International Conference on Intelligent Control and Information Processing (ICICIP), 2628 November. IEEE, New York (2015). https://doi.org/10.1109/ICICIP.2015.7388134
Huang, T, Li, C, Liu, X: Synchronization of chaotic systems with delay using intermittent linear state feedback. Chaos 18, Article ID 033122 (2008)
Huang, T, Li, C, Duan, S, Starzyk, JA: Robust exponential stability of uncertain delayed neural networks with stochastic perturbation and impulse effects. IEEE Trans. Neural Netw. Learn. Syst. 23(6), 866875 (2012)
Wen, S, Zeng, Z, Chen, MZQ, Huang, T: Synchronization of switched neural networks with communication delays via the eventtriggered control. IEEE Trans. Neural Netw. Learn. Syst. 28(1), 23342343 (2017). https://doi.org/10.1109/TNNLS.2016.2580609
Tu, Z, Jian, J, Wang, K: Global exponential stability in Lagrange sense for recurrent neural networks with both timevarying delays and general activation functions via LMI approach. Nonlinear Anal., Real World Appl. 12(12), 21742182 (2011)
Bao, C, Liu, Z, Xu, J: Transient chaos in smooth memristor oscillator. Chin. Phys. B 19(3), Article ID 030510 (2010)
Wu, A: Hyperchaos synchronization of memristor oscillator system via combination scheme. Adv. Differ. Equ. 2014, Article ID 86 (2014). https://doi.org/10.1186/16871847201486
Sanchez, EN, Perez, JP: Inputtostate stability (ISS) analysis for dynamic neural networks. IEEE Trans. Circuits Syst. I, Fundam. Theory Appl. 46(11), 13951398 (1999)
Acknowledgements
The authors sincerely thank the referees for their helpful suggestions, which greatly improved the paper. This research is supported by Chongqing Municipal Key Laboratory of Institutions of Higher Education (Grant No. [2017]3) and Program of Chongqing Development and Reform Commission (Grant No. 2017[1007]).
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Wu, H., Xiong, J., Hu, X. et al. Sandwich synchronization of memristorbased hyperchaos systems with time delays. Adv Differ Equ 2018, 19 (2018). https://doi.org/10.1186/s1366201714514
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DOI: https://doi.org/10.1186/s1366201714514
Keywords
 memristorbased
 hyperchaotic system
 time delays
 synchronization
 sandwich control