FPGA Implementation of Novel Synchronization Methodology for a New Chaotic System

This paper investigates the adaptive - synchronization of the fractional-order chaotic systems with nonidentical structures. Based on the stability of fractional-order systems and adaptive control technique, a general formula for designing the controller and parameters update law is proposed to achieve adaptive - synchronization between two different chaotic systems with different structures. The effective scheme parameters identification and - synchronization of chaotic systems can be realized simultaneously. Furthermore, two typical illustrative numerical simulations are given to demonstrate the effectiveness of the proposed scheme, for each case, we design the controller and parameter update laws in detail. The numerical simulations are performed to verify the effectiveness of the theoretical results.

In this paper, we proposed the FPGA implementation of complete synchronization methodology for a novel chaotic systems using adaptive control scheme. Chaotic systems are non linear dynamical system having at least one positive Lyapunov exponents. In this paper, first we derived a new adaptive controller and parameter update law to synchronize the identical novel chaotic system using adaptive control theory and Lyapunov stability theorem. Then the novel chaotic system, adaptive controllers and the synchronized chaotic system are implemented in FPGA vertex 6 using Xilinx System Generator technology. After implementation, the RTL schematic diagram, the source consumed by the novel chaotic system and the synchronized systems are obtained. The Isim smulation results are also given to show the effectiveness of our proposed synchronization methodology.

Sector-condition-based results for adaptive control and synchronization of chaotic systems under input saturation

This paper proposes a new finite-time controller that realizes multi-switching synchronization of chaotic systems with bounded disturbances using the drive and response system synchronization arrangement. The finite-time controller derives the synchronization error to zero within a specified time. The proposed controller consists of three basic terms; each of them accomplishes a distinct objective: (1) stability of the control loop, (2) smooth and fast convergence behavior of the synchronization error, and (3) disturbance rejection. This study also devises a methodology for designing the finite-time controller and describes a general approach that furnishes a systematic procedure for the analysis of the closed loop. The smooth behavior terminology introduced in (2) refers to the over-damped convergence of the synchronization error signals to zero and the synthesis of chattering-free control effort. The analysis, which assures the global stability of the closed loop, uses the second stability theorem of the Lyapunov, while the finite-time stability technique determines the finite-time convergence. This paper includes simulations of two numerical examples for the validation of the theoretical findings and discusses the comparative analysis. The proposed methodology is suitable to design controllers for a wide range of hyper(chaotic) systems. The contributions of the paper are: (1) describe an innovative generalize analytical methodology for the multi-switching combination synchronization of chaotic systems and (2) propose a novel controller design that insures the finite-time synchronization.

In this paper, we propose a control method for the synchronization of chaotic systems that does not require the systems to be connected, unlike existing methods such as that proposed by Pecora and Carroll in 1990. The method is based on the reinforcement learning algorithm. We apply our method to two discrete-time chaotic systems with mismatched parameters and achieve M step delay synchronization. Moreover, we extend the proposed method to the synchronization of continuous-time chaotic systems.

The coexistence of anti-synchronization and synchronization in chaotic systems is investigated. A novel algorithm is proposed to determine the variables of the master system that should anti-synchronize with corresponding variables of the slave system. Control strategies that guarantee the coexistence of synchronization and anti-synchronization in the unified chaotic system are presented; while numerical simulations are employed to validate and illustrate the effectiveness of the proposed method.

Chaotic neural networks consisting of a great number of chaotic neurons are able to reproduce the rich dynamics observed in biological nervous systems. In recent years, the memristor has attracted much interest in the efficient implementation of artificial synapses and neurons. This work addresses adaptive synchronization of a class of memristor-based neural chaotic systems using a novel adaptive backstepping approach. A systematic design procedure is presented. Simulation results have demonstrated the effectiveness of the proposed adaptive synchronization method and its potential in practical application of memristive chaotic oscillators in secure communication.

We examine the effect of additive noise and drift, in the dynamics of a chaotic driving signal, on the synchronization of chaotic response systems. Simple scaling laws associated with the synchronization deviation level under these types of contamination are presented. Time series used as the driving signals are experimentally measured from an electronic circuit and a mechanical system (a vibrating wire). The response systems are models that were obtained by fitting an ordinary differential equation to time series data. The possible relevance of this work to nondestructive testing, system identification, and communications is discussed. Finally, we present some results regarding the relationship between the synchronization deviation level and the coupling strength.

In this paper a topic regarding the synchronization of chaotic systems is dealt with: the case of separation and synchronization of many chaotic signals generated by different chaotic circuits and combined together is examined. In particular, an observer based strategy has been adopted, and an approach for the simultaneous stabilization of many Luenberger observers has been investigated to face the problem of separation and synchronization. The design strategy is based on linear matrix inequalities (LMIs). Indeed, the LMI problem is referred to have a solution if a dual optimization problem admits a solution. In our case the feasibility condition, if it does exist, allows us to establish that the separation and synchronization problem for the chosen circuit admits a solution. Some numerical simulations are reported. Further results refer to an experimental circuit showing the suitability of the approach. Furthermore, the use of the proposed scheme to transmit two or more information masked into two or more multiplexed chaotic signals and the design of suitable parameters through the introduced technique based on LMIs are discussed.

Chaos has important applications in physics, chemistry, biology, ecology, secure communications, cryptosystems and many scientific branches. Control and synchronization of chaotic systems are important research problems in chaos theory. Sliding mode control is an important method used to solve various problems in control systems engineering. In robust control systems, the sliding mode control is often adopted due to its inherent advantages of easy realization, fast response and good transient performance as well as insensitivity to parameter uncertainties and disturbance. In this work, we first investigate research in the dynamic analysis and properties of the enzymes-substrates reactions system with ferroelectric behaviour in the brain waves which was studied by Enjieu Kadji et al. (Chaos Solitons Fractals 32:862–882, 2007, [10]). Next, we apply multivariable super-twisting sliding mode control to globally stabilize all the trajectories of the enzymes-substrates biological chaotic system. Furthermore, we use multivariable super-twisting sliding mode control for the global chaos synchronization of identical enzymes-substrates biological chaotic systems. Super-twisting sliding mode control is very useful for the global stabilization and synchronization of the enzymes-substrates reaction system as it achieves finite time stability for the system. Numerical simulations using MATLAB are shown to illustrate all the main results derived in this work.

In this research work, we announce a six-term novel 3-D dissipative chaotic system with two quadratic nonlinearities. First, this work describes the dynamic equations and qualitative properties of the novel chaotic system. We show that the novel chaotic system has three unstable equilibrium points. We also show that the novel chaotic system has a rotation symmetry about the \(x_3\) axis. The Lyapunov exponents of the novel chaotic system are obtained as \(L_1 = 1.2334, L_2 = 0\) and \(L_3 = -4.7329\). Since the sum of the Lyapunov exponents is negative, the novel chaotic system is dissipative. Also, the Kaplan-Yorke dimension of the novel chaotic system is derived as \(D_{KY} = 2.2606\). Next, this work describes the active synchronization of identical novel chaotic systems with known parameters. Furthermore, this work describes the adaptive synchronization of identical novel chaotic systems with unknown parameters. Both the active and adaptive synchronization results are established using Lyapunov stability theory. MATLAB simulations are depicted to illustrate all the main results derived in this work for the six-term novel 3-D novel chaotic system.

A new adaptive iterative learning control (AILC) scheme is proposed to solve the finite-time hybrid function projective synchronization (HFPS) problem of chaotic systems with unknown periodic time-varying parameters. Fourier series expansion (FSE) is introduced to deal with the problem of uncertain time-varying parameters. The bound of the expanded remaining items is unknown. A typical convergent series is used to deal with the unknown bound in the design process of the controller. The adaptive iterative learning synchronization controller and parameter update laws are designed. Two different chaotic systems are synchronized asymptotically according to different proportional functions on a finite time interval by Lyapunov stability analysis. The simulation example proves the feasibility and effectiveness of the proposed method.

This paper investigates the problem of fuzzy impulsive control to synchronize two chaotic systems using a novel time-dependent Lyapunov function approach. Compared with the existing time-independent Lyapunov methods, the proposed method enables us to exploit more information on the impulsive intervals. Initially, using the Lyapunov technique and two parameterized linear matrix inequality (LMI) techniques, some less conservative synchronization criteria via a fuzzy impulsive controller using the states of both drive and response chaotic systems are derived. Subsequently, an LMI approach to designing such a fuzzy impulsive controller is developed to realize the synchronization. Finally, the proposed method is applied to the chaotic Lorenz system and Rosler system to illustrate its effectiveness.

PurposeThe purpose of this paper is to propose a novel and secure image transmission based on the unpredictable behavior of the chaotic systems.Design/methodology/approachThe proposed approach includes two main contributions: synchronization scheme and transmission scheme. The synchronization scheme benefits the advantage of the fractional-order active synchronization method. A new control law is derived to asymptotically synchronize the underlined fractional-order Bloch chaotic system. The validity of the proposed synchronization scheme is proved by the Lyapunov stability theorem. Then, a novel image transmission scheme is designed to transfer image data via chaotic signals, which modulates the encrypted data in the sender signals and demodulates it at the receiver side.FindingsNumerical simulations are provided to show the validity and effectiveness of the proposed image transmission system. Furthermore, the performance of the image transmission system is evaluated using some illustrative examples and their corresponding statistical tests. The results demonstrate the effectiveness of the proposed method in comparison with other proposed methods in this subject.Originality/valueA new chaos-based image transmission system is developed based on the synchronization of Bloch chaotic system. The introduced transmission system is interesting and could be applicable to any kind of secure image/video transmission.

Recently, a new six-term 3-D chaotic system with an exponential nonlinearity was discovered (Sundarapandian, 2013). This novel chaotic system has two saddle focus nodes and hence they are unstable. The maximal Lyapunov exponent (MLE) for the six-term Sundarapandian chaotic system was found as 3.2827 and the Lyapunov dimension of the Sundarapandian chaotic system was found as D <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</sub> = 2.1668. Complete synchronization of chaotic systems deals with the problem of asymptotically synchronizing the states of a pair of chaotic systems called as master and slave systems with the help of controllers attached to the slave system. Complete synchronization of chaotic systems has applications in many engineering areas such as secure communications, secure data encryption, cryptosystems, etc. This paper addresses the design of active and adaptive feedback controllers for completely synchronizing the states of identical six-term Sundarapandian chaotic systems with exponential nonlinearity. Active controllers are used when the system parameters a, b and c are available for measurement and the synchronization result is established using Lyapunov stability theory. Numerical simulations using MATLAB have been shown to demonstrate the proposed active and adaptive synchronization results for the novel chaotic system discussed in this paper.