Synchronization between two different noise-perturbed chaotic systems with unknown parameters

In this paper, a general method of synchronizing noise-perturbed chaotic systems with unknown parameters is proposed. Based on the LaSalle-type invariance principle for stochastic differential equations and by employing a combination of feedback control and adaptive control, some sufficient conditions of chaos synchronization between these noise-perturbed systems with unknown parameters are established. The model used in the research is the chaotic system, but the method is also applicable to the hyperchaotic systems. Unified system and noise-perturbed RSssler system, hyperchaotic Chen system and nolse-perturbed hyperchaotic RSssler system are taken for illustrative examples to demonstrate this technique.[第一段]     

Adaptive generalized synchronization between Chen system and a multi-scroll chaotic system

Based on Lyapunov theory, the adaptive generalized synchronization between Chen system and a multi-scroll chaotic system is investigated. According to the form of target function a proper adaptive controller is designed, by which the controlled Chen system can be synchronized with a multi-scroll chaotic system including unknown parameters. The Lyapunov direct method is exploited to prove that the synchronization error and parameter identification error both converge to zero. Numerical simulation results verify the feasibility of the proposed method further.     

Parameter identification and synchronization of an uncertain Chen chaotic system via adaptive control

A systematic design process of adaptive synchronization and parameter identification of an uncertain Chen chaotic system is provided.With this new and effective method,parameter identification and synchronization of the Chen system,with all the system parameters unknown,can be achieved simultaneously.Theoretical proof and numerical simulation demonstrate the effectiveness and feasibility of the proposed method.     

Theoretical and experimental study of Chen chaotic system with notch filter feedback control

Since the past two decades, the time delay feedback control method has attracted more and more attention in chaos control studies because of its simplicity and efficiency compared with other chaos control schemes. Recently, it has been proposed to suppress low-dimensional chaos with the notch filter feedback control method, which can be implemented in a laser system. In this work, we have analytically determined the controllable conditions for notch filter feedback controlling of Chen chaotic system in terms of the Hopf bifurcation theory. The conditions for notch filter feedback controlled Chen chaoitc system having a stable limit cycle solution are given. Meanwhile, we also analysed the Hopf bifurcation direction, which is very important for parameter settings in notch filter feedback control applications. Finally, we apply the notch filter feedback control methods to the electronic circuit experiments and numerical simulations based on the theoretical analysis. The controlling results of notch filter feedback control method well prove the feasibility and reliability of the theoretical analysis.     

A new four-dimensional hyperchaotic Chen system and its generalized synchronization

Based on the Chen chaotic system, a new four-dimensional hyperchaotic Chen system is constructed, and the basic dynamic behaviours of the system were studied, and the generalized synchronization has been observed in the coupled four-dimensional hyperchaotic Chen system with unknown parameters. The Routh--Hurwitz theorem is used to derive the conditions of stability of this system. Furthermore based on Lyapunov stability theory, the control laws and adaptive laws of parameters are obtained to make generalized synchronization of the coupled new four-dimensional hyperchaotic Chen systems. Numerical simulation results are presented to illustrate the effectiveness of this method.     

Adaptive regulation of uncertain chaos with dynamic neural networks

A novel adaptive control for uncertain nonlinear chaotic system is presented. A dynamical neural networks is used to perform ‘black box' identification. Based on the identifier, the state feedback control is employed to drive the unknown chaotic system toward the desired target. Simulations show the derived control via the neuro-identifier turns out to be very effective.     

Chaos synchronization between two different 4D hyperchaotic Chen systems

This paper presents chaos synchronization between two different four-dimensional (4D) hyperchaotic Chen systems by nonlinear feedback control laws. A modified 4D hyperchaotic Chen system is obtained by changing the nonlinear function of the 4D hyperchaotic Chen system, furthermore, an electronic circuit to realize two different 4D hyperchaotic Chen systems is designed. With nonlinear feedback control method, chaos synchronization between two different 4D hyperchaotic Chen systems is achieved. Based on the stability theory, the functions of the nonlinear feedback control for synchronization of two different 4D hyperchaotic Chen systems is derived, the range of feedback gains is determined. Numerical simulations are shown to verify the theoretical results.     

LMI-based output feedback fuzzy control of chaotic system with uncertainties

This paper studies the robust fuzzy control for nonlinear chaotic system in the presence of parametric uncertainties. An uncertain Takagi--Sugeno (T--S) fuzzy model is employed for fuzzy modelling of an unknown chaotic system. A sufficient condition formulated in terms of linear matrix inequality (LMI) for the existence of fuzzy controller is obtained. Then the output feedback fuzzy-model-based regulator derived from the LMI solutions can guarantee the stability of the closed-loop overall fuzzy system. The T--S fuzzy model ofthe chaotic Chen system is developed as an example for illustration. The effectiveness of the proposed controller design methodology is finally demonstrated through computer simulations on the uncertain Chen chaotic system.     

Adaptive Control on a Class of Uncertain Chaotic Systems

By using a simple combination of feedback entrainment control (with an updating feedback strength) and adaptive scheme, for a large class of chaotic systems, it is proven rigorously by using the invariance principle of differential equations that all unknown model parameters can be estimated dynamically and the uncertain system can be controlled to an arbitrary desired smooth orbit. The illustration of the Lorenz system and the corresponding numerical results on the effect of noise are given.     

Adaptive lag synchronization of uncertain dynamical systems with time delays via simple transmission lag feedback

In this paper we present an adaptive scheme to achieve lag synchronization for uncertain dynamical systems with time delays and unknown parameters. In contrast to the nonlinear feedback scheme reported in the previous literature, the proposed controller is a linear one which only involves simple feedback information from the drive system with signal popagation lags. Besides, the unknown parameters can also be identified via the proposed updating laws in spite of the existence of model delays and transmission lags, as long as the linear independence condition between the related function elements is satisfied. Two examples, i.e., the Mackey-Glass model with single delay and the Lorenz system with multiple delays, are employed to show the effectiveness of this approach. Some robustness issues are also discussed, which shows that the proposed scheme is quite robust in switching and noisy environment.     

Chen系统的自适应追踪控制

利用非线性单输入控制器实现混沌Chen系统的自适应追踪控制.根据Chen系统的结构特点选取合适的反馈方式，设计单输入自适应控制器，使Chen系统自适应追踪参数未知的Rossler系统的某一变量，并由Lyapunov直接方法证明误差信号渐近稳定于零.数值仿真结果表明该控制方法可行，且可以实现未知参数的辨识.     

不确定Chen系统的参数辨识与自适应同步

研究了不确定Chen系统的自适应同步和参数辨识，设计了自适应控制器和参数更新规则，理论证明了该控制器可使得两个Chen系统——驱动系统和未知参数的响应系统渐进地达到同步，并且可以辨识出响应系统的未知参数.数值模拟结果证明了该控制器的有效性. 关键词： 不确定Chen系统 自适应同步 参数辨识 控制器     

Chen氏混沌电路实现与同步控制实验研究

对Chen氏混沌系统的电路实现作了进一步的研究，推导出切实可行的电路参数.在此基础上利用Electronic Workbench电路仿真软件进行了仿真实验，并搭建实现了实际的Chen氏电路，在示波器上观察到了Chen氏混沌系统的混沌波形.同时，利用单变量耦合反馈控制方法对两个Chen氏系统的同步控制进行了实验研究，给出了实现同步的电路参数调节范围. 关键词： 混沌系统 Chen氏混沌 同步控制 电路实现     

Global exponential synchronization between Lü system and Chen system with unknown parameters and channel time-delay

This paper proposes a nonlinear feedback control method to realize global exponential synchronization with channel time-delay between the Lü system and Chen system,which are regarded as the drive system and the response system respectively.Some effective observers are produced to identify the unknown parameters of the Lü system.Based on the Lyapunov stability theory and linear matrix inequality technique,some sufficient conditions of global exponential synchronization of the two chaotic systems are derived.Simulation results show the effectiveness and feasibility of the proposed controller.     

Aharonov–Bohm effect in the ghost interference

Chaotic systems demonstrate complex behaviour in their state variables and their parameters, which generate some challenges and consequences. This paper presents a new synchronisation scheme based on integral sliding mode control (ISMC) method on a class of complex chaotic systems with complex unknown parameters. Synchronisation between corresponding states of a class of complex chaotic systems and also convergence of the errors of the system parameters to zero point are studied. The designed feedback control vector and complex unknown parameter vector are analytically achieved based on the Lyapunov stability theory. Moreover, the effectiveness of the proposed methodology is verified by synchronisation of the Chen complex system and the Lorenz complex systems as the leader and the follower chaotic systems, respectively. In conclusion, some numerical simulations related to the synchronisation methodology is given to illustrate the effectiveness of the theoretical discussions.     

Parameter estimation for chaotic systems with a Drift Particle Swarm Optimization method

Inspired by the motion of electrons in metal conductors in an electric field, we propose a variant of Particle Swarm Optimization (PSO), called Drift Particle Swarm Optimization (DPSO) algorithm, and apply it in estimating the unknown parameters of chaotic dynamic systems. The principle and procedure of DPSO are presented, and the algorithm is used to identify Lorenz system and Chen system. The experiment results show that for the given parameter configurations, DPSO can identify the parameters of the systems accurately and effectively, and it may be a promising tool for chaotic system identification as well as other numerical optimization problems in physics.