Adaptive H1 Anti-Synchronization for Time-Delayed Chaotic Neural Networks
نویسندگان
چکیده
In this paper, an adaptive H∞ control scheme is developed to study the antisynchronization behavior of time-delayed chaotic neural networks with unknown parameters. This adaptive H∞ anti-synchronization controller is designed based on LyapunovKrasovskii theory and an analytic expression of the controller with its adaptive laws of parameters is shown. The proposed synchronization method guarantees the asymptotical anti-synchronization of drive and response systems. Furthermore, this method reduces the effect of external disturbance to an H∞ norm constraint. The proposed controller can be obtained by solving a linear matrix inequality (LMI) problem. An illustrative example is given to demonstrate the effectiveness of the proposed method.
منابع مشابه
Linear matrix inequality approach for synchronization of chaotic fuzzy cellular neural networks with discrete and unbounded distributed delays based on sampled-data control
In this paper, linear matrix inequality (LMI) approach for synchronization of chaotic fuzzy cellular neural networks (FCNNs) with discrete and unbounded distributed delays based on sampled-data controlis investigated. Lyapunov-Krasovskii functional combining with the input delay approach as well as the free-weighting matrix approach are employed to derive several sufficient criteria in terms of...
متن کاملAnti-Synchronization of Complex Chaotic T-System Via Optimal Adaptive Sliding-Mode and Its Application In Secure Communication
In this paper, an optimal adaptive sliding mode controller is proposed for anti-synchronization of two identical hyperchaotic systems. We use hyperchaotic complex T-system for master and slave systems with unknown parameters in the slave system. To construct the optimal adaptive sliding mode controller, first a simple sliding surface is designed. Then, the optimal adaptive sliding mode controll...
متن کاملSynchronization of a Class of Delayed Chaotic Neural Networks with Fully Unknown Parameters
This paper presents a global asymptotic synchronization scheme for a class of delayed chaotic neural networks when the parameters of the drive system are fully unknown and different from those of the response system. Using the Lyapunov stability theory and the inverse optimal control approach, an adaptive synchronization controller is proposed to guarantee the global asymptotic synchronization ...
متن کاملIntermittent Impulsive Synchronization of Chaotic Delayed Neural Networks
In this paper, a novel intermittent impulsive synchronization scheme is proposed to realize synchronization of two chaotic delayed neural networks. Intermittent impulsive control breaks through the limitation of the upper bound of the impulsive intervals in general impulsive control. In our synchronization scheme, impulsive control is only activated in the control windows, rather than during th...
متن کاملParameters Identification and Synchronization of Chaotic Delayed Systems Containing Uncertainties and Time-Varying Delay
Time delays are ubiquitous in real world and are often sources of complex behaviors of dynamical systems. This paper addresses the problem of parameters identification and synchronization of uncertain chaotic delayed systems subject to time-varying delay. Firstly, a novel and systematic adaptive scheme of synchronization is proposed for delayed dynamical systems containing uncertainties based o...
متن کامل