Adaptive control and synchronization of uncertain unified chaotic system by cellular neural networks

This paper presents the adaptive control and synchronization scheme of uncertain unified chaotic system using cellular neural networks. The unified chaotic system is sensitive to its system parameter and can display Lorenz system, Lü system and Chen system, respectively. Based on Lyapunov stability theory, the adaptive controller with its corresponding parameter update law is designed such that the different unified chaotic system can be controlled or synchronized asymptotically. In addition, the proposed method guarantees the controller is independent of the uncertain parameter. A numerical simulation is used to demonstrate the effectiveness of the proposed scheme.