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

机译:不确定统一混沌系统的神经网络自适应控制与同步

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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.
机译:提出了一种基于细胞神经网络的不确定统一混沌系统的自适应控制与同步方案。统一混沌系统对其系统参数敏感,可以分别显示Lorenz系统,Lü系统和Chen系统。基于李雅普诺夫稳定性理论,设计了具有相应参数更新律的自适应控制器,从而可以渐近地控制或同步化不同的统一混沌系统。另外,所提出的方法保证了控制器独立于不确定参数。数值模拟被用来证明所提出的方案的有效性。

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