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Adaptive neural network synchronization for uncertain strick-feedback chaotic systems subject to dead-zone input

机译:带有死区输入的不确定震荡反馈混沌系统的自适应神经网络同步

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In this paper, an adaptive neural network (NN) synchronization controller is designed for two identical strict-feedback chaotic systems (SFCSs) subject to dead-zone input. The dead-zone models together with the system uncertainties are approximated by NNs. The dynamic surface control (DSC) approach is applied in the synchronization controller design, and the traditional problem of a??explosion of complexitya?? that usually occurs in the backstepping design can be avoided. The proposed synchronization method guarantees the synchronization errors tend to an arbitrarily small region. Finally, this paper presents two simulation examples to confirm the effectiveness and the robustness of the proposed control method.
机译:本文针对死区输入的两个相同的严格反馈混沌系统(SFCS)设计了自适应神经网络(NN)同步控制器。盲区模型以及系统不确定性可以通过神经网络进行近似。动态表面控制(DSC)方法被应用在同步控制器设计中,传统的问题是“爆炸性”。可以避免通常在反推设计中出现的问题。所提出的同步方法保证了同步误差趋于任意小的区域。最后,本文给出了两个仿真示例,以验证所提出控制方法的有效性和鲁棒性。

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