具有非线性扰动的时滞混沌神经网络系统同步控制

Adaptive Synchronization Control for Time-delay Chaotic Neural Network System with Nonlinear Perturbations

本文基于参数辨识和自适应控制研究了具有非线性扰动的时滞混沌神经网络系统的同步控制。所有的连接权值矩阵可以通过自适应律进行估计。此外,当非线性扰动的上界未知情况下,所设计的自适应同步控制器可以使主从系统达到同步。利用Lyapunov稳定性理论可以证明误差系统的稳定性。最后,通过一个数值仿真实验,验证了所提出方法的有效性。

In this study,the synchronization of time-delay chaotic neural networks system with nonlinear perturbations is developed based on parameter identification and adaptive control.All the connection weight matrixes can be efficiently estimated by adaptive laws.Moreover,the adaptive synchronization controller designed when the upper bound of nonlinear perturbations is unknown,which can make derive system and salve system achieve synchronization.Lyapunov stability theory is referred to prove the error system stable.Numerical simulations demonstrate the effectiveness of the proposed method.