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Adaptive Integral Observer-Based Synchronization for Chaotic Systems with Unknown Parameters and Disturbances

机译:基于自适应的积分观察者的混沌系统同步,具有未知参数和干扰

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摘要

Considering the effects of external perturbations on the state vector and the output of the original system, this paper proposes a new adaptive integral observer method to deal with chaos synchronization between the drive and response systems with unknown parameters. The analysis and proof are given by means of the Lyapunov stability theorem and Barbalat lemma. This approach has fewer constraints because many parameters related to chaotic system can be unknown, as shown in the paper. Numerical simulations are performed in the end and the results show that the proposed method is not only suitable to the representative chaotic systems but also applied to some neural network chaotic systems.
机译:考虑到外部扰动对状态矢量的影响和原始系统的输出,本文提出了一种新的自适应积分观察方法,可处理具有未知参数的驱动器和响应系统之间的混沌同步。通过Lyapunov稳定性定理和Barbalat Lemma提供了分析和证据。这种方法的限制较少,因为与混沌系统相关的许多参数可能是未知的,如纸张所示。最终执行数值模拟,结果表明,该方法不仅适用于代表性的混沌系统,还适用于某些神经网络混沌系统。

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