指数同步混沌系统的时滞相关稳定性

F. Hsiao
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引用次数: 0

摘要

研究了一类具有多时滞和传递噪声的混沌系统的同步问题。提出了一种动态补偿器来实现多时滞混沌系统的主从同步。首先,利用神经网络模型对具有多时滞的混沌系统进行逼近。然后,建立了神经网络模型动力学的线性微分包含(LDI)状态空间表示。在LDI状态空间表示的基础上,提出了基于Lyapunov直接法的误差动力学指数稳定性判据,以保证从系统的轨迹接近主系统的轨迹。随后,将该判据的稳定性条件重新表述为线性矩阵不等式。在此基础上,综合了模糊控制器,实现了混沌主从系统的指数同步。最后,本研究提供了一个数值例子,通过模拟来说明整个工作中所讨论的概念。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Delay-Dependant Stability of Chaotic Systems with Exponential Synchronization
This study is concerned with the synchronization problem for a class of chaotic systems with multiple time-delays and transmitted noise. A dynamic compensator is proposed to achieve the synchronization between master and slave chaotic systems with multiple timedelays. First, the neural-network (NN) model is employed to approximate the chaotic systems with multiple time delays. Then, a linear differential inclusion (LDI) state-space representation is established for the dynamics of the NN model. Based on the LDI state-space representation, an exponential stability criterion of error dynamics derived in terms of Lyapunov's direct method is proposed to ensure that the trajectories of the slave system can approach those of master system. Subsequently, the stability condition of this criterion is reformulated into a linear matrix inequality (LMI). Based on the LMI, a fuzzy controller is synthesized to realize the exponential synchronization of the chaotic master-slave systems. Finally, this study provides a numerical example with simulations is given to illustrate the concepts discussed throughout this work.
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