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首页> 外文期刊>Neural Networks and Learning Systems, IEEE Transactions on >Exponential Synchronization and L_2 -Gain Analysis of Delayed Chaotic Neural Networks Via Intermittent Control With Actuator Saturation
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Exponential Synchronization and L_2 -Gain Analysis of Delayed Chaotic Neural Networks Via Intermittent Control With Actuator Saturation

机译：带有执行器饱和的间歇控制的延迟混沌神经网络的指数同步和L_2增益分析

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摘要

By using an intermittent control approach, this paper is concerned with the exponential synchronization and L-2-gain analysis for a class of delayed master-slave chaotic neural networks subject to actuator saturation. Based on a switching strategy, the synchronization error system is modeled as a switched synchronization error system consisting of two subsystems, and each subsystem of the switched system satisfies a dwell time constraint due to the characteristics of intermittent control. A piecewise Lyapunov-Krasovskii functional depending on the control rate and control period is then introduced, under which sufficient conditions for the exponential stability of the constructed switched synchronization error system are developed. In addition, the influence of the exogenous perturbations on synchronization performance is constrained at a prescribed level. In the meantime, the intermittent linear state feedback controller can be derived by solving a set of linear matrix inequalities. More incisively, the proposed method is also proved to be valid in the case of aperiodically intermittent control. Finally, two simulation examples are employed to demonstrate the effectiveness and potential of the obtained results.
机译：通过使用间歇控制方法，本文涉及一类执行器饱和的时滞主-从混沌神经网络的指数同步和L-2-增益分析。基于切换策略，将同步误差系统建模为由两个子系统组成的切换同步误差系统，并且由于间歇控制的特性，切换系统的每个子系统都满足驻留时间约束。然后介绍了取决于控制速率和控制周期的分段Lyapunov-Krasovskii函数，在此条件下，为构造的开关同步误差系统的指数稳定性开发了充分的条件。另外，外来扰动对同步性能的影响被限制在规定的水平上。同时，可以通过求解一组线性矩阵不等式来导出间歇线性状态反馈控制器。更尖锐地讲，该方法在非周期性间歇控制中也是有效的。最后，通过两个仿真实例证明了所得结果的有效性和潜力。

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