This article investigates the stabilization property for the modeled memristive bidirectional associative memory neural networks with time-varying delay when the faulty signals received from the fluctuated controller. The non-fragile output-feedback controller is taken into account to counteract the impact of gain perturbations to end up with robust fault-tolerant setup. To tackle the weak signals in the actuator received from the fluctuated controller, control gain matrices encompass situations intended to memory non-fragile output-feedback controller. Based on the Lyapunov stability theory, differential inclusion theory, and congruence transformation, the sufficient condition for the global asymptotic stabilization property for the designed fault-tolerant memristive bidirectional associative memory neural network model is obtained in terms of linear matrix inequality by utilizing Wirtinger's inequality. Finally, numerical examples are approached with the state performance plots of the proposed memristive bidirectional associative memory neural network model with respect to the time-domain plane, to confirm the stabilization results and it illustrates the working mechanism of the designed controller.

中文翻译：

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针对执行器故障的延迟忆阻双向联想记忆神经网络的非脆弱输出反馈控制


本文研究了当从波动控制器接收到错误信号时，具有时变延迟的建模忆阻双向联想记忆神经网络的稳定性特性。考虑到非脆弱输出反馈控制器来抵消增益扰动的影响，最终实现稳健的容错设置。为了解决执行器中从波动控制器接收到的微弱信号，控制增益矩阵涵盖了旨在记忆非脆弱输出反馈控制器的情况。基于Lyapunov稳定性理论、微分包含理论和同余变换，利用Wirtinger不等式，从线性矩阵不等式的角度，得到了所设计的容错忆阻双向联想记忆神经网络模型全局渐近稳定性的充分条件。最后，通过数值例子与所提出的忆阻双向联想记忆神经网络模型在时域平面上的状态性能图进行比较，以确认稳定性结果，并说明了所设计的控制器的工作机制。