IEEE Trans Cybern. 2022 May;52(5):3359-3369. doi: 10.1109/TCYB.2020.3011527. Epub 2022 May 19.
In this article, the fault detection (FD) filter design problem is addressed for discrete-time memristive neural networks with time delays. When constructing the system model, an event-triggered communication mechanism is investigated to reduce the communication burden and a fault weighting matrix function is adopted to improve the accuracy of the FD filter. Then, based on the Lyapunov functional theory, an augmented Lyapunov functional is constructed. By utilizing the summation inequality approach and the improved reciprocally convex combination method, an FD filter that guarantees the asymptotic stability and the prescribed H performance level of the residual system is designed. Finally, numerical simulations are provided to illustrate the effectiveness of the presented results.
在本文中，针对具有时滞的离散时间忆阻神经网络，解决了故障检测（FD）滤波器设计问题。在构建系统模型时，研究了一种事件触发通信机制，以降低通信负担，并采用故障加权矩阵函数，提高 FD 滤波器的精度。然后，基于李雅普诺夫泛函理论，构造了增广李雅普诺夫泛函。利用求和不等式方法和改进的互凸组合方法，设计了 FD 滤波器，保证了残差系统的渐近稳定性和规定的 H 性能水平。最后，通过数值模拟验证了所提出结果的有效性。
