Wang Xin, Park Ju H, Liu Zongcheng, Yang Huilan
IEEE Trans Neural Netw Learn Syst. 2024 Jun;35(6):7602-7611. doi: 10.1109/TNNLS.2022.3217461. Epub 2024 Jun 3.
In this article, the dynamic event-triggered control problem of memristive neural networks (MNNs) under multiple cyber-attacks is considered. A novel dynamic event-triggering scheme (DETS) and the corresponding event-triggered controller are proposed by taking into consideration both denial-of-service and deception attacks (DoS-DAs). Then, a key lemma is established to show that the dynamic event-triggered controller can be used to solve the globally stochastically exponential stability (GSES) issue of concerned MNN under multiple cyber-attacks. Meanwhile, a novel Lyapunov functional is proposed based on the actual sampling pattern. It is shown that under our proposed dynamic event-triggered controller and Lyapunov functional, the concerned MNN can achieve GSES in the presence of DoS-DAs. In addition, our results include relevant results on event-triggered control of MNN with static event-triggering scheme (SETS) or without cyber-attacks as special cases. The effectiveness of the proposed event-triggered controller under multiple cyber-attacks is illustrated by a simulation example.
本文考虑了忆阻神经网络（MNNs）在多重网络攻击下的动态事件触发控制问题。通过同时考虑拒绝服务攻击和欺骗攻击（DoS-DAs），提出了一种新颖的动态事件触发方案（DETS）和相应的事件触发控制器。然后，建立了一个关键引理，以表明动态事件触发控制器可用于解决相关MNN在多重网络攻击下的全局随机指数稳定性（GSES）问题。同时，基于实际采样模式提出了一种新颖的李雅普诺夫泛函。结果表明，在我们提出的动态事件触发控制器和李雅普诺夫泛函下，相关MNN在存在DoS-DAs的情况下可以实现GSES。此外，我们的结果包括以静态事件触发方案（SETS）进行事件触发控制的MNN或无网络攻击的相关结果作为特殊情况。通过一个仿真例子说明了所提出的事件触发控制器在多重网络攻击下的有效性。
