Event-Triggered Control for Complex-Valued Hybrid Stochastic Multilinks Networks
研究了复值混合随机多层网络在事件触发控制下的稳定性问题，提出了更精确的随机事件触发序列，并给出了均方指数稳定和几乎必然指数稳定的条件，应用于Cohen-Grossberg神经网络和孤岛微电网模型。
In the article, a stabilized issue for complex-valued hybrid stochastic multilinks networks (CHSMNs) is investigated under event-triggered control (E-TC). In contrast to existing literature, the proposed E-TC defines the event-triggered instant sequence as the random sequence rather than the number sequence, which is more accurate concerning hybrid stochastic systems. Especially, a modified more general event-triggered function is proposed. After the Zeno behavior is eliminated by the contradiction, several stabilized conditions are established to guarantee the input-to-state stability and exponential stability in the mean square and almost surely exponential stability of CHSMNs, where studying in the complex domain and no splitting real and imaginary parts. Subsequently, we analyze the lower bound of the event-triggered intervals for E-TC in the sense of mathematical expectation. Whereafter, the stabilized problem for the Cohen–Grossberg neural networks (CSDLCNs) and the islanded micro grid model (IMGM) is considered as an application. Meanwhile, numerical simulations are presented for verification.