Event-triggered H∞ control for Markov jump delayed neural networks with redundant channels

This article discusses the problem of H-infinity control for Markov jump neural networks with time-varying delay and redundant channels under event-triggered scheme (ETS). First, considering the limited communication channel capacity of the network system, the ETS is introduced to reduce the network load and improve the network utilization. Second, the technique of redundant channels is employed to improve the successful rate of communication network, and two mutually independent random variables which obey Bernoulli distribution are used to reflect the phenomenon of data dropouts of the main channel and redundant channel, respectively. Third, a sufficient condition with a prescribed H-infinity disturbance attenuation performance is derived to ensure the stability of the closed-loop system. And according to a set of feasible linear matrix inequalities, the co-design of H-infinity controller and ETS is proposed. Finally, two simulation examples are given to prove the feasibility of this article.