伯努利原理
伯努利分布
人工神经网络
跳跃
频道(广播)
控制理论(社会学)
马尔可夫链
控制器(灌溉)
计算机科学
马尔可夫过程
理论(学习稳定性)
衰减
事件(粒子物理)
集合(抽象数据类型)
控制(管理)
数学
随机变量
人工智能
工程类
物理
机器学习
电信
统计
量子力学
航空航天工程
农学
光学
生物
程序设计语言
作者
Yao Xu,Hongqian Lu,Xingxing Song,Wuneng Zhou
摘要
Abstract This article discusses the problem of H 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 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 controller and ETS is proposed. Finally, two simulation examples are given to prove the feasibility of this article.
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