Event-triggered H_∞ filtering for discrete-time systems over unreliable networks with package dropouts

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• 作者：Lei Zhou^a ; ^bAuthor Vitae ; Rui Pan^aAuthor Vitae ; Xiaoqing Xiao^a ; ^{xiaoxqzl@126.com" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Tingting Sun^aAuthor Vitae
• 关键词：Discrete-time systems ; H&infin ; H&infin ; filter ; Event-triggered mechanism ; Package dropouts
• 刊名：Neurocomputing
• 出版年：2016
• 出版时间：19 December 2016
• 年：2016
• 卷：218
• 期：Complete
• 页码：346-353
• 全文大小：709 K

文摘

This paper considers the event-triggered H_∞$H_{\infty }$ filtering problem for discrete-time linear systems subject to package dropouts. The system measurement output is quantized before transmitted through the communication network with limited capacity. The event-triggered transmission mechanism is proposed and Bernoulli process is utilized to describe the package dropouts. A new sufficient condition is obtained such that the resulted error system is mean square exponentially stable and the filtering error satisfies the prescribed H_∞$H_{\infty }$ performance. Then, co-design algorithm for the parameters of filter and event-triggered condition is presented by means of linear matrix inequality approach. Moreover, the minimum attenuation level bound can be obtained by solving a convex optimization problem. Numerical simulations show the effectiveness and less conservativeness of the proposed approach.