引用本文: 朱凤增,闻继伟,彭力,等.带有随机测量数据丢失及切换拓扑的传感器网络分布式$l_2-l_infty$滤波器设计[J].控制与决策,2020,35(8):1841-1848
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 本文已被：浏览次   下载次 码上扫一扫！ 分享到： 微信 更多 字体:加大+|默认|缩小- 带有随机测量数据丢失及切换拓扑的传感器网络分布式$l_2-l_infty$滤波器设计 朱凤增,闻继伟,彭力,杨瑞田 (1. 江南大学物联网应用技术教育部工程中心，江苏无锡214122;2. 无锡太湖学院江苏省物联网应用技术重点建设实验室，江苏无锡214064)

DOI：10.13195/j.kzyjc.2018.1301

Distributed $l_2-l_infty$ filtering for sensor networks with missing measurements and switching topology
ZHU Feng-zeng,WEN Ji-wei,PENG Li,YANG Rui-tian
(1. Research Center of Engineering Applications for IOT,Jiangnan University,Wuxi 214122,China;2. Jiangsu Province Internet of Things Application Technology Key Construction Laboratory,Wuxi Taihu College, Wuxi 214064,China)
Abstract:
In this paper, the problem of $l_2-l_\infty$ filters design is addressed for sensor networks with missing measurements and switching topology. In a distributed filtering network, each local filter estimates the system states from not only its own information but also its neighboring filters’ information. Firstly, the missing measurements are described by a binary switching sequence satisfying a conditional probability distribution. Meanwhile, the topology under consideration evolves by an event switch which is assumed to be subject to a Markov chain. Then, by constructing a Lyapunov functional, a sufficient condition is derived to guarantee the $l_2-l_\infty$ performance and the exponential mean-square stability of the resulting filtering error dynamics. Subsequently, the design method of the distributed $l_2-l_\infty$ filters is obtained through the linear matrix inequality(LMI) technique. Finally, a numerical example is given to illustrate the effectiveness of the proposed method.
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