带有随机测量数据丢失及切换拓扑的传感器网络分布式l2-l∞滤波器设计

Distributed l2-l∞ filtering for sensor networks with missing measurements and switching topology

研究一类具有测量数据随机丢失以及网络拓扑结构随机切换的分布式l2-l∞滤波器设计问题.在分布式滤波器网络,每个本地滤波器估计系统的状态不仅基于节点自身信息,而且利用网络拓扑中邻居节点的信息.首先,采用已知概率分布的二进制序列描述传感器测量数据的随机丢失,Markov链描述滤波器网络拓扑结构的切换;其次,构造一个Lyapunov函数来分析滤波误差系统的l2-l∞性能,并研究其均方指数稳定性;再次,通过线性矩阵不等式(LMI)技术,给出分布式l2-l∞滤波器的设计方法;最后,通过数值例子验证所提方法的有效性.

In this paper,the problem of l2-l∞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 su?cient condition is derived to guarantee the l2-l∞performance and the exponential mean-square stability of the resulting filtering error dynamics.Subsequently,the design method of the distributed l2-l∞filters is obtained through the linear matrix inequality(LMI)technique.Finally,a numerical example is given to illustrate the e?ectiveness of the proposed method.