基于传感器网络的远程状态估计  

Remote state estimation based on sensor networks

作　　者：肖力[1] 孙志刚[1] 胡晓娅[1] 陈绵云[1] 

机构地区：[1]华中科技大学控制科学与工程系图像信息处理与智能控制教育部重点实验室,湖北武汉430074

出　　处：《控制理论与应用》2009年第7期763-766,共4页Control Theory & Applications

基　　金：国家自然科学基金资助项目(60802002);教育部博士点基金资助项目(20020487023)

摘　　要：针对传感器网络中的远程状态估计,提出一种多传感器切换的卡尔曼滤波器.通过分析估计误差的统计特性,证明估计误差的协方差具有边界,采用线性矩阵不等式的形式给出了边界的收敛条件.研究测量数据丢失对估计器性能的影响,使用临界到达概率作为估计器的稳定性判据,得到采用线性矩阵不等式求解临界到达概率的方法.数值仿真证实了结论的正确性.A switched Kalman filter is proposed to realize the remote state-estimation in sensor networks. The stochastic properties of the estimation error are studied; and the covariance of the estimation error is proved to have bounds. Convergence conditions of the bounds are given in terms of linear matrix inequalities. The effects of packet-dropping are considered; and the critical arrival probability is used as the stability criterion of the estimator. The bounds of the critical arrival probability are obtained by using linear matrix inequality approach. The results are tested by numerical simulations.

关 键 词：传感器网络 卡尔曼滤波 修正的黎卡提方程 临界到达概率 

分 类 号：TP212.9[自动化与计算机技术—检测技术与自动化装置] TN929.5[自动化与计算机技术—控制科学与工程]