文献类型：会议论文

英文题名：Prediction Consensus-Based Distributed Kalman Filtering with Packet Loss

作者：Fan, Sha[1];Yan, Huaicheng[1,3];Zhang, Hao[2];Wang, Mengling[1];Zhan, Xisheng[3]

机构：[1]East China Univ Sci & Technol, Key Lab Adv Control & Optimizat Chem Proc, Minist Educ, Shanghai 200237, Peoples R China;[2]Tongji Univ, Dept Control Sci & Engn, Shanghai 200092, Peoples R China;[3]Hubei Normal Univ, Coll Mechatron & Control Engn, Huangshi 435002, Peoples R China

会议论文集：36th Chinese Control Conference (CCC)

会议日期：JUL 26-28, 2017

会议地点：Dalian, PEOPLES R CHINA

语种：英文

外文关键词：Distributed state estimation; Packet loss; Kalman consensus filtering (KCF); State prediction consensus mechanism

摘要：This paper is concerned with the problem of distributed state estimation for linear discrete system with packet loss. A state prediction consensus mechanism is introduced to promote the estimation performance. By applying matrix theory, a sufficient condition for the convergence of the estimation error system is derived. Then, a numerical example is given to show the algorithm proposed in this paper has better consensus performance compared with a classical Kalman consensus filtering (KCF) by some simulations in real and packet-dropping cases, respectively. Finally, the influence of consensus coefficient and prediction consensus coefficient on the estimation error covariance are presented by simulation.