文献类型：期刊文献

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] Key Laboratory of Advanced Control and Optimization for Chemical Process of Ministry of Education, East China University of Science and Technology, Shanghai, 200237, China; [2] Department of Control Science and Engineering, Tongji University, Shanghai, 200092, China; [3] College of Mechatronics and Control Engineering, Hubei Normal University, Huangshi, 435002, China

年份：2017

起止页码：7950

外文期刊名：Chinese Control Conference, CCC

收录：EI(收录号：20174404320777)

语种：英文

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. ? 2017 Technical Committee on Control Theory, CAA.