Unbiased Minimum-Variance Filtering for Systems with Randomly Multi-Step Sensor Delays

被引：0
作者：
Zhang, Yilian [1 ,2 ]
Yang, Fuwen [1 ,2 ]
Han, Qing-Long [2 ]
机构：
[1] East China Univ Sci & Technol, Key Lab Adv Control & Optimizat Chem Proc, Minist Educ, Shanghai 200237, Peoples R China
[2] Cent Queensland Univ, Ctr Intelligent & Networked Syst, Rockhampton, Qld 4702, Australia
来源：
IECON 2014 - 40TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY | 2014年
关键词：
networked control systems; filtering; recursive estimation; Kalman filters; delay systems; stochastic processes; sensor system; communication networks; NETWORKED CONTROL-SYSTEMS; STATE ESTIMATION; PACKET DROPOUTS; TIME-SYSTEMS;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, a linear unbiased minimum-variance filtering problem is considered for a class of systems with randomly multi-step sensor delays. A new mathematical model is established for the multi-step sensor delays. Different from the augmented method for dealing with delayed systems, a linear unbiased minimum-variance filter design method is proposed without augmenting the state vector, which effectively reduces the filter dimensions. A recursive algorithm for calculating the filter gain matrix is developed. The simulation results illustrate the effectiveness of the proposed method.
引用
收藏
页码：3720 / 3725
页数：6
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