Optimal state estimation using randomly delayed measurements without time stamping. (14th May 2013)

• Record Type: Journal Article
• Authors: Yang, Yuanhua; Fu, Minyue; Zhang, Huanshui
• Is Part Of: International journal of robust and nonlinear control. Volume 24:Number 17(2014)
• Page Start: 2653
• Page End: 2668
• Publication Date: 2013-05-14
• Subjects: Automatic control -- Periodicals; Control theory -- Periodicals; Nonlinear systems -- Periodicals; 629.836
• DOI: 10.1002/rnc.3016
• Languages: English
• ISSNs: 1049-8923

Abstract

<abstract abstract-type="main" id="rnc3016-abs-0001"> <title>SUMMARY</title> <p id="rnc3016-para-0002">This paper studies an optimal state estimation (Kalman filtering) problem under the assumption that output measurements are subject to random time delays caused by network transmissions without time stamping. We first propose a random time delay model which mimics many practical digital network systems. We then study the so‐called <italic>unbiased, uniformly bounded</italic> linear state estimators and show that the estimator structure is given based on the average of all received measurements at each time for different maximum time delays. The estimator gains can be derived by solving a set of recursive discrete‐time Riccati equations. The estimator is guaranteed to be optimal in the sense that it is unbiased with uniformly bounded estimation error covariance. A simulation example shows the effectiveness of the proposed algorithm. Copyright © 2013 John Wiley &amp; Sons, Ltd.</p> </abstract>