Open AccessFast filtering algorithm for state estimation of lossy networks
Author(s) -
Lin Hong,
Xu Zhaowen,
Su Hongye,
Xu Yong,
Wu Zhengguang
Publication year - 2014
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/iet-cta.2014.0155
Subject(s) - lossy compression , algorithm , network packet , control theory (sociology) , computer science , covariance , state (computer science) , gaussian , transmission (telecommunications) , filter (signal processing) , mathematics , control (management) , statistics , artificial intelligence , computer network , telecommunications , physics , quantum mechanics , computer vision
The authors study the state estimation issue of networked control systems in which observations, control commands and acknowledgement (ACK) signals are randomly dropped. They show that unlike the transmission control protocol‐like or user datagram protocol‐like case, the probability density function of system state turns out to be Gaussian mixture with exponentially increasing terms because of the random losses of ACK signals, which makes the optimal filtering time‐consuming. They develop a sub‐optimal but computationally efficient filtering algorithm, named as fast filtering (FF), and establish a packet‐loss‐rate‐based sufficient condition for the boundedness of the expected estimation error covariance matrices. By a numerical example, the effectiveness of the proposed FF algorithm is illustrated, and the mutual influences of the packet losses of observations, control commands and ACK signals on the estimation performance are analysed.