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Kalman filtering over unreliable communication networks with bounded Markovian packet dropouts
Author(s) -
Xiao Nan,
Xie Lihua,
Fu Minyue
Publication year - 2008
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.1389
Subject(s) - observability , control theory (sociology) , kalman filter , covariance , markov chain , network packet , markov process , mathematics , bounded function , extended kalman filter , filter (signal processing) , discrete time and continuous time , computer science , statistics , mathematical analysis , control (management) , artificial intelligence , computer network , computer vision
We address the peak covariance stability of time‐varying Kalman filter with possible packet losses in transmitting measurement outputs to the filter via a packet‐based network. The packet losses are assumed to be bounded and driven by a finite‐state Markov process. It is shown that if the observability index of the discrete‐time linear time‐invariant (LTI) system under investigation is one, the Kalman filter is peak covariance stable under no additional condition. For discrete LTI systems with observability index greater than one, a sufficient condition for peak covariance stability is obtained in terms of the system dynamics and the probability transition matrix of the Markov chain. Finally, the validity of these results is demonstrated by numerical simulations. Copyright © 2008 John Wiley & Sons, Ltd.