Event-Based Measurement Updating Kalman Filter in Network Control Systems

An event based measurement updating method is introduced for discrete Kalman filters to estimate the state feedback of Lebesgue sampled data systems. It is proposed that the conventional prediction and the measurement updating stages of discrete Kalman filters are not processed at the same rate. The...

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Bibliographic Details
Published in2007 IEEE Region 5 Technical Conference pp. 138 - 141
Main Authors Anh Le, McCann, R.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.04.2007
Subjects
Communication system control
Control systems
Data communication
Degradation
Electric variables measurement
Kalman filters
Lebesgue sampling
Parameter estimation
Sampling methods
sensor networks
Stability
State estimation
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ISBN142441279X
9781424412792
DOI10.1109/TPSD.2007.4380368

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Summary:An event based measurement updating method is introduced for discrete Kalman filters to estimate the state feedback of Lebesgue sampled data systems. It is proposed that the conventional prediction and the measurement updating stages of discrete Kalman filters are not processed at the same rate. The prediction can be constant but the measurement rate is varied based on Lebesgue sampling. The measurement update portion is executed when an event takes place. The stability of discrete Kalman filters is investigated when the Lebesgue threshold is increased.
ISBN:142441279X
9781424412792
DOI:10.1109/TPSD.2007.4380368