State estimator for multisensor systems with irregular sampling and time-varying delays

I. Peñarrocha, R. Sanchis and J.A. Romero

International Journal of Systems Science, 2012, vol. 43, issue 8, 1441-1453

Abstract: This article addresses the state estimation in linear time-varying systems with several sensors with different availability, randomly sampled in time and whose measurements have a time-varying delay. The approach is based on a modification of the Kalman filter with the negative-time measurement update strategy, avoiding running back the full standard Kalman filter, the use of full augmented order models or the use of reorganisation techniques, leading to a lower implementation cost algorithm. The update equations are run every time a new measurement is available, independently of the time when it was taken. The approach is useful for networked control systems, systems with long delays and scarce measurements and for out-of-sequence measurements.

Date: 2012
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DOI: 10.1080/00207721.2011.625482

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