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

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  • I. Peñarrocha
  • R. Sanchis
  • J.A. Romero

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.

Suggested Citation

  • I. Peñarrocha & R. Sanchis & J.A. Romero, 2012. "State estimator for multisensor systems with irregular sampling and time-varying delays," International Journal of Systems Science, Taylor & Francis Journals, vol. 43(8), pages 1441-1453.
    • Handle: RePEc:taf:tsysxx:v:43:y:2012:i:8:p:1441-1453
    DOI: 10.1080/00207721.2011.625482
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    Cited by:

    1. J. Salt & V. Casanova & A. Cuenca & R. Pizá, 2014. "Multirate control with incomplete information over Profibus-DP network," International Journal of Systems Science, Taylor & Francis Journals, vol. 45(7), pages 1589-1605, July.

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