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Kalman filtering for time-delayed linear systems

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Abstract

This paper is to study the linear minimum variance estimation for discrete-time systems. A simple approach to the problem is presented by developing re-organized innovation analysis for the systems with instantaneous and double time-delayed measurements. It is shown that the derived estimator involves solving three different standard Kalman filtering with the same dimension as the original system. The obtained results form the basis for solving some complicated problems such as H ∞ fixed-lag smoothing, preview control, H ∞ filtering and control with time delays.

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Authors and Affiliations

  1. Research Center of Information and Control, Dalian University of Technology, Dalian, 116024, China

    Lu Xiao & Wang Wei

  2. Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen, 518055, China

    Lu Xiao

Authors
  1. Lu Xiao
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  2. Wang Wei
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Correspondence to Lu Xiao.

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Lu, X., Wang, W. Kalman filtering for time-delayed linear systems. SCI CHINA SER F 49, 461–470 (2006). https://doi.org/10.1007/s11432-006-2008-4

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  • DOI: https://doi.org/10.1007/s11432-006-2008-4

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