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l 2–l ∞ Filtering for Multirate Systems Based on Lifted Models

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Abstract

For a multirate sample-data system where the output sampling rate is slower than the input updating rate, we study the l 2–l ∞ filtering problems for fast state estimation by using the lifted model. The filtering problem is handled in the framework of linear matrix inequalities (LMIs) with a nonconvex constraint, which is numerically solved by the product reduction algorithm. Finally, the effectiveness of the proposed method is illustrated and verified by simulation examples.

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Authors and Affiliations

  1. Department of Mechanical Engineering, University of Saskatchewan, 57 Campus Drive, Saskatoon, SK, S7N 5A9, Canada

    Bo Yu & Yang Shi

  2. Institute of Acoustics, Chinese Academy of Sciences, Beijing, China

    Haining Huang

Authors
  1. Bo Yu
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  2. Yang Shi
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  3. Haining Huang
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Corresponding author

Correspondence to Yang Shi.

Additional information

This research was supported by the Natural Sciences and Engineering Research Council of Canada and the Canada Foundation for Innovation and the National Natural Science Foundation of China (60372105 and 60672118).

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Yu, B., Shi, Y. & Huang, H. l 2–l ∞ Filtering for Multirate Systems Based on Lifted Models. Circuits Syst Signal Process 27, 699–711 (2008). https://doi.org/10.1007/s00034-008-9058-3

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  • DOI: https://doi.org/10.1007/s00034-008-9058-3

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