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Deconvolution Estimation Problem for Measurement-Delay Systems with Packet Dropping

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Proceedings of 2016 Chinese Intelligent Systems Conference (CISC 2016)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 404))

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Abstract

This paper addresses the optimal deconvolution estimation problem for measurement-delay systems over a network subject to random packet dropout, which is modeled by independent and identically distributed Bernoulli processes. First, the state estimator problem is solved by utilizing the reorganized innovation analysis approach, which is given in the linear minimum mean square error sense (LMMSE). Then, the noise estimator is obtained based on the state estimator and the projection formula. Last, we provide a numerical example to declare that our proposed estimation approach is effective.

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Acknowledgments

This work is supported in part by the Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology, the Excellent Young Scholars Research Fund of Shandong Normal University, and the National Natural Science Foundation of China (61304013).

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Authors and Affiliations

  1. School of Information Science and Engineering, Shandong Normal University, Jinan, 250014, China

    Zhenhua Duan & Xinmin Song

  2. School of Electrical Engineering, University of Jinan, Jinan, 250022, China

    Xuehua Yan

Authors
  1. Zhenhua Duan
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  2. Xinmin Song
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  3. Xuehua Yan
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Corresponding author

Correspondence to Xinmin Song .

Editor information

Editors and Affiliations

  1. Beihang University , Beijing, China

    Yingmin Jia

  2. Beijing University of Posts and Telecommunications, Beijing, China

    Junping Du

  3. University of Science and Technology Beijing, Beijing, China

    Weicun Zhang

  4. Tsinghua University , Beijing, China

    Hongbo Li

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© 2016 Springer Science+Business Media Singapore

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Duan, Z., Song, X., Yan, X. (2016). Deconvolution Estimation Problem for Measurement-Delay Systems with Packet Dropping. In: Jia, Y., Du, J., Zhang, W., Li, H. (eds) Proceedings of 2016 Chinese Intelligent Systems Conference. CISC 2016. Lecture Notes in Electrical Engineering, vol 404. Springer, Singapore. https://doi.org/10.1007/978-981-10-2338-5_32

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  • DOI: https://doi.org/10.1007/978-981-10-2338-5_32

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-2337-8

  • Online ISBN: 978-981-10-2338-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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