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Quantised polynomial filtering for nonlinear systems with missing measurements

Published:2017-06-19 Issue:10 Volume:91 Page:2250-2260
ISSN:0020-7179
Container-title:International Journal of Control
language:en
Short-container-title:International Journal of Control

Author:

Liu Yang¹^ORCID,Wang Zidong²^ORCID,Zhou D. H.¹³^ORCID

Affiliation:

1. College of Electrical Engineering and Automation, Shandong University of Science and Technology , Qingdao, P.R. China

2. Department of Computer Science, Brunel University London , Uxbridge, Middlesex, UK

3. Department of Automation, Tsinghua University , Beijing, P.R. China

Funder

National Natural Science Foundation of China

Research Fund for the Taishan Scholar Project of Shandong Province of China

China Postdoctoral Science Foundation

Qingdao Postdoctoral Applied Research Projects

Publisher

Informa UK Limited

Subject

Computer Science Applications,Control and Systems Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/00207179.2017.1337933

Reference39 articles.

1. Gaussian regression and power spectral density estimation with missing data: The MICROSCOPE space mission as a case study

2. Mean-square H∞ filtering for stochastic systems: Application to a 2DOF helicopter

3. Central suboptimalH∞filter design for nonlinear polynomial systems

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