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A relaxed solution to unknown input observers for state and fault estimation

Tan, Daoliang; Patton, Ron J.; Patton, Ron; Wang, Xi

Authors

Daoliang Tan

Xi Wang



Abstract

A lot of effort has been devoted to the unknown input observer (UIO) research over the past years. However, the strong disturbance decoupling assumption (manifested as some rank constraint) is often implicitly embedded in much of the existing UIO work. With the purpose of state and fault estimation, this fact motivates us to investigate the viability of the UIO research when the strong disturbance decoupling is not possible, i.e., a “degenerate” problem of UIO decoupling exists. Inspired by the scheme of reducing the effect of external disturbance on estimation error, this paper incorporates the relaxed UIO (RxUIO) concept by means of the H∞H2, and mixed H2¡H∞ techniques. Necessary and sufficient conditions for the existence of different RxUIOs are presented in the tractable linear matrix inequality (LMI) form. Numerical experiments are presented to illustrate the effectiveness of the suggested method.

Journal Article Type Article
Publication Date Sep 1, 2015
Journal IFAC-PapersOnLine
Print ISSN 1474-6670
Electronic ISSN 2405-8963
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 28
Issue 21
Pages 1048-1053
APA6 Citation Tan, D., Patton, R. J., & Wang, X. (2015). A relaxed solution to unknown input observers for state and fault estimation. IFAC postprint volumes IPPV / International Federation of Automatic Control, 28(21), 1048-1053. https://doi.org/10.1016/j.ifacol.2015.09.665
DOI https://doi.org/10.1016/j.ifacol.2015.09.665
Keywords Fault diagnosis, Fault estimation, Unknown input observer, Linear matrix inequality
Publisher URL http://www.sciencedirect.com/science/article/pii/S2405896315017942
Copyright Statement © 2016 IFAC. Originally published in IFAC-PapersOnline, vol. 48, no. 21 by Elsevier Ltd. (DOI 10.1016/j.ifacol.2015.09.665)
Additional Information This is an authors accepted manuscript version of a paper published in IFAC-PapersOnLine, 2015, v.48 issue 21.

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Copyright Statement
© 2016 IFAC. Originally published in IFAC-PapersOnline, vol. 48, no. 21 by Elsevier Ltd. (DOI 10.1016/j.ifacol.2015.09.665)



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