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

Daoliang Tan; Ron J. Patton; Xi Wang

doi:10.1016/j.ifacol.2015.09.665

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

Daoliang Tan
, Ron J. Patton
, Xi Wang

School of Energy and Power Engineering

Collaborative Innovation Center of Advanced Aero-Engine
University of Hull
Beihang University

Research output: Contribution to journal › Conference article › peer-review

15 Scopus citations

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 (R_xUIO) concept by means of the H_∞, H₂, and mixed H₂/H_∞ techniques. Necessary and sufficient conditions for the existence of different R_xUIOs are presented in the tractable linear matrix inequality (LMI) form. Numerical experiments are presented to illustrate the effectiveness of the suggested method.

Original language	English
Pages (from-to)	1048-1053
Number of pages	6
Journal	IFAC-PapersOnLine
Volume	28
Issue number	21
DOIs	https://doi.org/10.1016/j.ifacol.2015.09.665
State	Published - 1 Sep 2015
Event	9th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes, SAFEPROCESS 2015 - Paris, France Duration: 2 Sep 2015 → 4 Sep 2015

Keywords

Fault diagnosis
Fault estimation
Linear matrix inequality
Unknown input observer

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10.1016/j.ifacol.2015.09.665

Cite this

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title = "A relaxed solution to unknown input observers for state and fault estimation",

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.",

keywords = "Fault diagnosis, Fault estimation, Linear matrix inequality, Unknown input observer",

author = "Daoliang Tan and Patton, \{Ron J.\} and Xi Wang",

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AU - Tan, Daoliang

AU - Patton, Ron J.

AU - Wang, Xi

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N2 - 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.

AB - 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.

KW - Fault diagnosis

KW - Fault estimation

KW - Linear matrix inequality

KW - Unknown input observer

UR - https://www.scopus.com/pages/publications/84992512936

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DO - 10.1016/j.ifacol.2015.09.665

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Y2 - 2 September 2015 through 4 September 2015

ER -

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

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