Journal article

Robust Fault Detection and Set-Theoretic UIO for Discrete-Time LPV Systems With State and Output Equations Scheduled by Inexact Scheduling Variables

Feng Xu, Junbo Tan, Ye Wang, Xueqian Wang, Bin Liang, Bo Yuan

IEEE Transactions on Automatic Control | Institute of Electrical and Electronics Engineers | Published : 2019

Abstract

This paper proposes a novel robust fault detection (FD) approach and designs a set-theoretic unknown input observer (SUIO) for linear parameter-varying (LPV) systems with both state and output equations scheduled by inexact scheduling variables. First, for such LPV systems, we propose a novel robust FD method by combing the set theory with the unknown input observer, which considers the bounds of measurement errors of scheduling variables to generate FD-oriented sets. In general, as long as sensors with sufficiently high precision are equipped to measure the scheduling variables, the bounds of measurement errors of scheduling variables can be less conservative than those direct bounds of sch..

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Grants

Awarded by National Natural Science Foundation of China


Awarded by Science and Technology Research Foundation of Shenzhen


Awarded by Science and Technology Planning Project of Guangdong


Funding Acknowledgements

This work was supported in part by the National Natural Science Foundation of China under Grant U1813216, in part by the Science and Technology Research Foundation of Shenzhen under Grant JCYJ20170412171459177 and Grant JCYJ20170817152701660, and in part by the Science and Technology Planning Project of Guangdong under Grant 2017B010116001.