Gain-scheduled robust fault detection on time-delay stochastic nonlinear systems

This paper studies the problem of continuous gain-scheduled robust fault detection (RFD) on a class of time-delay stochastic nonlinear systems with partially known jump rates. By means of gradient linearization procedure, stochastic linear models and filter-based residual signal generators are const...

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Main Authors: Yin, YanYan, Shi, P., Liu, F.
Format: Journal Article
Published: Institute of Electrical and Electronic Engineers 2011
Online Access:http://hdl.handle.net/20.500.11937/52127
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author Yin, YanYan
Shi, P.
Liu, F.
author_facet Yin, YanYan
Shi, P.
Liu, F.
author_sort Yin, YanYan
building Curtin Institutional Repository
collection Online Access
description This paper studies the problem of continuous gain-scheduled robust fault detection (RFD) on a class of time-delay stochastic nonlinear systems with partially known jump rates. By means of gradient linearization procedure, stochastic linear models and filter-based residual signal generators are constructed in the vicinity of selected operating states. Furthermore, in order to guarantee the sensitivity to faults and robustness against unknown inputs, an RFD filter (RFDF) is designed for such linear models by first designing H 8 filters that minimize the influences of the disturbances and modeling uncertainties and then a new performance index that increases the sensitivity to faults. Subsequently, a sufficient condition on the existence of RFDF is established in terms of linear matrix inequality techniques. Finally, a continuous gain-scheduled approach is employed to design continuous RFDFs on the entire nonlinear jump system. A simulation example is given to illustrate that the proposed RFDF can detect the faults correctly and shortly after the occurrences. © 2011 IEEE.
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spelling curtin-20.500.11937-521272017-09-13T15:40:02Z Gain-scheduled robust fault detection on time-delay stochastic nonlinear systems Yin, YanYan Shi, P. Liu, F. This paper studies the problem of continuous gain-scheduled robust fault detection (RFD) on a class of time-delay stochastic nonlinear systems with partially known jump rates. By means of gradient linearization procedure, stochastic linear models and filter-based residual signal generators are constructed in the vicinity of selected operating states. Furthermore, in order to guarantee the sensitivity to faults and robustness against unknown inputs, an RFD filter (RFDF) is designed for such linear models by first designing H 8 filters that minimize the influences of the disturbances and modeling uncertainties and then a new performance index that increases the sensitivity to faults. Subsequently, a sufficient condition on the existence of RFDF is established in terms of linear matrix inequality techniques. Finally, a continuous gain-scheduled approach is employed to design continuous RFDFs on the entire nonlinear jump system. A simulation example is given to illustrate that the proposed RFDF can detect the faults correctly and shortly after the occurrences. © 2011 IEEE. 2011 Journal Article http://hdl.handle.net/20.500.11937/52127 10.1109/TIE.2010.2103537 Institute of Electrical and Electronic Engineers restricted
spellingShingle Yin, YanYan
Shi, P.
Liu, F.
Gain-scheduled robust fault detection on time-delay stochastic nonlinear systems
title Gain-scheduled robust fault detection on time-delay stochastic nonlinear systems
title_full Gain-scheduled robust fault detection on time-delay stochastic nonlinear systems
title_fullStr Gain-scheduled robust fault detection on time-delay stochastic nonlinear systems
title_full_unstemmed Gain-scheduled robust fault detection on time-delay stochastic nonlinear systems
title_short Gain-scheduled robust fault detection on time-delay stochastic nonlinear systems
title_sort gain-scheduled robust fault detection on time-delay stochastic nonlinear systems
url http://hdl.handle.net/20.500.11937/52127