A novel approach to fault detection for fuzzy stochastic systems with nonhomogeneous processes
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In this paper, we consider a class of fuzzy stochastic systems with nonhomogeneous jump processes. Our focus is on the design of a fuzzy fault detection filter that is sensitive to faults but robust against unknown inputs. Furthermore, the error filtering system is stochastically stable. With reference to an H1 performance index and a new performance index, sufficient conditions to ensure the existence of a fuzzy robust fault detection filter are derived. Simulation studies are carried out, showing that the proposed fuzzy robust FD filter can rapidly detect the faults correctly.
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Delay-dependent robust fault detection for Markovian jump systems with partly unknown transition ratesChen, F.; Yin, YanYan; Liu, F. (2016)© 2015 The Franklin Institute. Published by Elsevier Ltd. All rights reserved. This paper focuses on delay-dependent robust fault detection (RFD) problem for continuous-time Markovian jump systems (MJSs) with partly unknown ...
Yin, YanYan; Shi, P.; Liu, F. (2011)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, ...
Yin, Y.; Shi, P.; Liu, F.; Teo, Kok Lay (2014)The problem of robust fault detection (RFD) is studied for a class of discrete-time stochastic systems with non-homogeneous jump processes. First, a filter-based residual signal generator is constructed. To guarantee the ...