Paper Info
Title
Reduced-Order Fault Detection Filter Design for Fuzzy Semi-Markov Jump Systems With Partly Unknown Transition Rates
Abstract
This article deals with the fault detection problem for a class of Takagi–Sugeno (T–S) fuzzy semi-Markov jump systems (FSMJSs) with partly unknown transition rates (PUTRs) subject to output quantization by designing a reduced-order filter. First, a more general PUTRs model is constructed to describe the situation that the information of some elements is completely unknown, where this model is affected simultaneously by PU information and time-varying parameter compared with the traditional PUTRs model. Second, we take full advantage of the reduced-order filter to address the fault detection problem for FSMJSs, in which the stochastic failure phenomenon is injected into the reduced-order filter. Besides, the logarithmic quantizer is employed to tackle the limited bandwidth problem in a communication channel. Consequently, the new sufficient conditions are developed based on the Lyapunov theory to obtain the desired reduced-order filter. Simulation results with respect to the tunnel diode circuit are provided to demonstrate the usefulness and availability of the established theoretical results.
Year
DOI
Venue
2022
10.1109/TSMC.2022.3163719
IEEE Transactions on Systems, Man, and Cybernetics: Systems
Keywords
DocType
Volume
Fuzzy semi-Markov jump systems (FSMJSs),partly unknown transition rates (PUTRs),reduced-order fault detection filter design,Takagi–Sugeno (T–S) fuzzy method
Journal
52
Issue
ISSN
Citations 
12
2168-2216
0
PageRank 
References 
Authors
0.34
50
4
Name
Order
Citations
PageRank
Linchuang Zhang1813.26
Yonghui Sun221413.74
Yingnan Pan352321.18
H. K. Lam43618193.15