Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/111365
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Type: Journal article
Title: Fault Detection Filtering for Nonhomogeneous Markovian Jump Systems via a Fuzzy Approach
Author: Li, F.
Shi, P.
Lim, C.
Wu, L.
Citation: IEEE Transactions on Fuzzy Systems, 2018; 26(1):131-141
Publisher: Institute of Electrical and Electronics Engineers
Issue Date: 2018
ISSN: 1063-6706
1941-0034
Statement of
Responsibility: 
Fanbiao Li, Peng Shi, Cheng-Chew Lim, Ligang Wu
Abstract: This paper investigates the problem of fault detection filter design for nonhomogeneous Markovian jump systems by a Takagi-Sugeno fuzzy approach. Attention is focused on the construction of a fault detection filter to ensure the estimation error dynamic to be stochastically stable and the prescribed performance requirement can be satisfied. The designed fuzzy model-based fault detection filter can guarantee the sensitivity of the residual signal to faults and the robustness of the external disturbances. By using the cone complementarity linearization algorithm, the existence conditions for the design of fault detection filters are provided. Meanwhile, the error between the residual signal and the fault signal is made as small as possible. Finally, a practical application are given to illustrate the effectiveness of the proposed technique.
Keywords: Fault detection (FD); filtering; nonhomogeneous Markovian jump systems (MJS); Takagi–Sugeno fuzzy
Rights: © 2016 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.
RMID: 0030068011
DOI: 10.1109/TFUZZ.2016.2641022
Grant ID: http://purl.org/au-research/grants/arc/DP140102180
http://purl.org/au-research/grants/arc/LP140100471
Appears in Collections:Electrical and Electronic Engineering publications

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