Title
Fault Detection Filter Design For Nonlinear Singular Systems With Markovian Jump Parameters
Abstract
The fault detection problem for a class of Markovian jump singular systems, subject to repeated scalar nonlinearities, is investigated. Sufficient conditions are obtained for the existence of a robust fault detection filter, designed to guarantee that the residual system is stochastically stale while achieving the desired performance. Furthermore, the cone complementarity linearization approach is utilized to transform the original nonconvex feasibility issue into a sequential minimization issue, in terms of linear matrix inequalities, which are calculated with standard optimization software. Thus, it is possible to construct an ideal fault detection filter, if the earlier conditions have feasible solutions. Finally, a numerical example is given to illustrate the effectiveness of this approach.
Year
DOI
Venue
2021
10.1109/JSYST.2020.3031348
IEEE SYSTEMS JOURNAL
Keywords
DocType
Volume
Fault detection, Nonlinear systems, Linear matrix inequalities, Neural networks, Integrated circuit modeling, Dynamical systems, Transforms, Fault detection filter, Markovian jump systems (MJSs), nonlinear systems, singular systems
Journal
15
Issue
ISSN
Citations 
3
1932-8184
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Shuai Yang101.35
Yao Wen2201.90
Bingna Qiao340.76
Kai Wang421.99
Xiaojie Su5185172.94