Title
Fast-Convergent Fault Detection And Isolation In An Uncertain Scenario
Abstract
In this paper, a fast-convergent fault detection and isolation architecture is proposed for linear MIMO continuous-time systems. By exploiting a system decomposition technique and making use of kernel-based deadbeat estimators, the state variables can be estimated in a non-asymptotic way. Estimation residuals are then defined to detect the occurrence of a fault and identify the occurring fault function after fault detection. In the noisy scenario, thresholds are defined for the residual to distinguish the effect of the noise from that of the fault. Numerical examples are included to characterize the effectiveness of the proposed FDI architecture.
Year
DOI
Venue
2018
10.1109/CDC.2018.8618966
2018 IEEE CONFERENCE ON DECISION AND CONTROL (CDC)
Field
DocType
ISSN
Kernel (linear algebra),Residual,Control theory,Computer science,Fault detection and isolation,MIMO,State variable,Estimator
Conference
0743-1546
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Peng Li102.03
Francesca Boem28312.10
Gilberto Pin313617.21
T Parisini4935113.17