Title
An Integrated Learning and Filtering Approach for Fault Diagnosis of a Class of Nonlinear Dynamical Systems.
Abstract
This paper develops an integrated filtering and adaptive approximation-based approach for fault diagnosis of process and sensor faults in a class of continuous-time nonlinear systems with modeling uncertainties and measurement noise. The proposed approach integrates learning with filtering techniques to derive tight detection thresholds, which is accomplished in two ways: 1) by learning the modeli...
Year
DOI
Venue
2017
10.1109/TNNLS.2015.2504418
IEEE Transactions on Neural Networks and Learning Systems
Keywords
Field
DocType
Fault diagnosis,Fault detection,Adaptation models,Uncertainty,Noise measurement,Nonlinear systems,Measurement uncertainty
Stuck-at fault,Nonlinear system,Noise measurement,Fault detection and isolation,Computer science,Measurement uncertainty,Filter (signal processing),Input/output,Artificial intelligence,Observer (quantum physics),Machine learning
Journal
Volume
Issue
ISSN
28
4
2162-237X
Citations 
PageRank 
References 
8
0.46
29
Authors
3
Name
Order
Citations
PageRank
Christodoulos Keliris1573.75
Marios Polycarpou22020206.96
T Parisini3935113.17