Title
Model-based fault detection, estimation, and prediction for a class of linear distributed parameter systems.
Abstract
This paper addresses a new model-based fault detection, estimation, and prediction scheme for linear distributed parameter systems (DPSs) described by a class of partial differential equations (PDEs). An observer is proposed by using the PDE representation and the detection residual is generated by taking the difference between the observer and the physical system outputs. A fault is detected by comparing the residual to a predefined threshold. Subsequently, the fault function is estimated, and its parameters are tuned via a novel update law. Though state measurements are utilized initially in the parameter update law for the fault function estimation, the output and input filters in the modified observer subsequently relax this requirement. The actuator and sensor fault functions are estimated and the time to failure (TTF) is calculated with output measurements alone. Finally, the performance of detection, estimation and a prediction scheme is evaluated on a heat transfer reactor with sensor and actuator faults.
Year
DOI
Venue
2016
10.1016/j.automatica.2015.12.028
Automatica
Keywords
Field
DocType
Fault detection,Fault estimation,Fault prognosis,Partial differential equations,Distributed parameter systems
Residual,Physical system,Fault detection and isolation,Control theory,Heat transfer,Distributed parameter system,Observer (quantum physics),Partial differential equation,Mathematics,Actuator
Journal
Volume
Issue
ISSN
66
C
0005-1098
Citations 
PageRank 
References 
11
0.67
8
Authors
3
Name
Order
Citations
PageRank
Jia Cai1131.47
Hasan Ferdowsi2464.35
Sarangapani Jagannathan3113694.89