DocumentCode :
1775307
Title :
Detection and isolation of process faults from actuator faults and sensor faults for a typical MIMO dynamic system
Author :
Lin, Paul P. ; Zhu, James H.
Author_Institution :
Cleveland State Univ., Cleveland, OH, USA
fYear :
2014
fDate :
18-20 June 2014
Firstpage :
371
Lastpage :
376
Abstract :
For a typical MIMO (Multiple-Input Multiple-Output) nonlinear dynamic system, fault detection and isolation usually aim at process faults with an assumption that actuator faults and sensor faults do not occur at the same time, which is not always the case. This paper uses Extended State Observer for real-time process fault detection and fuzzy inference for fault isolation. It then investigates the coupling relationship among process faults, actuator faults and sensor faults, and presents how a combination of different types of faults could lead to undetected faults or false fault detection and isolation. Finally, a method to isolate actuator faults from process faults is presented. A three-tank MIMO nonlinear system is used to help illustrate the presented fault detection and isolation techniques.
Keywords :
MIMO systems; fault diagnosis; fuzzy reasoning; nonlinear control systems; observers; MIMO dynamic system; actuator faults; extended state observer; fuzzy inference; multiple-input multiple-output nonlinear dynamic system; process fault detection; process fault isolation; sensor faults; Automation; Conferences;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control & Automation (ICCA), 11th IEEE International Conference on
Conference_Location :
Taichung
Type :
conf
DOI :
10.1109/ICCA.2014.6870948
Filename :
6870948
Link To Document :
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