Fault detection and isolation for a three tank system based on a bilinear model of the supervised process

Bahir, L. El; Kinnaert, Michel

doi:10.1049/cp:19980449

Cited by 8 publications

(2 citation statements)

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“…Based on the nonlinear model of degree N, an observer has been designed and applied to an experimental hydraulic system to detect the fault in the case of bilinear and polynomial nonlinearities by Shields & Du (2000). In L. El Bahir & M. Kinnaert (1998), time-varying innovation generators integrated with generalized likelihood ratio tests have been developed based on a bilinear model for fault diagnosis purposes. In Rincon-Pasaye et al (2008), a comparison has been held between two observer types to test their reliability in fault detection using a small number of measurements from the plant.…”

Section: Introductionmentioning

confidence: 99%

Fault detection in a three-tank hydraulic system using unknown input observer and extended Kalman filter

HASSAN

Mohammed

Demirkol

2021

JER is an international, peer-reviewed journal that publishes f

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This paper presents the problem of fault diagnosis in a three-tank hydraulic system. A mathematical model of the system is developed in order to apply two different observing algorithms. Unknown Input Observer (UIO) and Extended Kalman Filter (EKF) have been used to detect and isolate actuator and sensor faults. For Unknown Input Observer (UIO), residuals are calculated from the measured and estimated output according to the eigenvalues of the system after processed by Linear Matrix Inequality (LMI). Extended Kalman filter uses process and measurement noise variances for state estimation. Unknown Input Observer and Extended Kalman Filter's performance in fault estimation and isolation is evaluated under different scenarios. Using Extended Kalman Filter (EKF), faults can be diagnosed effectively in the presence of noise, while Unknown Input Observer (UIO) is working better in the absence of noise, and simulation results illustrate that clearly.

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Section: Introductionmentioning

confidence: 99%

Fault detection in a three-tank hydraulic system using unknown input observer and extended Kalman filter

HASSAN

Mohammed

Demirkol

2021

JER is an international, peer-reviewed journal that publishes f

View full text Add to dashboard Cite

show abstract

“…Based on the nonlinear model, [112] have designed an observer using the bilinear model representation of the three-tank system to detect a leakage from a pipe. A diagnostic system based also on a bilinear model has been considered in [7], where time varying innovation generators combined with generalized likelihood ratio tests are designed to detect and isolate faults. The robustness of a sliding mode observer (SMO) to detect faults in the presence of noise on the measurements was tested in real-time [105].…”

Section: Introductionmentioning

confidence: 99%