This paper reviews the use of set-membership methods in robust fault detection and isolation (FDI) and tolerant control (FTC). Set-membership methods use a deterministic unknown-but-bounded description of noise and parametric uncertainty (interval models). These methods aims to check the consistency between observed and predicted behavior by using simple sets to approximate the set of possible ...

In this paper a generic method for fault detection and isolation (FDI) in manufacturing systems considered as discrete event systems (DES) is presented. The method uses an identified model of the closed loop of plant and controller built on the basis of observed fault free system behavior. An identification algorithm known from literature is used to determine the fault detection model in form o...

This paper presents an adaptive Generalized Likelihood Ratio (GLR) test for multiple Faults Detection and Isolation (FDI) in stochastic linear dynamic systems. Based on the work of Willsky and Jones (1976), we propose a modified generalized likelihood ratio test, allowing detection, isolation and estimation of multiple sequential faults. Our contribution aims to maximise the good decision rate ...

In this paper, the problem of fault diagnosis of a wind farm is addressed using interval parity equations. Fault detection is based on the use of parity equations and unknown but bounded description of the noise and modeling errors. The fault detection test is based on checking the consistency between the measurements and the model by finding if the formers are inside the interval prediction bo...

This paper deals with the design of robust Fault Detection and Isolation (FDI) filters for atmospheric re-entry vehicles subjected to actuator faults. The FDI technique is based on carefully chosen linear models of the controlled vehicle about the available on-board reference trajectories. The modelling process allows for both Lateral/directional and longitudinal motions. Design trade-offs are ...

Modern computers and computing techniques allow for the rapid processing of data and permit the development of real-time fault detection and isolation (FDI) tools. For nuclear power plants, these tools are designed to aid the operator by first detecting and then isolating system faults. This paper introduces an original methodology for FDI merging analytical redundancy and neural network techni...

In this paper, an observer-based fault detection and isolation (FDI) method for a biological wastewater treatment process (WWTP) is presented. The residual is generated utilizing an Extended Luenberger function observer. The FDI of a set of sensors faults is done by using a bank of Luenberger observers. The implementation of the proposed approach and the results obtained from its application to...

This paper presents a fault detection method based on a classical transfer function parameter estimation algorithm in the discrete time domain. Non persistently exciting inputs plant an important problem for the convergence of the estimator. Here, the forgetting factor is adapted on-line in order to improve the convergence. Redundant discrete time transfer functions are used to improve the isol...

The paper proposes a bond graph approach to model based fault detection and isolation (FDI) that uses residual sinks. These elements couple a reference model of a process engineering system to a bond graph model of the system that is subject to disturbances caused by faults. In this paper it is assumed that two faults do not appear simultaneously. The underlying mathematical model is a Differen...

Critical infrastructure systems (CIS) are complex large-scale systems which in turn require highly sophisticated supervisory control systems to ensure that high performance can be achieved and maintained under adverse conditions. The global CIS Real-Time Control (RTC) need of operating in adverse conditions involves, with a high probability, sensor and actuator malfunctions (faults). This probl...