Fault detection, isolation, and reconfiguration (FDIR) is an important and challenging problem in many engineering applications and continues to be an active area of research in the control community. This paper presents a survey of the various model-based FDIR methods developed in the last decade. In the paper, the FDIR problem is divided into the fault detection and isolation (FDI) step, and the controller reconfiguration step. For FDI, we discuss various model-based techniques to generate residuals that are robust to noise, unknown disturbance, and model uncertainties, as well as various statistical techniques of testing the residuals for abrupt changes (or faults). We then discuss various techniques of implementing reconfigurable control strategy in response to faults.

A Survey of Fault Detection, Isolation, and Reconfiguration Methods

Technical Communique: Fault isolation filter design for linear stochastic systems

Generating directional residuals with dynamic parity relations

In this paper, the sensor data is transmitted only when the absolute value of difference between the current sensor value and the previously transmitted one is greater than the given threshold value. Based on this send-on-delta scheme which is one of the event-triggered sampling strategies, a modified fault isolation filter for a discrete-time networked control system with multiple faults is then implemented by a particular form of the Kalman filter. The proposed fault isolation filter improves the resource utilization with graceful fault estimation performance degradation. An illustrative example is given to show the efficiency of the proposed method.

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Fault isolation filter for networked control system with event-triggered sampling scheme.

The fault detection problem is studied in this paper for a class of linear networked control systems (NCS) with communication delays. The aim is to generate residual signals which, in the fault-free case, are supposed to be identical to zero. In practice, this condition is not respected due to various factors such as measurements noises, model uncertainties, and in particular for NCS communication-induced delays. In this work, the communication delays are described as a random Markov jump process and a fault isolation filter is developed. Directional residuals, decoupled from the disturbance, are generated to ensure the treatment of multiple faults appearing simultaneously or sequentially. The parameters of the filter are determined to satisfy H∞ disturbance attenuation and poles assignment constraints in the frame of Markov jump linear systems. Sufficient conditions for the existence of the fault detection filter are set in terms of linear matrix inequalities. An illustrative example is given to show the efficiency of the proposed method for NCS. Copyright © 2008 John Wiley & Sons, Ltd.

Robust fault diagnosis of networked control systems

Park and Rizzoni (1993) obtained closed-form expressions for detection filters; i.e. the structure of all detection filters for a given fault direction was defined. An important consequence of these results is that they permit the formation of the optimal detection filter problem, for optimization with respect to process and measurement noises. The necessary conditions for the existence of the optimal detection filter are obtained, and a numerical solution technique is shown to be feasible by virtue of the uniqueness of the detection filter gains. From an optimization point of view the problem can be regarded as optimal estimation with some structural constraints on the observer gain. This problem is solved for both the continuous-time and the discrete-time cases.

Jaehong Park

Papers

A new interpretation of the fault-detection filter Part 2. The optimal detection filter