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The following topics are dealt with: abnormal events management; sliding mode methods; fault-tolerant control systems; intelligent monitoring; sensor network scheduling; fault detection; large-scale distributed systems; and space domain.
This paper presents a new scheme for actuator fault detection and isolation (FDI) with application to actuator health monitoring on an aircraft. The Single Model Active Fault Detection and Isolation System (SMAC-FDI) efficiently detects and isolates a faulty actuator in a system. This method has a short response time and is robust against model uncertainties, sensor noise, external disturbances. The...
This paper discusses the problem of designing the sliding-mode-based sensor faults estimation in a general structure suitable on the actuator as well as sensor faults detection and estimation. The problem addressed is indicated as an unified algebraic approach giving sufficient conditions of solution. Lyapunov inequality implying from two linear matrix inequalities are outlined to posses a stabile...
Time series trend extraction is of great interest in data mining research recently. For example, it can be applied in system monitoring to detect faults and abnormalities in process industry and medical care. In this paper, a trend extraction algorithm based on variable time window length median filter is presented. The trend filtered can not only reflect the basic geometry of noised signal, but also...
Wavelet-based techniques for fault detection usually employ one of two basic approaches, namely (a) decomposition of a measured signal containing fault-related information or (b) decomposition of a residue calculated as the difference between sensor readings and the output of a model. An alternative approach, which was recently proposed in, consists of employing the wavelet transform to identify a...
For sequential jumps detection, isolation and estimation in discrete-time stochastic linear systems, Willsky and Jones. have developed the Generalized Likelihood Ratio (GLR) test. After each detection and isolation of one jump, the treatment of another possible jump is obtained by a direct state estimate and covariance incrementation of the Kalman filter originally designed on the jump-free system...
This paper investigates the detection filter design problem for the detection and isolation of faults in linear parameter varying (LPV) systems by means of dynamic inversion where the system matrix depends affinely from the parameters. A method for the construction of the inverse, relying on the concept of parameter varying invariant subspaces and related concepts of classical geometrical system theory...
Sliding mode methods have been historically studied because of their strong robustness properties to a certain class of uncertainty. This is achieved by employing nonlinear control/injection signals to force the system trajectories to attain in finite time a motion along a surface in the state-space. This paper will consider how these ideas can be exploited for fault detection (specifically fault...
In this paper the design of sliding mode observers for gyro and thruster fault detection and isolation in the Mars Express satellite is presented. The results are part of a project with the goal of examining the potential applicability of the sliding mode observer technique to on-board satellite deployment. A Monte Carlo campaign has been performed to assess the performance and robustness of the sliding...
The problem of model-based fault detection is studied with application of the Kalman filter for residual generation. The filter has two important incoming parameters, the state noise and the output noise covariance matrices, which tuning is analyzed in order to optimize the fault detection performance. The problem is formulated through an appropriate optimization criteria and applied to the oscillatory...
A method for failure detection and isolation for redundant aircraft sensors is presented. The outputs of the concerned sensors are involved in the computation of flight law controls, and the objective is to eliminate any perturbation before propagation in the control loop when selecting a unique flight parameter among a set (generally 3) of redundant measurements. The particular case of an oscillatory...
In this paper, a design methodology and implementation architecture for diagnosers in the framework of hybrid systems is proposed. The design methodology is based on the hybrid automata model that represents the system behaviour by means of the interaction of continuous dynamics and discrete events. The architecture is composed by means of modules which realize the mode recognition and diagnostic...
This paper addresses the problem of design a fault detection system for switched systems with unknown inputs. The residual generator based robust fault detection filter (RFDF) will be used, where the switching signal is assumed to be known, and the continuous states will be estimated, resulting a generation of residual signals for each linear model. Dwell-time constraint will be used to ensure the...
Significant research has been carried out over the past three decades in the area of fault tolerant control. Most methods available in the chemical engineering literature are capable of detecting, identifying, estimating and accommodating faults for nonlinear processes with continuous states without state dependent and controlled switching. This work is aimed at developing a method for diagnosing...
This paper presents the application of standard PCA technique to fault diagnosis system design. Based on the fault detectability analysis of existed test statistics, the joint use of some test statistics is recommended. Our further study is dedicated to develop a fault isolation approach based on likelihood ratio test, on which the off-set and scaling fault can be easily isolated with explicit off-set...
A new approach to fault detection and isolation that combines Principal Component Analysis (PCA), Clustering and Pattern Recognition is presented. Single, multiple faults which may cause errors in the sensor readings and/or in the actuators as well as process faults are considered. Determination of the number of principal components is based on the statistical test ANOVA following the approach proposed...
In this paper, Sensors FDI scheme of Linear Discrete-Time Periodic Systems using Principal Component Analysis (PCA) is proposed. The idea of this FDI scheme is to model the Linear Discrete-Time Periodic System with multiple models PCA denoted T-PCA (T is the period). For this approach, a database of measurements collected on a system in normal process operation and the period T of this system are...
This work focuses on fault detection applied to static converters. A new method for estimating parameters of dynamic model of the buck converter is proposed, based on recent algebraic parameters estimators. The diagnosis scheme developed in this paper computes online the filter capacitor aging by determining the equivalent series resistance (ESR). The capacitance and inductance value are also estimated...
In this paper, the sliding mode approach is used to control of a quadrotor unmanned aerial vehicle (UAV) in the presence of external disturbance and actuator fault. Fault detection unit can detect the actuator fault using a state estimator. Then it reconfigures the structure of controller such that some control performance is achieved. The proposed control structure has the advantage of disturbance...
In this paper, we present a multiple-model based method of analyzing for the longitudinal controller performance loss caused by actuator faults in the aircraft elevator system. More specifically, we consider the effects of the failure-induced elevator actuator bandwidth reduction integrated with the longitudinal flight dynamics. Results of the proposed multiple-model based fault detection, isolation,...
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