Wyniki wyszukiwania - Biblioteka Nauki

1

Supervisory fault tolerant control with integrated fault detection and isolation: A switched system approach

100%

Yang H. , Jiang B. , Cocquempot V. , Lu L.

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nr 1

87-97

EN

This paper focuses on supervisory fault tolerant control design for a class of systems with faults ranging over a finite cover. The proposed framework is based on a switched system approach, and relies on a supervisory switching within a family of pre-computed candidate controllers without individual fault detection and isolation schemes. Each fault set can be accommodated either by one candidate controller or by a set of controllers under an appropriate switching law. Two aircraft examples are included to illustrate the efficiency of the proposed method.

2

Application properties of methods for fault detection and isolation in the diagnosis of complex large-scale processes

100%

Kościelny J. M. , Syfert M.

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tom Vol. 62, nr 3

571--582

EN

The survey presents a selection of the methods of the fault detection and isolation suitable to be useful for the diagnostics of the complex, large scale industrial processes. The paper focuses on these methods that have appropriately high level of potential applicability in industrial practice. The novelty of the paper relies on the discussion of the dependency of the level of knowledge about diagnosed process and recommended diagnostic approaches. Appropriate recommendations were given in the convenient form of the table.

3

Active fault tolerant control of nonlinear systems: The cart-pole example

88%

Bonfè M. , Castaldi P. , Mimmo N. , Simani S.

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nr 3

441-455

EN

This paper describes the design of fault diagnosis and active fault tolerant control schemes that can be developed for nonlinear systems. The methodology is based on a fault detection and diagnosis procedure relying on adaptive filters designed via the nonlinear geometric approach, which allows obtaining the disturbance de-coupling property. The controller reconfiguration exploits directly the on-line estimate of the fault signal. The classical model of an inverted pendulum on a cart is considered as an application example, in order to highlight the complete design procedure, including the mathematical aspects of the nonlinear disturbance de-coupling method based on the nonlinear differential geometry, as well as the feasibility and efficiency of the proposed approach. Extensive simulations of the benchmark process and Monte Carlo analysis are practical tools for assessing experimentally the robustness and stability properties of the developed fault tolerant control scheme, in the presence of modelling and measurement errors. The fault tolerant control method is also compared with a different approach relying on sliding mode control, in order to evaluate benefits and drawbacks of both techniques. This comparison highlights that the proposed design methodology can constitute a reliable and robust approach for application to real nonlinear processes.

4

Residual generator fuzzy identification for automotive diesel engine fault diagnosis

88%

Simani S.

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nr 2

419-438

EN

Safety in dynamic processes is a concern of rising importance, especially if people would be endangered by serious system failure. Moreover, as the control devices which are now exploited to improve the overall performance of processes include both sophisticated control strategies and complex hardware (input-output sensors, actuators, components and processing units), there is an increased probability of faults. As a direct consequence of this, automatic supervision systems should be taken into account to diagnose malfunctions as early as possible. One of the most promising methods for solving this problem relies on the analytical redundancy approach, in which residual signals are generated. If a fault occurs, these residual signals are used to diagnose the malfunction. This paper is focused on fuzzy identification oriented to the design of a bank of fuzzy estimators for fault detection and isolation. The problem is treated in its different aspects covering the model structure, the parameter identification method, the residual generation technique, and the fault diagnosis strategy. The case study of a real diesel engine is considered in order to demonstrate the effectiveness the proposed methodology.

5

Fault detection and isolation with robust principal component analysis

75%

Tharrault Y. , Mourot G. , Ragot J. , Maquin D.

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nr 4

429-442

EN

Principal component analysis (PCA) is a powerful fault detection and isolation method. However, the classical PCA, which is based on the estimation of the sample mean and covariance matrix of the data, is very sensitive to outliers in the training data set. Usually robust principal component analysis is applied to remove the effect of outliers on the PCA model. In this paper, a fast two-step algorithm is proposed. First, the objective was to find an accurate estimate of the covariance matrix of the data so that a PCA model might be developed that could then be used for fault detection and isolation. A very simple estimate derived from a one-step weighted variance-covariance estimate is used (Ruiz-Gazen, 1996). This is a “local” matrix of variance which tends to emphasize the contribution of close observations in comparison with distant observations (outliers). Second, structured residuals are used for multiple fault detection and isolation. These structured residuals are based on the reconstruction principle, and the existence condition of such residuals is used to determine the detectable faults and the isolable faults. The proposed scheme avoids the combinatorial explosion of faulty scenarios related to multiple faults to be considered. Then, this procedure for outliers detection and isolation is successfully applied to an example with multiple faults.

6

Application of Sensitivity Theory to Fuzzy Logic Based Fdi

63%

Dalton T. , Klotzek P. , Frank P. M.

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tom Vol. 9, no 3

619-636

EN

This paper describes an application of sensitivity theory to the analysis of a certain class of fuzzy systems which can be used for fault detection and isolation (FDI). The work is divided into three main tasks. The first is the mathematical representation of some class of fuzzy systems. This is followed by an application of sensitivity theory to fuzzy systems based on the approach detailed in the first part. Finally, this method is applied to a fuzzy fault diagnosis scheme for the two-tank system, and the results compared with those achieved by the application of sensitivity theory to a non-fuzzy diagnosis scheme for the same system. Simulation results for the fuzzy and non-fuzzy fault diagnosis schemes are presented, which verify the results obtained via the application of sensitivity theory.

7

Evolutionary Multi-Objective Pareto Optimisation of Diagnostic State Observers

51%

Kowalczuk Z. , Suchomski P. , Białaszewski T.

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tom Vol. 9, no 3

689-709

EN

A multi-objective Pareto-optimisation procedure for the design of residual generators which constitute a primary instrument for model-based fault detection and isolation (FDI) in systems of plant monitoring and control is considered. An evolutionary approach to the underlying multi-objective optimisation problem is utilised. The resulting robust observer detector allows for FDI, taking into account the issue of false alarms.