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1

Active fault tolerance control of a wind turbine system using an unknown input observer with an actuator fault

Li S., Wang H., Aitouche A., Tian Y., Christov N.

International Journal of Applied Mathematics and Computer Science

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2018

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Vol. 28, no. 1

69--81

EN

This paper proposes a fault tolerant control scheme based on an unknown input observer for a wind turbine system subject to an actuator fault and disturbance. Firstly, an unknown input observer for state estimation and fault detection using a linear parameter varying model is developed. By solving linear matrix inequalities (LMIs) and linear matrix equalities (LMEs), the gains of the unknown input observer are obtained. The convergence of the unknown input observer is also analysed with Lyapunov theory. Secondly, using fault estimation, an active fault tolerant controller is applied to a wind turbine system. Finally, a simulation of a wind turbine benchmark with an actuator fault is tested for the proposed method. The simulation results indicate that the proposed FTC scheme is efficient.

2

Robust fault detection of singular LPV systems with multiple time-varying delays

Hassanabadi A. H., Shafiee M., Puig V.

International Journal of Applied Mathematics and Computer Science

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2016

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Vol. 26, no. 1

45--61

EN

In this paper, the robust fault detection problem for LPV singular delayed systems in the presence of disturbances and actuator faults is considered. For both disturbance decoupling and actuator fault detection, an unknown input observer (UIO) is proposed. The aim is to compute a residual signal which has minimum sensitivity to disturbances while having maximum sensitivity to faults. Robustness to unknown inputs is formulated in the sense of the H∞-norm by means of the bounded real lemma (BRL) for LPV delayed systems. In order to formulate fault sensitivity conditions, a reference model which characterizes the ideal residual behavior in a faulty situation is considered. The residual error with respect to this reference model is computed. Then, the maximization of the residual fault effect is converted to minimization of its effect on the residual error and is addressed by using the BRL. The compromise between the unknown input effect and the fault effect on the residual is translated into a multi-objective optimization problem with some LMI constraints. In order to show the efficiency and applicability of the proposed method, a part of the Barcelona sewer system is considered.

3

Comparison of four state observer design algorithms for MIMO system

Vinodh K. E., Jovitha J, Ayyappan S.

Archives of Control Sciences

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2013

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Vol. 23, no. 2

243--256

EN

A state observer is a system that models a real system in order to provide an estimate of the internal state of the system. The design techniques and comparison of four different types of state observers are presented in this paper. The considered observers include Luenberger observer, Kalman observer, unknown input observer and sliding mode observer. The application of these observers to a Multiple Input Multiple Output (MIMO) DC servo motor model and the performance of observers is assessed. In order to evaluate the effectiveness of these schemes, the simulated results on the position of DC servo motor in terms of residuals including white noise disturbance and additive faults are compared.

4

Parity equations-based unknown input estimator for multiple-input multiple-output linear systems

Sumisławska M., Larkowski T., Burnham K. J.

Systems Science

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2010

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Vol. 36, no 3

49-59

EN

This paper presents a novel approach to the problem of unknown input estimation of multiple-input multiple-output systems. In the setup considered the measured output signals are affected by white zero-mean Gaussian measurement noise. The observer developed here is based on the parity equations concept and the Lagrange multiplier method is used to obtain an analytical solution for the filter parameters, hence minimising the unwanted effect of the noise. The paper extends the concept of the parity equation based unknown input observer approach, which has been previously developed by the authors for the case of single-input single-output systems. A simulation study is carried out, which illustrates a potential application of the proposed approach to a steel rolling mill for the purpose of improving the control performance.

5

Fault diagnosis of non-linear dynamical systems using analytical and soft computing methods

Korbicz J.

Journal of Automation Mobile Robotics and Intelligent Systems

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2007

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Vol. 1, No. 1

7-23

EN

The paper deals with the problems of robust fault detection using analytical methods (observers and unknown input observers) and soft computing techniques (neural networks, neuro-fuzzy networks and genetic programming). The model-based approach to Fault Detection and Isolation (FDI) is considered. In particular, observers for non-linear Lipschitz systems and extended unknown input observers are discussed. In the case of soft computing techniques, the main objective is to show how to employ the bounded-error approach to determine the uncertainty of the GMDH and neuro-fuzzy networks. It is shown that based on soft computing models uncertainty defined as a confidence range for the model output, adaptive thresholds can be defined. The final part of the paper presents two illustrative examples that confirm the effectiveness of the unknown input observers and the neuro-fuzzy networks approaches.

6

Robust fault detection using analytical and sort computing methods

Korbicz J.

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2006

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Vol. 54, nr 1

75-88

EN

The paper focuses on the problem of robust fault detection using analytical methods and soft computing. Taking into account the model-based approach to Fault Detection and Isolation (FDI), possible applications of analytical models, and first of all observers with unknown inputs, are considered. The main objective is to show how to employ the bounded-error approach to determine the uncertainty of soft computing models (neural networks and neuro-fuzzy networks). It is shown that based on soft computing models uncertainty defined as a confidence range for (he model output, adaptive thresholds can be described. The paper contains a numerical example that illustrates the effectiveness of the proposed approach for increasing the reliability of fault detection. A comprehensive simulation study regarding the DAMADICS benchmark problem is performed in the final part.

7

Perfect reduced-order unknown-input observer for standard systems

Krzemiński S., Kaczorek T.

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2004

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Vol. 52, nr 2

103-107

EN

The problem of the design of a perfect reduced-order unknown-input observer for standard systems is formulated and solved. The procedure of designing the observer using well-known canonical form is proposed and illustrated with a numerical example. Necessary and sufficient conditions for the solvability of the procedure are given.