Active Fault Diagnosis Based on Stochastic Tests

Poulsen, Niels Kjølstad; Niemann, Hans Henrik

doi:10.2478/v10006-008-0043-6

Cited by 57 publications

(30 citation statements)

References 17 publications

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“…This area has been considered in a number of papers Campbell and Nikoukhah, 2004b;Kerestecioglu and Zarrop, 1994;Niemann, 2006b;Nikoukhah, 1994;1998;Nikoukhah et al, 2000;Poulsen and Niemann, 2008) and books (Campbell and Nikoukhah, 2004a;Kerestecioglu, 1993;Zhang, 1989).…”

Section: Fault Diagnosismentioning

confidence: 99%

“…As output from the diagnosis system, a standard residual signal known from the passive FDI approach is applied (Frank and Ding, 1994). Using the AFD approach of Niemann (2005;2006b), as well as Poulsen and Niemann (2008), the auxiliary input is injected into the closed-loop system in such a way that the residual is decoupled from the auxiliary input in the nominal case. In the event of parametric faults (system changes), the residual will contain a component related to the auxiliary input.…”

Section: Fault Diagnosismentioning

confidence: 99%

See 1 more Smart Citation

A model-based approach to fault-tolerant control

Niemann¹

2012

International Journal of Applied Mathematics and Computer Science

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A model-based controller architecture for Fault-Tolerant Control (FTC) is presented in this paper. The controller architecture is based on a general controller parameterization. The FTC architecture consists of two main parts, a Fault Detection and Isolation (FDI) part and a controller reconfiguration part. The theoretical basis for the architecture is given followed by an investigation of the single parts in the architecture. It is shown that the general controller parameterization is central in connection with both fault diagnosis as well as controller reconfiguration. Especially in relation to the controller reconfiguration part, the application of controller parameterization results in a systematic technique for switching between different controllers. This also allows controller switching using different sets of actuators and sensors.

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Section: Fault Diagnosismentioning

confidence: 99%

Section: Fault Diagnosismentioning

confidence: 99%

A model-based approach to fault-tolerant control

Niemann¹

2012

International Journal of Applied Mathematics and Computer Science

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“…The possibility of isolating a fault is evident for cases of single faults. Isolation if multiple faults should occur could be accomplished using active fault isolation techniques (Poulsen and Niemann, 2008), (Gelso and Blanke, 2009). The remedial action in case of an airspeed sensor system fault would be to avoid using airspeed in the avionics.…”

Section: Airspeed System Defectmentioning

confidence: 99%

A Framework for Diagnosis of Critical Faults in Unmanned Aerial Vehicles

Hansen

Blanke

Adrian³

2014

IFAC Proceedings Volumes

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Unmanned Aerial Vehicles (UAVs) need a large degree of tolerance towards faults.If not diagnosed and handled in time, many types of faults can have catastrophic consequences if they occur during flight. Prognosis of faults is also valuable and so is the ability to distinguish the severity of the different faults in terms of both consequences and the frequency with which they appear. In this paper flight data from a fleet of UAVs is analysed with respect to certain faults and their frequency of appearance. Data is taken from a group of UAV's of the same type but with small differences in weight and handling due to different types of payloads and engines used. Categories of critical faults, that could and have caused UAV crashes are analysed and requirements to diagnosis are formulated. Faults in air system sensors and in control surfaces are given special attention. In a stochastic framework, and based on a large number of data logged during flights, diagnostic methods are employed to diagnose faults and the performance of these fault detectors are evaluated against flight data. The paper demonstrates a significant potential for reducing the risk of unplanned loss of remotely piloted vehicles used by the Danish Navy for target practice.

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“…The input signal designed to improve the quality of detection can be inconvenient from a control perspective. Therefore, integrated active fault detection and control for deterministic uncertain models (Niemann, 2006;Poulsen and Niemann, 2008;Ashari et al, 2012b) and stochastic models (Blackmore et al, 2008) was studied.…”

Section: Introductionmentioning

confidence: 99%

On infinite horizon active fault diagnosis for a class of non-linear non-Gaussian systems

Punčochář

Šmandl

2014

International Journal of Applied Mathematics and Computer Science

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The paper considers the problem of active fault diagnosis for discrete-time stochastic systems over an infinite time horizon. It is assumed that the switching between a fault-free and finitely many faulty conditions can be modelled by a finite-state Markov chain and the continuous dynamics of the observed system can be described for the fault-free and each faulty condition by non-linear non-Gaussian models with a fully observed continuous state. The design of an optimal active fault detector that generates decisions and inputs improving the quality of detection is formulated as a dynamic optimization problem. As the optimal solution obtained by dynamic programming requires solving the Bellman functional equation, approximate techniques are employed to obtain a suboptimal active fault detector.

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Active Fault Diagnosis Based on Stochastic Tests

Cited by 57 publications

References 17 publications

A model-based approach to fault-tolerant control

A model-based approach to fault-tolerant control

A Framework for Diagnosis of Critical Faults in Unmanned Aerial Vehicles

On infinite horizon active fault diagnosis for a class of non-linear non-Gaussian systems

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