AIRBUS efforts towards advanced real-time Fault Diagnosis and Fault Tolerant Control

Goupil, Philippe; Boada-Bauxell, Josep; Marcos, Andrés; Cortet, Emmanuel; Kerr, Murray; Costa, Hugo

doi:10.3182/20140824-6-za-1003.01945

Cited by 54 publications

(54 citation statements)

References 14 publications

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“…Signal-based identification approaches offer an easier but robust way to identify stall load situations. As described by Goupil et al (2014), during a stall load the surface seems to be stuck at its current position. Hence, the signal based identification logic for jammed actuators presented by Varga and Ossmann (2014) using a variance measure of the output signal provides a good starting point for signal based stall load identification.…”

Section: 42mentioning

confidence: 99%

“…Stall loads are intermittent saturations of the actuator, which occur when the aerodynamics loads temporarily exceed the maximum available actuator force produced by the hydraulic pressure in the system. The net effect is a temporarily stucking of the control surface at its current position (Goupil et al, 2014). Although this phenomenon can be interpreted as a certain type of LOE fault, in most cases it has merely the character of a nuisance (thus to be ignored), due to its short time appearance.…”

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confidence: 99%

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Detection and Identification of Loss of Efficiency Faults of Flight Actuators

Ossmann¹,

Varga²

2015

International Journal of Applied Mathematics and Computer Science

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We propose linear parameter-varying (LPV) model-based approaches to the synthesis of robust fault detection and diagnosis (FDD) systems for loss of efficiency (LOE) faults of flight actuators. The proposed methods are applicable to several types of parametric (or multiplicative) LOE faults such as actuator disconnection, surface damage, actuator power loss or stall loads. For the detection of these parametric faults, advanced LPV-model detection techniques are proposed, which implicitly provide fault identification information. Fast detection of intermittent stall loads (seen as nuisances, rather than faults) is important in enhancing the performance of various fault detection schemes dealing with large input signals. For this case, a dedicated fast identification algorithm is devised. The developed FDD systems are tested on a nonlinear actuator model which is implemented in a full nonlinear aircraft simulation model. This enables the validation of the FDD system's detection and identification characteristics under realistic conditions. Keywords: aerospace engineering, fault detection and diagnosis, loss of efficiency type of faults, flight actuator faults.

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Section: 42mentioning

confidence: 99%

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confidence: 99%

Detection and Identification of Loss of Efficiency Faults of Flight Actuators

Ossmann¹,

Varga²

2015

International Journal of Applied Mathematics and Computer Science

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“…However, one of the lessons learnt from the ADDSAFE project relating to sensor FDI, is that because of the uncertainty, the isolation logic required to determine the source of the faults from the three available sensors is challenging and computationally intensive and contributes to more of the execution time than the underlying observer design itself. This results in the schemes being considered as 'expensive' in terms of computation time in the flight control computer [16].…”

Section: Motivationmentioning

confidence: 99%

Sensor redundancy based FDI using an LPV sliding mode observer

Chen

Edwards

Alwi

2018

IET Control Theory & Applications

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SUMMARYIn this paper, a linear parameter varying (LPV) sliding mode sensor fault detection and isolation (FDI) scheme is proposed wherein knowledge of the measurement redundancy is utilised to achieve FDI in multiple channels simultaneously. Such a situation is common in some state-of-the-art aircraft fault diagnosis systems where information is generally/mainly measured based on triplex redundancy. The scheme proposed in this paper is based on an LPV sliding mode observer and exploits the so-called equivalent output error injection signal to create estimates of the measurement faults. In the case of sensor measurement redundancy, and where there exists a fault free (but unknown) sensor amongst the set of measurements, the fault reconstruction performance of the observer can be improved by isolating and using the output error injection signal associated with the fault free redundant sensor. Simulation results using the RECONFIGURE benchmark model demonstrate the effectiveness of the scheme.

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“…RECONFIGURE BENCHMARK MODEL The Reconfiguration of Control in Flight for Integral Global Upset Recovery (RECONFIGURE) project aims to study fault tolerant scenarios for a passenger aircraft. The benchmark mainly consists of a high-fidelity nonlinear aircraft model which is used to simulate nominal flight conditions and realistic fault scenarios [34]. The validated aircraft model has been delivered to the consortium by Airbus to explore various fault tolerant mechanisms.…”

Section: Remarkmentioning

confidence: 99%

“…The benchmark model covers the complete nonlinear flight domain along with the sensors, actuators, flight control computers, guidance and navigation mechanisms, etc. [34]. Several linear models (which covers a limited operating range) at various operating points were provided by AIRBUS.…”

Section: Remarkmentioning

confidence: 99%

Fault detection in uncertain LPV systems with imperfect scheduling parameter using sliding mode observers

Chandra¹,

Alwi

Edwards

2017

European Journal of Control

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This paper presents a sliding mode fault detection scheme for linear parameter varying (LPV) systems with uncertain or imperfectly measured scheduling parameters. In the majority of LPV systems, it is assumed that the scheduling parameters are exactly known. In reality due to noise or possibly faulty sensors, it is sometimes impossible to have accurate knowledge of the scheduling parameters and a design based on the assumption of perfect knowledge of the scheduling parameters cannot be guaranteed to work well in this situation. This paper proposes a sliding mode observer scheme to reconstruct actuator and sensor faults in a situation where the scheduling parameters are imperfectly known. The efficacy of the approach is demonstrated on simulation data taken from the nonlinear RECONFIGURE benchmark model . One approach to extending linear methods to make them work effectively across the whole plant operating range is to design (linear) observers at select operating points, and then schedule the gains with respect to certain parameters [4]. One of the main difficulties with gain scheduling is the selection of the operating points and how to choose the gains at intermediate points. Furthermore, formally, between the operating points the stability of the observer cannot be guaranteed.A more rigorous alternative approach is based on so-called linear parameter varying (LPV) system designs. In the LPV approach the gains are automatically scheduled with respect to the plant varying parameters. Another advantage is many nonlinear systems can be naturally approximated by LPV systems [13] [20]). However in all these papers the scheduling parameters are assumed to be perfectly known. However in reality this may not be the case: for example inaccurate sensors and/or faults can lead to imperfect knowledge of the parameters. The use of this corrupted information will affect the performance of the observer. The design of Luenberger-like observers in scenarios involving uncertain scheduling parameters has been investigated. In [21], using a Linear matrix inequality (LMI) framework an LPV observer was proposed. Later, a controller and a combined controllerobserver scheme for inexact continuous LPV polytopic systems was presented in [22], [23]. In [24], [25] H ∞ filters were employed to deal with uncertainty in the scheduling parameters; exploiting parameter dependent LMI methods. More recently, an H ∞ filter has been proposed to deal with both additive and multiplicative uncertainties in the LPV parameters in [26]. Recent applications of these ideas to aerospace systems have been explored in [27], [28]. A fault reconstruction scheme for LPV systems with perfect scheduling parameter knowledge, using H ∞ methods has been investigated in [29]. Very few papers have addressed specifically the fault reconstruction problem for LPV systems with uncertain scheduling parameters, notable exceptions are [30]. To the authors' knowledge,

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AIRBUS efforts towards advanced real-time Fault Diagnosis and Fault Tolerant Control

Cited by 54 publications

References 14 publications

Detection and Identification of Loss of Efficiency Faults of Flight Actuators

Detection and Identification of Loss of Efficiency Faults of Flight Actuators

Sensor redundancy based FDI using an LPV sliding mode observer

Fault detection in uncertain LPV systems with imperfect scheduling parameter using sliding mode observers

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