A Nonlinear Observer-Based Strategy for Aircraft Oscillatory Failure Detection: A380 Case Study

Alcorta-Garcia, E.; Zolghadri, Ali; Goupil, Philippe

doi:10.1109/taes.2011.6034665

Cited by 59 publications

(24 citation statements)

References 18 publications

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“…The gain L 2 has been proposed in [21] in order to improve the robustness abilities of (2) and to relax restrictiveness of the LMIs used for the observer design. The gains L 3 and L 4 have been introduced in [22] to improve robustness of the system with respect to v, d, θ and sensitivity with respect to f . These gains have to be assigned to guarantee (or to ¦nd a trade-o¨) the system stability and performance, and to satisfy the required estimation and fault detection speci¦cations.…”

Section: Robust Observer Equationsmentioning

confidence: 99%

Nonlinear observer techniques for oscillatory failure case detection

Efimov

Zolghadri

2013

Progress in Flight Dynamics, Guidance, Navigation, Control, Fault Detection, and Avionics

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The problem of observer design for fault detection in a class of nonlinear systems subject to parametric and signal uncertainties is studied. The design procedure includes formalized optimization of observer free parameters in terms of trade-o¨s for fault detection performance and robustness to external disturbances or model uncertainties. The technique makes use of some monotonicity conditions imposed on the estimation error dynamics. E©ciency of the proposed approach is demonstrated through the Oscillatory Failure Case (OFC) in aircraft control surface servoloops.

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Section: Robust Observer Equationsmentioning

confidence: 99%

Nonlinear observer techniques for oscillatory failure case detection

Efimov

Zolghadri

2013

Progress in Flight Dynamics, Guidance, Navigation, Control, Fault Detection, and Avionics

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“…An overview of the recent development of FTC methods for aerial vehicles are given in [1], [2], [3] and [4]. Specific fault diagnosis approaches are treated in [5], [6], [7] and [8] related to control surfaces, and in [9] to the airspeed sensor system. Two control techniques, sliding mode control (SMC) [10], [11] and L 1 adaptive control [12], are claimed to offer robust properties against matched uncertainties.…”

Section: Introductionmentioning

confidence: 99%

Performance Comparison of Controllers with Fault-Dependent Control Allocation for UAVs

Sørensen

Hansen

Breivik

et al. 2017

J Intell Robot Syst

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This paper combines fault-dependent control allocation with three different control schemes to obtain fault tolerance in the longitudinal control of unmanned aerial vehicles. The paper shows that faultdependent control allocation is able to accommodate actuator faults that would otherwise be critical and it makes a performance assessment for the different control algorithms: an L 1 adaptive backstepping controller; a robust sliding mode controller; and a standard PID controller. The actuator faults considered are the partial to total loss of the elevator, which is a critical component for the safe operation of unmanned aerial vehicles. During nominal operation, only the main actuator, namely the elevator, is active for pitch control. In the event of a partial or total loss of the elevator, faultdependent control allocation is used to redistribute control to available healthy actuators. Using simulations of a Cessna 182 aircraft model, controller performance and robustness are evaluated by metrics that assess control accuracy and energy use. System uncertainties are investigated over an envelope of pertinent variation, showing that sliding mode and L 1 adaptive backstepping provide robustness, where PID control falls short. Additionally, a key finding is that the fault-dependent

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“…Classical diagnostic techniques was shown, but on simulated data. Specific faults and failure modes have also attracted considerable attention, performance monitoring and detection of oscillatory behavior was treated in [17]. Research on the airspeed sensor problem using multiple sensors have been treated in [18] and [19] who analyzed performance of linear time-invariant fault detection methods applied on parallel airspeed sensors, but more general results on airspeed sensor fault diagnosis have been sparse.…”

Section: Introductionmentioning

confidence: 99%

Diagnosis of Airspeed Measurement Faults for Unmanned Aerial Vehicles

Hansen

Blanke²

2014

IEEE Trans. Aerosp. Electron. Syst.

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Abstract-Airspeed sensor faults are common causes for incidents with unmanned aerial vehicles with pitot tube clogging or icing being the most common causes. Timely diagnosis of such faults or other artifacts in signals from airspeed sensing systems could potentially prevent crashes. This paper employs parameter adaptive estimators to provide analytical redundancies and a dedicated diagnosis scheme is designed. Robustness is investigated on sets of flight data to estimate distributions of test statistics. The result is robust diagnosis with adequate balance between false alarm rate and fault detectability.

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A Nonlinear Observer-Based Strategy for Aircraft Oscillatory Failure Detection: A380 Case Study

Abstract: International audienc

Cited by 59 publications

References 18 publications

Nonlinear observer techniques for oscillatory failure case detection

Nonlinear observer techniques for oscillatory failure case detection

Performance Comparison of Controllers with Fault-Dependent Control Allocation for UAVs

Diagnosis of Airspeed Measurement Faults for Unmanned Aerial Vehicles

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