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The problem of active fault-tolerant control with reconfiguration mechanism for uncertain linear systems with external disturbances is addressed applying the supervisory control approach. A key feature of the proposed approach is establishment of a set of conditions providing mutual performance in the sense of taking into account the interaction of the fault detection, isolation, and accommodation subsystems in order to achieve global fault-tolerance performance with guaranteed global stability. The efficiency of the approach is demonstrated in an example of computer simulation for a flight system benchmark.

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The work presented in this paper is undertaken within the European FP7 funded Advanced Fault Diagnosis for Sustainable Flight Guidance and Control (ADDSAFE) project. The goal is to propose new fault detection and fault diagnosis techniques that could significantly help developing environmentally-friendlier aircraft. In this paper, LPV model-based fault detection schemes are proposed and compared for robust and early detection of faults in aircraft control surfaces servo-loop. The proposed methodologies are based on a slight modification of the H 1 =H _ LPV optimization techniques proposed in [1] and [2] for systems modelled in, first polytopic manner, second linear fractional representation fashion. Both the methods aim at designing fault detection filters with enhanced fault transmission H gain and large H 1 nuisance attenuation. A complete Monte Carlo campaign from a high representative simulator, provided by Airbus as a part of the ADDSAFE project, demonstrates the potential of the proposed techniques. It is shown that both the proposed fault detection schemes can be embedded within the structure of in-service monitoring systems as a part of the Flight Control Computer software.

In avionics and aerospace multisensor systems, reliable and early detection of individual sensor faults present substantial challenges to health monitoring designers of such systems. This study addresses the problem of sensor fault diagnosis. The proposed solution is based on a non-homogeneous high-order sliding mode observer used to estimate the faults, theoretically in finite time and in the presence of bounded disturbances. The sensor faults are estimated for the class of systems satisfying the structural property of strong observability. A key feature of the proposed solution is concerned by the effect that measurement noise could have on fault reconstruction. It is shown that the fault estimation error is bounded in the L ∞ -norm sense, and an upper bound is theoretically derived. The method is applied to the problem of sensor fault estimation of a large transport aircraft. Simulation results as well as a pilot experiment are presented to demonstrate the potential of the proposed method.

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