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This article deals with the reliability analysis and architecture definition of a fault-tolerant electro-mechanical actuator system for unmanned aerial vehicle applications. Starting from the basic layout of the flight control system of a medium altitude long endurance unmanned aerial vehicle, the attention is focused on the fault mode analysis of the single electromechanical actuator system, with the purpose of pointing out the effects of architectural choices on the system reliability. The electro-mechanical actuator system, developed to be a self-monitoring equipment, has three operating modes: normal, fail-operative and fail-safe. Reliability and safety budgets are quantitatively evaluated via fault tree analysis using typical failure rates of system components, and the most critical paths are identified and discussed

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The aim of air data systems is the determination of flight parameters (such as pressure altitude, Mach number, angles of attack and sideslip) from measurements of local pressures and of local flow angles on wings or fuselage provided by a proper set of sensors. The active and integrated use of flight parameters in a full-authority fly-bywire flight-control system imposes redundant system architecture to achieve an adequate level of reliability and safety. In this paper a methodology for air data computation is proposed that allows the flight parameters to be evaluated on the basis of data measured by four multifunction air data probes. It takes into account the effects of the modification of aircraft configuration during flight, as well as the effects of aircraft maneuver. Finally, it includes dedicated algorithms for the management of redundancy, which are able to detect possible system failures and to provide consolidated outputs. The methodology has been implemented in the Matlab/Simulink environment and a preliminary comparison of the results with flight test data showed satisfactory performance. Nomenclaturebetween the section of installation of the probes and the center of mass of the aircraft f front = characteristic function of the stand alone probe for the frontal pressure f i = flow angle function of the ith probe f Li = local pressure function f M LE = compensation function of Mach number for δ LE f M TE = compensation function of Mach number for δ TE f P LE = compensation function of static pressure for δ LE f P TE = compensation function of static pressure for δ TE f slot = characteristic function of the stand alone probe for the slot pressure M Li = local Mach number at the location point of the ith probe M ∞ = asymptotic Mach number M ∞ = consolidated Mach number M ∞ = Mach number compensated for configuration effects M= Mach number calculated in the previous step P front i = frontal pressure measured by the ith probe P slot i = slot pressure measured by the ith probe P sa = asymptotic static pressurē P sa = consolidated static pressurê P sa = static pressure compensated for configuration effects U s = component of V s along the X axis of the body-fixed reference frame V cg = airspeed at the center of mass V s = airspeed at the section of installation of the probes x i , y i , z i = position of the ith probe (body-fixed reference frame) α = angle of attack α = consolidated angle of attack β = angle of sideslip β = consolidated angle of sideslip γ = specific heat ratio of air δ LE = deflection of the wing leading edge surface δ TE = deflection of the wing trailing edge surface λ i = local flow angle of the ith probê λ i = local flow angle compensated for roll rate effects Ω(P, Q, R) = angular velocity (roll rate P, pitch rate Q, yaw rate R)

The paper deals with the use of neural networks for the determination of pressure altitude and Mach number of a fly-by-wire high-performance aircraft during flight. In previous works the authors developed a methodology based on polynomial calibration functions for the determination of such flight parameters, together with the angles of attack and sideslip. Such an approach provided successful results, but the use of different polynomial functions in different areas was needed to map the entire flight envelope. The fading methodologies for the management of polynomial functions overlap and considerably increased both procedure complexity and the time to spent for the procedure tuning. In particular, the calibration functions related to the Mach number and static-pressure estimation are susceptible to these problems because of their high nonlinearity. The alternative approach studied in this paper, based on neural networks, provides a level of accuracy comparable with that of polynomial functions. However, such an approach is simpler, because it allows the entire flight envelope to be mapped by means of a single network for each output parameter, and so it eliminates the fading problems. In addition, the new procedure is extremely easier to tune when new data from flight tests are available. This is a very important point, because several versions of the air data computation algorithms are generally to be developed in parallel with the flight-envelope enlargement of a new aircraft

The current paper deals with the study of the electrical failures in fault-tolerant\ud flight actuators, with particular reference to the short circuits of the servovalve coils. A highfidelity\ud model of the servovalve of a modern fly-by-wire actuator is developed and validated\ud through experiments, focusing attention on the characterization of the component dynamics in\ud case of partial and total short circuits of the direct-drive motor coils. The servovalve model is\ud then used to simulate a typical on-ground built-in-test procedure to determine the limit\ud condition for the detection of a partial short circuit. Finally, once different possible\ud combinations of short circuits are injected, the degradation of performances of the whole\ud actuator is characterized through experiments, and the servovalve model is used to justify the\ud test results, highlighting and discussing the effects of the failures on the system dynamics

The work deals with the design of the force control in a hydraulic workbench for primary flight actuators, to be used for hardware-in-the-loop simulations of a modern Fly-By-Wire Flight Control System. For this application, a high-bandwidth force response is needed in order to simulate aerodynamic loads on the control surfaces, but plant uncertainties can imply significant limitations. The variation of structural stiffness, due to hinge play and hinge local deformation, the uncertainties related to the flight actuator stiffness and the ones related to the hydraulic plant parameters lead to the necessity of a robust approach to the design of the force control. In the paper, a nominal LTI model of the plant is developed and the closed-loop force control is designed by means of a loop-shaping approach for different values of the bandwidth. The stability of the closed-loop force-controlled system is then verified by a robustness analysis, assuming the structural stiffness, the flight actuator stiffness, and some of the hydraulic plant characteristics as uncertain parameters. The bandwidth of the force control is determined by finding an optimal compromise between dynamic performance and stability margin. Finally, in order to overcome the additional problems related to the flight actuator movements due to aircraft manoeuvres, a compensation feedback based on the flight actuator acceleration is proposed.

The paper deals with the development and the performance characterization of model-based health-monitoring algorithms for the detection of faults in an electro-mechanical flight control actuator for unmanned aerial system flight controls. Two real-time executable position-tracking algorithms, based on predictors with different levels of complexity, are developed and compared in terms of false alarms rejection and fault-detection capabilities, by using a high-fidelity model of the actuator. The algorithms’ performances are evaluated by simulating severe flight manoeuvres, with the actuator in normal condition and with relevant faults (motor coil faults, motor magnet degradation, voltage supply decrease). The results demonstrate that an efficient health-monitoring management can be obtained by using an accurate position-tracking monitor for prompt fault-detection and fail-safe mode engagement, and additional actuator monitors for fault-isolation only