System for controlling a device provided with at least one redundant sensor for detecting and isolating failures of said sensors

Abstract

This system for controlling an aircraft engine (1) provided with at least one item of equipment (1i) comprises one or more redundant sensors (3) each capable of measuring an operating variable of the aircraft engine (1), and two measurement channels (3ia, 3ib) of the redundant sensor for each item of equipment (1i), at least one control means (2a, 2b) configured to determine a command intended for the at least one item of equipment (1i) as a function of the measurement of at least one variable and a selected measurement. The system comprises a computing means (5) configured to determine the selected measurement by means of an observer (5a) comprising two Kalman filters using an operating model of the aircraft engine (1). The computing means (5) is configured to detect a failure of one of the measurement channels (3ia, 3ib), and to adjust the operating model as a function of at least one individual characteristic of the aircraft engine (1).

Description

[0001] DESCRIPTION

[0002] TITLE: Control system for a device equipped with at least one redundant sensor with detection and isolation of failures of said sensors

[0003] Technical field

[0004] The technical field of the invention is control systems, and more specifically observer control systems.

[0005] In a non-limiting application, the invention relates to cylinder control systems acting on an actuator of an aircraft engine, such as a cylinder controlling the injection of fuel into the engine, and the control of the operation of the cylinder.

[0006] Previous techniques

[0007] State-of-the-art aircraft engine control systems use various types of sensors that measure a monitored operating parameter. In the case of cylinders controlling fuel injection, the sensors measure the position of the cylinders in order to monitor compliance with an injection setpoint.

[0008] This measurement is redundant. Two measurement channels are therefore used and should ideally provide the same measurement value, within measurement uncertainties.

[0009] State-of-the-art control systems do not allow for the localization of bias or drift in one of the measurement channels of a redundant sensor. In fact, in the event of a cross-check failure, determined by a difference between measurement channels greater than a threshold, an arbitrary choice is made of the channel with the minimum value, the channel with the maximum value, or an average of the two measurement channels. There is therefore a risk of continuing to use an erroneous measurement or a value dependent on this erroneous measurement.

[0010] From the state of the prior art, the following documents are known. Document US20200201312 discloses a technology for isolating and detecting faults on aeronautical anemometric sensors (total pressure, static pressure, etc.). To achieve this, it is described to use a bank of KALMAN filters and its residuals (i.e. differences between the estimated measurement and the actual measurement) coupled with a truth table to detect and isolate a faulty sensor or to reconfigure it on its model in the event of a fault.

[0011] Document CN 1 101 18128 describes a similar teaching but based on a particular formatting of the residues (WSSR: Weighted Sum of Squares of Residuals) for isolation and detection.

[0012] Document US2009043447 also describes a similar teaching, but based on different indicators (delta on averages of the evolutions of the states and / or the residues) to detect and isolate faults. In addition, in the case where the faulty sensor cannot be isolated, a probabilistic approach (occurrence of faults) is used.

[0013] These different state-of-the-art documents allow to detect the fault of a sensor among a set of sensors measuring different physical quantities. Moreover, these different documents are based on different Kalman filter architectures in the form of "banks": several different Kalman filters are used with the same sensors and the interpretation of the residuals (i.e. differences between the model outputs and the sensor measurements) allows to detect the sensor of a physical quantity that is faulty.

[0014] The applicant proposed in the unpublished patent application FR 2 200 875 a method based on a Kalman filter using a model representative of the operation of the device for the detection of the healthy channel during a gap between measurement channels on a redundant sensor.

[0015] However, the use of such a method can reveal significant differences between the model's predictions and the corresponding quantities measured in flight. These differences are due to several factors, in particular manufacturing variability, engine aging or variations in power and air sampling. Presentation of the invention

[0016] In view of the above, the aim of the invention is to improve the accuracy of the model in order to reduce the deviations between the predictions and the corresponding quantities measured in flight.

[0017] The subject of the invention is therefore a system for controlling an aircraft engine provided with at least one piece of equipment, the control system comprising at least one redundant sensor capable of each measuring an operating quantity of the aircraft engine, and two measurement channels of the redundant sensor for each piece of equipment, at least one control means configured to determine a command intended for the at least one piece of equipment as a function of the measurement of at least one operating quantity of the aircraft engine and a measurement selected for the controlled equipment.

[0018] The system further comprises a calculation means configured to determine the measurement selected for the at least one controlled equipment, by an observer comprising two Kalman filters each using the same operating model of the aircraft engine, as a function of the at least one measurement of the operating quantity of the aircraft engine and the measurements of the measurement channels of the redundant sensor for the controlled equipment.

[0019] The calculation means is configured to detect a failure of one of the measurement channels of the redundant sensor so as to exclude the measurement channel therefrom, the calculation means being further configured to recalibrate the operating model as a function of at least one individual characteristic of the aircraft engine.

[0020] Such a control system allows the model to be recalibrated according to the individual characteristics of the aircraft engine and thus improves the accuracy of the estimates made by the observer based on Kalman filters. The robustness of the accommodation of a failure is thus improved.

[0021] According to one characteristic, the calculation means comprises: an observer comprising two Kalman filters each using the same operating model of the aircraft engine and determining for one an estimate of a bias of a first measurement channel, and for the other an estimate of a bias of a second measurement channel, as a function of the at least one measurement of the operating magnitude of the aircraft engine, the measurement of the first measurement channel of the redundant sensor and the measurement of the second measurement channel of the redundant sensor, a comparison means configured to emit a selection signal as a function of a comparison between, on the one hand, the absolute value of the difference between the estimate of the bias of the first measurement channel and the estimate of the bias of the second measurement channel, and on the other hand, a predetermined verification threshold between the two measurement channels,

[0022] - a selection device configured to transmit the selected measurement equal to the measurement of the first measurement channel, to the measurement of the second measurement channel or to the average of the measurements of the first measurement channel and of the second measurement channel according to said selection signal, and

[0023] - a recalibration means configured to recalibrate the operating model used by said observer as a function of corrective factors representative of at least one individual characteristic of the aircraft engine.

[0024] For example, the recalibration means includes a memory intended for storing the corrective factors in the form of a map.

[0025] Advantageously, the recalibration means is configured to iteratively update the values ​​of the mapping when the aircraft engine is operating in a stabilized regime.

[0026] Such a recalibration means allows the recalibration of the model according to the individual characteristics of the aircraft engine taking into account both the manufacturing variability and its evolution over time. Preferably, the iterative update is carried out according to a predetermined gain factor.

[0027] Advantageously, the comparison means is configured to carry out the following steps: the bias estimates are stored at the moment when it is determined that the difference in absolute value between the measurement of the first measurement channel and the measurement of the second measurement channel is greater than a predetermined threshold and a selection signal is emitted indicating to the selection device to transmit a selected measurement equal to the measurement of the measurement channel of the redundant sensor for which the absolute value of its bias estimate is the lowest. Preferably, the bias estimates continue to be carried out even after storage.

[0028] For example, the redundant sensor's measuring channels measure the position of the cylinders controlling the variable geometries of the compressors, the variable nozzle section or the fuel metering valve.

[0029] According to another aspect, the invention relates to a method for controlling an aircraft engine provided with at least one piece of equipment, at least one sensor capable of measuring an operating quantity of the aircraft engine, and measurement channels of the redundant sensor for each piece of equipment, the control method comprising steps of: determining a command intended for at least one piece of equipment as a function of the at least one measurement of the operating quantity of the aircraft engine and a measurement selected for the controlled equipment, determining a measurement selected for the at least one controlled equipment, by an observer comprising two Kalman filters each using the same operating model of the aircraft engine adjusted by corrective factors representative of at least one individual characteristic of the aircraft engine,as a function of at least one measurement of the operating magnitude of the aircraft engine and measurements of the measurement channels of the redundant sensor for the controlled equipment. Advantageously, the control method comprises a prior step of iteratively updating the corrective factors carried out when the aircraft engine is operating in a stabilized regime.,

[0030] According to another aspect, the invention relates to an aircraft equipped with a control system or comprising a control method as described above.

[0031] Brief description of the drawings

[0032] Other aims, characteristics and advantages of the invention will appear on reading the following description, given solely by way of non-limiting example, and made with reference to the appended drawings in which:

[0033] [Fig 1] illustrates the main elements of a control system based on two Kalman filters according to the invention;

[0034] [Fig 2] illustrates the main elements of a calculation means provided on a control system according to the invention; and

[0035] [Fig 3] illustrates a flowchart of an update of the corrective factors according to the invention.

[0036] Detailed description of at least one embodiment

[0037] The control system according to the invention is based on the use of two Kalman filters to detect and locate a simple failure of a redundant sensor in order to accommodate acquisition on the healthy channel instead of arbitrarily choosing a channel and potentially selecting the wrong channel. According to the invention, the two Kalman filters are identical, but each supplied by a different measurement channel, namely a first measurement channel called the local channel for one and a second measurement channel called the "cross" channel for the other.

[0038] In an application to an aircraft, and to the control of the engine of an aircraft, it is then possible to avoid an engine event, such as a loss of thrust control LOTC (acronym for "Loss of Thrust Control"). Figure 1 illustrates the main elements of a control system based on an observer comprising two Kalman filters according to the invention.

[0039] As previously stated, such a control system has applications in aeronautics and is used to control a device, such as an engine for an aircraft. For example, the control system may be used for controlling the operation of a fuel injection control actuator in an aircraft engine.

[0040] Thus, an aircraft engine 1 is controlled by a control means 2a, 2b as a function of the difference between a setpoint CS of an operating parameter of the aircraft engine 1 (for example, the rotation speed) and a measurement Y by a sensor 3 of the operating parameter of the aircraft engine 1 corresponding to the setpoint CS.

[0041] The difference between the CS setpoint and the Y measurement is determined by means of a subtractor 4.

[0042] The first control means 2a may be an open-loop or closed-loop control means and makes it possible to determine the control uc The second control means 2b is a closed-loop control means.

[0043] More precisely, the first control means 2a makes it possible to determine a control instruction u c as a function of the difference between the setpoint CS and the measurement Y when the first control means 2a is a closed-loop control means. The first control means 2a makes it possible to determine a control setpoint u c as a function of the measurement Y when the first control means 2a is an open-loop control means. This control instruction u c is received by a second control means 2b in order to determine a command u of at least one equipment li taking into account a selected measurement u s received from a computing means 5 comprising an observer 5a based on two Kalman filters 5ai and 5a2 (figure 2).

[0044] It will be understood that the use of two control means 2a, 2b makes it possible to control several separate pieces of equipment li acting on the devices as a function of the measurement Y and / or the setpoint CS according to the structure of the first control means 2a. In the case of an aeronautical engine controlled in this way, the pieces of equipment li controlled may be the fuel meter or the variable geometry blades of said engine. These pieces of equipment contribute to the operation of the engine, and to the realization of the control, for example the rotation speed of the engine. It is thus understood that to realize the setpoint CS through the measurement Y, the control u is of vector type, and comprises a measurement selected for each piece of equipment li of the aircraft engine 1. It should be noted that the quantities u c , u s , CS, Y, UL and ux can be vectors.

[0045] In order to ensure that each device 11 carries out the command determined by the second control means 2b, measurement channels 3ia, 3ib specific to each device 11 are used. Each pair of measurement channels 3ia, 3ib is derived from the redundancy of a measurement sensor and its acquisition chain. They thus measure the same quantity so that the measurement is always available even in the event of failure of one of the measurement channels 3ia, 3ib of a specific redundant sensor. The measurements of the first measurement channel 3ia, or local channel, of several sensors (with i varying from 1 to j) can be concatenated in the vector UL. The measurements of the second measurement channel 3ib, or cross channel, of several sensors can be concatenated in the vector u x. In Figure 1, a single piece of equipment li is illustrated for the sake of readability. It will be understood that an aircraft engine is generally equipped with multiple pieces of equipment li, each equipped with several specific redundant sensors, each redundant sensor using a pair of measurement channels 3ia, 3ib.

[0046] However, this redundancy then poses the problem of determining the measurement channels 3ia,3ib to be taken into account in the calculation of the selected measurement u s to be transmitted to the second control means 2b.

[0047] Indeed, simple cases such as the absence of a signal or identical signals can be handled with logical operators. However, more complex cases such as a drift or bias of a measurement channel of a sensor cannot be handled in this way. The calculation means 5 receives as input the measurements UL, UX of the measurement channels 3ia, 3ib of the redundant sensor and one or more measurements Y of the sensor 3. It outputs the selected measurement signal u s to the second control means 2b. The calculation means 5 is provided with an observer 5a comprising two Kalman filters 5ai and 5a2 (figure 2), making it possible to determine the selected measurement u s according to the signals of the sensors UL,UX,Y. The observer uses a model representative of the operation of the aircraft engine 1 and of at least one piece of equipment li and makes it possible to isolate a faulty measurement channel coming from one of the measurement channels 3ia,3ib of the redundant sensor measuring each piece of equipment li.

[0048] The selected measurement us is obtained by comparing the additive biases estimated on the first measurement channel 3ia with the additive biases estimated on the second measurement channel 3ib. The Kalman filters then allow, by varying in real time the additive biases on each of the model inputs, to converge the model outputs with the Y measurements of the engine. Convergence allows to minimize the residuals. The biases obtained then directly represent the difference between the real measurement of the controlled equipment (determined by observation via its effect on the aircraft engine) and the chosen measurement UL, UX from one of the measurement channels 3ia, 3ib of the sensor.

[0049] The adjustment of the filter performance (gains) is optimally achieved through the resolution of a standard problem (e.g., RICCATI algebraic equation).

[0050] More precisely, the calculation means 5 carries out the estimation of the biases associated with each measurement channel 3ia or 3ib of the redundant sensor.

[0051] Figure 2 illustrates the main elements of the calculation means 5 according to the invention.

[0052] The calculation means 5 comprises an observer 5a using two Kalman filters referenced 5ai and 5a2, a comparison means 5b, and a selection device referenced 5c.

[0053] As indicated previously, the observer 5a uses a model representative of the operation of the aircraft engine 1. In the preferred embodiment, the model used is a tangent linearized model and the observer 5a comprises two Kalman filters using this same model, but each fed by a different measurement channel. It remains, however, possible to use any disturbance estimator which uses a tangent linearized model. It is also possible to replace the tangent linearized model with a physical and non-linear model. In the latter case, the Kalman filters used to estimate the disturbances on the actuator signals are extended Kalman filters which make it possible to locally linearize the problem.

[0054] The representative model of the operation of the aircraft engine 1 is based on a state representation of the system represented by the aircraft engine 1.

[0055] As is known, a state representation of a linear system can be written: where A, B, C, D are matrices that allow us to represent the contributions of the states xk and the commands uk on the value of the states at the following instant xk+i and the measurements yk.

[0056] However, real systems are generally non-linear and their state representation then takes the following general form: where f and g are any functions which allow the system to be linearized by Taylor series developments around any operating point of the system.

[0057] We then obtain in the vicinity of a point {x0, u0} the following linearized tangent state representation: in which,

[0058] In the context of accommodating measurement deviation failure on a redundant sensor on an aircraft engine, such as an LVDT sensor

[0059] (acronym for "Linear Variable Differential Transformer") measuring the linear position of a cylinder on one of the motor actuators, we can choose the following state representation:

[0060] XN2 the rotation speed of the low pressure (LP) shaft,

[0061] XN25 the rotation speed of the high pressure (HP) shaft,

[0062] T2 the temperature in the thermodynamic plane of the LP compressor, T25 the temperature in the thermodynamic plane of the HP compressor,

[0063] P2 the pressure upstream of the LP compressor,

[0064] WF32 the fuel flow into the combustion chamber,

[0065] XN2R the reduced speed of the LP shaft,

[0066] XN25R reduced HP shaft speed,

[0067] WF32R2 reduced fuel flow in the combustion chamber, A8 variable nozzle section,

[0068] ARDE the angle of the LP compressor inlet steering wheel,

[0069] - ASTA the angle of the variable stators of the HP compressor, DPQ23 the ratio between the static pressure and the total pressure in an intermediate plane between the LP and HP compressors, PS32Q2 the reduced static pressure in the combustion chamber, T std a standard reference temperature, P std a standard reference pressure.

[0070] Note that the XN2 and XN25 regimes are both in the x states, since they are governed by a differential equation that we consider through the state representation, and in the y measurements since we measure them.

[0071] We then have: 11

[0072] The coefficients a ij , b ij , c ij , d ij , present in the matrices A, B, C, D as the elements of x0(XN2R0and XN25R0), u O (WF32R20, A80, ARDE0and ASTA0) and y0(XN2R0, XN25R0, DPQ23O and PS32Q20) are obtained by a classic identification procedure.

[0073] Note that the first two lines of C and D are trivial since we have XN2R k = XN2R k and XN25R k = XN25R k .

[0074] As the engine behavior evolves with its load, we can identify matrices A, B, C, D and vectors x0, u0,y0 for operating points progressively distributed between idle and full throttle. We then obtain a state representation conforming to equation 1 for each operating point, and between two identified operating points the system model is given by a term-by-term interpolation of the elements of these matrices.

[0075] The operating quantity representing the position along the operating line can typically be PS32Q2, i.e. the reduced static pressure in the combustion chamber. However, it is still possible to use any other quantity that evolves bijectively with the engine load. For example, it is possible to use operating quantities such as pressure P32, speeds XN2, XN25, reduced speeds XN2R, XN25R, fuel flow WF32 or reduced fuel flow WF32R2.

[0076] This representation is just on the ground, but the engine behavior also varies according to the ambient air conditions, themselves a function of the altitude (noted ALT) and the Mach number (noted XM) of the aircraft. The values ​​of the coefficients of A, B, C, D, x0, u0, y0 are therefore not only derived from a one-dimensional interpolation along the operating line, but also from an interpolation in a cube whose three dimensions are typically PS32Q2, ALT and XM.

[0077] We can then express the state representation in the following form:

[0078] It should be noted that although the determination of the values ​​of the elements x0, u0, y0 has been described with reference to an interpolation typically carried out from a table of values, it is possible to use instead, mathematical functions representing the evolution of each quantity of the model along an operating line.

[0079] Also, although the description refers to altitude and Mach number to take into account ambient air conditions, it remains possible to replace these sequences with other quantities representative of the air conditions at the engine terminals.

[0080] The Kalman filters 5ai and 5a2 of the observer 5a make it possible, taking into account one or more measurements Y, to determine, respectively, an estimate of the bias of the first measurement channel ÛL corresponding to the measurement UL of the first measurement channel 3ia of the redundant sensor, and an estimate of the bias of the second measurement channel ûx corresponding to the measurement u x of the second measuring channel 3ib of the redundant sensor.

[0081] The comparison means 5b is configured to determine a selection signal, denoted sel, as a function of the comparison between, on the one hand, the absolute value of the difference between the estimate of the bias ÛL of the first measurement channel and the estimate of the bias ûx of the second measurement channel, and on the other hand, a predetermined verification threshold between the two measurement channels, a so-called “cross-check” threshold.

[0082] The choice of the selected measurement is made according to the cross-check threshold. If the cross-check threshold is not exceeded, the arithmetic mean of the two measurement channels is selected.

[0083] If the cross-check threshold is exceeded, there are two possible cases. In the first case, if the estimated bias on the first measurement channel of the actuator affected by the cross-check failure is greater in absolute value than the estimated bias on the second measurement channel, the measurement of the second channel is selected. In the second case, if the estimated bias on the first channel of the actuator affected by the cross-check failure is less than or equal in absolute value to the estimated bias on the second measurement channel, the measurement of the first channel is selected.

[0084] Depending on the result of the comparisons, the selection signal sel is then transmitted to a selection device 5c also receiving as input the measurement UL of the first measurement channel 3ia and the measurement u x of the second measuring channel 3ib.

[0085] The selection device 5c comprises a calculation means 5d configured to carry out the average of the measurement UL of the first measurement channel 3ia and of the measurement u x of the second measurement channel 3ib. The selection device 5c also comprises a logic gate 5e receiving as input on the one hand the selection signal sel and on the other hand the measurement UL of the first measurement channel 3ia, the measurement Ux of the second measurement channel 3ib and the average of the measurement UL of the first measurement channel 3ia and the measurement u x of the second measuring channel 3ib.

[0086] Depending on the sel selection signal received, the selection device 5c transmits the UL measurement of the first measurement channel 3ia, the u measurement x of the second measurement channel 3ib or the average of the UL measurement of the first measurement channel 3ia and the u measurement x of the second measuring channel 3ib in the form of the selected measuring signal us.

[0087] The following [Table 1] illustrates the truth table resulting from the actions of the comparison means 5b and the selection device 5c.

[0088] [Table 1]

[0089] The calculation means 5 makes it possible to detect that a measurement channel 3ia, 3ib is broken or faulty. A measurement channel is considered to be faulty if the difference measured between the two channels is greater than the cross-check threshold and if the estimate of the bias associated with the other channel is lower in absolute value than that of the channel in question. The observer then uses the measurements provided by the healthy measurement channel of the redundant sensor. This arbitration can be done in the form of a truth table.

[0090] The calculation means 5 comprises a recalibration means referenced 5f configured to recalibrate the operating model of the aircraft engine 1 used by the observer 5a as a function of corrective factors representative of at least one individual characteristic of the aircraft engine. The recalibration consists of correcting the tangent linearized state representation described by the equations 8 which becomes:

[0091] The reference point x0, u0,y0n' appears more directly in the state representation, but each element of equation 11 is corrected by multiplying each operating quantity by a correction factor denoted k, specific to the corrected quantity and which depends on the position along the operating line, typically as a function of PS32Q2.

[0092] Such recalibration by corrective factors k makes it possible to correct the operating model of the aircraft engine by taking into account the individual characteristics of the aircraft engine.

[0093] To ensure the effectiveness of the Kalman filters in designating the healthy channel, and to prevent a recalibration from updating corrective factors when a difference between measurement channels has appeared, the calculation means 5 is configured according to a predefined difference threshold. If the difference measured between the measurement channels is below the predefined difference threshold, the calculation means is configured to perform the recalibration and to deactivate the Kalman filters. Conversely, if the difference measured between the measurement channels is equal to or above the predefined difference threshold, the calculation means is configured to deactivate the recalibration and activate the Kalman filters. For example, if the measurement differences between the local channel and the cross channel are less than 50% of the cross-check threshold for each of the four actuators considered, the recalibration is activated and the Kalman filters estimating the disturbances on the control signals are deactivated.Otherwise, the Kalman filters are enabled and the recalibration is disabled. Alternatively, it is still possible to keep the 5ai and 5a2 Kalman filters enabled and disable the recalibration when the predefined deviation threshold is exceeded.

[0094] The corrective factors are stored in a memory 5g of the recalibration means 5f in the form of a map. The map may correspond to a set of tables, each table linking a corrective factor to an operating parameter of the aircraft engine.

[0095] The recalibration means 5f is configured to regularly update this mapping in order to take into account the evolution of the individual characteristics of the aircraft engine 1 over time, in particular with respect to aging.

[0096] On first use, the mapping or tables are initialized with unit values. In other words, before the first flight, the elements of each table containing the values ​​of the correction factors are all equal to 1.

[0097] The updating of the corrective factors is carried out in a similar manner at each iteration and for each element to be recalibrated.

[0098] The updating of the corrective factors is carried out when the aircraft engine is operating in a stabilized regime. The operation in stabilized regime is determined in relation to a predefined threshold. For example, a controlled device is considered to be operating in stabilized regime if the average variation of parameters representative of its operation considered over at least one predetermined period is less than a predetermined threshold. For example, an aircraft engine can be considered to be operating in stabilized regime if the following indicator I(t) has a value less than 1. In other words, if I(t) = 1 then the average variation of XN25R and WF32R2, taken with respect to the instants t — 1s, t — 3s and t — 5s, is worth 1%.

[0099] The following describes the flowchart of Figure 3 which summarizes the architecture of the calculation code associated with the updating of the corrective factors and implemented by the recalibration means 5f within the framework of the control system according to the invention.

[0100] The description is given as an example and with reference to WF32R2, i.e. the reduced fuel flow in the combustion chamber. The calculation code can of course be transposed in a similar manner to any other operating quantity to be recalibrated.

[0101] As previously stated, the kwF32R2 correction factors are stored in the 5g memory of the 5f recalibration module in the form of a map or tables.

[0102] Updating the correction factors begins with a step 10 of determining the input values.

[0103] The input values ​​consist of atmospheric parameters measured by probes, mechanical parameters measured by sensors present on the engine and calculated parameters specified below.

[0104] Preferably, the input values ​​include the current values ​​of PS32Q2, ALT, XM and the fuel flow rate, denoted WF32R2 mesuré . The input values ​​also include the current value of WF32R2o obtained by interpolation as a function of PS32Q2, ALT and XM from a table obtained by a conventional identification procedure. The input values ​​further include the value of the correction factor kwF32R2 obtained by linear interpolation in the corresponding table as a function of PS32Q2, as a function of the coordinate XPS32Q2 within a given mesh and the corresponding tabular values ​​at the nodes of the mesh.

[0105] In the next calculation step, the recalibration module 5f first calculates the corrected value WF32R2 corr from the current reference point by multiplying the current value of the quantity to be corrected by the corresponding corrective factor: (14)

[0106] During the same calculation step 11, the recalibration module 5f calculates the relative deviation ΔWF32R2 between the expected fuel flow rate and the measured fuel flow rate: (15) ' '

[0107] During the same calculation step 11, the recalibration module 5f calculates the filtered relative deviation ΔWF32R2 filtre by multiplying the relative deviation by a predetermined gain factor WF32R2 which allows you to adjust the speed of convergence: (16)

[0108] In the next update step 12, the recalibration module 5f assigns the filtered relative deviation ΔWF32R2 filtreat the two nodes adjacent to the current value of PS32Q2, in the table of correction factors kWF32R2, au pro rata of the proximity of the current PS32Q2 with each of these two nodes. Noting I PS32Q2 the index of the current mesh of this table, we then have: (18)

[0109] The update of the correction factors of the quantities XN2R0, XN25R0, DPQ230, PS32Q20, A80, ARDE0 and ASTA0 are identical to that of WF32R20, replacing the table k WF32R2 By the corresponding table.

[0110] The control system has been described in relation to a single quantity measured by two specific measurement channels 3ia, 3ib of a redundant sensor. However, the control system can be extended to at least two quantities each measured by two specific measurement channels of redundant sensors. In this case, the same observer 5a based on two Kalman filters 5a1 and 5a2 is used to determine the estimation of the bias of the measurement channels for each quantity taken into account. For each quantity, two bias estimates, a means of comparison, and a means of selection are then available.

[0111] The control system allows:

[0112] • to isolate, for each redundant sensor, the faulty channel from the healthy channel and thus be able to reconfigure itself,

[0113] • to use the same observer based on two Kalman filters and fed by different measurement channels. Thus, unlike the state of the art which uses a bank of different Kalman filters, this makes it possible to optimize the control system (reducing the impact on memory or CPU load)

[0114] • to obtain an estimate of the bias directly dependent on the measurements and easily interpretable subsequently (unlike the residuals used in the state of the art)

[0115] • to improve the accuracy of disturbance estimates and therefore the robustness of the designation of the healthy channel by recalibrating the model used by the observer based on the Kalman filter.

[0116] Applied to an aircraft, and in particular to the control of an aircraft engine, the control system makes it possible to be robust to failure during flight and to provide a diagnosis for replacement at the end of the mission.

Claims

CLAIMS 1. System for controlling an aircraft engine (1) provided with at least one piece of equipment (1i), the control system comprising at least one redundant sensor (3) each capable of measuring an operating quantity of the aircraft engine (1), and two measurement channels (3ia, 3ib) of the redundant sensor for each piece of equipment (li), at least one control means (2a, 2b) configured to determine a command to the at least one piece of equipment (li) as a function of the measurement of at least one operating quantity of the aircraft engine (1) and of a measurement selected for the controlled piece of equipment (li), the system further comprising a calculation means (5) configured to determine the measurement selected for the at least one piece of equipment (li) controlled, by an observer (5a) comprising two Kalman filters (5ai, 5a2) each using the same operating model of the aircraft engine (1),as a function of at least one measurement of the operating quantity of the aircraft engine (1) and the measurements of the measuring channels (3ia, 3ib) of the redundant sensor for the controlled equipment (li), characterized in that the calculation means (5) is configured to detect a failure of one of the measuring channels (3ia, 3ib) of the redundant sensor so as to exclude the measuring channel therefrom, the calculation means (5) being further configured to recalibrate the operating model as a function of at least one individual characteristic of the aircraft engine (1)., 2. Control system according to claim 1, wherein the calculation means (5) comprises: - a comparison means (5b) configured to emit a selection signal as a function of a comparison between, on the one hand, the absolute value of the difference between the estimate of the bias (ÛL) of the first measurement channel (3ia) and the estimate of the bias (ûx) of the second measurement channel (3ib), and on the other hand, a predetermined verification threshold between the two measurement channels, - a selection device (5c) configured to transmit the selected measurement equal to the measurement of the first measurement channel, to the measurement of the second measurement channel or to the average of the measurements of the first measurement channel and the second measurement channel as a function of said selection signal, and - a recalibration means (5f) configured to recalibrate the operating model used by said observer (5a) as a function of corrective factors representative of at least one individual characteristic of the aircraft engine; the two Kalman filters (5ai, 5a2) of the observer (5a) determining for one (5ai) an estimate of a bias (ÛL) of a first measurement channel (3ia), and for the other (5a2) an estimate of a bias (ûx) of a second measurement channel (3ib), as a function of the at least one measurement of the operating quantity of the aircraft engine, of the measurement of the first measurement channel of the redundant sensor and of the measurement of the second measurement channel of the redundant sensor.

3. System according to claim 2, in which the recalibration means (5f) comprises a memory (5g) intended for storing the corrective factors in the form of a map.

4. System according to claim 3, in which the recalibration means is configured to iteratively update the values ​​of the mapping when the aircraft engine is operating in a stabilized regime.

5. System according to claim 4, in which the iterative updating is carried out according to a predetermined gain factor.

6. Control system according to any one of claims 2 to 5, in which the comparison means (5b) is configured to carry out the following steps: the bias estimates are stored at the moment when it is determined that the difference in absolute value between the measurement of the first measurement channel and the measurement of the second measurement channel is greater than a predetermined threshold and a selection signal is emitted indicating to the selection device (5c) to transmit a selected measurement equal to the measurement of the redundant sensor measurement channel for which the absolute value of its bias estimate is the lowest.

7. Control system according to any one of claims 1 to 6, in which the measurement channels of the redundant sensor measure the position of the cylinders controlling the variable geometries of the compressors, the variable section of the nozzle or the fuel metering valve.

8. Method for controlling an aircraft engine (1) provided with at least one piece of equipment (1i), at least one sensor (3) capable of measuring an operating quantity of the aircraft engine, and measurement channels (3ia, 3ib) of the redundant sensor for each piece of equipment (li), the control method comprising steps of: determining a command intended for at least one piece of equipment (li) as a function of the at least one measurement of the operating quantity of the aircraft engine and a measurement selected for the controlled piece of equipment (li), determining a measurement selected for the controlled at least one piece of equipment (li), by an observer (5a) comprising two Kalman filters (5ai, 5a2) each using the same operating model of the aircraft engine adjusted by corrective factors representative of at least one individual characteristic of the aircraft engine (1),depending on at least one measurement of the operating quantity of the aircraft engine (1) and the measurements of the measuring channels (3ia, 3ib) of the redundant sensor for the controlled equipment (li)., 9. Method according to claim 8 comprising a prior step of iteratively updating said corrective factors carried out when the aircraft engine (1) is operating in a stabilized regime.

10. Aircraft equipped with a control system according to any one of claims 1 to 7 or equipped with a system implementing a control method according to claim 8 or 9.

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