Electromagnetic misoperation prevention control method

Abstract

The invention discloses an anti-electromagnetic misoperation control method, and relates to the technical field of aircraft wing flap control systems. The method comprises the following steps: monitoring a multi-source operation state signal of a flap control system in real time, establishing a multi-stage fault-tolerant strategy library taking flight safety as a core, and performing online intelligent diagnosis on the multi-source operation state signal based on a preset electromagnetic interference characteristic model so as to distinguish a normal flap control instruction from an abnormal instruction or signal distortion caused by electromagnetic interference; an instruction channel protection mechanism is established, and when an instruction contradicts with the current flight state or an electrical signal of a driving motor and mechanical feedback of a flap cannot be self-consistent on a physical model, it is judged that the instruction is an electromagnetic error instruction; and when a plurality of nodes of the flap control system simultaneously have characteristic abnormities and an interference source cannot be determined, a system-level protection safety keeping strategy is triggered. The anti-interference capability, survivability and safety of the aircraft flap control system are improved, misoperation caused by electromagnetic interference is effectively prevented, and flight safety is guaranteed.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of aircraft wing flap control systems, in particular to a control method for preventing electromagnetic misoperation. BACKGROUND

[0002] Modern aircraft actuation systems, especially emergency release systems such as landing gear and flap emergency release, are the last physical barrier to flight safety. Such systems are developing towards electrification and even full electrification, and the core driving unit is a high-power-density permanent magnet motor and driver. In a complex airborne electromagnetic environment, serious challenges are faced. In the prior art, passive filtering technology can attenuate some interference, but it cannot cope with instantaneous and high-energy electromagnetic pulses. These disturbances may tamper with sensor signals and distort control commands, leading to catastrophic misoperation of the system. SUMMARY

[0003] Based on the above technical problems, the present application provides a control method and system for preventing electromagnetic misoperation, which can actively identify, intelligently decide and immediately suppress electromagnetic interference, and can ensure the highest reliability of the emergency system in extreme electromagnetic environments.

[0004] To solve the above technical problems, the present application provides a control method for preventing electromagnetic misoperation, which is applied to an aircraft flap electric drive actuation emergency system, and includes the following steps: S1, real-time monitoring of multi-source operating state signals of the flap control system; S2, establishing a multi-level fault-tolerant strategy library with flight safety as the core, based on a pre-set electromagnetic interference characteristic model, online intelligent diagnosis is performed on the multi-source operating state signals to distinguish normal flap control commands from abnormal commands or signal distortion caused by electromagnetic interference; S3, establishing an instruction channel protection mechanism, when the command contradicts the current flight state or the electrical signal of the driving motor and the mechanical feedback of the flap cannot be self-consistent on the physical model, it is determined as an electromagnetic miscommand; S4, when characteristic abnormalities occur in multiple nodes of the flap control system at the same time and the disturbance source cannot be determined, the system-level protection safety maintenance strategy is triggered.

[0005] Further, the multi-source operating state signals are monitored by sensors, wherein the command sensor and the actual position sensor respectively give the command and the obtained feedback; if the command jumps and the feedback remains unchanged, it indicates that the sensor is interfered by electromagnetic interference or its link has a fault feature, triggering the suppression of the command action; if the command remains unchanged and the feedback jumps, it indicates that the feedback sensor itself is interfered or the mechanical transmission mechanism has a non-command sudden displacement, triggering the rejection of the contaminated feedback signal and the change to rely on redundant information for control; if the command and the feedback both jump but do not match, it indicates that there are multiple interferences or system-level faults, triggering the safety strategy to suppress the action and maintain the current safe state.

[0006] Further, the multi-level fault-tolerant strategy library includes command layer protection, sensing layer fault tolerance, and execution layer guarantee. The command layer protection performs flight state verification on abnormal commands, makes rationality judgment in combination with parameters including airspeed and height, and checks whether the command exceeds the safety boundary under the current flight state. The sensing layer fault tolerance includes automatically switching to a software sensor composed of motor current and a dynamics model when the control link sensor fails, and continuously correcting through the motor current signal. The execution layer guarantee includes monitoring the deviation between the motor current command position and the actual position, and if the motor current does not change after receiving the command, it indicates that the command may not be executed or the sensor fails.

[0007] Further, the sensing layer fault tolerance also includes establishing a sensor failure protection mechanism based on virtual sensors, and if it is detected that the flap position sensor signal is invalid due to interference, it is switched to redundant estimation based on motor current and flap dynamics model.

[0008] Further, the sensor failure protection mechanism based on virtual sensors specifically includes that when the flap control system detects abnormal features of the position sensor signal and the motor current waveform remains normal features, the flap control system switches to the virtual sensor based on the model, switches to the position estimation mode of the motor current state observer and the flap dynamics model, maintains the stable control of the flap control system by real-time solving the balance relationship between the motor electromagnetic torque and the load torque.

[0009] Further, the motor current state observer integrates the motor mathematical model, receives the command voltage from the controller, and calculates the predicted current value that should be generated in theory based on the input and the current estimated motor state of the observer itself; The flap control system collects the actual current value of the motor winding through the current sensor in real time, the observer compares the predicted current value with the actual measured current to obtain the current error; The current error is input to a correction link based on a proportional-integral-derivative controller or a Kalman filter to correct the estimated values of back electromotive force and rotational speed; The estimated motor rotational speed and mechanical position of the model converge to their true values, so as to provide reliable state feedback for the flap control system when the sensor fails.

[0010] Further, when the flap control system enters the sensor failure mode, the electromagnetic torque is obtained in real time from the motor current observer, the current flight parameters are obtained through the aircraft data bus, the flap position estimated value of the last control period is read as the initial condition, the real-time load torque is calculated based on the current airspeed and the flap position estimated value through the aerodynamic model, the electromagnetic torque and the real-time load torque are substituted into the dynamic equation, the current angular acceleration is obtained by solving, the system rotational speed is obtained by time integration of the angular acceleration, and the accurate flap position information is obtained by twice integration of the rotational speed.

[0011] Further, the instruction channel protection mechanism specifically includes, when an abnormal feature is detected in the control instruction channel, and each position feedback signal remains stable, the flap control system performs flight state verification on the instruction; If there is a logical conflict between the instruction and the current flight parameters, the abnormal instruction is discarded; If the instruction does not meet the maximum speed and acceleration preset by the flap actuator, and the airspeed is much higher than the flap lowering limit speed, the instruction to lower the flap greatly is received, the abnormal instruction is triggered to be discarded; If the instruction is disturbed, an adaptive Kalman filter based on the motor state is started to reconstruct the signal, the Kalman filter is used as a dynamic observer deeply coupled with the motor system, the physical response of the motor itself is used as the final basis for verifying and correcting the credibility of the instruction signal, a state space model related to the dynamic relationship of the motor is established, a state transition model reflecting the coupling relationship between the instruction and the motor current is established, and the instruction channel and the motor current are observed, the trust weight of the filter is dynamically adjusted according to the actual state of the motor, and the reliability of the instruction channel is judged through the motor current Further, the state space model related to the dynamic relationship of the motor further includes, When the instruction innovation is less than the preset threshold, it indicates that the instruction channel is severely disturbed, and the motor body is running normally; the reconstructed instruction output by the filter ignores the instruction channel glitches and remains smooth; If the instruction innovation and the current innovation are both greater than the preset threshold, it indicates that there is an instruction change or a system-level disturbance affecting the instruction and the motor power supply at the same time, and the flight state verifier is reported; if the instruction change is denied by the flight state logic, the instruction is discarded; if the logic is reasonable, the instruction is considered valid.

[0012] Further, the strategy of triggering system-level protection safety retention when multiple nodes of the system simultaneously have characteristic abnormalities and the interference source cannot be determined specifically specifically includes, When the system detects a serious abnormality or interference, multiple nodes of the flap control system simultaneously have characteristic abnormalities and the interference source cannot be determined, the strategy of triggering system-level protection safety retention is triggered, the system immediately stops executing new control instructions, controls the flap to maintain the current configuration, simultaneously activates a backup sensor network to reevaluate the system state, continuously monitors key parameters, and after the system state is confirmed to be stable, resumes normal operation or enters a degraded operation mode according to a predetermined program. When the system detects a serious failure, multiple nodes of the system simultaneously have characteristic abnormalities, and in the flap control system execution layer guarantee, the control bandwidth and dynamic performance are reduced to switch to a conservative control law to facilitate the flap to maintain a slow stable lowering rate.

[0013] Compared with the prior art, the beneficial effects of the present application include: through multi-source signal monitoring, intelligent diagnosis, multi-level fault tolerance and deep model fusion, a depth defense system is constructed. Instead of relying on a single sensor or instruction channel, through multi-dimensional cross verification and soft redundancy based on a physical model, in a complex electromagnetic interference environment, the anti-interference ability, survivability and safety of the aircraft flap control system are greatly improved, the misoperation caused by electromagnetic interference is effectively prevented, and flight safety is ensured. BRIEF DESCRIPTION OF DRAWINGS

[0014] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the prior art and the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0015] Figure 1 Flowchart of the anti-electromagnetic misoperation control method of the present application; Figure 2 Information classification diagram of the multi-source judgment system of the present application for preventing electromagnetic misoperation; Figure 3 Sensor failure protection flowchart based on virtual sensors of the present application; Figure 4 Flowchart of the anti-electromagnetic misoperation control method of the present application for verifying the detection of abnormal processing of the channel; Figure 5 Flowchart of the anti-electromagnetic misoperation control method of the present application for preventing multiple nodes from simultaneously having characteristic abnormalities; Figure 6 Flowchart of the anti-electromagnetic misoperation control method of the present application for preventing multiple nodes from simultaneously having characteristic abnormalities. DETAILED DESCRIPTION

[0016] The core of the present application is to provide an electromagnetic misoperation prevention control method, which effectively reduces skin effect, local magnetic density unevenness and eddy current loss, and improves motor stability.

[0017] To make the purposes, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0018] As shown in Figure 1 The present application provides an electromagnetic misoperation prevention control method, which is applied to an airplane flap electric drive actuation emergency system and includes the following steps: Step S1, real-time monitoring of multi-source operating state signals of a flap control system; The multi-source operating state signals include a flap command position, a flap actual position, a drive motor current, an airplane airspeed and a flap hatch state. The multi-source heterogeneous information that can be used for misoperation judgment of a flap emergency release system is as shown in Figure 2

[0019] Step S2, establishment of a multi-level fault-tolerant strategy library with flight safety as the core, online intelligent diagnosis of the multi-source operating state signals based on a preset electromagnetic interference characteristic model, so as to distinguish normal flap control commands from abnormal commands or signal distortion caused by electromagnetic interference; The present application establishes a multi-level fault-tolerant strategy library with flight safety as the core, including command layer protection, sensing layer fault tolerance and execution layer guarantee.

[0020] 1) The command layer verifies abnormal commands in flight state, and makes rationality judgment in combination with airspeed, altitude and other parameters. A multi-modal anti-interference knowledge base is preset in the system, and a rule base is predefined according to airplane design criteria and flight mechanics. The core logic is to check whether the command exceeds the safety boundary under the current flight state.

[0021] 2) Sensing layer fault tolerance, when the flap position sensor, motor rotor position sensor and other control link sensors fail, automatically switch to a software sensor composed of motor current and a dynamics model. The model is a model-based state observer, which is a real-time running, virtual flap control system model, which runs in parallel with the physical system and is continuously corrected through real measurable signals such as motor current. ​

[0022] 3) The execution layer guarantees the deviation of the motor current command position and the actual position, which will be reflected in the current of the driving motor. A large and continuous position error will cause current saturation. If there is no corresponding change in the motor current after receiving the command, it means that the command may not be executed or the sensor is malfunctioning. The flap movement speed estimated by the motor back electromotive force / speed can be cross-verified with the speed obtained by differentiating the position sensor.

[0023] The application also includes the construction of a multi-modal anti-interference knowledge base. At key nodes of the flap control system, including the flap control computer, the control bus, the position command sensor, the motor rotor position sensor, the flap surface position sensor, the motor drive controller control chip, the motor drive controller drive circuit, the motor drive controller current sensor, the permanent magnet synchronous motor, the power module, the main power supply and return circuit, a distributed data acquisition network is established. Synchronously capture key parameters such as the current waveform of the motor driver, the DC bus voltage ripple, the flap command position trajectory, and the rotary transformer feedback signal.

[0024] Inject interference signals specifically through a professional interference simulator. Inject common-mode interference at the position sensor interface, differential-mode interference at the motor drive circuit, and transient pulse groups at the control bus to construct a flap control system interference sample library with clear labels. The sample library specifically includes the following: In this step, when an unexpected command pulse is identified in the flap control channel, the unexpected command pulse is cross-verified with the current actual position of the flap and the airspeed of the aircraft, and if it is confirmed as a ghost command, it is silenced and discarded. In the sensing layer fault tolerance, a sensor failure protection mechanism based on a virtual sensor is established. The virtual sensor is a virtual sensor composed of software algorithms and mathematical models. If it is detected that the flap position sensor signal is malfunctioning due to interference, switch to redundant estimation based on motor current and flap dynamics model to ensure that the emergency release process continues to complete. The virtual sensor estimates the accurate position of the flap in real time by analyzing available, undisturbed signals, such as motor current, so that the flap control system continues to operate stably and safely in the event of a true sensor failure.

[0025] Sensor failure protection based on virtual sensors such as Figure 3The system detects abnormal features of the position sensor signal, such as resolver decoding jump, signal amplitude anomaly. While the motor current waveform remains normal features, the system can seamlessly switch to a model-based virtual sensor, that is, the system will automatically switch to the motor current state observer and the position estimation mode of the flap dynamics model, which maintains the stable control of the flap control system by real-time solving the balance relationship between the motor electromagnetic torque and the load torque. The specific implementation is as follows.

[0026] Specifically, a high-fidelity motor mathematical model is integrated into the motor current state observer. The model receives the command voltage (V) from the controller, and based on this input, combined with the current estimated state of the observer itself, calculates the predicted current value I_predicted that should be generated in theory. In parallel, the system collects the actual current value I_measured of the motor winding in real time through a high-precision current sensor, and the observer compares the predicted current I_predicted with the actual measured current I_measured to obtain the current error Error = I_measured - I_predicted. This error signal is the key diagnostic information, which is mainly derived from the deviation between the estimated value and the true value of the back electromotive force of the observer internal model. This current error is input to a correction link based on a proportional-integral-derivative controller or Kalman filter to correct the estimated value of the back electromotive force and the speed. Through the continuous iteration of the above process, the dynamic characteristics of the observer internal model will gradually approach the operating characteristics of the real motor. Finally, the motor speed and mechanical position estimated by the model will converge to their true values, thereby providing reliable state feedback for the control system when the sensor fails.

[0027] Next, the motion state of the system is accurately calculated by the motor drive torque and external load. The core dynamics equation is established.

[0028] J·dω / dt = T_motor - T_load - B·ω Wherein the physical parameters are defined as follows: J: equivalent moment of inertia of the system, including the motor rotor, reduction mechanism and flap wing converted to the motor shaft total inertia dω / dt: angular acceleration, representing the rate of change of system speed T_motor: motor output electromagnetic torque, provided in real time by the motor current observer T_load: aerodynamic load torque, is a key input variable of the model B·ω: system damping torque, covering mechanical friction and fluid resistance and other factors.

[0029] The load torque T_load is obtained through aerodynamic model calculations. This functional relationship was established through wind tunnel testing and flight data verification, and its functional relationship is as follows: T_load = f(V_air, δ, h, ...) in: V_air: Flight airspeed δ: Flap deflection angle h: Flight altitude This functional relationship was established through wind tunnel testing and flight data verification to ensure that it can accurately reflect aerodynamic loads under different flight conditions.

[0030] When the system enters the sensor failure response mode, it acquires the electromagnetic torque T_motor in real time from the motor current observer, obtains flight parameters such as current airspeed and altitude through the aircraft data bus, reads the flap position estimate from the previous control cycle as the initial condition, and calculates the real-time load torque T_load based on the current airspeed and flap position estimate through the aerodynamic model. Substituting T_motor and T_load into the core dynamic equation, the system solves for the current angular acceleration dω / dt, integrates the angular acceleration over time to obtain the system speed ω, and integrates the speed twice to finally obtain the precise flap position information.

[0031] Step S3: Establish a command channel protection mechanism. When a command contradicts the current flight status or the electrical signal of the drive motor and the mechanical feedback of the flap cannot be reconciled in the physical model, it is determined to be an electromagnetic erroneous command. In this step, the mission context, such as flight phase and aircraft attitude, is taken as the highest priority logical constraint, and the physical coupling relationship between motor current, torque and position is used as a built-in physical verifier.

[0032] Command channel protection such as Figure 4 As shown. When an abnormal characteristic is detected in the control command channel, such as abnormal command pulse width or command change rate exceeding the limit, while the feedback signals at each position remain stable, the system first performs a flight status check on the command. If the command has a logical conflict with parameters such as current airspeed and altitude, the abnormal command is discarded directly. If the command does not conform to the preset maximum speed and acceleration of the flap actuator, or if the airspeed is much higher than the flap deployment limit speed, a command to significantly deploy the flaps is received. If any of these problems occur, the top-level logic rejection is triggered, and the abnormal command is discarded directly.

[0033] If the instruction logic is reasonable but interference exists, an adaptive Kalman filter based on the motor state is activated for signal reconstruction. The Kalman filter is used as a dynamic observer deeply coupled with the motor system, utilizing the motor's own physical response as the ultimate basis for verifying and correcting the reliability of the instruction signal. A state-space model relating to the motor's dynamic relationship is established.

[0034] X k = [ Cmd k CmdRate k , I_motor k ] Cmd k : The command value (e.g., command angle) at time k. CmdRate k The rate of change of instructions at time k. I_motor k : Motor current observation at time k (from a high-precision current sensor).

[0035] Establish a state transition model that establishes the coupling relationship between the response command and the motor current. X k =A·X k-1 +w k The state transition matrix A can be designed as follows: , k is a coupling coefficient, representing the degree of influence of the command change rate on the motor current (approximately the torque coefficient). α is a factor reflecting the motor's electrical time constant, representing the inertia of the current response. w k It is process noise.

[0036] Simultaneously observe the command channel and motor current.

[0037] Z k =H·X k +v k Z k = [Measured command value, Measured motor current value] X k : State vector. X k = [Actual command value, Actual command rate of change, Actual motor current value] H is the observation matrix, H = [1, 0, 0; 0, 0, 1], v k Observation noise represents the errors and interference introduced by the measuring instrument itself.

[0038] Based on the actual condition of the motor, the "trust weight" of the filter is dynamically adjusted. The reliability of the command channel is judged by the physical truth of motor current. The specific steps are as follows: Calculate the new information: For this system, the information has two components. ν_cmd: Instruction news (disturbed instruction - predicted instruction) ν_current: Current information (measured current - predicted current) The innovation here refers to the difference between the actual measured current value and the current value predicted by the filter based on previous states and models at a certain moment. When the command innovation is large but the current innovation is small, it means that the command channel is severely interfered with, but the motor itself is operating normally. The reconstructed command output by the filter... The system ignores glitches in the command channel, maintaining a smooth flow. If both the command and current updates are large, this could indicate a real, abrupt command change or a system-level disturbance affecting both the command and motor power. This large update event is reported to the highest-level flight status checker. If the abrupt command is rejected by the flight status logic, it is discarded; if the logic is sound, it is considered a valid command. In this embodiment, the magnitude of the update is determined by its absolute value. An absolute value less than 2 to 3 times its theoretical standard deviation is considered normal prediction error caused by model imperfections and measurement noise, which the filter uses to fine-tune the state estimate. An absolute value greater than 3 times its theoretical standard deviation is a strong statistical signal indicating an "unexpected event," which could be interference, a malfunction, or a sudden, legitimate operation. Since different sensors have different normal or theoretical standard values, the theoretical standard value for the update is not limited here.

[0039] Step S4: When multiple nodes in the system exhibit abnormal characteristics simultaneously and the source of interference cannot be identified, the system-level protection and security maintenance strategy is triggered. In this invention, all abnormal diagnostic results and handling measures are recorded in the system event log, while the flap control system is kept in a safe state to avoid malfunctions or jamming in a dangerous intermediate state under electromagnetic interference.

[0040] When the system detects a serious anomaly or interference, and multiple nodes in the system simultaneously exhibit characteristic anomalies, protection mechanisms such as... Figure 5 As shown. When multiple nodes in the system simultaneously exhibit abnormal characteristics, and the source of interference cannot be clearly identified, the system-level protection and safety maintenance strategy is triggered. The system immediately stops executing new control commands, maintains the flaps in their current configuration, and activates the backup sensor network to reassess the system status. During this process, key parameters are continuously monitored. Once the system status is confirmed to be stable, normal operation is restored according to a predetermined procedure, or a degraded operation mode is entered.

[0041] When the system detects a serious fault, and multiple nodes in the system simultaneously exhibit characteristic anomalies, protective measures such as... Figure 6As shown, in the execution layer assurance of the flap control system, moderate performance degradation is achieved through a triple collaborative mechanism. First, by reducing the control bandwidth and dynamic performance, a conservative control law is switched to maintain a slow and stable flap deployment rate. That is, the system switches from high-performance state feedback control or adaptive control to low-gain PID control with simple structure and fixed parameters, or even open-loop speed control, to avoid triggering violent mechanical responses and oscillations, trading speed for stability and robustness. This also avoids system oscillations caused by model estimation errors.

[0042] Secondly, the control objective is simplified. The high requirement of quickly and accurately reaching and maintaining multiple intermediate positions under normal conditions is abandoned; the system's sole objective shifts from precise path tracking to safely reaching the destination. A single constant speed command is used, allowing the motors to operate at a safe and constant speed until the flaps reach their mechanical limit and are locked.

[0043] Selective sacrifice of redundancy. Under normal circumstances, the left and right flaps are driven by their respective actuators, but the control system strictly compares their positions to ensure synchronized movement. If one side leads by more than a certain threshold, the system will automatically adjust or issue an alarm to prevent the aircraft from generating unexpected roll moments. In severe fault mode, the synchronization requirements for the left and right flaps are relaxed, prioritizing the reliable release of one flap, with the faulty flap releasing at an extremely slow, conservative speed. The pilot compensates for the roll moment generated by the deployment of one flap by manipulating the ailerons and rudder by pushing the stick.

[0044] This invention discloses a control method for preventing electromagnetic malfunctions, relating to the field of aircraft flap control systems. It involves real-time monitoring of multi-source operational status signals of the flap control system, establishing a multi-level fault-tolerant strategy library centered on flight safety, and performing online intelligent diagnosis of the multi-source operational status signals based on a preset electromagnetic interference characteristic model to distinguish between normal flap control commands and abnormal commands or signal distortions caused by electromagnetic interference. A command channel protection mechanism is established; when a command contradicts the current flight state or the electrical signal of the drive motor and the mechanical feedback of the flap cannot be reconciled in the physical model, it is determined to be an electromagnetic malfunction command. When multiple nodes of the flap control system simultaneously exhibit characteristic anomalies and the source of interference cannot be clearly identified, a system-level protection and safety maintenance strategy is triggered. This invention constructs a defense-in-depth system through multi-source signal monitoring, intelligent diagnosis, multi-level fault tolerance, and deep model fusion. Instead of relying on a single sensor or command channel, it significantly improves the anti-interference capability, survivability, and safety of the aircraft flap control system in complex electromagnetic interference environments through multi-dimensional cross-validation and soft redundancy based on a physical model, effectively preventing malfunctions caused by electromagnetic interference and ensuring flight safety.

[0045] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatuses, devices, and computer-readable storage media disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple; relevant details can be found in the method section.

[0046] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0047] The electromagnetic malfunction prevention control method provided in this application has been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the embodiments above are only for the purpose of helping to understand the method and its core ideas. It should be noted that those skilled in the art can make several improvements and modifications to this application without departing from the principles of this application, and these improvements and modifications also fall within the protection scope of the claims of this application.

Claims

1. A method for preventing electromagnetic malfunction control, characterized in that, The steps include the following: S1, real-time monitoring of multi-source operating status signals of the flap control system; S2. Establish a multi-level fault-tolerant strategy library with flight safety as the core. Based on the preset electromagnetic interference characteristic model, perform online intelligent diagnosis on the multi-source operating status signals to distinguish between normal flap control commands and abnormal commands or signal distortions caused by electromagnetic interference. S3, establish a command channel protection mechanism. When a command contradicts the current flight status or the electrical signal of the drive motor and the mechanical feedback of the flap cannot be reconciled in the physical model, it is judged as an electromagnetic erroneous command. S4: When multiple nodes of the flap control system simultaneously exhibit characteristic anomalies and the source of interference cannot be identified, the system-level protection and safety maintenance strategy is triggered.

2. The anti-electromagnetic malfunction control method according to claim 1, characterized in that, The multi-source operating status signals are monitored by sensors, where the command sensor and the actual position sensor respectively provide commands and receive feedback. If the command changes but the feedback remains unchanged, it indicates that the sensor is subject to electromagnetic interference or that its link has malfunctioned, triggering the suppression of command actions. If the command remains unchanged but the feedback changes, it indicates that the feedback sensor itself is interfered with or that the mechanical transmission mechanism has experienced a sudden, non-command-related displacement, triggering the rejection of contaminated feedback signals and switching to control based on redundant information. If both the command and feedback change but do not match, it indicates the presence of multiple interferences or a system-level fault, triggering a safety strategy to suppress actions and maintain the current safe state.

3. The anti-electromagnetic malfunction control method according to claim 1, characterized in that, The multi-level fault tolerance strategy library includes instruction layer protection, sensor layer fault tolerance, and execution layer protection. The command layer protection verifies the flight status of abnormal commands, and makes a reasonable judgment based on parameters including airspeed and altitude, and checks whether the command exceeds the safety boundary of the current flight status. The fault tolerance of the sensing layer includes automatically switching to a software sensor composed of motor current and dynamic model when the sensor in the control loop fails, and continuously correcting through the motor current signal; The execution layer protection includes monitoring the deviation between the commanded position and the actual position of the motor current. If the motor current does not change after receiving the command, it indicates that the command may not have been executed or the sensor may have failed.

4. The anti-electromagnetic malfunction control method according to claim 3, characterized in that, The fault tolerance of the sensing layer also includes establishing a sensor failure protection mechanism based on virtual sensors. If the flap position sensor signal is detected to be faulty due to interference, it will switch to redundant estimation based on motor current and flap dynamics model.

5. The anti-electromagnetic malfunction control method according to claim 4, characterized in that, The establishment of a sensor failure protection mechanism based on virtual sensors specifically includes the following steps: when the flap control system detects abnormal characteristics in the position sensor signal, while the motor current waveform remains normal, the flap control system switches to a model-based virtual sensor, switching to the position estimation mode of the motor current state observer and the flap dynamic model. By calculating the balance relationship between the motor electromagnetic torque and the load torque in real time, the stable control of the flap control system is maintained.

6. The anti-electromagnetic malfunction control method according to claim 5, characterized in that, The motor current state observer integrates the motor mathematical model, receives the command voltage from the controller, and calculates the theoretically expected current value based on this input and the observer's own current estimate of the motor state. The flap control system collects the actual current value of the motor winding in real time through a current sensor. The observer compares the predicted current value with the actual measured current to obtain the current error. The current error is input to a correction circuit based on a proportional-integral-derivative controller, a Kalman filter, or other intelligent methods to correct the estimated values ​​of back electromotive force and rotational speed. The motor speed and mechanical position estimated by the model converge to their true values, so as to provide reliable status feedback for the flap control system in the event of sensor failure.

7. The anti-electromagnetic malfunction control method according to claim 6, characterized in that, When the flap control system enters the sensor failure response mode, it acquires electromagnetic torque in real time from the motor current observer, obtains current flight parameters through the aircraft data bus, reads the flap position estimate from the previous control cycle as initial conditions, calculates real-time load torque based on the current airspeed and flap position estimate through the aerodynamic model, substitutes the electromagnetic torque and the real-time load torque into the dynamic equation, solves to obtain the current angular acceleration, performs time integration on the angular acceleration to obtain the system speed, performs a second integration on the speed to obtain the precise flap position information.

8. The anti-electromagnetic malfunction control method according to claim 7, characterized in that, The command channel protection mechanism specifically includes that when abnormal features are detected in the control command channel and the feedback signals at each position remain stable, the flap control system performs flight status verification on the command. If the command conflicts logically with the current flight parameters, the abnormal command is discarded; If the maximum speed and acceleration preset by the flap actuator are not met, and the airspeed is much higher than the flap deployment limit speed, a command to deploy the flaps significantly will be received, triggering a jettison error command. If interference exists in the command, an adaptive Kalman filter based on the motor state is activated to reconstruct the signal. The Kalman filter is used as a dynamic observer deeply coupled with the motor system. The physical response of the motor itself is used as the final basis for verifying and correcting the credibility of the command signal. A state-space model of the dynamic relationship with the motor is established, and a state transition model reflecting the coupling relationship between the command and the motor current is established. The command channel and the motor current are observed simultaneously. The trust weight of the filter is dynamically adjusted according to the actual state of the motor. The reliability of the command channel is judged by the motor current.

9. The anti-electromagnetic malfunction control method according to claim 8, characterized in that, The establishment of the state-space model relating to the dynamic relationship of the motor further includes, When the current information of the instruction is less than the preset threshold, it indicates that the instruction channel is severely interfered with, but the motor itself is operating normally; the reconstructed instruction output by the filter ignores the glitches in the instruction channel and remains smooth. If both the command information and the current information are greater than the preset threshold, it indicates that there is a command change or a system-level interference that simultaneously affects the command and the motor power supply, and the flight status verifier is notified. If the command change is rejected by the flight status logic, the command is discarded. If the flight control system's judgment logic is reasonable, it is considered a valid command.

10. The anti-electromagnetic malfunction control method according to claim 1, characterized in that, The strategy for triggering system-level security protection when multiple nodes in the system simultaneously exhibit abnormal characteristics and the source of interference cannot be clearly identified includes the following: When the system detects a serious anomaly or interference, and multiple nodes of the flap control system simultaneously exhibit characteristic anomalies and the source of interference cannot be identified, the system-level protection and safety maintenance strategy is triggered. The system immediately stops executing new control commands, controls the flaps to maintain the current configuration, and activates the backup sensor network to reassess the system status, continuously monitors key parameters, and resumes normal operation or enters degraded operation mode according to the predetermined procedure after the system status is confirmed to be stable. When the system detects a serious fault, and multiple nodes of the system exhibit characteristic anomalies simultaneously, the flap control system execution layer ensures that the control bandwidth and dynamic performance are reduced in order to maintain a slow and stable flap deployment rate.

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