A method, system, and medium for wing disturbance rejection control with turbulence dynamic sensing

Abstract

This application provides a wing disturbance rejection control method, system, and medium with turbulence dynamic sensing. The method includes: acquiring transient air pressure change data on the wing surface; preprocessing the transient air pressure change data to obtain raw flow field data, i.e., high-frequency fluctuation data; rapidly processing and extracting features from the raw flow field data, analyzing turbulence intensity and main pulsation frequency to obtain current airflow state information; determining whether the current airflow state information is harmful disturbance information based on set safety conditions; if it is determined to be harmful disturbance information, calculating disturbance rejection information, calculating the vibration frequency and average amplitude matching the disturbance rejection information to obtain disturbance rejection control commands; adjusting the wing vibration state and rotation opening angle based on the disturbance rejection control commands to obtain control result information; and actively suppressing or eliminating adverse effects on the aircraft through a closed-loop control logic of real-time sensing, intelligent decision-making, and rapid execution, thereby improving control performance.

Description

Technical Field

[0001] This application relates to the field of wing control technology, and more specifically, to a wing disturbance rejection control method, system, and medium with turbulence dynamic sensing. Background Technology

[0002] Atmospheric turbulence is a key factor affecting flight safety and comfort, widely present in both low- and high-altitude environments, but its causes and manifestations differ significantly. In the low-altitude region, turbulence is mainly caused by surface friction and thermal effects, manifesting as intense and direct disturbances. When surface airflow passes over rough terrain such as mountains and buildings, strong mechanical turbulence is formed, especially in mountain waves generated on the leeward slope, where numerous potentially dangerous vortex structures exist. Simultaneously, uneven heating of the surface due to solar radiation creates thermal convection, causing clear-sky turbulence; when this convection further develops into cumulus clouds, the intense updrafts and downdrafts within can lead to severe flight turbulence. Furthermore, microbursts, as one of the most dangerous forms of low-altitude turbulence, are characterized by their sudden onset and intense downdrafts, posing a significant threat to aircraft during takeoff and landing.

[0003] In high-altitude environments, turbulence is more insidious and difficult to predict, with "clear-sky turbulence" being a typical example. This type of turbulence often occurs in the air without obvious cloud cover and is closely related to strong wind shear in jet streams, wind shear layers in stable atmospheric stratification (which may trigger Kelvin-Helmholtz instability waves), and mountain waves propagating from low to high altitudes. Due to the lack of visible water vapor condensation, it is difficult to effectively identify turbulence using conventional airborne radar and visual observation, making clear-sky turbulence a major safety hazard for high-altitude flight.

[0004] Regardless of its source, turbulence has multifaceted impacts on fixed-wing and eVTOL aircraft. In terms of structural safety, severe turbulence can cause instantaneous overload, pushing the aircraft's structural strength limits. Long-term, repeated turbulence accelerates fatigue accumulation in the airframe, shortening its service life. Regarding flight performance, turbulence makes it difficult to maintain stable altitude and airspeed, hinders attitude control, and significantly increases the pilot's workload. Furthermore, turbulence directly affects passenger safety and comfort. Severe turbulence can easily lead to collisions with unsecured passengers and crew, and can also cause baggage and equipment displacement, creating cabin safety hazards.

[0005] Currently, responses to atmospheric turbulence mainly rely on weather warnings, pilot experience, and conventional flight control strategies. There is a lack of airborne systems capable of real-time perception and proactive disturbance suppression at the moment turbulence occurs. Therefore, developing a system and device capable of dynamically sensing turbulence and implementing real-time disturbance mitigation control is of great significance for improving flight safety, comfort, and operational stability, and is a key issue that urgently needs to be addressed in the field of aviation technology. Summary of the Invention

[0006] The purpose of this application is to provide a wing disturbance rejection control method, system, and medium with turbulence dynamic perception. Through a closed-loop control logic of real-time perception, intelligent decision-making, and rapid execution, it can actively suppress or eliminate adverse effects on the aircraft and improve control performance.

[0007] This application embodiment also provides a wing disturbance rejection control method with turbulence dynamic perception, including: real-time acquisition of transient air pressure change data on the wing surface based on a distributed micro pressure sensor array and / or a high-frequency acquisition airspeed meter; The transient air pressure change data on the wing surface is preprocessed to obtain the raw flow field data; The raw flow field data is processed and features are extracted quickly to analyze the turbulence intensity and main fluctuation frequency, thus obtaining the current airflow state information. Based on the established safety conditions, determine whether the current airflow status information is harmful disturbance information; If the disturbance is identified as harmful, the disturbance rejection information is calculated. The vibration frequency and average amplitude that match the disturbance rejection information are calculated to obtain the disturbance rejection control command. Based on the disturbance rejection control command, the vibration state and rotation opening angle of the wing are adjusted to obtain the control result information.

[0008] Optionally, in the wing disturbance rejection control method with turbulence dynamic sensing described in the embodiments of this application, the transient pressure change data on the wing surface is preprocessed to obtain the original flow field data, specifically including: Acquire transient pressure change data, analyze high-frequency fluctuation data, unify the time base of transient pressure change data and high-frequency fluctuation data, and synchronize the time series to obtain unified time series acquisition data; The collected data in a uniform time series is processed to standardize the format to obtain standard format data; The wavelet threshold denoising algorithm is used to remove noise and outliers from standard format data to obtain preliminary preprocessed data. The preliminary preprocessed data were subjected to correlation analysis and validity verification to obtain the verification results; Based on the verification results, preliminary preprocessed data that are greater than or equal to the set verification conditions are selected to obtain the original flow field data.

[0009] Optionally, in the wing disturbance rejection control method with turbulence dynamic sensing described in the embodiments of this application, the raw flow field data is rapidly processed and features are extracted to analyze the turbulence intensity and main fluctuation frequency, thereby obtaining the current airflow state information. Specifically, this includes: The original flow field data is acquired, and the original flow field data is converted from the time domain to the frequency domain based on the fast Fourier transform to map the time domain flow field data to the frequency domain to obtain the frequency domain flow field data. High-frequency noise is removed using a frequency domain filtering algorithm to obtain the noise-reduced frequency domain flow field data; Feature extraction is performed on the noise-reduced frequency domain flow field data based on the POD analysis algorithm to obtain feature values; Turbulence intensity and main pulsation frequency are calculated based on eigenvalues. The turbulence intensity and main pulsation frequency are compared with preset feature thresholds, and turbulence intensity and main pulsation frequency that are greater than or equal to the preset feature thresholds are selected. Based on the selected turbulence intensity and main pulsation frequency, the flight parameters are analyzed to obtain the current airflow state information.

[0010] Optionally, in the wing disturbance rejection control method with turbulence dynamic perception described in the embodiments of this application, determining whether the current airflow state information is harmful disturbance information based on the set safety condition information specifically includes: Multi-dimensional safety conditions are pre-defined based on aircraft type, flight phase, wing structural strength parameters, and comfort, economy, or safety parameters. The turbulence intensity and main pulsation frequency in the current airflow status information are compared one by one with the set multi-dimensional safety condition information to analyze the real-time flight attitude parameters of the aircraft and determine whether there is a risk of attitude instability. If the turbulence intensity and main pulsation frequency in the current airflow state information are greater than or equal to the set multi-dimensional safety condition information, and the flight attitude parameters are greater than or equal to the set attitude deviation threshold, then it is determined to be harmful disturbance information. If the turbulence intensity and main pulsation frequency in the current airflow state information are less than the set multi-dimensional safety condition information and the flight attitude parameters are less than the set attitude deviation threshold, then it is determined to be harmless disturbance information. If the turbulence intensity and main pulsation frequency in the current airflow status information are greater than or equal to the set multi-dimensional safety condition information and the flight attitude parameters are less than the set attitude deviation threshold, then it is determined to be harmless disturbance information.

[0011] Optionally, in the wing disturbance rejection control method with turbulence dynamic sensing described in the embodiments of this application, the vibration state and rotation opening angle of the wing are adjusted based on the disturbance rejection control command to obtain control result information, specifically including: Obtain the anti-disturbance control command, parse the anti-disturbance control command, and decompose it to obtain the target vibration parameters and target angle parameters; The driving strategy information is obtained based on the target vibration parameters and the target angle parameters; The actuator is controlled based on the drive strategy information to adjust the vibration frequency and the target angle; The actual vibration and angle parameters of the aircraft after parameter adjustment are collected to obtain control result information.

[0012] Optionally, the wing disturbance rejection control method with turbulence dynamic sensing described in the embodiments of this application further includes a control result information verification step, as follows: Acquire control result information, compare the control result information with the set control condition information, and obtain control effect data; Feedback information is generated based on control effect data; The comparison results are obtained by comparing the feedback information with the turbulence intensity and main pulsation frequency before the disturbance. Based on the comparison results, analyze whether the control result information meets the standard anti-disturbance information; If this is achieved, the aircraft will be controlled based on anti-disturbance control commands; If this is not achieved, adjust the vibration frequency and average amplitude.

[0013] Secondly, embodiments of this application provide a wing disturbance rejection control system with turbulence dynamic sensing. The system includes a memory and a processor. The memory includes a program for a wing disturbance rejection control method with turbulence dynamic sensing. When the program for the wing disturbance rejection control method with turbulence dynamic sensing is executed by the processor, it implements the following steps: Real-time acquisition of transient air pressure change data on the wing surface based on a distributed micro pressure sensor array and / or a high-frequency acquisition airspeed meter; The transient air pressure change data on the wing surface is preprocessed to obtain the raw flow field data; The raw flow field data is processed and features are extracted quickly to analyze the turbulence intensity and main fluctuation frequency, thus obtaining the current airflow state information. Based on the established safety conditions, determine whether the current airflow status information is harmful disturbance information; If the disturbance is identified as harmful, the disturbance rejection information is calculated. The vibration frequency and average amplitude that match the disturbance rejection information are calculated to obtain the disturbance rejection control command. Based on the disturbance rejection control command, the vibration state and rotation opening angle of the wing are adjusted to obtain the control result information.

[0014] Optionally, in the wing disturbance rejection control system with turbulence dynamic sensing described in the embodiments of this application, the transient pressure change data on the wing surface is preprocessed to obtain the raw flow field data, specifically including: Acquire transient pressure change data, analyze high-frequency fluctuation data, unify the time base of transient pressure change data and high-frequency fluctuation data, and synchronize the time series to obtain unified time series acquisition data; The collected data in a uniform time series is processed to standardize the format to obtain standard format data; The wavelet threshold denoising algorithm is used to remove noise and outliers from standard format data to obtain preliminary preprocessed data. The preliminary preprocessed data were subjected to correlation analysis and validity verification to obtain the verification results; Based on the verification results, preliminary preprocessed data that are greater than or equal to the set verification conditions are selected to obtain the original flow field data.

[0015] Optionally, in the wing disturbance rejection control system with turbulence dynamic sensing described in the embodiments of this application, the raw flow field data is rapidly processed and features are extracted to analyze the turbulence intensity and main pulsation frequency, thereby obtaining the current airflow state information, specifically including: The original flow field data is acquired, and the original flow field data is converted from the time domain to the frequency domain based on the fast Fourier transform to map the time domain flow field data to the frequency domain to obtain the frequency domain flow field data. High-frequency noise is removed using a frequency domain filtering algorithm to obtain the noise-reduced frequency domain flow field data; Feature extraction is performed on the noise-reduced frequency domain flow field data based on the POD analysis algorithm to obtain feature values; Turbulence intensity and main pulsation frequency are calculated based on eigenvalues. The turbulence intensity and main pulsation frequency are compared with preset feature thresholds, and turbulence intensity and main pulsation frequency that are greater than or equal to the preset feature thresholds are selected. Based on the selected turbulence intensity and main pulsation frequency, the flight parameters are analyzed to obtain the current airflow state information.

[0016] Thirdly, embodiments of this application also provide a computer-readable storage medium, which includes a wing disturbance rejection control method program with turbulence dynamic perception. When the wing disturbance rejection control method program with turbulence dynamic perception is executed by a processor, it implements the steps of the wing disturbance rejection control method with turbulence dynamic perception as described in any of the preceding claims.

[0017] As can be seen from the above, the wing anti-disturbance control method, system, and medium with turbulence dynamic perception provided in this application embodiment acquires transient air pressure change data on the wing surface in real time based on a distributed micro pressure sensor array and / or a high-frequency acquisition airspeed meter; preprocesses the transient air pressure change data on the wing surface to obtain raw flow field data, the transient air pressure change data including high-frequency fluctuation data; rapidly processes and extracts features from the raw flow field data, analyzes the turbulence intensity and main pulsation frequency to obtain current airflow state information; determines whether the current airflow state information is harmful disturbance information based on set safety condition information; if it is determined to be harmful disturbance information, calculates anti-disturbance information, calculates the vibration frequency and average amplitude matching the anti-disturbance information to obtain anti-disturbance control commands, adjusts the wing vibration state and rotation opening angle based on the anti-disturbance control commands to obtain control result information; through a closed-loop control logic of real-time perception, intelligent decision-making, and rapid execution, it actively suppresses or eliminates adverse effects on the aircraft, improving control performance. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 A flowchart of a wing disturbance rejection control method with turbulence dynamic sensing provided in an embodiment of this application; Figure 2 A logic diagram of a wing disturbance rejection control system with turbulence dynamic perception provided for an embodiment of this application; Figure 3 A schematic diagram of the overall structure of the wing disturbance rejection control system with turbulence dynamic sensing provided in the embodiments of this application; Figure 4 A schematic diagram of the disturbance rejection actuator based on a thin-film flexible material design for a wing disturbance rejection control system with turbulence dynamic sensing provided in an embodiment of this application; Figure 5 A schematic diagram of the root torsion spring controlled disturbance rejection actuator of the wing disturbance rejection control system with turbulence dynamic perception provided in the embodiments of this application; Figure 6 A schematic diagram of an anti-disturbance mechanism based on actuator front-end damper adjustment for a wing anti-disturbance control system with turbulence dynamic perception provided in an embodiment of this application; Figure 7A schematic diagram of a vibrator based on loudspeaker acoustic wave excitation for a wing anti-disturbance control system with turbulence dynamic perception provided in an embodiment of this application. Detailed Implementation

[0020] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0021] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, the terms "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0022] Please refer to Figure 1 , Figure 1 This is a flowchart of a wing disturbance rejection control method with turbulence dynamic sensing, according to some embodiments of this application. This wing disturbance rejection control method with turbulence dynamic sensing is used in a terminal device and includes the following steps: S101 is based on a distributed micro pressure sensor array and / or a high-frequency acquisition airspeed meter to collect real-time data on transient air pressure changes on the wing surface. S102, preprocesses the transient air pressure change data on the wing surface to obtain the raw flow field data; S103 performs rapid processing and feature extraction on the raw flow field data, analyzes the turbulence intensity and main pulsation frequency, and obtains the current airflow state information; S104, determine whether the current airflow status information is harmful disturbance information based on the set safety condition information; S105, if the disturbance information is determined to be harmful, the disturbance information is calculated, the vibration frequency and average amplitude matched by the disturbance information are calculated, the disturbance control command is obtained, and the vibration state and rotation opening angle of the wing are adjusted based on the disturbance control command to obtain the control result information.

[0023] According to an embodiment of the present invention, the transient pressure change data on the wing surface is preprocessed to obtain the raw flow field data, specifically including: Transient pressure data includes high-frequency fluctuation data. By acquiring transient pressure data, analyzing high-frequency fluctuation data, and unifying the time base of transient pressure data and high-frequency fluctuation data, time-series synchronization is performed to obtain unified time-series collected data. The collected data in a uniform time series is processed to standardize the format to obtain standard format data; The wavelet threshold denoising algorithm is used to remove noise and outliers from standard format data to obtain preliminary preprocessed data. The preliminary preprocessed data were subjected to correlation analysis and validity verification to obtain the verification results; Based on the verification results, preliminary preprocessed data that are greater than or equal to the set verification conditions are selected to obtain the original flow field data.

[0024] It should be noted that the transient air pressure change data on the wing surface is collected in real time based on a distributed micro pressure sensor array, and high-frequency fluctuation data of the incoming flow velocity is collected simultaneously based on a high-frequency airspeed meter. The acquisition timing is synchronized through a unified time reference during the acquisition of the two types of data. Collaborative preprocessing: Preprocessing operations are performed on the collected transient pressure change data and high-frequency fluctuation data respectively. Preprocessing includes data denoising, outlier removal and format standardization. Among them, wavelet threshold denoising algorithm is used for data denoising, 3σ criterion is used for outlier removal, and format standardization converts the two types of data into a unified triplet format of timestamp-physical quantity-unit to obtain preliminary preprocessed data. Analysis and Validation: Correlation analysis and validity verification are performed on the preliminary preprocessed data. Correlation analysis calculates the correlation coefficient between transient changes in air pressure and fluctuations in incoming flow velocity, retaining valid data segments with an absolute correlation coefficient value ≥ 0.6. Validity verification checks the data missing rate and noise level. When the data missing rate is ≤ 5% and the noise amplitude is ≤ 5% of the peak value of the original data, it is considered valid, identified as the original flow field data, and transmitted to the intelligent control subsystem. If the verification fails, the acquisition and preprocessing are re-executed.

[0025] According to an embodiment of the present invention, the raw flow field data is rapidly processed and its features are extracted to analyze the turbulence intensity and main fluctuation frequency, thereby obtaining the current airflow state information, specifically including: The original flow field data is acquired, and the original flow field data is converted from the time domain to the frequency domain based on the fast Fourier transform to map the time domain flow field data to the frequency domain to obtain the frequency domain flow field data. High-frequency noise is removed using a frequency domain filtering algorithm to obtain the noise-reduced frequency domain flow field data; Feature extraction is performed on the noise-reduced frequency domain flow field data based on the POD analysis algorithm to obtain feature values; Turbulence intensity and main pulsation frequency are calculated based on eigenvalues. The turbulence intensity and main pulsation frequency are compared with preset feature thresholds, and turbulence intensity and main pulsation frequency that are greater than or equal to the preset feature thresholds are selected. Based on the selected turbulence intensity and main pulsation frequency, the flight parameters are analyzed to obtain the current airflow state information.

[0026] According to an embodiment of the present invention, determining whether the current airflow state information is harmful disturbance information based on set safety condition information specifically includes: Multi-dimensional safety conditions are pre-defined based on aircraft type, flight phase, wing structural strength parameters, and comfort, economy, or safety parameters. The turbulence intensity and main pulsation frequency in the current airflow status information are compared one by one with the set multi-dimensional safety condition information to analyze the real-time flight attitude parameters of the aircraft and determine whether there is a risk of attitude instability. If the turbulence intensity and main pulsation frequency in the current airflow state information are greater than or equal to the set multi-dimensional safety condition information, and the flight attitude parameters are greater than or equal to the set attitude deviation threshold, then it is determined to be harmful disturbance information. If the turbulence intensity and main pulsation frequency in the current airflow state information are less than the set multi-dimensional safety condition information and the flight attitude parameters are less than the set attitude deviation threshold, then it is determined to be harmless disturbance information. If the turbulence intensity and main pulsation frequency in the current airflow status information are greater than or equal to the set multi-dimensional safety condition information and the flight attitude parameters are less than the set attitude deviation threshold, then it is determined to be harmless disturbance information.

[0027] According to an embodiment of the present invention, the vibration state and rotation opening angle of the wing are adjusted based on anti-disturbance control commands to obtain control result information, specifically including: Obtain the anti-disturbance control command, parse the anti-disturbance control command, and decompose it to obtain the target vibration parameters and target angle parameters; The driving strategy information is obtained based on the target vibration parameters and the target angle parameters; The actuator is controlled based on the drive strategy information to adjust the vibration frequency and the target angle; The actual vibration and angle parameters of the aircraft after parameter adjustment are collected to obtain control result information.

[0028] According to an embodiment of the present invention, a control result information verification step is further included, as follows: Acquire control result information, compare the control result information with the set control condition information, and obtain control effect data; Feedback information is generated based on control effect data; The comparison results are obtained by comparing the feedback information with the turbulence intensity and main pulsation frequency before the disturbance. Based on the comparison results, analyze whether the control result information meets the standard anti-disturbance information; If this is achieved, the aircraft will be controlled based on anti-disturbance control commands; If this is not achieved, adjust the vibration frequency and average amplitude.

[0029] like Figures 2-7 As shown, in a second aspect, embodiments of this application provide a wing disturbance rejection control system with turbulence dynamic perception. The system includes a memory and a processor. The memory includes a program for a wing disturbance rejection control method with turbulence dynamic perception. When the program for the wing disturbance rejection control method with turbulence dynamic perception is executed by the processor, it implements the following steps: Real-time acquisition of transient air pressure change data on the wing surface based on a distributed micro pressure sensor array and / or a high-frequency acquisition airspeed meter; The transient air pressure change data on the wing surface is preprocessed to obtain the raw flow field data; The raw flow field data is processed and features are extracted quickly to analyze the turbulence intensity and main fluctuation frequency, thus obtaining the current airflow state information. Based on the established safety conditions, determine whether the current airflow status information is harmful disturbance information; If the disturbance is identified as harmful, the disturbance rejection information is calculated. The vibration frequency and average amplitude that match the disturbance rejection information are calculated to obtain the disturbance rejection control command. Based on the disturbance rejection control command, the vibration state and rotation opening angle of the wing are adjusted to obtain the control result information.

[0030] It should be noted that the system mainly comprises three functional subsystems: 1. Flow sensing subsystem: This subsystem, serving as the system's perception layer, primarily consists of sensors or sensor arrays responsible for real-time acquisition of flow field data related to the wing. Typically, it can include (the following sensors can be used in combination or individually): (1) Distributed micro pressure sensor array: with a high chord length distribution density, from the leading edge of the wing to the anti-disturbance device, with an interval distance of no more than 0.1c, where c is the chord length of the wing, it is deployed in the key area of ​​the upper surface of the wing (in front of the anti-disturbance device) to monitor the transient changes of local air pressure on the upper surface of the wing in real time, thereby calculating and processing the location of the airflow separation point, turbulence intensity Tu1 and main pulsation frequency f1 (the highest energy level pulsation frequency based on POD analysis) on the wing surface.

[0031] (2) High-frequency acquisition airspeed meter: It is arranged at the leading edge of the wing or in front of the nose to accurately measure the high-frequency fluctuations of the incoming flow velocity, thereby processing to obtain the turbulence intensity Tu1 and the pulsation frequency f1 (the highest pulsation frequency based on POD analysis).

[0032] 2. Intelligent Control Subsystem: This subsystem, acting as the system's computing and control unit, is responsible for processing sensor information and generating control commands. Its core is: A dedicated microcomputer or intelligent flight control unit rapidly processes and extracts features from the data collected and uploaded by sensors in the flow sensing subsystem to obtain the incoming turbulence intensity Tu1 and pulsation frequency f1. It then determines in real time whether the current airflow state constitutes a harmful disturbance. If it is a harmful disturbance, it calculates the vibration frequency f2 of the disturbance suppression device based on the disturbance suppression control design criterion f2=af1 (the coefficient a ranges from 0.5 to 0.7, generally a compromise value of 0.6). The optimal average amplitude of the disturbance suppression device is set at A=0.05b (b is the length of the disturbance suppression device along the flow direction, generally b=0.15c is optimal).

[0033] 3. Disturbance-resistant execution subsystem: This subsystem, acting as the system's actuator, is responsible for translating control commands into actual aerodynamic control actions. The disturbance rejection actuator is mounted on the upper wing surface, resembling a quadrilateral flat plate with a chordal length b = 0.15c and an optimal spanwise length that covers the entire wing span (as much as possible). The optimal mounting position of the actuator's front end is 0.6c from the wing's leading edge. It serves two purposes: ① When the aircraft needs to decelerate or descend, the actuator rotates around its front end via a hydraulic system to a specific angle α, maintaining lift and increasing drag; ② Through its disturbance rejection vibration structure, it eliminates or suppresses the influence of incoming turbulence on wing lift oscillations and lift magnitude, maintaining wing lift and mitigating the vertical vibrations caused by turbulent flow.

[0034] The anti-disturbance actuator can actively vibrate in four ways to suppress the effects of incoming turbulence on the wing, specifically including: (1) Anti-disturbance actuator based on thin film flexible material design: This method is generally used in model aircraft and small UAVs (takeoff weight not exceeding 25kg), and does not require flow sensing and intelligent control subsystems. It can independently passively torsion and flexible vibration, which can suppress the influence of incoming turbulence on the wing. Based on experience, a quadrilateral flat film material is designed, generally a PET sheet (thickness varies from 0.05-0.2mm, depending on the size of the aircraft, all of which are effective). It is attached to the corresponding position on the upper surface of the wing by polyimide tape or other single-sided adhesive. The tape width is generally 20mm, half of which is attached to the wing surface and half of which is attached to the film material surface. The tape thickness is 0.035-0.08mm, and the equivalent torque is 5. 10-3-2 10⁻² N·m / rad.

[0035] (2) Anti-disturbance actuator controlled by root torsion spring: The torque M of the torsion spring is adjusted by rotating θ by a motor or servo motor (M=K). θ, where K is the stiffness of the torsion spring), is matched with the mass m of the quadrilateral plate, thereby controlling and adjusting the passive vibration frequency f2 of the quadrilateral plate excited by the flow. In addition, the average amplitude A of the plate is monitored to be within the range of 0.05b ± 0.02b.

[0036] (3) Anti-disturbance mechanism based on damper adjustment at the front end of actuator: The actuator relies on the hydraulic system to push the anti-disturbance panel to rotate around its front end and open to a specific angle α. The air pressure inside the air suspension between the front end of the actuator and the panel is adjusted by the air compressor, thereby realizing the adjustment of the passive vibration frequency f2 of the quadrilateral plate excited by the flow. In addition, the average amplitude A of the plate is monitored to be within the range of 0.05b±0.02b.

[0037] (4) Vibrator based on loudspeaker acoustic wave excitation: Vibrators are arranged on an anti-disturbance plate. The vibrators are quadrilateral with a chord length of not less than b1 = 0.2b and a spanwise length of not less than 0.2b. The surface of each vibrator is covered by a flexible film. Each cavity is a sealed cavity with a built-in loudspeaker or loudspeaker array. The amplitude and vibration frequency of the loudspeaker are adjusted by current, so that the film forms a vibration frequency f2 and an average amplitude of A.

[0038] According to an embodiment of the present invention, the transient pressure change data on the wing surface is preprocessed to obtain the raw flow field data, specifically including: Acquire transient pressure change data, analyze high-frequency fluctuation data, unify the time base of transient pressure change data and high-frequency fluctuation data, and synchronize the time series to obtain unified time series acquisition data; The collected data in a uniform time series is processed to standardize the format to obtain standard format data; The wavelet threshold denoising algorithm is used to remove noise and outliers from standard format data to obtain preliminary preprocessed data. The preliminary preprocessed data were subjected to correlation analysis and validity verification to obtain the verification results; Based on the verification results, preliminary preprocessed data that are greater than or equal to the set verification conditions are selected to obtain the original flow field data.

[0039] According to an embodiment of the present invention, the raw flow field data is rapidly processed and its features are extracted to analyze the turbulence intensity and main fluctuation frequency, thereby obtaining the current airflow state information, specifically including: The original flow field data is acquired, and the original flow field data is converted from the time domain to the frequency domain based on the fast Fourier transform to map the time domain flow field data to the frequency domain to obtain the frequency domain flow field data. High-frequency noise is removed using a frequency domain filtering algorithm to obtain the noise-reduced frequency domain flow field data; Feature extraction is performed on the noise-reduced frequency domain flow field data based on the POD analysis algorithm to obtain feature values; Turbulence intensity and main pulsation frequency are calculated based on eigenvalues. The turbulence intensity and main pulsation frequency are compared with preset feature thresholds, and turbulence intensity and main pulsation frequency that are greater than or equal to the preset feature thresholds are selected. Based on the selected turbulence intensity and main pulsation frequency, the flight parameters are analyzed to obtain the current airflow state information.

[0040] In summary, the present invention has the following significant advantages: Significantly improves flight quality and safety boundaries: The system can effectively suppress wing flutter and delay stall angle of attack, enabling the aircraft to maintain attitude stability under complex weather conditions and fly more smoothly, fundamentally improving flight safety and handling quality.

[0041] Achieving a leap from passive acceptance to active control: Through the closed-loop control logic of "real-time perception - intelligent decision-making - rapid execution", the aircraft is no longer a passive recipient of aerodynamic disturbances, but is transformed into an intelligent agent that can actively suppress or even eliminate adverse effects.

[0042] With broad application prospects: This system architecture is not only suitable for large civil passenger aircraft, but its modular and intelligent features can also be widely applied to small and medium-sized drones, flying wing aircraft and other aircraft that are sensitive to weight, cost and aerodynamic efficiency, helping them to better cope with challenges such as low-altitude turbulence and wind shear.

[0043] A third aspect of the present invention provides a computer-readable storage medium including a wing disturbance rejection control method program with turbulence dynamics perception, wherein when the wing disturbance rejection control method program with turbulence dynamics perception is executed by a processor, it implements the steps of the wing disturbance rejection control method with turbulence dynamics perception as described in any of the above claims.

[0044] This invention discloses a wing disturbance rejection control method, system, and medium with turbulence dynamic sensing. It utilizes a distributed micro pressure sensor array and / or a high-frequency airspeed meter to collect real-time transient pressure change data on the wing surface. The transient pressure change data is preprocessed to obtain raw flow field data. This raw flow field data undergoes rapid processing and feature extraction to analyze turbulence intensity and main pulsation frequency, yielding current airflow state information. Based on predefined safety conditions, it is determined whether the current airflow state information constitutes a harmful disturbance. If deemed harmful, disturbance rejection information is calculated, including the vibration frequency and average amplitude matching the disturbance rejection information, resulting in disturbance rejection control commands. Based on these commands, the wing's vibration state and rotation opening angle are adjusted to obtain control results. Through a closed-loop control logic of real-time sensing, intelligent decision-making, and rapid execution, adverse effects on the aircraft are actively suppressed or eliminated, improving control effectiveness.

[0045] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.

[0046] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units. They may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.

[0047] In addition, in the various embodiments of the present invention, each functional unit can be integrated into one processing unit, or each unit can be a separate unit, or two or more units can be integrated into one unit; the integrated unit can be implemented in hardware or in the form of hardware plus software functional units.

[0048] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0049] Alternatively, if the integrated units of the present invention are implemented as software functional modules and sold or used as independent products, they can also be stored in a readable storage medium. Based on this understanding, the technical solutions of the embodiments of the present invention, or the parts that contribute to the prior art, can be embodied in the form of a software product. This software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROM, RAM, magnetic disks, or optical disks.

Claims

1. A wing disturbance rejection control method with turbulence dynamic sensing, characterized in that, include: Real-time acquisition of transient air pressure change data on the wing surface based on a distributed micro pressure sensor array and / or a high-frequency acquisition airspeed meter; The transient air pressure change data on the wing surface is preprocessed to obtain the raw flow field data; The raw flow field data is processed and features are extracted quickly to analyze the turbulence intensity and main fluctuation frequency, thus obtaining the current airflow state information. Based on the established safety conditions, it is determined whether the current airflow status information is harmful disturbance information, specifically including: Multi-dimensional safety conditions are pre-defined based on aircraft type, flight phase, wing structural strength parameters, and comfort, economy, or safety parameters. The turbulence intensity and main pulsation frequency in the current airflow status information are compared one by one with the set multi-dimensional safety condition information to analyze the real-time flight attitude parameters of the aircraft and determine whether there is a risk of attitude instability. If the turbulence intensity and main pulsation frequency in the current airflow state information are greater than or equal to the set multi-dimensional safety condition information, and the flight attitude parameters are greater than or equal to the set attitude deviation threshold, then it is determined to be harmful disturbance information. If the turbulence intensity and main pulsation frequency in the current airflow state information are less than the set multi-dimensional safety condition information and the flight attitude parameters are less than the set attitude deviation threshold, then it is determined to be harmless disturbance information. If the turbulence intensity and main pulsation frequency in the current airflow state information are greater than or equal to the set multi-dimensional safety condition information and the flight attitude parameters are less than the set attitude deviation threshold, then it is determined to be harmless disturbance information. If the disturbance is identified as harmful, anti-disturbance information is calculated. The vibration frequency and average amplitude matched to the anti-disturbance information are then calculated to obtain anti-disturbance control commands. Based on these commands, the wing's vibration state and rotation opening angle are adjusted to obtain control result information, specifically including: Obtain the anti-disturbance control command, parse the anti-disturbance control command, and decompose it to obtain the target vibration parameters and target angle parameters; The driving strategy information is obtained based on the target vibration parameters and the target angle parameters; The actuator is controlled based on the drive strategy information to adjust the vibration frequency and the target angle; The actual vibration and angle parameters of the aircraft after parameter adjustment are collected to obtain control result information.

2. The wing disturbance rejection control method with turbulence dynamic sensing according to claim 1, characterized in that, The transient pressure change data on the wing surface is preprocessed to obtain the raw flow field data, specifically including: Acquire transient pressure change data, analyze high-frequency fluctuation data, unify the time base of transient pressure change data and high-frequency fluctuation data, and synchronize the time series to obtain unified time series acquisition data; The collected data in a uniform time series is processed to standardize the format to obtain standard format data; The wavelet threshold denoising algorithm is used to remove noise and outliers from standard format data to obtain preliminary preprocessed data. The preliminary preprocessed data were subjected to correlation analysis and validity verification to obtain the verification results; Based on the verification results, preliminary preprocessed data that are greater than or equal to the set verification conditions are selected to obtain the original flow field data.

3. The wing disturbance rejection control method with turbulence dynamic sensing according to claim 2, characterized in that, The raw flow field data is rapidly processed and its features extracted. Turbulence intensity and dominant fluctuation frequency are analyzed to obtain current airflow state information, specifically including: The original flow field data is acquired, and the time-domain to frequency-domain transformation is performed on the original flow field data based on the fast Fourier transform to map the time-domain flow field data to the frequency domain to obtain the frequency-domain flow field data. High-frequency noise is removed using a frequency domain filtering algorithm to obtain the noise-reduced frequency domain flow field data; Feature extraction is performed on the noise-reduced frequency domain flow field data based on the POD analysis algorithm to obtain feature values; Turbulence intensity and main pulsation frequency are calculated based on eigenvalues. The turbulence intensity and main pulsation frequency are compared with preset feature thresholds, and turbulence intensity and main pulsation frequency that are greater than or equal to the preset feature thresholds are selected. Based on the selected turbulence intensity and main pulsation frequency, the flight parameters are analyzed to obtain the current airflow state information.

4. The wing disturbance rejection control method with turbulence dynamic sensing according to claim 1, characterized in that, It also includes a control result information verification step, as detailed below: Acquire control result information, compare the control result information with the set control condition information, and obtain control effect data; Feedback information is generated based on control effect data; The comparison results are obtained by comparing the feedback information with the turbulence intensity and main pulsation frequency before the disturbance. The comparison results are analyzed to determine whether the control results meet the standard anti-disturbance information; if so, the aircraft is controlled based on the anti-disturbance control commands. If this is not achieved, adjust the vibration frequency and average amplitude.

5. A wing disturbance rejection control system with turbulence dynamic sensing, characterized in that, The system includes a memory and a processor. The memory contains a program for a wing disturbance rejection control method with turbulence dynamics perception. When the program for the wing disturbance rejection control method with turbulence dynamics perception is executed by the processor, it performs the following steps: Real-time acquisition of transient air pressure change data on the wing surface based on a distributed micro pressure sensor array and / or a high-frequency acquisition airspeed meter; The transient air pressure change data on the wing surface is preprocessed to obtain the raw flow field data; The raw flow field data is processed and features are extracted quickly to analyze the turbulence intensity and main fluctuation frequency, thus obtaining the current airflow state information. Based on the established safety conditions, it is determined whether the current airflow status information is harmful disturbance information, specifically including: Multi-dimensional safety conditions are pre-defined based on aircraft type, flight phase, wing structural strength parameters, and comfort, economy, or safety parameters. The turbulence intensity and main pulsation frequency in the current airflow status information are compared one by one with the set multi-dimensional safety condition information to analyze the real-time flight attitude parameters of the aircraft and determine whether there is a risk of attitude instability. If the turbulence intensity and main pulsation frequency in the current airflow state information are greater than or equal to the set multi-dimensional safety condition information, and the flight attitude parameters are greater than or equal to the set attitude deviation threshold, then it is determined to be harmful disturbance information. If the turbulence intensity and main pulsation frequency in the current airflow state information are less than the set multi-dimensional safety condition information and the flight attitude parameters are less than the set attitude deviation threshold, then it is determined to be harmless disturbance information. If the turbulence intensity and main pulsation frequency in the current airflow state information are greater than or equal to the set multi-dimensional safety condition information and the flight attitude parameters are less than the set attitude deviation threshold, then it is determined to be harmless disturbance information. If the disturbance is identified as harmful, anti-disturbance information is calculated. The vibration frequency and average amplitude matched to the anti-disturbance information are then calculated to obtain anti-disturbance control commands. Based on these commands, the wing's vibration state and rotation opening angle are adjusted to obtain control result information, specifically including: Obtain the anti-disturbance control command, parse the anti-disturbance control command, and decompose it to obtain the target vibration parameters and target angle parameters; The driving strategy information is obtained based on the target vibration parameters and the target angle parameters; The actuator is controlled based on the drive strategy information to adjust the vibration frequency and the target angle; The actual vibration and angle parameters of the aircraft after parameter adjustment are collected to obtain control result information.

6. The wing disturbance rejection control system with turbulence dynamic sensing according to claim 5, characterized in that, The transient pressure change data on the wing surface is preprocessed to obtain the raw flow field data, specifically including: Acquire transient pressure change data, analyze high-frequency fluctuation data, unify the time base of transient pressure change data and high-frequency fluctuation data, and synchronize the time series to obtain unified time series acquisition data; The collected data in a uniform time series is processed to standardize the format to obtain standard format data; The wavelet threshold denoising algorithm is used to remove noise and outliers from standard format data to obtain preliminary preprocessed data. The preliminary preprocessed data were subjected to correlation analysis and validity verification to obtain the verification results; Based on the verification results, preliminary preprocessed data that are greater than or equal to the set verification conditions are selected to obtain the original flow field data.

7. The wing disturbance rejection control system with turbulence dynamic sensing according to claim 6, characterized in that, The raw flow field data is rapidly processed and its features extracted. Turbulence intensity and dominant fluctuation frequency are analyzed to obtain current airflow state information, specifically including: The original flow field data is acquired, and the time-domain to frequency-domain transformation is performed on the original flow field data based on the fast Fourier transform to map the time-domain flow field data to the frequency domain to obtain the frequency-domain flow field data. High-frequency noise is removed using a frequency domain filtering algorithm to obtain the noise-reduced frequency domain flow field data; Feature extraction is performed on the noise-reduced frequency domain flow field data based on the POD analysis algorithm to obtain feature values; Turbulence intensity and main pulsation frequency are calculated based on eigenvalues. The turbulence intensity and main pulsation frequency are compared with preset feature thresholds, and turbulence intensity and main pulsation frequency that are greater than or equal to the preset feature thresholds are selected. Based on the selected turbulence intensity and main pulsation frequency, the flight parameters are analyzed to obtain the current airflow state information.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a wing disturbance rejection control method program with turbulence dynamics awareness, which, when executed by a processor, implements the steps of the wing disturbance rejection control method with turbulence dynamics awareness as described in any one of claims 1 to 4.

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