Wing anti-disturbance control method and system with turbulence dynamic sensing function and medium

Abstract

The invention provides a wing anti-disturbance control method and system with turbulence dynamic perception and a medium. The method comprises the following steps: acquiring air pressure transient change data of the surface of a wing; preprocessing the air pressure transient change data to obtain flow field original data, namely high-frequency fluctuation data; performing rapid processing and feature extraction on the original data of the flow field, and analyzing turbulence intensity and main pulsation frequency to obtain current airflow state information; judging whether the current airflow state information is harmful disturbance information or not based on the set safety condition information; if it is judged that the disturbance information is harmful disturbance information, calculating anti-disturbance information, calculating vibration frequency and average amplitude matched with the anti-disturbance information to obtain an anti-disturbance control instruction, and adjusting the vibration state and the rotation opening angle of the wing based on the anti-disturbance control instruction to obtain control result information; through closed-loop control logic of real-time sensing, intelligent decision making and rapid execution, the adverse influence on the aircraft is actively inhibited or eliminated, and the control effect is improved.

Description

A method, system, and medium for wing disturbance rejection control with turbulence dynamic sensing 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 also provides a wing disturbance rejection control method with turbulence dynamic sensing, comprising: 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; preprocessing the transient air pressure change data on the wing surface to obtain raw flow field 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 condition information; 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, and adjusting the wing vibration state and rotation opening angle based on the disturbance rejection control commands to obtain 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, this includes: acquiring transient pressure change data, analyzing high-frequency fluctuation data, unifying the time base of the transient pressure change data and the high-frequency fluctuation data, and performing time synchronization to obtain unified time-series acquisition data; standardizing the format of the unified time-series acquisition data to obtain standard format data; removing noise and outliers from the standard format data based on a wavelet threshold denoising algorithm to obtain preliminary preprocessed data; performing correlation analysis and validity verification on the preliminary preprocessed data to obtain verification results; and selecting preliminary preprocessed data that are greater than or equal to the set verification condition information based on the verification results to obtain the original flow field data.

[0009] Optionally, in the wing disturbance rejection control method with turbulence dynamic perception 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 to obtain the current airflow state information. Specifically, this includes: acquiring the raw flow field data; performing a time-domain to frequency-domain transformation on the raw flow field data based on Fast Fourier Transform to map the time-domain flow field data to the frequency domain to obtain frequency-domain flow field data; removing high-frequency noise based on a frequency-domain filtering algorithm to obtain denoised frequency-domain flow field data; extracting features from the denoised frequency-domain flow field data based on a POD analysis algorithm to obtain feature values; calculating the turbulence intensity and main pulsation frequency based on the feature values; comparing the turbulence intensity and main pulsation frequency with a preset feature threshold to select turbulence intensity and main pulsation frequency that are greater than or equal to the preset feature threshold; and analyzing flight parameters based on the selected turbulence intensity and main pulsation frequency 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 set safety condition information specifically includes: setting multi-dimensional safety condition information in advance based on aircraft type, flight stage, wing structural strength parameters, and comfort, economy, or safety parameters; comparing the turbulence intensity and main pulsation frequency in the current airflow state information with the set multi-dimensional safety condition information one by one, analyzing the real-time flight attitude parameters of the aircraft, and determining 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.

[0011] Optionally, in the wing anti-disturbance control method with turbulence dynamic perception described in the embodiments of this application, adjusting the wing's vibration state and rotation opening angle based on the anti-disturbance control command to obtain control result information specifically includes: acquiring the anti-disturbance control command; parsing the anti-disturbance control command to obtain target vibration parameters and target angle parameters; obtaining drive strategy information based on the target vibration parameters and target angle parameters; controlling the actuator to adjust the vibration frequency and target angle based on the drive strategy information; and collecting the actual vibration parameters and angle parameters of the aircraft after parameter adjustment to obtain control result information.

[0012] Optionally, the wing disturbance rejection control method with turbulence dynamic perception described in this application embodiment further includes a control result information verification step, specifically as follows: acquiring control result information, comparing the control result information with the set control condition information to obtain control effect data; generating feedback information based on the control effect data; comparing the feedback information with the turbulence intensity and main pulsation frequency before disturbance rejection to obtain a comparison result; analyzing whether the control result information meets the standard disturbance rejection information based on the comparison result; if it does, controlling the aircraft based on the disturbance rejection control command; if it does not meet the standard, adjusting the vibration frequency and average amplitude.

[0013] Secondly, embodiments of this application provide a wing anti-disturbance control system with turbulence dynamic perception. The system includes a memory and a processor. The memory includes a program for a wing anti-disturbance control method with turbulence dynamic perception. When executed by the processor, the program 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 airspeed sensor; preprocessing the transient air pressure change data on the wing surface to obtain raw flow field 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 determined to be harmful disturbance information, calculating anti-disturbance information, calculating the vibration frequency and average amplitude matching the anti-disturbance information to obtain anti-disturbance control commands; adjusting the wing's vibration state and rotation opening angle based on the anti-disturbance control commands to obtain control result information.

[0014] Optionally, in the wing disturbance rejection control system with turbulence dynamic perception described in this application embodiment, the transient pressure change data on the wing surface is preprocessed to obtain the original flow field data. Specifically, this includes: acquiring transient pressure change data, analyzing high-frequency fluctuation data, unifying the time base of the transient pressure change data and the high-frequency fluctuation data, and performing time synchronization to obtain unified time-series acquisition data; standardizing the format of the unified time-series acquisition data to obtain standard format data; removing noise and outliers from the standard format data based on a wavelet threshold denoising algorithm to obtain preliminary preprocessed data; performing correlation analysis and validity verification on the preliminary preprocessed data to obtain verification results; and selecting preliminary preprocessed data that are greater than or equal to the set verification condition information based on the verification results to obtain the original flow field data.

[0015] Optionally, in the wing disturbance rejection control system with turbulence dynamic perception described in this application embodiment, the raw flow field data is rapidly processed and features extracted to analyze turbulence intensity and main pulsation frequency to obtain current airflow state information. Specifically, this includes: acquiring raw flow field data; performing time-domain to frequency-domain conversion on the raw flow field data based on Fast Fourier Transform to map the time-domain flow field data to the frequency domain to obtain frequency-domain flow field data; removing high-frequency noise based on a frequency-domain filtering algorithm to obtain denoised frequency-domain flow field data; extracting features from the denoised frequency-domain flow field data based on a POD analysis algorithm to obtain feature values; calculating turbulence intensity and main pulsation frequency based on the feature values; comparing the turbulence intensity and main pulsation frequency with a preset feature threshold to select turbulence intensity and main pulsation frequency greater than or equal to the preset feature threshold; and analyzing flight parameters based on the selected turbulence intensity and main pulsation frequency to obtain 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 is a flowchart of the wing disturbance rejection control method with turbulence dynamic perception provided in an embodiment of this application; Figure 2 is a logic diagram of the wing disturbance rejection control system with turbulence dynamic perception provided in an embodiment of this application; Figure 3 is a schematic diagram of the overall structure of the wing disturbance rejection control system with turbulence dynamic perception provided in an embodiment of this application; Figure 4 is a schematic diagram of the disturbance rejection actuator based on thin-film flexible material design in the wing disturbance rejection control system with turbulence dynamic perception provided in an embodiment of this application; Figure 5 is a schematic diagram of the disturbance rejection actuator controlled by the root torsion spring in the wing disturbance rejection control system with turbulence dynamic perception provided in an embodiment of this application; Figure 6 is a schematic diagram of the disturbance rejection mechanism based on actuator front-end damper adjustment in the wing disturbance rejection control system with turbulence dynamic perception provided in an embodiment of this application; Figure 7 is a schematic diagram of the vibrator based on loudspeaker acoustic wave excitation in the wing disturbance rejection 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, which is a flowchart of a wing disturbance rejection control method with turbulence dynamic sensing in 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, 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 airspeed sensor; S102, preprocessing the transient air pressure change data on the wing surface to obtain raw flow field data; S103, rapid processing and feature extraction of the raw flow field data, analysis of turbulence intensity and main pulsation frequency to obtain current airflow state information; S104, determining whether the current airflow state information is harmful disturbance information based on set safety condition information; S105, if 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.

[0023] According to an embodiment of the present invention, the transient pressure change data on the wing surface is preprocessed to obtain the original flow field data. Specifically, this includes: acquiring the transient pressure change data, which includes high-frequency fluctuation data, analyzing the high-frequency fluctuation data, unifying the time base of the transient pressure change data and the high-frequency fluctuation data, and synchronizing them in time series to obtain unified time series acquisition data; standardizing the format of the unified time series acquisition data to obtain standard format data; removing noise and outliers from the standard format data based on a wavelet threshold denoising algorithm to obtain preliminary preprocessed data; performing correlation analysis and validity verification on the preliminary preprocessed data to obtain verification results; and selecting preliminary preprocessed data that are greater than or equal to the set verification condition information based on the verification results to obtain the original flow field data.

[0024] It should be noted that the system uses a distributed micro pressure sensor array to collect real-time transient pressure change data on the wing surface, while simultaneously collecting high-frequency fluctuation data of the incoming airflow velocity using a high-frequency airspeed sensor. The acquisition timing is synchronized between the two types of data through a unified time reference. Collaborative preprocessing involves performing preprocessing operations on the collected transient pressure change data and high-frequency fluctuation data, including data denoising, outlier removal, and format standardization. Specifically, wavelet threshold denoising is used, outlier removal employs the 3σ criterion, and format standardization converts both types of data into a unified time-varying format. The data is preprocessed by using a triplet format of stamp-physical quantity-unit. Analysis and verification: Correlation analysis and validity verification are performed on the 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 ≥ 0.6. Validity verification checks the data missing rate and noise level. Data is considered valid when the missing rate is ≤ 5% and the noise amplitude is ≤ 5% of the peak value of the original data, and is then used as the original flow field data and transmitted to the intelligent control subsystem. If the verification fails, the acquisition and preprocessing process is repeated.

[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 pulsation frequency, thereby obtaining the current airflow state information. Specifically, this includes: acquiring the raw flow field data; performing a time-domain to frequency-domain transformation on the raw flow field data based on Fast Fourier Transform (FFT) to map the time-domain flow field data to the frequency domain, obtaining frequency-domain flow field data; removing high-frequency noise using a frequency-domain filtering algorithm to obtain denoised frequency-domain flow field data; extracting features from the denoised frequency-domain flow field data using a POD analysis algorithm to obtain feature values; calculating the turbulence intensity and main pulsation frequency based on the feature values; comparing the turbulence intensity and main pulsation frequency with a preset feature threshold to select turbulence intensities and main pulsation frequencies greater than or equal to the preset feature threshold; and analyzing flight parameters based on the selected turbulence intensity and main pulsation frequency 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: pre-setting multi-dimensional safety condition information based on aircraft type, flight stage, wing structural strength parameters, and comfort, economy, or safety parameters; comparing the turbulence intensity and main pulsation frequency in the current airflow state information with the set multi-dimensional safety condition information one by one, analyzing the real-time flight attitude parameters of the aircraft, and determining 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.

[0027] According to an embodiment of the present invention, adjusting the vibration state and rotation opening angle of the wing based on anti-disturbance control commands to obtain control result information specifically includes: acquiring anti-disturbance control commands; parsing the anti-disturbance control commands to obtain target vibration parameters and target angle parameters; obtaining drive strategy information based on the target vibration parameters and target angle parameters; controlling the actuator to adjust the vibration frequency and target angle based on the drive strategy information; and collecting the actual vibration parameters and angle parameters of the aircraft after parameter adjustment to obtain control result information.

[0028] According to an embodiment of the present invention, a control result information verification step is further included, specifically as follows: acquiring control result information, comparing the control result information with the set control condition information to obtain control effect data; generating feedback information based on the control effect data; comparing the feedback information with the turbulence intensity and main pulsation frequency before disturbance rejection to obtain a comparison result; analyzing whether the control result information meets the standard disturbance rejection information based on the comparison result; if it does, controlling the aircraft based on the disturbance rejection control command; if it does not meet the standard, adjusting the vibration frequency and average amplitude.

[0029] As shown in Figures 2-7, in a second aspect, embodiments of this application provide a wing disturbance rejection control system with turbulence dynamic perception. This system includes a memory and a processor. The memory contains a program for a wing disturbance rejection control method with turbulence dynamic perception. When executed by the processor, the program 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 airspeed sensor; preprocessing the transient air pressure change data on the wing surface to obtain raw flow field 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 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's vibration state and rotation opening angle based on the disturbance rejection control commands to obtain control result information.

[0030] It should be noted that the system mainly includes three functional subsystems: 1. Flow sensing subsystem: This subsystem serves as the sensing layer of the system and is mainly composed of sensors or sensor arrays, responsible for real-time acquisition of flow field data related to the wing. Typically, it can be (the following sensors can be combined or used individually): (1) Distributed micro pressure sensor array: With a high chord length distribution density, it extends 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 wing chord length. It is deployed in key areas on the upper surface of the wing (in front of the anti-disturbance device) to monitor the transient changes in local air pressure on the upper surface of the wing in real time, thereby calculating and processing the location of the airflow separation point and the turbulence intensity Tu1 and the 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 serves as the system's computing and control unit, responsible for processing sensor information and generating control commands. Its core is a dedicated microcomputer or intelligent flight control unit: it rapidly processes and extracts features from the data collected and uploaded by sensors in the flow sensing subsystem, obtaining the incoming flow 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 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 suppressor is mounted on the upper wing surface and, from an overall perspective, is a quadrilateral flat plate with a chordal length b = 0.15c. Ideally, its spanwise length should cover the entire wing span (as much as possible). The optimal mounting position of the disturbance suppressor'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 disturbance suppressor rotates around its front end via a hydraulic system to open to a specific angle α, maintaining lift and increasing drag; ② Through its anti-disturbance 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 of the wing caused by turbulent flow.

[0034] The anti-disturbance actuator can actively vibrate in four forms to suppress the effect of incoming turbulence on the wing. Specifically, it includes: (1) Anti-disturbance actuator based on thin film flexible material: This method is generally used on model aircraft and small UAVs (takeoff weight not greater than 25kg), and does not require flow sensing and intelligent control subsystem. It can independently passively twist and vibrate flexibly to suppress the effect 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 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 is attached to the wing surface and half 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 original flow field data. Specifically, this includes: acquiring transient pressure change data, analyzing high-frequency fluctuation data, unifying the time base of the transient pressure change data and the high-frequency fluctuation data, and performing time-series synchronization to obtain unified time-series acquisition data; standardizing the format of the unified time-series acquisition data to obtain standard format data; removing noise and outliers from the standard format data based on a wavelet threshold denoising algorithm to obtain preliminary preprocessed data; performing correlation analysis and validity verification on the preliminary preprocessed data to obtain verification results; and selecting preliminary preprocessed data that are greater than or equal to the set verification condition information based on the verification results 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 pulsation frequency, thereby obtaining the current airflow state information. Specifically, this includes: acquiring the raw flow field data; performing a time-domain to frequency-domain transformation on the raw flow field data based on Fast Fourier Transform (FFT) to map the time-domain flow field data to the frequency domain, obtaining frequency-domain flow field data; removing high-frequency noise using a frequency-domain filtering algorithm to obtain denoised frequency-domain flow field data; extracting features from the denoised frequency-domain flow field data using a POD analysis algorithm to obtain feature values; calculating the turbulence intensity and main pulsation frequency based on the feature values; comparing the turbulence intensity and main pulsation frequency with a preset feature threshold to select turbulence intensities and main pulsation frequencies greater than or equal to the preset feature threshold; and analyzing flight parameters based on the selected turbulence intensity and main pulsation frequency to obtain the current airflow state information.

[0040] In summary, the present invention has the following significant advantages: significantly improved flight quality and safety margins: the system can effectively suppress wing flutter and delay stall angle of attack, enabling the aircraft to maintain attitude stability under complex weather conditions, resulting in smoother flight and 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. If it is determined to be harmful disturbance information, the anti-disturbance information is calculated, the vibration frequency and average amplitude matched by the anti-disturbance information are calculated, and the anti-disturbance control command is obtained. Based on the anti-disturbance control command, the vibration state and rotation opening angle of the wing are adjusted to obtain the 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, this includes: acquiring transient pressure change data, analyzing high-frequency fluctuation data, unifying the time base of the transient pressure change data and the high-frequency fluctuation data, and synchronizing them to obtain time-series acquired data; standardizing the format of the time-series acquired data to obtain standard format data; removing noise and outliers from the standard format data using a wavelet threshold denoising algorithm to obtain preliminary preprocessed data; performing correlation analysis and validity verification on the preliminary preprocessed data to obtain verification results; and selecting preliminary preprocessed data that are greater than or equal to the set verification conditions based on the verification results to obtain the raw flow field data.

3. The wing disturbance rejection control method with turbulence dynamic sensing according to claim 2, characterized in that, The process involves rapidly processing and extracting features from the raw flow field data, analyzing turbulence intensity and dominant pulsation frequency to obtain current airflow state information. Specifically, this includes: acquiring the raw flow field data; performing a time-domain to frequency-domain transformation on the raw flow field data using Fast Fourier Transform (FFT) to map the time-domain flow field data to the frequency domain, obtaining frequency-domain flow field data; removing high-frequency noise using a frequency-domain filtering algorithm to obtain denoised frequency-domain flow field data; extracting features from the denoised frequency-domain flow field data using a Point of Desire (POD) analysis algorithm to obtain eigenvalues; calculating turbulence intensity and dominant pulsation frequency based on the eigenvalues; comparing the turbulence intensity and dominant pulsation frequency with preset feature thresholds, and selecting turbulence intensity and dominant pulsation frequency values ​​greater than or equal to the preset feature thresholds; and analyzing flight parameters based on the selected turbulence intensity and dominant pulsation frequency to obtain current airflow state information.

4. The wing disturbance rejection control method with turbulence dynamic sensing according to claim 3, characterized in that, The determination of whether current airflow status information constitutes harmful disturbance information is based on pre-defined safety conditions. Specifically, this includes: pre-setting multi-dimensional safety conditions based on aircraft type, flight stage, wing structural strength parameters, and comfort, economy, or safety parameters; comparing the turbulence intensity and dominant pulsation frequency in the current airflow status information with the pre-defined multi-dimensional safety conditions one by one, analyzing the aircraft's real-time flight attitude parameters, and determining whether there is a risk of attitude instability; if the turbulence intensity and dominant pulsation frequency in the current airflow status information are greater than or equal to the pre-defined multi-dimensional safety conditions, and the flight attitude parameters are greater than or equal to the pre-defined attitude deviation threshold, then it is determined to be harmful disturbance information; if the turbulence intensity and dominant pulsation frequency in the current airflow status information are less than the pre-defined multi-dimensional safety conditions, and the flight attitude parameters are less than the pre-defined attitude deviation threshold, then it is determined to be harmless disturbance information; if the turbulence intensity and dominant pulsation frequency in the current airflow status information are greater than or equal to the pre-defined multi-dimensional safety conditions, and the flight attitude parameters are less than the pre-defined attitude deviation threshold, then it is determined to be harmless disturbance information.

5. The wing disturbance rejection control method with turbulence dynamic sensing according to claim 4, characterized in that, The control result information is obtained by adjusting the vibration state and rotation opening angle of the wing based on the anti-disturbance control command. Specifically, this includes: acquiring the anti-disturbance control command; parsing the anti-disturbance control command to obtain the target vibration parameters and target angle parameters; obtaining the drive strategy information based on the target vibration parameters and target angle parameters; controlling the actuator to adjust the vibration frequency and target angle based on the drive strategy information; and collecting the actual vibration parameters and angle parameters of the aircraft after parameter adjustment to obtain the control result information.

6. The wing disturbance rejection control method with turbulence dynamic sensing according to claim 5, characterized in that, It also includes a control result information verification step, as follows: acquire control result information, compare the control result information with the set control condition information to obtain control effect data; generate feedback information based on the control effect data; compare the feedback information with the turbulence intensity and main pulsation frequency before disturbance rejection to obtain the comparison result; analyze whether the control result information meets the standard disturbance rejection information based on the comparison result; if it does, control the aircraft based on the disturbance rejection control command; if it does not, adjust the vibration frequency and average amplitude.

7. 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 anti-disturbance control method with turbulence dynamic sensing. When the program 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 airspeed sensor; preprocessing the transient air pressure change data on the wing surface to obtain raw flow field 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 anti-disturbance information, calculating the vibration frequency and average amplitude matching the anti-disturbance information to obtain anti-disturbance control commands; adjusting the wing vibration state and rotation opening angle based on the anti-disturbance control commands to obtain control result information.

8. The wing disturbance rejection control system with turbulence dynamic sensing according to claim 7, characterized in that, The transient pressure change data on the wing surface is preprocessed to obtain the raw flow field data. Specifically, this includes: acquiring transient pressure change data, analyzing high-frequency fluctuation data, unifying the time base of the transient pressure change data and the high-frequency fluctuation data, and synchronizing them to obtain time-series acquired data; standardizing the format of the time-series acquired data to obtain standard format data; removing noise and outliers from the standard format data using a wavelet threshold denoising algorithm to obtain preliminary preprocessed data; performing correlation analysis and validity verification on the preliminary preprocessed data to obtain verification results; and selecting preliminary preprocessed data that are greater than or equal to the set verification conditions based on the verification results to obtain the raw flow field data.

9. The wing disturbance rejection control system with turbulence dynamic sensing according to claim 8, characterized in that, The process involves rapidly processing and extracting features from the raw flow field data, analyzing turbulence intensity and dominant pulsation frequency to obtain current airflow state information. Specifically, this includes: acquiring the raw flow field data; performing a time-domain to frequency-domain transformation on the raw flow field data using Fast Fourier Transform (FFT) to map the time-domain flow field data to the frequency domain, obtaining frequency-domain flow field data; removing high-frequency noise using a frequency-domain filtering algorithm to obtain denoised frequency-domain flow field data; extracting features from the denoised frequency-domain flow field data using a Point of Desire (POD) analysis algorithm to obtain eigenvalues; calculating turbulence intensity and dominant pulsation frequency based on the eigenvalues; comparing the turbulence intensity and dominant pulsation frequency with preset feature thresholds, and selecting turbulence intensity and dominant pulsation frequency values ​​greater than or equal to the preset feature thresholds; and analyzing flight parameters based on the selected turbulence intensity and dominant pulsation frequency to obtain current airflow state information.

10. 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 6.

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