Method for modifying control signals of a gust generator based on flow field feedback

Abstract

The application discloses a gust generator control signal correction method based on a flow field feedback, and relates to the field of gust simulation. The method comprises the following steps: obtaining actual flow field characteristic parameters of a flow field generated by an initial actuation control signal of a gust generator based on current base flow information and a target monitoring point; determining predicted flow field characteristic parameters corresponding to the current base flow information and the initial actuation control information based on a mapping relationship between the actuation control signal of the gust generator, the base flow information and the flow field characteristic parameters; calculating flow field characteristic parameter deviations based on the actual flow field characteristic parameters and the predicted flow field characteristic parameters; determining a correction amount of the initial actuation control signal based on the flow field characteristic parameter deviations; and correcting the initial actuation control signal based on the correction amount to obtain a target actuation control signal, wherein the target actuation control signal is used to generate a target flow field, so as to ensure that an actually generated flow field is close to the target flow field.

Description

Technical Field

[0001] This application relates to the field of gust simulation, and in particular to a method for correcting the control signal of a gust generator based on flow field feedback. Background Technology

[0002] In wind tunnel testing, it is often necessary to construct unsteady flow fields with specific time-varying patterns within the test section for the study of research objects such as aircraft, wind turbines, or bridges under unsteady aerodynamic environments.

[0003] In related technologies, the oscillation pattern of the blades in a oscillating blade gust generator is pre-set to periodically or non-periodically disturb the incoming flow, thereby forming a target flow field during wind tunnel testing. However, existing gust generator control methods mostly employ biased open-loop control, that is, directly providing the blade oscillation control signal based on experience or pre-calibrated results. This method makes it difficult to ensure that the actual flow field waveform generated in the wind tunnel matches the pre-desired target waveform when operating conditions change, the target waveform is complex, or high precision requirements are needed. Summary of the Invention

[0004] The purpose of this application is to provide a method for correcting the control signal of a gust generator based on flow field feedback, so as to ensure that the actual generated flow field is close to the target flow field.

[0005] To achieve the above objectives, this application provides the following solution: In a first aspect, this application provides a method for correcting the control signal of a gust generator based on flow field feedback. The method includes: Acquire the actual flow field characteristic parameters of the flow field generated at the target monitoring point based on the current basic inflow information and the initial actuation control signal of the gust generator; Based on the pre-built mapping relationship between the actuation control signal of the gust generator, the basic incoming flow information and the flow field characteristic parameters, the predicted flow field characteristic parameters corresponding to the current basic incoming flow information and the initial actuation control information are determined. Based on the actual flow field characteristic parameters and the predicted flow field characteristic parameters, the deviation of the flow field characteristic parameters is calculated; Based on the deviation of the flow field characteristic parameters, the correction amount of the initial actuation control signal is determined; The initial actuation control signal is corrected based on the correction amount to obtain the target actuation control signal, which is used to generate the target flow field.

[0006] In an optional embodiment, the gust generator control signal correction method based on flow field feedback further includes: Acquire basic sample flow information and sample actuation control signals for the gust generator; Based on the sample basic inflow information and the sample actuation control signal of the gust generator, the actual flow field characteristic parameters of the sample corresponding to the sample basic inflow information and the sample actuation control signal are determined; Based on the sample actuation control signal, sample basic inflow information, and sample actual flow field characteristic parameters, a mapping relationship between the actuation control signal, basic inflow information, and flow field characteristic parameters of the gust generator is constructed.

[0007] In an optional embodiment, the gust generator control signal correction method based on flow field feedback further includes: The mapping relationship is corrected based on the deviation of the flow field characteristic parameters.

[0008] In one optional embodiment, the mapping relationship is corrected based on the deviation of the flow field characteristic parameters, including: If the mapping relationship includes sample actuation control signals and sample basic inflow information, then the flow field characteristic parameters corresponding to the sample actuation control signals and sample basic inflow information in the mapping relationship are corrected based on the flow field characteristic parameter deviation. If the mapping relationship does not include the sample actuation control signal and / or sample basic incoming flow information, then determine the first interval to which the sample actuation control signal and / or sample basic incoming flow information belongs in the mapping relationship; The flow field characteristic parameters corresponding to the first interval are determined based on the actuation control signal and basic incoming flow information corresponding to the first interval. Based on the deviation of the flow field characteristic parameters, a linear interpolation method is used to correct the flow field characteristic parameters corresponding to the first interval.

[0009] In one optional embodiment, based on the deviation of the flow field characteristic parameters, a linear interpolation method is used to correct the flow field characteristic parameters corresponding to the first interval, including: Determine a first distance between the sample actuation control signal and the corresponding actuation control signal in the first interval, and / or determine a second distance between the sample basic incoming flow information and the corresponding basic incoming flow information in the first interval; The first interpolation weights are determined based on the first distance and / or the second distance; Based on the flow field characteristic parameters corresponding to the first interval and the first interpolation weight, the deviation of the flow field characteristic parameters corresponding to the first interval is determined; The flow field characteristic parameters corresponding to the first interval are corrected based on the deviation of the flow field characteristic parameters corresponding to the first interval.

[0010] In one optional embodiment, the predicted flow field characteristic parameters corresponding to the current basic inflow information and the initial actuation control information are determined based on a pre-built mapping relationship between the actuation control signal of the gust generator, basic inflow information, and flow field characteristic parameters, including: If the mapping relationship includes the initial actuation control signal and the current basic inflow information, then the flow field characteristic parameters corresponding to the actuation control signal and the basic inflow information in the mapping relationship are determined as the predicted flow field characteristic parameters corresponding to the initial actuation control signal and the current basic inflow information. If the initial actuation control signal and / or the current basic incoming flow information are not included in the mapping relationship, then determine the second interval to which the initial actuation control signal and / or the current basic incoming flow information belong in the mapping relationship; Determine the flow field characteristic parameters corresponding to the second interval based on the actuation control signal and / or basic incoming flow information corresponding to the second interval; Based on the flow field characteristic parameters corresponding to the second interval, the linear interpolation method is used to determine the flow field characteristic parameters corresponding to the initial actuation control signal and the current basic incoming flow information.

[0011] In one optional embodiment, based on the flow field characteristic parameters corresponding to the second interval, a linear interpolation method is used to determine the predicted flow field characteristic parameters corresponding to the initial actuation control signal and the current basic inflow information, including: Determine the third distance between the initial actuation control signal and the corresponding actuation control signal in the second interval, and / or determine the fourth distance between the current basic incoming flow information and the corresponding basic incoming flow information in the second interval; The second interpolation weights are determined based on the third and / or fourth distances; Based on the flow field characteristic parameters corresponding to the second interval and the second interpolation weight, the predicted flow field characteristic parameters corresponding to the initial actuation control signal and the current basic incoming flow information are determined.

[0012] Secondly, this application provides a gust generator control signal correction device based on flow field feedback, comprising: The acquisition module is used to acquire the actual flow field characteristic parameters of the flow field generated by the target monitoring point based on the current basic inflow information and the initial actuation control signal of the gust generator; The first determining module is used to determine the predicted flow field characteristic parameters corresponding to the current basic inflow information and the initial actuation control information based on the pre-built mapping relationship between the actuation control signal of the gust generator, the basic inflow information and the flow field characteristic parameters. The calculation module is used to calculate the deviation of the flow field characteristic parameters based on the actual flow field characteristic parameters and the predicted flow field characteristic parameters; The second determining module is used to determine the correction amount of the initial actuation control signal based on the deviation of the flow field characteristic parameters; The correction module is used to correct the initial actuation control signal based on the correction amount to obtain the target actuation control signal, which is used to generate the target flow field.

[0013] Thirdly, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the flow field feedback-based gust generator control signal correction method described above.

[0014] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method for correcting the control signal of a gust generator based on flow field feedback.

[0015] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the flow field feedback-based gust generator control signal correction method described above.

[0016] According to the specific embodiments provided in this application, the following technical effects are disclosed: This application provides a method for correcting the control signal of a gust generator based on flow field feedback. The method involves obtaining the actual flow field characteristic parameters of the flow field generated at the target monitoring point based on the current basic inflow information and the initial actuation control signal of the gust generator; determining the predicted flow field characteristic parameters corresponding to the current basic inflow information and the initial actuation control information based on a pre-constructed mapping relationship between the gust generator's actuation control signal, the basic inflow information, and the flow field characteristic parameters; calculating the flow field characteristic parameter deviation based on the actual and predicted flow field characteristic parameters; determining the correction amount for the initial actuation control signal based on the flow field characteristic parameter deviation; and correcting the initial actuation control signal based on the correction amount to obtain the target actuation control signal, which is used to generate the target flow field. Using the target flow field waveform as the desired input and the actual flow field characteristic parameters measured in real time in the wind tunnel test section as the feedback input, a gust generator control model is established. Based on the deviation between the measured and predicted flow field characteristic parameters, the generator blade swing angle control signal is adjusted in real time, thereby continuously approximating the target flow field. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart illustrating a method for correcting the control signal of a gust generator based on flow field feedback in one embodiment of this application. Figure 2A schematic diagram of the initial actuation control signal provided in an embodiment of this application; Figure 3 A schematic diagram of a target actuation control signal provided in an embodiment of this application; Figure 4 A schematic diagram of a flow field generated using methods provided by related technologies; Figure 5 A schematic diagram of the target flow field provided in an embodiment of this application; Figure 6 A schematic diagram of the functional modules of a gust generator control signal correction device based on flow field feedback provided in an embodiment of this application; Figure 7 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0019] 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 some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0020] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0021] In one exemplary embodiment, such as Figure 1 As shown, a method for correcting the control signal of a gust generator based on flow field feedback is provided. This method is executed by a computer device, specifically by a terminal or server alone, or by both a terminal and a server. The method includes the following steps: Step S101: Obtain the actual flow field characteristic parameters of the flow field generated by the target monitoring point based on the current basic inflow information and the initial actuation control signal of the gust generator.

[0022] In one alternative embodiment, the basic incoming flow information refers to the time-averaged directional velocity of the flow field.

[0023] It should be noted that the time-averaged flow velocity of the flow field refers to the mainstream velocity when the airflow is stable and uniform in the test section during wind tunnel testing without any disturbance.

[0024] In another optional embodiment, the gust generator control signal correction method based on flow field feedback provided in this application further includes: acquiring the flow field form, flow field distribution characteristics, and gust generator disturbance area of ​​the target flow field; and determining the target monitoring point based on the flow field form, flow field distribution characteristics, and gust generator disturbance area.

[0025] It should be noted that the target monitoring point is a monitoring point capable of monitoring the flow field characteristic parameters used to characterize the target flow field. The flow field characteristic parameters include at least one of the following parameters: flow velocity, vertical velocity, and lateral velocity, or flow field characteristic quantities calculated from a combination of the above variables.

[0026] The target flow field is the desired flow field. Flow field types include steady and unsteady flow fields. Flow field distribution characteristics may include at least one of the following: velocity uniformity, airflow stability and turbulence, directional uniformity, and axial static pressure gradient. Velocity uniformity refers to the distribution of airflow velocity in the test section space. Airflow stability and turbulence refer to the degree of airflow velocity fluctuation over time. Directional uniformity refers to the angle between the airflow direction and the wind tunnel axis. Axial static pressure gradient refers to the static pressure variation of the airflow along the flow direction.

[0027] In another alternative embodiment, the initial actuation control signal of the gust generator refers to the initial command signal sent to the actuator at the start of the test, which is used to set the initial blade angle and initial angular velocity of the blades.

[0028] In another alternative embodiment, a flow field velocity measurement device is used to obtain the actual flow field characteristic parameters of the flow field generated at the target monitoring point based on the current basic inflow information and the initial actuation control signal of the gust generator.

[0029] It should be noted that the flow field velocity measurement device needs to have characteristics such as high response frequency, fast calculation speed, and small disturbance to the flow field to meet the requirements of real-time closed-loop control of gust flow field. In a specific embodiment, the flow field velocity measurement device includes, but is not limited to: laser Doppler velocimetry equipment, hot-wire anemometer, or other devices capable of high-speed real-time velocity measurement, etc., and this application does not limit it.

[0030] Step S102: Based on the pre-built mapping relationship between the actuation control signal of the gust generator, the basic incoming flow information and the flow field characteristic parameters, determine the predicted flow field characteristic parameters corresponding to the current basic incoming flow information and the initial actuation control information.

[0031] In an optional embodiment, the method for correcting the control signal of a gust generator based on flow field feedback provided in this application further includes: acquiring sample basic inflow information and sample actuation control signal of the gust generator; determining the sample actual flow field characteristic parameters corresponding to the sample basic inflow information and sample actuation control signal based on the sample basic inflow information and sample actuation control signal; and constructing a mapping relationship between the actuation control signal of the gust generator, basic inflow information, and flow field characteristic parameters based on the sample actuation control signal, sample basic inflow information, and sample actual flow field characteristic parameters.

[0032] In another optional embodiment, the predicted flow field characteristic parameters corresponding to the current basic inflow information and the initial actuation control information are determined based on a pre-built mapping relationship between the actuation control signal of the gust generator, the basic inflow information, and the flow field characteristic parameters. This includes: if the mapping relationship includes the initial actuation control signal and the current basic inflow information, then the flow field characteristic parameters corresponding to the actuation control signal and the basic inflow information in the mapping relationship are determined as the predicted flow field characteristic parameters corresponding to the initial actuation control signal and the current basic inflow information; if the mapping relationship does not include the initial actuation control signal and / or the current basic inflow information, then the second interval to which the initial actuation control signal and / or the current basic inflow information belongs in the mapping relationship is determined; the flow field characteristic parameters corresponding to the second interval are determined based on the actuation control signal and / or the basic inflow information corresponding to the second interval; and the predicted flow field characteristic parameters corresponding to the initial actuation control signal and the current basic inflow information are determined using a linear interpolation method based on the flow field characteristic parameters corresponding to the second interval.

[0033] In one specific embodiment, based on the flow field characteristic parameters corresponding to the second interval, a linear interpolation method is used to determine the predicted flow field characteristic parameters corresponding to the initial actuation control signal and the current basic incoming flow information. This includes: determining a third distance between the initial actuation control signal and the corresponding actuation control signal in the second interval, and / or determining a fourth distance between the current basic incoming flow information and the corresponding basic incoming flow information in the second interval; determining a second interpolation weight based on the third distance and / or the fourth distance; and determining the predicted flow field characteristic parameters corresponding to the initial actuation control signal and the current basic incoming flow information based on the flow field characteristic parameters corresponding to the second interval and the second interpolation weight.

[0034] In one specific embodiment, the actuation control signal includes blade angle and blade angular velocity, the basic incoming flow information includes incoming flow velocity, and the flow field characteristic parameters include vertical velocity. Assuming the angular velocity is a fixed value, the mapping relationship can be shown in the table below: Table 1

[0035] Assuming the current incoming flow speed 25 m / s, blade angle 15°, angular velocity The current inflow velocity is 300° / s, located between nodes A / C and B / D, and the current blade angle is located between nodes A / B and C / D. The current inflow velocity is 5 units away from the lower limit of 20° and 5 units away from the upper limit of 30°. The normalized weight is: =0.5. The current blade angle is 5 units away from the lower limit of 10 and 5 units away from the upper limit of 20. The normalized weight is: =0.5.

[0036] Using the following formula, a weighted sum is performed according to the interpolation weights to obtain the predicted vertical velocity corresponding to the current base inflow velocity, blade angle, and angular velocity: ; in, 1 represents the predicted vertical velocity corresponding to the current incoming flow velocity, blade angle, and angular velocity. This represents the vertical velocity corresponding to an incoming flow velocity of 20 m / s, a blade angle of 10°, and an angular velocity of 300° / s. and Indicates the normalized weights. This represents the vertical velocity corresponding to an incoming flow velocity of 20 m / s, a blade angle of 20°, and an angular velocity of 300° / s. This represents the vertical velocity corresponding to an incoming flow velocity of 30 m / s, a blade angle of 10°, and an angular velocity of 300° / s. This indicates the vertical velocity corresponding to an incoming flow velocity of 30 m / s, a blade angle of 20°, and an angular velocity of 300° / s.

[0037] Substituting the above values ​​into the above formula, we get: 1 = 3.75 m / s.

[0038] Step S103: Calculate the deviation of the flow field characteristic parameters based on the actual flow field characteristic parameters and the predicted flow field characteristic parameters.

[0039] In one optional embodiment, the difference between the actual flow field characteristic parameters and the predicted flow field characteristic parameters, the relative deviation, the root mean square error, etc., are used as the flow field characteristic parameter deviation.

[0040] In another optional embodiment, the gust generator control signal correction method based on flow field feedback provided in this application further includes: correcting the mapping relationship based on the deviation of flow field characteristic parameters.

[0041] In one specific embodiment, the mapping relationship is corrected based on the deviation of the flow field characteristic parameters, including: If the mapping relationship includes sample actuation control signals and sample basic inflow information, then the flow field characteristic parameters corresponding to the sample actuation control signals and sample basic inflow information in the mapping relationship are corrected based on the flow field characteristic parameter deviation. If the mapping relationship does not include the sample actuation control signal and / or the sample basic incoming flow information, then determine the first interval to which the sample actuation control signal and / or the sample basic incoming flow information belongs in the mapping relationship; determine the flow field characteristic parameters corresponding to the first interval based on the actuation control signal and basic incoming flow information corresponding to the first interval; and correct the flow field characteristic parameters corresponding to the first interval using a linear interpolation method based on the deviation of the flow field characteristic parameters.

[0042] In a more specific embodiment, based on the deviation of the flow field characteristic parameters, a linear interpolation method is used to correct the flow field characteristic parameters corresponding to the first interval, including: determining a first distance between the sample actuation control signal and the corresponding actuation control signal in the first interval, and / or determining a second distance between the sample basic incoming flow information and the corresponding basic incoming flow information in the first interval; determining a first interpolation weight based on the first distance and / or the second distance; determining the deviation of the flow field characteristic parameters corresponding to the first interval based on the flow field characteristic parameters corresponding to the first interval and the first interpolation weight; and correcting the flow field characteristic parameters corresponding to the first interval based on the deviation of the flow field characteristic parameters corresponding to the first interval.

[0043] In one alternative example, the mapping relationship is shown in Table 1, assuming the incoming flow velocity of the new sample is 25 m / s and the sample blade angle is... The sample angular velocity is 15°. The sample inflow velocity is 300° / s, located between nodes A / C and B / D, and the sample blade angle is located between nodes A / B and C / D. The sample inflow velocity is 5 units away from the lower limit of 20 and also 5 units away from the upper limit of 30. The normalized weights are: =0.5. The sample blade angle is 5 units away from the lower limit of 10 and 5 units away from the upper limit of 20. The normalized weight is: =0.5.

[0044] Substituting the above values ​​into the above formula, we obtain: the predicted vertical velocity corresponding to the sample inflow velocity, blade angle, and angular velocity: 2 = 3.75 m / s. Assume the actual vertical velocity corresponding to the sample flow velocity, blade angle, and angular velocity. If the velocity is 4.5 m / s, then the total vertical velocity deviation corresponding to the sample inflow velocity, blade angle, and angular velocity is: =0.75.

[0045] Using the following formula, a weighted sum is performed according to the first interpolation weight to obtain the vertical velocity deviation corresponding to each node: =0.1875; = =0.1875; = =0.1875; = =0.1875; in, This indicates the vertical velocity deviation corresponding to an incoming flow velocity of 20 m / s, a blade angle of 10°, and an angular velocity of 300° / s. This indicates the vertical velocity deviation corresponding to an incoming flow velocity of 20 m / s, a blade angle of 20°, and an angular velocity of 300° / s. This indicates the vertical velocity deviation corresponding to an incoming flow velocity of 30 m / s, a blade angle of 10°, and an angular velocity of 300° / s. This indicates the vertical velocity deviation corresponding to an incoming flow velocity of 30 m / s, a blade angle of 20°, and an angular velocity of 300° / s. This represents the total vertical velocity deviation corresponding to the sample inflow velocity, blade angle, and angular velocity.

[0046] Step S104: Determine the correction amount of the initial actuation control signal based on the deviation of the flow field characteristic parameters.

[0047] In one optional embodiment, the correction amount of the initial actuation control signal is calculated using a preset control algorithm based on the deviation of the flow field characteristic parameters.

[0048] In one specific embodiment, the preset control algorithm can be a proportional-integral-derivative control algorithm, a feedforward and feedback coupled control algorithm, a model predictive control algorithm, or other closed-loop correction algorithms, and this application does not limit it.

[0049] In a more specific embodiment, taking the proportional-integral-derivative control algorithm as an example, the correction amount of the initial actuation control signal is calculated using the following formula: ; in, This is the correction amount for the initial actuation control signal at the current time t. , , These are the proportional, integral, and differential coefficients, respectively. This represents the deviation of the flow field characteristic parameters at the current time t.

[0050] It should be noted that, The initial value can be the slope of the vertical velocity as a function of the current angular velocity and the swing angle. , , It can be determined based on the response curve during actual operation.

[0051] Step S105: Correct the initial actuation control signal based on the correction amount to obtain the target actuation control signal.

[0052] In one optional embodiment, the initial actuation control signal is corrected based on the correction amount, and the target actuation control signal is calculated using the following formula: ; in, This is the initial actuation control signal corresponding to time t. This is the correction amount corresponding to time t. The actuation control signal for the next cycle at time t is the target actuation control signal, where T represents the cycle period of the actuation control signal.

[0053] It should be noted that the target actuation control signal is used to generate the target flow field.

[0054] In another alternative embodiment, Figure 2 This is a schematic diagram of the initial actuation control signal provided in an embodiment of this application. The horizontal axis represents time, and the vertical axis represents the blade angle that changes over time. Figure 3 This is a schematic diagram of a target actuation control signal provided in an embodiment of this application, where the horizontal axis represents time and the vertical axis represents the blade angle changing over time. Compared to Figure 2 The initial actuation control signal provided. Figure 3 The target actuation control signal contains deviations to counteract waveform distortion. Figure 4 This is a schematic diagram of a flow field generated using methods provided by related technologies, with time on the horizontal axis and vertical velocity on the vertical axis. Figure 5 This is a schematic diagram of the target flow field provided in an embodiment of this application, where the horizontal axis represents time and the vertical axis represents vertical velocity. Compared to Figure 5 The target flow field is provided. Figure 4 The flow field in the middle exhibits distortion at peak positions and other locations.

[0055] This application also provides an application scenario in which the above-described method for correcting gust generator control signals based on flow field feedback is applied. Specifically, the method for correcting gust generator control signals based on flow field feedback provided in this embodiment can be applied in wind tunnel testing scenarios. The method involves: acquiring the actual flow field characteristic parameters of the flow field generated at the target monitoring point based on the current basic inflow information and the initial actuation control signal of the gust generator; determining the predicted flow field characteristic parameters corresponding to the current basic inflow information and the initial actuation control information based on a pre-constructed mapping relationship between the actuation control signal of the gust generator, the basic inflow information, and the flow field characteristic parameters; calculating the flow field characteristic parameter deviation based on the actual flow field characteristic parameters and the predicted flow field characteristic parameters; determining the correction amount of the initial actuation control signal based on the flow field characteristic parameter deviation; correcting the initial actuation control signal based on the correction amount to obtain the target actuation control signal, which is used to generate the target flow field to ensure that the actually generated flow field is close to the target flow field. In this way, an unsteady flow field with a specific time variation pattern can be constructed in the test section of the wind tunnel test, which can be used to study research objects such as aircraft, wind turbines or bridges in unsteady aerodynamic environments.

[0056] Based on the same inventive concept, this application also provides a flow field feedback-based gust generator control signal correction device for implementing the above-mentioned flow field feedback-based gust generator control signal correction method. The solution provided by this device is similar to the solution described in the above method. Therefore, the specific limitations of one or more flow field feedback-based gust generator control signal correction device embodiments provided below can be found in the limitations of the flow field feedback-based gust generator control signal correction method described above, and will not be repeated here.

[0057] In one exemplary embodiment, such as Figure 6 As shown, a gust generator control signal correction device based on flow field feedback is provided, comprising: The acquisition module is used to acquire the actual flow field characteristic parameters of the flow field generated by the target monitoring point based on the current basic inflow information and the initial actuation control signal of the gust generator; The first determining module is used to determine the predicted flow field characteristic parameters corresponding to the current basic inflow information and the initial actuation control information based on the pre-built mapping relationship between the actuation control signal of the gust generator, the basic inflow information and the flow field characteristic parameters. The calculation module is used to calculate the deviation of the flow field characteristic parameters based on the actual flow field characteristic parameters and the predicted flow field characteristic parameters; The second determining module is used to determine the correction amount of the initial actuation control signal based on the deviation of the flow field characteristic parameters; The correction module is used to correct the initial actuation control signal based on the correction amount to obtain the target actuation control signal, which is used to generate the target flow field.

[0058] In an optional embodiment, the apparatus further includes a module for performing the following operations: Acquire basic sample flow information and sample actuation control signals for the gust generator; Based on the sample basic inflow information and the sample actuation control signal of the gust generator, the actual flow field characteristic parameters of the sample corresponding to the sample basic inflow information and the sample actuation control signal are determined; Based on the sample actuation control signal, sample basic inflow information, and sample actual flow field characteristic parameters, a mapping relationship between the actuation control signal, basic inflow information, and flow field characteristic parameters of the gust generator is constructed.

[0059] In an optional embodiment, the apparatus further includes a module for performing the following operations: The mapping relationship is corrected based on the deviation of the flow field characteristic parameters.

[0060] In an optional embodiment, the apparatus further includes a module for performing the following operations: If the mapping relationship includes sample actuation control signals and sample basic inflow information, then the flow field characteristic parameters corresponding to the sample actuation control signals and sample basic inflow information in the mapping relationship are corrected based on the flow field characteristic parameter deviation. If the mapping relationship does not include the sample actuation control signal and / or sample basic incoming flow information, then determine the first interval to which the sample actuation control signal and / or sample basic incoming flow information belongs in the mapping relationship; The flow field characteristic parameters corresponding to the first interval are determined based on the actuation control signal and basic incoming flow information corresponding to the first interval. Based on the deviation of the flow field characteristic parameters, a linear interpolation method is used to correct the flow field characteristic parameters corresponding to the first interval.

[0061] In an optional embodiment, the apparatus further includes a module for performing the following operations: Determine a first distance between the sample actuation control signal and the corresponding actuation control signal in the first interval, and / or determine a second distance between the sample basic incoming flow information and the corresponding basic incoming flow information in the first interval; The first interpolation weights are determined based on the first distance and / or the second distance; Based on the flow field characteristic parameters corresponding to the first interval and the first interpolation weight, the deviation of the flow field characteristic parameters corresponding to the first interval is determined; The flow field characteristic parameters corresponding to the first interval are corrected based on the deviation of the flow field characteristic parameters corresponding to the first interval.

[0062] In one alternative embodiment, the first determining module is configured to: If the mapping relationship includes the initial actuation control signal and the current basic inflow information, then the flow field characteristic parameters corresponding to the actuation control signal and the basic inflow information in the mapping relationship are determined as the predicted flow field characteristic parameters corresponding to the initial actuation control signal and the current basic inflow information. If the initial actuation control signal and / or the current basic incoming flow information are not included in the mapping relationship, then determine the second interval to which the initial actuation control signal and / or the current basic incoming flow information belong in the mapping relationship; Determine the flow field characteristic parameters corresponding to the second interval based on the actuation control signal and / or basic incoming flow information corresponding to the second interval; Based on the flow field characteristic parameters corresponding to the second interval, the linear interpolation method is used to determine the flow field characteristic parameters corresponding to the initial actuation control signal and the current basic incoming flow information.

[0063] In one optional embodiment, the first determining module is specifically used for: Determine the third distance between the initial actuation control signal and the corresponding actuation control signal in the second interval, and / or determine the fourth distance between the current basic incoming flow information and the corresponding basic incoming flow information in the second interval; The second interpolation weights are determined based on the third and / or fourth distances; Based on the flow field characteristic parameters corresponding to the second interval and the second interpolation weight, the predicted flow field characteristic parameters corresponding to the initial actuation control signal and the current basic incoming flow information are determined.

[0064] In one exemplary embodiment, a computer device, such as Figure 7 As shown, the electronic device includes: a processor 701; and a memory 702, which stores a computer program. When the processor 701 executes the computer program, it implements the steps in the above-described method embodiments.

[0065] Those skilled in the art will understand that Figure 7 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0066] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0067] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0068] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0069] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0070] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0071] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0072] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for correcting the control signal of a gust generator based on flow field feedback, characterized in that, The method for correcting the control signal of a gust generator based on flow field feedback includes: Acquire the actual flow field characteristic parameters of the flow field generated at the target monitoring point based on the current basic inflow information and the initial actuation control signal of the gust generator; Based on the pre-constructed mapping relationship between the actuation control signal of the gust generator, the basic incoming flow information and the flow field characteristic parameters, the predicted flow field characteristic parameters corresponding to the current basic incoming flow information and the initial actuation control information are determined; Based on the actual flow field characteristic parameters and the predicted flow field characteristic parameters, the deviation of the flow field characteristic parameters is calculated; Based on the deviation of the flow field characteristic parameters, the correction amount of the initial actuation control signal is determined; The initial actuation control signal is corrected based on the correction amount to obtain the target actuation control signal, which is used to generate the target flow field.

2. The method for correcting the control signal of a gust generator based on flow field feedback according to claim 1, characterized in that, The method for correcting the control signal of a gust generator based on flow field feedback also includes: Acquire basic sample flow information and sample actuation control signals of the gust generator; Based on the sample basic inflow information and the sample actuation control signal of the gust generator, the actual flow field characteristic parameters of the sample corresponding to the sample basic inflow information and the sample actuation control signal are determined; Based on the sample actuation control signal, the sample basic inflow information, and the sample actual flow field characteristic parameters, a mapping relationship between the actuation control signal, basic inflow information, and flow field characteristic parameters of the gust generator is constructed.

3. The method for correcting the control signal of a gust generator based on flow field feedback according to claim 2, characterized in that, The method for correcting the control signal of a gust generator based on flow field feedback also includes: The mapping relationship is corrected based on the deviation of the flow field characteristic parameters.

4. The method for correcting the control signal of a gust generator based on flow field feedback according to claim 3, characterized in that, The correction of the mapping relationship based on the deviation of the flow field characteristic parameters includes: If the mapping relationship includes the sample actuation control signal and the sample basic inflow information, then the flow field characteristic parameters corresponding to the sample actuation control signal and the sample basic inflow information in the mapping relationship are corrected based on the flow field characteristic parameter deviation; If the mapping relationship does not include the sample actuation control signal and / or the sample basic incoming flow information, then the first interval to which the sample actuation control signal and / or the sample basic incoming flow information belongs in the mapping relationship is determined; The flow field characteristic parameters corresponding to the first interval are determined based on the actuation control signal and basic incoming flow information corresponding to the first interval. Based on the deviation of the flow field characteristic parameters, a linear interpolation method is used to correct the flow field characteristic parameters corresponding to the first interval.

5. The method for correcting the control signal of a gust generator based on flow field feedback according to claim 4, characterized in that, The step of correcting the flow field characteristic parameters corresponding to the first interval using a linear interpolation method based on the deviation of the flow field characteristic parameters includes: Determine a first distance between the sample actuation control signal and the corresponding actuation control signal in the first interval, and / or determine a second distance between the sample basic incoming flow information and the corresponding basic incoming flow information in the first interval; The first interpolation weight is determined based on the first distance and / or the second distance; Based on the flow field characteristic parameters corresponding to the first interval and the first interpolation weight, the deviation of the flow field characteristic parameters corresponding to the first interval is determined; The flow field characteristic parameters corresponding to the first interval are corrected based on the deviation of the flow field characteristic parameters corresponding to the first interval.

6. The method for correcting the control signal of a gust generator based on flow field feedback according to claim 1, characterized in that, The method for determining the predicted flow field characteristic parameters corresponding to the current basic inflow information and the initial actuation control information based on the pre-built mapping relationship between the gust generator's actuation control signal, basic inflow information, and flow field characteristic parameters includes: If the mapping relationship includes the initial actuation control signal and the current basic incoming flow information, then the flow field characteristic parameters corresponding to the actuation control signal and the basic incoming flow information in the mapping relationship are determined as the predicted flow field characteristic parameters corresponding to the initial actuation control signal and the current basic incoming flow information. If the initial actuation control signal and / or the current basic incoming flow information are not included in the mapping relationship, then the second interval to which the initial actuation control signal and / or the current basic incoming flow information belong in the mapping relationship is determined; The flow field characteristic parameters corresponding to the second interval are determined based on the actuation control signal and / or basic incoming flow information corresponding to the second interval. Based on the flow field characteristic parameters corresponding to the second interval, the flow field characteristic parameters corresponding to the initial actuation control signal and the current basic incoming flow information are determined by linear interpolation.

7. The method for correcting the control signal of a gust generator based on flow field feedback according to claim 6, characterized in that, The step of determining the predicted flow field characteristic parameters corresponding to the initial actuation control signal and the current basic inflow information using a linear interpolation method based on the flow field characteristic parameters corresponding to the second interval includes: Determine a third distance between the initial actuation control signal and the corresponding actuation control signal in the second interval, and / or determine a fourth distance between the current basic incoming flow information and the corresponding basic incoming flow information in the second interval; The second interpolation weights are determined based on the third distance and / or the fourth distance; Based on the flow field characteristic parameters corresponding to the second interval and the second interpolation weight, the predicted flow field characteristic parameters corresponding to the initial actuation control signal and the current basic incoming flow information are determined.

8. A gust generator control signal correction device based on flow field feedback, characterized in that, The gust generator control signal correction device based on flow field feedback includes: The acquisition module is used to acquire the actual flow field characteristic parameters of the flow field generated by the target monitoring point based on the current basic inflow information and the initial actuation control signal of the gust generator; The first determining module is used to determine the predicted flow field characteristic parameters corresponding to the current basic inflow information and the initial actuation control information based on the pre-constructed mapping relationship between the actuation control signal of the gust generator, the basic inflow information and the flow field characteristic parameters; The calculation module is used to calculate the deviation of the flow field characteristic parameters based on the actual flow field characteristic parameters and the predicted flow field characteristic parameters; The second determining module is used to determine the correction amount of the initial actuation control signal based on the deviation of the flow field characteristic parameters; The correction module is used to correct the initial actuation control signal based on the correction amount to obtain the target actuation control signal, which is used to generate the target flow field.

9. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the steps of the method for correcting the control signal of a gust generator based on flow field feedback as described in any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the method for correcting the control signal of a gust generator based on flow field feedback as described in any one of claims 1-7.

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