A method and system for shape sensing and control of a variable aircraft wing

Abstract

The application discloses a morphing aircraft wing shape sensing and control method and system, and belongs to the technical field of aircraft flight detection and control. The actual angle of the wing and the state quantity of the sweepback angle and the span of the wing are determined. When the error between the actual angle of the wing and the required angle exceeds the preset error threshold, the motion state of the feature point is predicted through Kalman filtering, the sweepback angle and the span of the wing are updated to obtain the change quantity of the sweepback angle and the span, and the state quantity is time-stamped and synchronized, and then multi-source information fusion is performed to obtain the state estimation value of the sweepback angle and the span. The state estimation value, the current flight attitude information of the aircraft and the error between the actual angle of the wing and the required angle are used as the input of the controller to adaptively adjust the sweepback angle and the span until the error between the actual angle of the wing and the required angle meets the error threshold. The method can improve the accuracy and robustness of dynamic deformation monitoring and control of the morphing wing.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of aircraft flight detection and control, and more particularly to a variable aircraft wing shape sensing and control method and system. BACKGROUND

[0002] With the increasing demand for multi-mission, multi-flight envelope aircraft, the traditional fixed configuration wing has been difficult to maintain optimal performance in different flight states.

[0003] Variable wing (variable sweep angle, variable span) technology can optimize lift, drag and maneuverability of the aircraft in different working conditions by actively adjusting the wing shape. For example, at high speed cruise, a large sweep angle and a small span are used to reduce drag; at take-off and low speed flight stage, a small sweep angle and a large span are used to improve lift.

[0004] Currently, the common methods for wing shape deformation monitoring include contact sensors such as strain gauges and fiber Bragg gratings. This method can only measure a single point, and cannot cover and detect the overall shape deviation or local structural abnormalities of the wing. Moreover, such contact sensors can affect the structure of the wing itself. The existing contact sensors cannot real-time sense the actual wing deformation state. When there is a gap in mechanical transmission, external force interference or environmental influence, the control command and the actual wing shape may not be consistent. The existing wing deformation control strategy is mostly based on pre-setting or model predictive control, and lacks dynamic adjustment of wing shape according to flight attitude (climbing, cruising, diving, etc.).

[0005] In summary, in the existing variable wing technology, when the monitoring process of wing deformation (including sweep angle and span change) is disturbed by external force or environment, the variable wing cannot be adjusted in attitude accurately only by sensor detection. SUMMARY

[0006] To solve the above problems, the present application provides a variable aircraft wing shape sensing and control method and system. When the error between the actual angle of the wing and the required angle exceeds the preset error threshold, the feature points are updated in real time through state prediction, and then the change amount of the sweep angle and the span of the wing is determined. After time stamp alignment and synchronization processing of the sweep angle and the span state amount of the wing obtained by the sensor, and multi-source information fusion, the random noise and systematic deviation caused by a single sensor can be effectively suppressed, the stability and reliability of state estimation can be improved, and stable estimation of the span and sweep angle parameters can be realized.

[0007] To solve the above technical problems, the present application discloses a variable aircraft wing shape sensing and control method, comprising the following steps:

[0008] Obtaining the positions of preset feature points on the inner wing segment and the outer wing segment of the variable wing, and determining the actual angle of the wing; obtaining the state quantities of the sweepback angle and the span of the wing through sensors mounted on the rotating shaft of the aircraft;

[0009] When the error between the actual angle of the wing and the required angle exceeds a preset error threshold, the feature points fail in vision, the motion state of the feature points is predicted through Kalman filtering to obtain updated feature points; the updated feature points are sequentially subjected to three-dimensional reconstruction and deformation calculation, and the change quantities of the sweepback angle and the span of the wing are estimated;

[0010] After time stamp alignment and synchronous processing of the state quantities and the change quantities of the sweepback angle and the span of the wing, multi-source information fusion is performed to obtain the state estimation value of the sweepback angle and the span of the wing;

[0011] Obtaining the current flight attitude information of the aircraft; taking the state estimation value, the current flight attitude information of the aircraft and the error between the actual angle of the wing and the required angle as inputs of a controller, the sweepback angle and the span are adaptively adjusted until the error between the actual angle of the wing and the required angle meets the error threshold.

[0012] Preferably, the obtaining of the positions of preset feature points on the inner wing segment and the outer wing segment of the variable wing, and the determination of the actual angle of the wing specifically comprises:

[0013] Extracting the center coordinates of the feature points at the zero position of the wing, collecting the first frame of images at the zero position, and selecting all feature points on the surface of the wing through artificial interactive mode;

[0014] Taking any feature point corner as a reference, a search area with a certain radius around the feature point corner is set, the similarity is calculated point by point through sliding template, and a matching score map is generated; the position with the highest similarity in the matching score map is selected to determine the sub-pixel coordinates of the feature point corner;

[0015] According to the sub-pixel coordinates of the feature point corner, the three-coordinate measuring machine is used to obtain the three-dimensional coordinates of the feature point in the wing coordinate system;

[0016] After coordinate conversion of the three-dimensional coordinates, the feature points of the inner wing segment and the outer wing segment are respectively subjected to straight line fitting, and the straight line equations representing the directions of the inner wing segment and the outer wing segment are obtained, and the actual angle of the wing is obtained by determining the included angle between the two straight lines.

[0017] Preferably, when the error between the actual angle of the wing and the required angle exceeds a preset error threshold, the feature points fail in vision, the motion state of the feature points is predicted through Kalman filtering to obtain updated feature points, and the specific steps comprise:

[0018] Obtaining the images of the positions of feature points in each frame;

[0019] The feature point detection and matching are performed on each frame of image of the feature point position by establishing a mapping relationship between the actual angle of the wing and the position of the feature point, to obtain sub-pixel level image coordinates of all feature point corners;

[0020] According to the sub-pixel level image coordinates of all feature point corners, whether the feature point has visual failure is determined by determining the confidence of the feature point;

[0021] When the confidence of the feature point exceeds the confidence threshold requirement, the feature point has visual failure, a motion state prediction method based on Kalman filtering is used to update the position and track the trajectory of the feature point with visual failure, to obtain the updated feature point.

[0022] Preferably, the updated feature point is sequentially subjected to three-dimensional reconstruction and deformation calculation, to obtain the change of the sweepback angle and the span length of the wing in real time, specifically including:

[0023] The sub-pixel level image coordinates of all updated feature point corners are obtained, and the world coordinates of all updated feature point corners are obtained through three-dimensional reconstruction;

[0024] According to the world coordinates of all updated feature point corners, the feature points of the inner wing segment and the outer wing segment are evenly distributed in two rows, each row of the inner wing segment includes two or more feature points, and each row of the outer wing segment includes at least one feature point, a certain feature point in a certain row of the inner wing segment is taken as a reference point, and all feature points are projected onto the tangent plane of the wing surface where the reference point is located, and the tangent plane is the z-axis plane;

[0025] In the tangent plane, a straight line is taken as the reference point, a straight line fitting is performed on all feature points of the inner wing segment on the straight line to obtain a vector A, a least square straight line fitting is performed on all feature points of another row of the inner wing segment to obtain a vector B, and average unitization is performed on the vectors A and B to obtain a direction vector C of the wing along the span direction, and the change amount of the angle of the sweepback angle of the wing is obtained by calculating the angle change of the direction vector C.

[0026] The distance change of each feature point of the outer wing segment relative to all feature points of the inner wing segment in the tangent plane where the reference point is located is determined and average unitization is performed, to obtain the expansion change amount of the outer wing segment relative to the inner wing segment, i.e. the change amount of the span length.

[0027] Preferably, the state estimation value, the current flight attitude information of the aircraft and the error between the actual angle of the wing and the required angle are taken as the inputs of the controller, to adaptively adjust the sweepback angle and the span length until the error between the actual angle of the wing and the required angle meets the error threshold, specifically including:

[0028] The error between the actual angle of the wing and the required angle, the state estimation value and the flight attitude information of the aircraft are taken as the inputs of the fuzzy PID controller, when the error between the actual angle of the wing and the required angle is greater than the preset error threshold, the PID parameters k p 、k i 、k d :

[0029] When the current flight attitude of the aircraft is rapid climbing or diving flight stage, the fuzzy PID controller increases k d and reduces k i , and the output control instruction is large sweepback angle and small span;

[0030] When the current flight attitude of the aircraft is cruising stage, the fuzzy PID controller increases k i , and the output control instruction is small sweepback angle and large span.

[0031] Preferably, the wing sweepback angle and span state quantity and change quantity are time stamped, aligned and synchronized, and then multi-source information fusion is performed to obtain the state estimation value of the wing sweepback angle and span. Specifically, it comprises:

[0032] The wing sweepback angle and span state quantity and change quantity are aligned to a unified timestamp, and linear interpolation or spline interpolation is used to process the non-synchronous data to obtain the state quantity and change quantity after time stamp alignment and synchronization processing;

[0033] The state quantity and change quantity after time stamp alignment and synchronization processing are subjected to multi-source information fusion, the state of the wing sweepback angle and span is predicted through Kalman filtering algorithm, and the state estimation value of the wing sweepback angle and span is obtained.

[0034] Preferably, the current flight attitude information of the aircraft is obtained by a sensor code carried on the rotating shaft of the aircraft, including pitch angle, roll angle, angular velocity and acceleration.

[0035] Preferably, it further comprises a variable aircraft wing shape sensing and control system, comprising:

[0036] An attitude measurement module for obtaining the current flight attitude information of the aircraft;

[0037] A visual online monitoring module is configured to acquire positions of preset feature points on surfaces of inner and outer wing segments of a morphing wing, and determine an actual angle of the wing; a sensor mounted on a rotating shaft of the aircraft is configured to acquire state quantities of a sweepback angle and a span length of the wing; when an error between the actual angle of the wing and a required angle exceeds a preset error threshold, the feature points are visually failed, the motion state of the feature points is predicted through Kalman filtering, and updated feature points are obtained; the updated feature points are sequentially subjected to three-dimensional reconstruction and deformation calculation, and the change amount of the sweepback angle and the span length of the wing is obtained through estimation.

[0038] A multi-source information fusion module is configured to perform time stamp alignment and synchronization processing on the state quantities and the change amounts of the sweepback angle and the span length of the wing, and perform multi-source information fusion to obtain state estimation values of the sweepback angle and the span length of the wing.

[0039] A control execution module is configured to take the state estimation values, current flight attitude information of the aircraft, and the error between the actual angle of the wing and the required angle as inputs of a controller, and perform adaptive adjustment on the sweepback angle and the span length until the error between the actual angle of the wing and the required angle meets the error threshold.

[0040] Compared with the prior art, the present application has the following beneficial effects:

[0041] The morphing aircraft wing shape perception and control method provided by the present application acquires positions of preset feature points on surfaces of inner and outer wing segments of a morphing wing, and determines an actual angle of the wing; when an error between the actual angle of the wing and a required angle exceeds a preset error threshold, the feature points are visually failed, the motion state of the feature points is predicted through Kalman filtering, and updated feature points are obtained; the updated feature points are sequentially subjected to three-dimensional reconstruction and deformation calculation, and the change amount of the sweepback angle and the span length of the wing is obtained through estimation. BRIEF DESCRIPTION OF DRAWINGS

[0042] Figure 1 A flowchart of the morphing aircraft wing shape perception and control method provided by the present application;

[0043] Figure 2A schematic diagram of a variant wing provided for an embodiment of the present application;

[0044] Figure 3 A schematic diagram of a variant wing provided for an embodiment of the present application Figure 2 A schematic diagram of a rear-sweep angle and a rear-span length of a wing shown in the figure are rotated and deformed;

[0045] Figure 4 A schematic diagram of a variant aircraft wing shape sensing and control system provided for an embodiment of the present application;

[0046] Figure 5 A visual online monitoring module composition detail module provided for an embodiment of the present application;

[0047] In the figure: 11, inner wing segment; 12, outer wing segment; 13, linear motion unit; 14, rotary motion unit; 21-28, feature points. DETAILED DESCRIPTION

[0048] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present application. Figures 1-5 The terms described in the present application are only used for describing the specific embodiments, and are not used for limiting the present application.

[0049] EMBODIMENT

[0050] As Figure 1 shown, a variant aircraft wing shape sensing and control method proposed by the present application comprises the following steps:

[0051] S1: Obtain the positions of the preset feature points on the surfaces of the inner wing segment and the outer wing segment of the variant wing, determine the actual angle of the wing, and obtain the state quantities of the rear-sweep angle and the span length of the wing through the sensors mounted on the rotating shaft of the aircraft;

[0052] S2: When the error between the actual angle of the wing and the required angle exceeds the preset error threshold, the feature points are visually failed, the motion state of the feature points is predicted through Kalman filtering to obtain updated feature points, the updated feature points are sequentially subjected to three-dimensional reconstruction and deformation calculation, and the change amounts of the rear-sweep angle and the span length of the wing are estimated;

[0053] S3: The state quantities and the change amounts of the rear-sweep angle and the span length of the wing are time-stamped and synchronously processed, and then subjected to multi-source information fusion to obtain the state estimation values of the rear-sweep angle and the span length of the wing;

[0054] S4: Obtain the current flight attitude information of the aircraft; take the state estimation values, the current flight attitude information of the aircraft, and the error between the actual angle of the wing and the required angle as the inputs of the controller, and perform adaptive adjustment on the rear-sweep angle and the span length until the error between the actual angle of the wing and the required angle satisfies the error threshold.

[0055] In step S1, the positions of the preset feature points on the inner wing segment and the outer wing segment surfaces of the variable wing are acquired, and the actual angle of the wing is determined, specifically including:

[0056] The inner wing segment can rotate around the fuselage root hinge to change the sweepback angle, and the outer wing segment can change the span length by stretching in the wing span direction, and a plurality of feature points with high contrast are uniformly distributed on the surfaces of the inner wing segment and the outer wing segment;

[0057] The center coordinates of the feature points at the zero position of the wing are extracted, the first frame of image at the zero position is collected, and all feature points on the surface of the wing are selected by manual interaction;

[0058] Taking any feature point corner as a reference, a search area with a certain radius is set around it, the similarity is calculated point by point by sliding template, and a matching score map is generated; the position with the highest similarity in the matching score map is selected to determine the sub-pixel coordinates of the feature point corner;

[0059] According to the sub-pixel coordinates of the feature point corner, the three-coordinate measuring machine is used to obtain the three-dimensional coordinates of the feature point in the wing coordinate system;

[0060] After coordinate conversion of the three-dimensional coordinates, the feature points of the inner wing segment and the outer wing segment are respectively subjected to straight line fitting, and the straight line equations representing the directions of the inner wing segment and the outer wing segment are obtained, and the actual angle of the wing is obtained by determining the included angle between the two straight lines.

[0061] In step S2, when the error between the actual angle of the wing and the required angle exceeds the preset error threshold, the feature points are visually failed, and the motion state of the feature points is predicted by Kalman filtering to obtain updated feature points, specifically including:

[0062] An image of the position of each frame of feature points is acquired;

[0063] The image of each frame of feature points is subjected to feature point detection and matching by establishing a mapping relationship between the actual angle of the wing and the position of the feature points, and the sub-pixel level image coordinates of all feature point corners are obtained;

[0064] According to the sub-pixel level image coordinates of all feature point corners, the confidence of the feature points is determined to determine whether the feature points are visually failed;

[0065] When the confidence of the feature points exceeds the confidence threshold requirement, the feature points are visually failed, and a motion state prediction method based on Kalman filtering is used to update the position and track the trajectory of the visually failed feature points to obtain updated feature points.

[0066] The updated feature points are then subjected to 3D reconstruction and deformation calculations. The changes in the wing's sweep angle and span are estimated, specifically including:

[0067] Obtain the subpixel-level image coordinates of all feature point corners after the update, and obtain the world coordinates of all feature point corners through 3D reconstruction.

[0068] Based on the updated world coordinates of all feature point corners, such as Figure 2 The diagram shown is a schematic of a variant wing provided in an embodiment of the present invention. The feature points of the inner wing section and the outer wing section are evenly distributed in two rows. Each row of the inner wing section includes two or more feature points; each row of the outer wing section includes at least one feature point. Taking a certain feature point of a certain row of the inner wing section as a reference point, all feature points are projected onto the tangent plane of the wing surface where the reference point is located. The tangent plane is the z-axis plane.

[0069] In the tangent plane, using feature point 21 as the reference point and the reference point as the straight line, vector A is obtained by fitting a straight line to all feature points 21, 22, and 23 on the inner wing segment along the straight line; vector B is obtained by fitting a least-squares straight line to all feature points 24, 25, and 26 on the other row of the inner wing segment; vectors A and B are averaged and normalized to obtain the wing's direction vector C along the wingspan; by calculating the angular change of the direction vector C, the change in the wing's sweep angle is obtained.

[0070] The distance changes of feature points 27 and 28 of the outer wing segment relative to all feature points 21-26 of the inner wing segment in the tangential plane where feature point 21 is located (as a reference point) are determined and averaged to obtain the expansion and contraction changes of the outer wing segment relative to the inner wing segment, i.e., the change in span.

[0071] like Figure 3 As shown, this is for Figure 2 A schematic diagram of the sweep angle for rotational deformation and the elongation for stretching deformation.

[0072] In step S3, the wing sweep angle and span state variables and their changes are aligned to a unified timestamp, ensuring that the wing sweep angle and span state variables and the estimated changes in wing sweep angle and span have a unified time reference. Linear interpolation or spline interpolation is used to process the asynchronous data, and the timestamp-aligned and synchronized state variables and their changes are obtained by compensating for the time difference. The timestamp-aligned and synchronized state variables and their changes are then fused with the wing sweep angle and span state variables acquired by the sensors using a Kalman filter algorithm to obtain high-precision state estimates of the wing sweep angle and span.

[0073] In step S4, the state estimation value, the current flight attitude information of the aircraft and the error between the actual angle of the wing and the required angle are taken as the inputs of the controller to adaptively adjust the sweepback angle and the span length until the error between the actual angle of the wing and the required angle meets the error threshold, specifically comprising:

[0074] The error between the actual angle of the wing and the required angle, the state estimation value and the flight attitude information of the aircraft are taken as the inputs of the fuzzy PID controller, and when the error between the actual angle of the wing and the required angle is greater than the preset error threshold, the PID parameters k p , k i , k d are dynamically adjusted; wherein in the high dynamic working condition of rapid climb or dive, the fuzzy PID controller suppresses rapid disturbance and overshoot by increasing k d and reducing k i ; and in the steady-state working condition of cruise, the control precision is improved by increasing k i .

[0075] When the current flight attitude of the aircraft is in the rapid climb or dive flight stage, the control instruction output by the fuzzy PID controller is large sweepback angle and small span length.

[0076] When the current flight attitude of the aircraft is in the cruise stage, the control instruction output by the fuzzy PID controller is small sweepback angle and large span length.

[0077] As shown in Figure 4 , the present application further provides a variable aircraft wing shape sensing and control system, comprising:

[0078] An attitude measurement module is configured to acquire the current flight attitude information of the aircraft by using an inertial measurement unit (IMU), the IMU being an attitude sensor mounted on the rotating shaft of the aircraft, and the current flight attitude information of the aircraft being obtained by encoding, and the flight attitude information including the pitch angle, the roll angle, the angular velocity and the acceleration, etc.

[0079] A visual online monitoring module is configured to acquire the positions of the preset feature points on the surfaces of the inner wing segment and the outer wing segment of the variable wing to determine the actual angle of the wing, and acquire the state quantities of the sweepback angle and the span length of the wing by using the sensors mounted on the rotating shaft of the aircraft; when the error between the actual angle of the wing and the required angle exceeds the preset error threshold, the feature points are visually failed, the motion state of the feature points is predicted by using Kalman filtering to obtain the updated feature points, and the change amount of the sweepback angle and the span length of the wing is estimated by sequentially performing three-dimensional reconstruction and deformation calculation on the updated feature points. Multi-thread parallel processing is adopted to realize high-speed processing from image acquisition to feature point matching to deformation calculation, and the real-time performance of the wing deformation data transmission is realized.

[0080] Specifically, asFigure 5 As shown, the visual online monitoring module includes an image acquisition module, a feature point detection and matching module, a three-dimensional reconstruction and deformation calculation module, a displacement visualization module, and a serial communication module.

[0081] The image acquisition module is mounted on the fuselage or tail of the aircraft, and covers the entire wing in the visual angle, and is used to acquire feature point images on the surface of the wing; the feature point detection and matching module is used to extract the center coordinates of the feature points and perform matching; the three-dimensional reconstruction and deformation calculation module is used to calculate the change in the sweep angle and the span length of the wing before and after deformation through three-dimensional reconstruction of the extracted feature points.

[0082] The feature point detection and matching module includes two steps of first frame selection and template matching. Under normal visual conditions, when the error between the actual angle of the wing corresponding to the feature points and the required angle meets the preset error threshold, the feature point detection at the zero position of the wing is first performed, that is, the image acquisition module first acquires a picture at the zero position of the wing, and then all feature points on the surface of the wing are selected through manual interaction to obtain the integer pixel position of each feature point corner. Subsequently, in a specified search window, the feature point corner position is accurately refined from the integer pixel level to the sub-pixel level using the image gray gradient and the iterative least squares optimization, and a small range of image regions centered on the feature point corner are extracted as template images for subsequent matching.

[0083] In the image subsequently acquired by the image acquisition module, based on the template matching algorithm, a search area with a certain radius is set around the initial feature point corner as a reference. For each pixel point in the search area, an image region with the same size as the template image centered on the pixel point is taken as a candidate target, and similarity calculation is performed with the template image, so as to obtain the similarity value of each pixel point, and finally generate a matching score map. Subsequently, the position with the highest similarity is selected from the score map to preliminarily determine the integer pixel coordinates of the feature point corner. Further, a fitting window is constructed in the local high-similarity region of the matching score map, and a quadratic surface fitting method is used to model the similarity distribution, so as to accurately estimate the maximum matching position and realize sub-pixel level matching accuracy. Finally, the initial reference feature point corner coordinates are updated to the coordinates of the pixel point with the highest score in the current frame, for matching in the next frame.

[0084] Each frame of image can obtain the sub-pixel level image coordinates of all feature point corners through the feature point detection and matching module, and then obtain the world coordinates of all feature point corners through three-dimensional reconstruction in the three-dimensional reconstruction and deformation calculation module, and then perform deformation calculation using the obtained world coordinates of the feature point corners.

[0085] In particular, by determining the confidence of the feature points, it is determined whether the feature points are valid; when the confidence of the feature points exceeds the confidence threshold requirement, the feature points are lost, by determining the confidence of the feature points, it is determined whether the feature points are valid, when the feature points are lost due to external disturbance, a motion state prediction method based on Kalman filtering is used to update the position of the feature points and extrapolate the trajectory, and the updated feature points are obtained.

[0086] The updated feature points are detected and tracked by template matching, and after obtaining the sub-pixel level image coordinates of all the updated feature points, three-dimensional reconstruction and deformation calculation are performed, and the changes of the sweepback angle and the span of the wing are obtained in real time.

[0087] The displacement visualization module is used to convert the feature point displacement and wing shape parameters output by the visual online monitoring module into graphical data and display them in real time in the form of dynamic curves, so as to realize intuitive and visual monitoring of the wing deformation process.

[0088] The serial communication module is used to realize data interaction between the visual online monitoring module and the control execution module through serial communication.

[0089] The multi-sensor fusion module is used to perform timestamp alignment and synchronization processing on the changes of the sweepback angle and the span of the wing when the vision is invalid and the sweepback angle and the span of the wing when the vision is normal, and then perform multi-source information fusion to obtain the state estimation value of the sweepback angle and the span of the wing. The fusion design can effectively suppress the random noise and systematic deviation caused by a single sensor, and improve the stability and reliability of the state estimation.

[0090] The encoder is used to record the number of rotations of the stepping motor and the steering engine, and the theoretical rotation angle of the inner wing segment of the wing and the stretching change amount of the outer wing segment relative to the inner wing segment can be calculated respectively.

[0091] The stepping motor can be replaced by any linear output device such as a linear push rod, and the encoder can be any sensor that records the output amount of the linear output device.

[0092] The control execution module includes control instructions and a variable wing; the state estimation value, the current flight attitude information of the aircraft, and the error between the actual angle of the wing and the required angle are taken as the inputs of the fuzzy PID controller, the error is identified and corrected, the sweepback angle and the span of the aircraft in different flight stages are adaptively adjusted, and the corresponding control instructions are generated (when it is identified that the aircraft is in the climbing state, the control instructions of large sweepback angle and small span are generated); the variable wing includes a linear motion unit and a rotary motion unit; the linear motion unit is used to drive the rocker arm to realize variable sweepback according to the control instructions of the control execution module, and a stepper motor is used to drive a lead screw to drive the variable wing to rotate around the wing root to realize variable sweepback motion. The rotary motion unit is used to realize variable span according to the control instructions of the control execution module, and a continuous rotary rudder is used to drive a steel wire rope to drive the outer wing segment to stretch or contract along the wing span direction to realize span change.

[0093] The control execution module generates control instructions according to the flight attitude information measured by the attitude measurement module, adopts a fuzzy PID controller, takes the flight attitude information obtained by the IMU as the auxiliary input of the fuzzy controller, dynamically adjusts the PID parameters k p , k i , k d , realizes adaptive fuzzy PID control of the attitude, and stops until the error between the actual angle of the wing and the required angle meets the error threshold.

[0094] When it is detected that the error between the actual angle of the wing and the required angle of the feature points caused by external disturbance exceeds the preset error threshold, a visual failure smooth switching mechanism based on the confidence degree of real-time acquisition of the changes of the sweepback angle and the span of the wing is used to determine the position update and trajectory extrapolation of the feature points, and the updated feature points are obtained.

[0095] The visual failure smooth switching mechanism includes a visual confidence determination unit, a prediction update unit, and a switching execution unit; the visual confidence determination unit determines whether the visual data is effective based on the number of feature points, the matching residual, and the confidence threshold; when the visual feature points are lost due to external interference (light change or local occlusion), the prediction update unit uses a motion state prediction method based on Kalman filtering to update the position and extrapolate the trajectory of the visual feature points, to obtain the updated feature points to maintain continuous observation; and the updated feature points are sequentially subjected to three-dimensional reconstruction and deformation calculation to real-time acquire the changes of the sweepback angle and the span of the wing.

[0096] The visual failure smooth switching mechanism is responsible for processing the stability of the lifting system in complex environments such as light change, cloud occlusion, and smoke interference.

[0097] The visual online measurement module designed by the application adopts a non-contact visual measurement method to make up for contact measurement methods such as strain gauges and accelerometers, can observe the full-field deformation without affecting the airfoil structure, and is simple in structure and convenient to maintain.

[0098] The variant aircraft wing shape sensing and control system designed by the application can realize real-time monitoring of the wing deformation process and visualization of feature point displacement.

[0099] Based on the Kalman filtering algorithm, the wing sweepback angle and span length state variables obtained by the sensor and the change variables of the estimated wing sweepback angle and span length are time-stamped, aligned and synchronized, and then multi-source information fusion is performed, a control-oriented wing aerodynamic shape parameter calculation model is established, and stable estimation of the span length and sweepback angle parameters can be realized.

[0100] The integrated visual failure smooth switching mechanism can improve the stability of vision in complex environments such as light changes, cloud cover, smoke interference, etc.

[0101] According to the flight state information of the aircraft, the wing shape is automatically adjusted by the fuzzy PID controller until the error between the actual angle of the wing and the required angle meets the error threshold, so that stable estimation of the span length and sweepback angle parameters can be realized, and the aerodynamic efficiency and task adaptability of the aircraft are improved.

[0102] The above is only a preferred specific embodiment of the application, but the protection scope of the application is not limited thereto, any skilled person in the art can make equivalent replacement or change according to the technical scheme and inventive concept of the application within the technical range disclosed by the application, which should be covered within the protection scope of the application.

[0103] In addition, all technical and scientific terms used by the application have the same meaning as generally understood by those skilled in the art to which the application belongs, unless otherwise specified. All documents mentioned in the specification are incorporated by reference to disclose and describe the methods related to the documents. In the event of any conflict with any incorporated document, the content of the specification shall prevail.

Claims

1. A method for sensing and controlling the wing shape of a morphing aircraft, characterized in that, Includes the following steps: The positions of preset feature points on the inner and outer wing sections of the variant wing are obtained to determine the actual wing angle; the sweep angle and span of the wing are obtained through sensors mounted on the aircraft's rotation axis. When the error between the actual wing angle and the required angle exceeds the preset error threshold, the feature point becomes visually ineffective. The motion state of the feature point is predicted by Kalman filtering to obtain the updated feature point. The updated feature point is then subjected to three-dimensional reconstruction and deformation calculation in sequence, and the changes in the wing sweep angle and span are estimated. After aligning and synchronizing the state variables and changes of the wing sweep angle and span with timestamps and then fusing multi-source information, the state estimates of the wing sweep angle and span are obtained. The system acquires the current flight attitude information of the aircraft; using the state estimate, the current flight attitude information of the aircraft, and the error between the actual wing angle and the required angle as inputs to the controller, it adaptively adjusts the sweep angle and span until the error between the actual wing angle and the required angle meets the error threshold.

2. The method for sensing and controlling the wing shape of a morphing aircraft according to claim 1, characterized in that, The process of obtaining the positions of preset feature points on the inner and outer wing sections of the variant wing to determine the actual wing angle specifically includes: Extract the center coordinates of feature points at the zero-point position of the wing, acquire the first frame of the zero-point position image, and select all feature points on the wing surface through manual interaction; Using any feature point corner as a reference, a search area of ​​a certain radius is set around it. The similarity is calculated point by point through a sliding template to generate a matching score map. The position with the highest similarity in the matching score map is selected to determine the sub-pixel coordinates of the feature point corner. Based on the sub-pixel coordinates of the feature point corner points, a coordinate measuring machine is used to obtain the three-dimensional coordinates of the feature point in the wing coordinate system. After performing coordinate transformation on the three-dimensional coordinates, straight line fitting is performed on the feature points of the inner and outer wing sections respectively to obtain the corresponding straight line equations representing the directions of the inner and outer wing sections. By determining the included angle between the two straight lines, the actual angle of the wing is obtained.

3. The method for sensing and controlling the wing shape of a morphing aircraft according to claim 2, characterized in that, When the error between the actual wing angle and the required angle exceeds a preset error threshold, the feature point experiences visual failure. Kalman filtering is then used to predict the motion state of the feature point, resulting in an updated feature point. Specifically, this includes: Obtain the image of the feature point locations for each frame; By establishing a mapping relationship between the actual wing angle and the feature point position, feature point detection and matching are performed on the image of each frame of feature point position to obtain the sub-pixel level image coordinates of all feature point corners. Based on the subpixel-level image coordinates of all feature point corners, the confidence level of the feature points is determined to determine whether the feature points have experienced visual failure. When the confidence level of a feature point exceeds the confidence threshold, the feature point becomes visually ineffective. A motion state prediction method based on Kalman filtering is used to update the position and track the trajectory of the feature point that has become visually ineffective, and the updated feature point is obtained.

4. The method for sensing and controlling the wing shape of a morphing aircraft according to claim 3, characterized in that, The process of sequentially performing 3D reconstruction and deformation calculations on the updated feature points to obtain real-time changes in the wing's sweep angle and span specifically includes: Obtain the subpixel-level image coordinates of all feature point corners after the update, and obtain the world coordinates of all feature point corners through 3D reconstruction; Based on the updated world coordinates of all feature points and corner points, the feature points of the inner wing section and the outer wing section are evenly distributed in two rows. Each row of the inner wing section includes more than two feature points; each row of the outer wing section includes at least one feature point. Taking a certain feature point of a certain row of the selected inner wing section as a reference point, all feature points are projected onto the tangent plane of the wing surface where the reference point is located. The tangent plane is the z-axis plane. In the tangent plane, with the reference point as a straight line, a vector A is obtained by fitting a straight line to all feature points of the inner wing segment on the straight line; a vector B is obtained by fitting a least-squares straight line to all feature points of the other row of the inner wing segment; vectors A and B are averaged and normalized to obtain the wing's direction vector C along the wingspan direction; by calculating the angular change of the direction vector C, the change in the wing's sweep angle is obtained. The distance change of each feature point of the outer wing segment relative to all feature points of the inner wing segment on the tangent plane of the reference point is determined and averaged to obtain the amount of expansion and contraction of the outer wing segment relative to the inner wing segment, i.e., the amount of span change.

5. The method for sensing and controlling the wing shape of a morphing aircraft according to claim 1, characterized in that, The controller uses the state estimate, the aircraft's current flight attitude information, and the error between the actual and required wing angles as inputs to adaptively adjust the sweep angle and span until the error between the actual and required wing angles meets an error threshold. Specifically, this includes: The error between the actual and required wing angles, the state estimate, and the aircraft's flight attitude information are used as inputs to the fuzzy PID controller. When the error between the actual and required wing angles exceeds a preset error threshold, the PID parameter k is dynamically adjusted. p k i k d : When the aircraft's current flight attitude is in a rapid climb or dive phase, the fuzzy PID controller increases k... d and reduce k i The output control command is a large sweep angle and a small span; When the aircraft is currently in the cruise phase, the fuzzy PID controller increases k... i The output control command is a small sweep angle and a large span.

6. The method for sensing and controlling the wing shape of a morphing aircraft according to claim 1, characterized in that, The process of aligning and synchronizing the state variables and changes of the wing sweep angle and span using timestamps, followed by multi-source information fusion to obtain state estimates of the wing sweep angle and span, specifically includes: Align the wing sweep angle and span state variables and changes to a unified timestamp, and use linear interpolation or spline interpolation to process the asynchronous data to obtain the state variables and changes after timestamp alignment and synchronization. The state variables and changes after timestamp alignment and synchronization are fused with multi-source information, and the state prediction of the wing sweep angle and span is performed by the Kalman filter algorithm to obtain the state estimates of the wing sweep angle and span.

7. The method for sensing and controlling the wing shape of a morphing aircraft according to claim 1, characterized in that, The current flight attitude information of the aircraft is obtained by encoding through sensors mounted on the aircraft's rotation axis, including pitch angle, roll angle, angular velocity, and acceleration.

8. A wing shape sensing and control system for a morphing aircraft, characterized in that, include: The attitude measurement module is used to acquire the current flight attitude information of the aircraft; The visual online monitoring module is used to acquire the positions of preset feature points on the inner and outer wing sections of the variant wing to determine the actual wing angle; it acquires the wing's sweep angle and span state variables through sensors mounted on the aircraft's rotation axis; when the error between the actual wing angle and the required angle exceeds a preset error threshold, the feature points experience visual failure, and the motion state of the feature points is predicted using Kalman filtering to obtain updated feature points; the updated feature points are then subjected to 3D reconstruction and deformation calculations to estimate the changes in the wing's sweep angle and span. The multi-source information fusion module is used to align and synchronize the state variables and changes of the wing sweep angle and span after time stamping, and then perform multi-source information fusion to obtain the state estimates of the wing sweep angle and span. The control execution module is used to adaptively adjust the sweep angle and span using the state estimate, the current flight attitude information of the aircraft, and the error between the actual wing angle and the required angle as inputs to the controller, until the error between the actual wing angle and the required angle meets the error threshold.

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