A wind disturbance resisting control method and system for a stealth multi-rotor unmanned aerial vehicle

Abstract

The application discloses a wind interference resisting control method and system for a stealth multi-rotor unmanned aerial vehicle, and relates to the technical field of unmanned aerial vehicle flight control. The method comprises the following steps: constructing a dynamic model containing the aerodynamic characteristics of a stealth fairing, taking the additional aerodynamic force and the additional aerodynamic moment suffered by the stealth fairing in a wind field as independent items; extracting the aerodynamic parameters of the stealth fairing under different equivalent incoming airflow wind speeds, attack angles and sideslip angles, and constructing a wind load mathematical mapping model; obtaining the flight data of the unmanned aerial vehicle, and calculating the current additional aerodynamic force and the additional aerodynamic moment in combination with the wind load mathematical mapping model; converting the current additional aerodynamic force and the additional aerodynamic moment into feedforward control quantities; calculating feedback control quantities, and converting the feedforward control quantities and the feedback control quantities into flight control instructions. The application overcomes the severe aerodynamic side effects brought by the stealth fairing while completely retaining the extremely low radar detectability of the unmanned aerial vehicle, and improves the flight stability and the trajectory tracking accuracy in a complex wind field.

Description

Technical Field

[0001] This invention relates to the field of unmanned aerial vehicle (UAV) flight control technology, and specifically to a wind-damping control method and system for stealth multi-rotor UAVs with fairings. Background Technology

[0002] When a drone is in operation, its exposed motors, propellers, battery packs, flight control modules, and complex cable layout constitute multiple strong radar scattering sources, resulting in a significantly high radar cross-section (RCS), making it extremely easy for radar systems to detect and track. Therefore, there is an urgent need to improve the stealth performance of multi-rotor drones.

[0003] To achieve effective stealth, existing technologies attempt to transfer the stealth design concepts of fixed-wing UAVs to multi-rotor platforms, such as using radar-absorbing materials, shape modification, and structural shielding. However, due to the highly dispersed power systems and compact airframe of multi-rotor UAVs, traditional methods are difficult to apply directly. In recent years, a new type of stealthy multi-rotor UAV has achieved physical shielding of major scattering sources such as motors and rotors by integrating a fairing with a wedge structure and swept-back wrapping on the outside of the airframe. This significantly reduces the RCS of typical radar bands such as X and Ku, providing a feasible path for the systematic stealth of multi-rotor platforms.

[0004] However, this stealth-optimized design brings significant aerodynamic side effects. The large-area non-streamlined structure of the fairing is equivalent to an additional asymmetric airfoil in the airflow. Under forward flow conditions, especially in complex wind fields such as crosswinds, it is highly susceptible to boundary layer separation, vortex shedding, and unsteady aerodynamic forces, generating severe and nonlinear additional lift and moment disturbances. These disturbances are highly time-varying and nonlinear. Traditional PID control algorithms based on linear models and error feedback suffer from phase lag and do not incorporate the additional aerodynamic loads introduced by the fairing into the control model. This results in system response lag, insufficient control bandwidth, and difficulty in effectively suppressing gust interference, often leading to altitude fluctuations, attitude oscillations, and even uncontrolled rollovers.

[0005] Therefore, while achieving radar stealth, ensuring the flight stability of UAVs in complex dynamic wind fields has become a key bottleneck for the practical application of this type of stealthy multi-rotor UAV. Summary of the Invention

[0006] The purpose of this application is to overcome the technical defects of existing stealth multirotor UAVs, such as severe aerodynamic disturbances and poor wind resistance caused by adding stealth fairings, and to provide a control method for stealth multirotor UAVs to resist wind disturbances. The specific steps are as follows: A method for wind disturbance control of a stealth multi-rotor unmanned aerial vehicle (UAV), the UAV including a stealth fairing, comprising the following steps: A dynamic model incorporating the aerodynamic characteristics of the stealth fairing is constructed, and the additional aerodynamic forces and moments experienced by the stealth fairing in the wind field are explicitly introduced as independent terms. Extract the aerodynamic parameters of the stealth fairing under different equivalent incoming wind speeds, angles of attack and sideslip angles, and construct a mathematical mapping model of wind load; Acquire flight data during the flight of the UAV, and calculate the current additional aerodynamic force and additional aerodynamic torque based on the current flight data and the wind load mathematical mapping model; The current additional aerodynamic forces and additional aerodynamic torques are converted into feedforward control variables; total disturbance data is acquired, and feedback control variables are generated based on the total disturbance data; the feedforward control variables and feedback control variables are then converted into flight control commands.

[0007] This invention also proposes a wind-damping resistance control system for a stealthy multi-rotor unmanned aerial vehicle, comprising: The main processor is used to implement the wind disturbance control method for the stealth multi-rotor UAV described above and to issue flight control commands. An IO processor, installed in the drone body, receives flight control commands transmitted from the main processor, and sends drive commands to the drone's brushless motors and commands to adjust the speed of the propellers according to the flight control commands. The data acquisition unit is used to acquire the absolute ground speed, airspeed, and attitude information of the UAV during flight.

[0008] Beneficial effects: The wind disturbance control method proposed in this invention, which is oriented towards stealth configuration characteristics, can sense, model and compensate for complex aerodynamic disturbances caused by fairings in real time, and realize feedforward compensation and robust feedback control of wind loads. Thus, while ensuring low observability, it maintains high-precision attitude stability and trajectory tracking capability. This control method integrates aerodynamic modeling, disturbance observation and adaptive control strategy, breaks through the limitations of traditional control framework, and provides technical support for the coordinated optimization of stealth and flight performance. Attached Figure Description

[0009] Figure 1 This is a flowchart of the overall wind resistance control method; Figure 2 This is the overall block diagram of the wind disturbance resistance control system; Figure 3 Detailed block diagram of the wind disturbance resistance control system; Figure 4 This is a three-dimensional structural diagram of the stealth multi-rotor UAV of this application; Figure 5 This is a top view of the stealth multi-rotor unmanned aerial vehicle of this application.

[0010] Explanation of the labels in the diagram: 1-Lever arm, 2-Center plate upper plate, 3-Center plate lower plate, 4-Stealth fairing, 5-Propeller, 6-Motor, 7-Battery, 8-Flight control terminal, 9-Multi-sensor fusion navigation unit, 10-RTK high-precision antenna, 11-Data link, 12-Wedge shape, 13-Sweep shape. Detailed Implementation

[0011] To make the objectives, technical solutions, and advantages of this application clearer, the wind resistance control method for a stealth multi-rotor unmanned aerial vehicle (UAV) proposed in this application will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only for explaining this application and are not intended to limit this application. The descriptions of steps 100, 200, etc., herein are not limited by an absolute temporal relationship. Any simple modifications or substitutions based on the substance of this application fall within the protection scope of this application.

[0012] Combination Figure 4 and Figure 5 As shown in the figure, the hardware platform of the stealth multi-rotor UAV provided in this embodiment mainly includes: an airframe, and a stealth fairing 4 fixed to the outside of the airframe. The body includes several lever arms 1, a central plate upper plate 2, and a central plate lower plate 3. Several lever arms are fixedly connected at one end to the stealth fairing, and at the other end are fixed a propeller 5, a center plate upper plate 2, and a center plate lower plate 3; The upper plate 2 and lower plate 3 of the center plate are the main control boards, including motors 6, batteries 7, flight control terminals 8, multi-sensor fusion navigation units 9, RTK high-precision antennas 10, and data links 11. The motors are specifically brushless motors.

[0013] The stealth radome 4 includes a wedge shape 12 and a swept-back shape 13. The wedge and swept-back shapes are stealth structural design methods based on classical electromagnetic scattering theory, which can reduce the radar cross-section (RCS).

[0014] Furthermore, its stealth fairing 4 is coated with radar-absorbing paint, and the fuselage and stealth fairing 4 are made of lightweight composite materials. The stealth fairing 4 is used to shield the motor, propeller, battery and flight control module, so that its average radar cross-section in the X and Ku bands in the head-on direction is less than 0.001㎡, and effectively avoids the propeller micro-Doppler effect.

[0015] This embodiment and accompanying drawings further disclose a cross-shaped symmetrical structure of the body. The four right-angled regions of the cross shape are prone to forming a corner reflector effect, resulting in a high RCS peak at certain specific incident angles.

[0016] As a preferred option, the flight control terminal 8 features a dual-processor architecture.

[0017] Based on the aforementioned hardware platform, this embodiment provides a wind-resistant control method for a stealthy multi-rotor unmanned aerial vehicle (UAV), such as... Figures 1-3 This includes the following steps: Step 100: Construct a dynamic model that includes the aerodynamic characteristics of the stealth fairing, and explicitly introduce the additional aerodynamic force and additional aerodynamic torque experienced by the stealth fairing in the wind field as independent terms. Step 200: Extract the aerodynamic parameters of the stealth fairing under different equivalent incoming wind speeds, angles of attack and sideslip angles, and construct a mathematical mapping model of wind load; Step 300: Acquire flight data during the flight of the UAV, and calculate the current additional aerodynamic force and additional aerodynamic torque based on the current flight data and the wind load mathematical mapping model. Step 400: Convert the current additional aerodynamic force and additional aerodynamic torque into feedforward control quantities; Step 500: Obtain total disturbance data, generate feedback control quantity based on total disturbance data, and convert feedforward control quantity and feedback control quantity into flight control commands.

[0018] Regarding step 100, based on the rigid body dynamics model of a traditional multi-rotor UAV, the additional wind load on the stealth fairing 4 in a complex wind field is explicitly introduced as an independent term, namely the additional aerodynamic force and additional aerodynamic torque on the stealth fairing 4.

[0019] In the body coordinate system of the UAV, the translational dynamics equations and rotational dynamics equations are established, where equation (1) is the translational dynamics equation and equation (2) is the rotational dynamics equation: (1); (2); Where m is the total mass of the UAV, V is the linear velocity vector of the UAV in the body coordinate system, and Ω is the angular velocity vector of the UAV. A dot “·” above the symbols for V and Ω indicates the first derivative of the physical quantity with respect to time t, i.e., the rate of change. F thrust F is the total thrust generated by the drone's power system. gravity For gravity, F wind Additional aerodynamic forces introduced for the stealth fairing, where J is the rotational inertia matrix, and M... thrust To control the torque, M gyro M is the gyroscopic torque. wind To provide additional aerodynamic torque.

[0020] Among them, the additional aerodynamic force is mainly the additional lift along the Z-axis, and the additional aerodynamic torque is mainly the pitching torque and the rolling torque.

[0021] For step 200, since the nonlinear aerodynamic characteristics are difficult to express analytically, this embodiment first performs offline simulation analysis on the swept-back shape 13 and wedge shape 12 of the stealth fairing 4 using computational fluid dynamics (CFD) software.

[0022] The three-dimensional model of the stealth fairing was constructed using computational fluid dynamics software. The aerodynamic parameters of the stealth fairing under different equivalent incoming wind speeds, angles of attack, and sideslip angles were extracted, and a mathematical mapping model of the additional aerodynamic forces and additional aerodynamic moments was established.

[0023] At different equivalent incoming air velocity V W Sweep calculations are performed at angles of attack α and sideslip angle β to extract the corresponding aerodynamic parameters. Specifically, a dimensionless mathematical mapping model for the additional aerodynamic forces and moments is established: (3); (4); Among them, F wind_z To add lift, M wind_θ For the additional pitching moment, ρ is the air density, S is the reference frontal area of ​​the stealth fairing, and c is the reference aerodynamic chord. L (α, β) represents the additional lift coefficient of the stealth fairing, C m (α, β) are the additional pitching moment coefficients of the stealth fairing.

[0024] The simulation process is implemented using software; the main steps are disclosed below: Step 201: Construct a 3D model of the stealth fairing on the computer; Step 202: Mesh the entire model and add boundary layer meshes at the boundaries; Step 203, Set the equivalent incoming air velocity V W =10m / s (for example), change the angle α from -20° to +20°, and β from -20° to +20°.

[0025] Step 204: Using a suitable turbulence model, the CFD software calculates the forces acting on the stealth fairing at each angle, primarily focusing on the additional lift F. wind_z Additional pitching moment M wind_θ .

[0026] Step 205: Extract the corresponding aerodynamic parameters and use formulas (3) and (4) to back-calculate the additional lift coefficient and additional pitching moment coefficient.

[0027] Step 206 yields a data table showing the variation of the additional lift coefficient and the additional pitching moment coefficient with α and β.

[0028] The specific angles of α and β are adjusted according to the actual simulation needs, and the content disclosed herein is for implementation reference only.

[0029] In practice, it has been found that the stealth fairing has a relatively small impact on the X-axis (drag) and Y-axis (side force). Alternatively, to simplify calculations, the simulation only models the most critical additional lift F. wind_z and additional pitching moment M wind_θ In the actual flight calculation process, the forces in unimportant directions are set to 0. If it is necessary to calculate the forces in other directions, the calculation can be performed according to the simulation process described above.

[0030] For step 300, the flight data includes the absolute ground speed, airspeed and attitude information of the UAV during flight; Step 301: Calculate the current three-dimensional wind speed using the velocity triangle vector relationship based on the absolute ground speed, airspeed, and attitude information; Step 302: Construct an attitude matrix based on attitude information, convert the current three-dimensional wind speed to the body coordinate system, and calculate the relative angle of attack and sideslip angle in real time; Step 303: Input the current three-dimensional wind speed, relative angle of attack, and sideslip angle into the wind load aerodynamic mapping model to calculate the current additional aerodynamic force and additional aerodynamic torque.

[0031] During actual drone flight, real-time wind field identification relies on multiple sensors. Data is collected through a multi-sensor fusion navigation unit 9 and an RTK high-precision antenna 10. The sensor fusion navigation unit 9 includes sensors such as an IMU and a magnetic compass.

[0032] By filtering out noise and errors using the EKF filtering algorithm, a more accurate and reliable absolute ground speed V for the UAV is obtained than that obtained using a single sensor. g Attitude information includes roll, pitch, and yaw angles.

[0033] Among them, the IMU high-frequency response, the RTK high-precision antenna 10 achieve high-precision absolute positioning, and the magnetic compass orientation complements each other's weaknesses. Combined with the airborne airspeed meter, the current airspeed vector V is obtained. a The current three-dimensional wind speed is calculated using the velocity triangle vector relationship. : ; Construct an attitude matrix based on the currently acquired attitude information, and include the current three-dimensional wind speed. The vector representation is converted to the body coordinate system, and the relative angle of attack α and sideslip angle β are calculated in real time. The calculated values ​​are then... Substituting α and β into the established mathematical mapping model formulas (3) and (4), the additional lift F acting on the stealth fairing is calculated in real time. wind_z and additional pitching moment Mwind_θ .

[0034] In this embodiment, a dual-processor configuration is used, wherein the main processor of the flight control terminal 8 calculates in real time the additional lift F currently experienced by the stealth fairing. wind_z and additional pitching moment M wind_θ With additional lift F wind_z and additional pitching moment M wind_θ Additional aerodynamic forces F introduced by constructing a stealth fairing wind and additional aerodynamic torque M wind .

[0035] ; ; If the rolling moment was calculated during implementation, then the calculated rolling moment should be placed in M. wind The first component is the X-axis. Other components are constructed using the same principle.

[0036] With the construction of additional aerodynamic force F wind and additional aerodynamic torque M wind Substituting the disturbance term into formulas (1) and (2) for feedforward compensation, the current additional aerodynamic force and additional aerodynamic torque are converted into feedforward control quantities.

[0037] As a preferred embodiment, the main processor is used to perform feedforward control calculation and feedback control calculation at a frequency greater than 100Hz.

[0038] Regarding step 400, in order to solve the problem of lag in response of traditional PID controllers, this application adopts a composite control strategy that combines feedforward compensation and active disturbance rejection control (ADRC), and executes it efficiently on a dual-processor heterogeneous architecture.

[0039] Step 401: Convert the current additional aerodynamic force and additional aerodynamic torque into feedforward control quantities, and add the feedforward control quantities to the total control quantity. Specifically, the additional lift F calculated in real time wind_z and additional pitching moment M wind_θ As a known feedforward control variable, it is converted into the desired motor speed compensation variable ΔU to counteract aerodynamic forces based on the UAV's control allocation matrix. This feedforward branch adds the feedforward control variable (feedforward compensation variable) to the total control variable, responding in advance to external wind loads and eliminating the main systematic deviations caused by the large windward area of ​​the stealth fairing.

[0040] Step 500: Obtain total disturbance data and generate feedback control quantity based on total disturbance data; The total disturbance data includes: the 3D model error of the stealth fairing (errors existing in CFD modeling), residual disturbances not covered by the wind load aerodynamic mapping model, random high-frequency disturbances from gusts, and perturbations of internal parameters of the UAV control system.

[0041] An active disturbance rejection controller (ADRC) was designed in the main processor and closed-loop compensation was implemented. Step 501: Configure the tracking differentiator (TD) to perform smooth transition processing on the input attitude command θ and altitude command H respectively. The attitude channel outputs a smooth tracking signal v1 and its differential signal v2, and the altitude channel outputs a smooth tracking signal v 1_H and its differential signal v 2_H .

[0042] Step 502: Configure the Extended State Observer (ESO) to estimate the system's output state z1 (including attitude and altitude estimation), unmeasurable state z2 (including angular velocity or vertical velocity estimation), and total disturbance z3 in real time based on the actual output parameters and control input parameters. The total disturbance z3 includes the three-dimensional model error of the stealth fairing, residual disturbances not covered by the wind load aerodynamic mapping model, random high-frequency disturbances from gusts, and perturbations of internal parameters of the UAV control system.

[0043] Step 503: Calculate the tracking error by subtracting the smoothed tracking signal and differential signal output by TD from the actual state estimated by ESO to obtain the attitude angle error e1=v1-z1, attitude angular velocity error e2=v2-z2, and altitude error e 1_H =v 1_H -z 1_H and altitude speed error e 2_H =v 2_H -z 2_H .

[0044] Step 504: Based on the above tracking error, calculate the basic control quantity u0 using the nonlinear state error feedback control law (NLSEF).

[0045] Step 505, (Disturbance Compensation): Compensate for the estimated total disturbance z3, that is, eliminate the total disturbance z3 estimated by ESO from the feedforward control quantity, and divide it by the nominal control gain value b0 to obtain the ADRC feedback control quantity U. ADRC = (u0 - z3) / b0.

[0046] The main processor will issue the final control instructions, U total =U ADRC +△U is sent to the IO processor of the flight control terminal 8. As a highly reliable low-level control node, the IO processor accurately converts the control commands into PWM signals to drive the brushless motor 6 and dynamically adjust the speed of each propeller 5.

[0047] Through the specific implementation methods described above, this application transforms the aerodynamic side effects of the stealth fairing from unknown interference to partially known interference (feedforward control variables), combined with the remaining observation interference (ADRC observation compensation). The dual-processor architecture ensures that high-frequency aerodynamic calculations and control outputs do not interfere with each other. This application not only endows stealth multi-rotor UAVs with excellent gust resistance and attitude control accuracy, but also perfectly accommodates the streamlined appearance sacrificed for stealth, achieving system-level synergy between low observability and high stable flight performance.

[0048] Further disclosure of a wind-damping resistance control system for a stealth multi-rotor unmanned aerial vehicle, such as Figure 2 As shown, it includes: The main processor is used to implement the wind disturbance control method for the stealth multi-rotor UAV and to issue flight control commands. An IO processor, installed in the drone body, receives flight control commands transmitted from the main processor, and sends drive commands to the drone's brushless motors and commands to adjust the speed of the propellers according to the flight control commands. The data acquisition unit is used to acquire the absolute ground speed, airspeed, and attitude information of the UAV during flight.

[0049] The system, as shown in the figure, includes a main processor and an I / O processor. The processor connects to the acquisition end, the execution end, and the data link, and receives data from the acquisition end.

[0050] The data acquisition unit includes a multi-sensor fusion navigation unit, an RTK high-precision antenna, and an airborne airspeed indicator. The data link and ground communication module form a data transmission channel, enabling air-to-ground communication. The I / O processor connects to the execution unit, transmitting flight control commands to the brushless motors.

[0051] A further disclosure is a computer-readable storage medium storing a computer program that, when executed by a computer, enables the method described above. Exemplarily, the computer program can be divided into one or more modules / units, one or more of which are stored in memory and executed by a processor. Data I / O interface transmission is performed via input and output interfaces to complete the present invention. One or more modules / units can be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program in a computer device. The computer device can be a desktop computer, laptop, handheld computer, or cloud server, etc. The computer device may include, but is not limited to, memory and processor. Those skilled in the art will understand that this embodiment is merely an example of a computer device and does not constitute a limitation on the computer device. It may include more or fewer components, or combine certain components, or different components. For example, the computer device may also include an input device, network access device, bus, etc. The processor unit can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0052] Memory can be an internal storage unit of a computer device, such as a hard drive or RAM. Memory can also be an external storage device of a computer device, such as a plug-in hard drive, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card. Furthermore, memory can include both internal and external storage units of a computer device. Memory is used to store computer programs and other programs and data required by the computer device. Memory can also be used for temporary storage on output devices. The aforementioned storage media include various media that can store program code, such as USB flash drives, portable hard drives, Read-Only Memory (ROM), Random Access Memory (RAM), discs, or optical discs.

Claims

1. A method for wind disturbance control of a stealth multi-rotor unmanned aerial vehicle (UAV), wherein the stealth multi-rotor UAV includes a stealth fairing, characterized in that, Includes the following steps: A dynamic model incorporating the aerodynamic characteristics of the stealth fairing is constructed, and the additional aerodynamic forces and moments experienced by the stealth fairing in the wind field are explicitly introduced as independent terms. Extract the aerodynamic parameters of the stealth fairing under different equivalent incoming wind speeds, angles of attack and sideslip angles, and construct a mathematical mapping model of wind load; Acquire flight data during the flight of the UAV, and calculate the current additional aerodynamic force and additional aerodynamic torque based on the current flight data and the wind load mathematical mapping model; The current additional aerodynamic forces and additional aerodynamic torques are converted into feedforward control variables; total disturbance data is acquired, and feedback control variables are generated based on the total disturbance data; the feedforward control variables and feedback control variables are then converted into flight control commands.

2. The method according to claim 1, characterized in that, The flight data includes the absolute ground speed, airspeed, and attitude information of the UAV during flight. Based on absolute ground speed, airspeed, and attitude information, the current three-dimensional wind speed is calculated using the velocity triangle vector relationship. An attitude matrix is ​​constructed based on attitude information, and the current three-dimensional wind speed is transformed into the body coordinate system to calculate the relative angle of attack and sideslip angle in real time. Input the current three-dimensional wind speed, relative angle of attack, and sideslip angle into the wind load aerodynamic mapping model to calculate the current additional aerodynamic force and additional aerodynamic moment.

3. The method according to claim 1, characterized in that, The process of converting the current additional aerodynamic force and additional aerodynamic torque into feedforward control quantities includes: The calculated additional aerodynamic force and additional aerodynamic torque are converted into motor speed compensation for the UAV propeller, and the motor speed compensation is used as the feedforward control quantity.

4. The method according to claim 1, characterized in that, The process involves extracting aerodynamic parameters of the stealth fairing under different equivalent incoming wind speeds, angles of attack, and sideslip angles, and constructing a wind load mathematical mapping model, including: Construct a three-dimensional model of the stealth fairing, which includes a swept-back shape and a wedge shape; Computational fluid dynamics software was used to extract the aerodynamic parameters of the stealth fairing under different equivalent incoming wind speeds, angles of attack, and sideslip angles, and a mathematical mapping model of the additional aerodynamic forces and additional aerodynamic moments was established.

5. The method according to claim 1, characterized in that, The total disturbance data includes: the three-dimensional model error of the stealth fairing, residual disturbances not covered by the wind load aerodynamic mapping model, random high-frequency disturbances from gusts, and perturbations of internal parameters of the UAV control system.

6. The method according to claim 1, characterized in that, The construction of the dynamic model including the aerodynamic characteristics of the stealth fairing involves explicitly introducing the additional aerodynamic forces and moments experienced by the stealth fairing in the wind field as independent terms. This includes: establishing translational and rotational dynamic equations in the UAV's body coordinate system, where equation (1) is the translational dynamic equation and equation (2) is the rotational dynamic equation. （1）； （2）； Where m is the total mass of the UAV, V is the linear velocity vector of the UAV in the body coordinate system, Ω is the angular velocity vector of the UAV, and a dot "·" above the symbols of V and Ω indicates the first derivative of the physical quantity with respect to time t. thrust F is the total thrust generated by the drone's power system. gravity For gravity, F wind Additional aerodynamic forces introduced for the stealth fairing, where J is the rotational inertia matrix, and M... thrust To control the torque, M gyro M is the gyroscopic torque. wind To provide additional aerodynamic torque.

7. The method according to claim 4, characterized in that, The establishment of the mathematical mapping model for the additional aerodynamic force and the additional aerodynamic moment includes the establishment of the dimensionless mathematical mapping model for the additional lift and the additional pitching moment, wherein formula (3) is the dimensionless mathematical mapping model for the additional lift and formula (4) is the dimensionless mathematical mapping model for the additional pitching moment. （3）； （4）； Among them, F wind_z To add lift, M wind_θ To add pitch moment, V W The equivalent incoming air velocity is given by ρ, air density is given by S, the reference frontal area of ​​the stealth fairing is given by c, and the reference aerodynamic chord length is given by C. L (α, β) represents the additional lift coefficient of the stealth fairing, C m (α, β) are the additional pitching moment coefficients of the stealth fairing.

8. The method according to claim 1, characterized in that, Also includes: Flight control commands are sent to the IO processor installed on the drone body, and the IO processor is connected to the drone's motors.

9. A wind-damping resistance control system for a stealth multi-rotor unmanned aerial vehicle, characterized in that, include: The main processor is configured to implement the method described in any one of claims 1 to 8, and to issue flight control commands. An IO processor, installed in the drone body, receives flight control commands transmitted from the main processor, and sends drive commands to the drone's brushless motors and commands to adjust the speed of the propellers according to the flight control commands. The data acquisition unit is used to acquire the absolute ground speed, airspeed, and attitude information of the UAV during flight.

10. The system according to claim 9, characterized in that, The main processor is used to perform feedforward control calculation and feedback control calculation at a frequency greater than 100Hz.

11. 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 wind disturbance control method for the stealth multi-rotor unmanned aerial vehicle as described in any one of claims 1 to 8.

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