UAV control method, control device and UAV

Abstract

The present application provides a control method, a control device and a drone for a drone, which are applied to the field of drone control. The control method for a drone includes: obtaining a quad-rotor drone model; constructing a quad-rotor drone model; obtaining a first interference term of the drone within a preset time according to the quad-rotor drone model; obtaining a drone attitude control rate according to the quad-rotor drone model, the first interference term and an adaptive term, so as to control the attitude of the drone, wherein the first interference term includes uncertain interference and external interference of the quad-rotor drone model. By considering multiple interference factors of the drone during flight and effectively controlling the drone within a preset time during the control process, the attitude of the drone can be controlled more accurately and quickly.

Description

Technical Field

[0001] The present application relates to the field of drone control, and more specifically, to a drone control method, a drone control device, and a drone. Background Art

[0002] As a highly flexible and maneuverable aircraft, quad-rotor drones have been widely used in military, logistics, rescue, and environmental monitoring. As a key technology in quad-rotor drone flight control, attitude angle control directly affects the stability and maneuverability of drones. Therefore, how to accurately and quickly control the attitude of drones is a technical problem that needs to be solved urgently. Summary of the invention

[0003] The present application provides a control method, a control device and a drone of a drone, which control the attitude of the drone more accurately and quickly by considering multiple interference factors of the drone during flight and effectively controlling the drone within a preset time during the control process.

[0004] In a first aspect, a control method for a drone is provided, the control method comprising: constructing a quadrotor drone model; obtaining a first interference term of the drone within a preset time according to the quadrotor drone model; obtaining an attitude control rate of the drone according to the quadrotor drone model, the first interference term and an adaptive term to perform attitude control on the drone, wherein the first interference term includes uncertain interference of the quadrotor drone model and external interference.

[0005] Through the technical solution of the embodiment of the present application, by taking into account multiple interference factors of the UAV during flight and effectively controlling the UAV within a preset time during the control process, the attitude of the UAV can be controlled more accurately and quickly, and by adding adaptive items during the attitude control process, the control unit adaptively adjusts the attitude during the adjustment process, so that the attitude of the UAV can be accurately controlled.

[0006] In some possible implementations, obtaining a first interference term within a preset time according to a quad-rotor drone model includes: obtaining the first interference term within a preset time through a sliding mode design according to the quad-rotor drone model.

[0007] Through the technical solution of the embodiment of the present application, by adding a preset time item in the sliding mode design algorithm, that is, by presetting the time, the sliding membrane surface can converge to the desired equilibrium point within a predetermined finite time during the control process, thereby achieving fast and accurate control of the attitude angle of the drone.

[0008] In some possible embodiments, according to the quadrotor drone model, a first interference term within a preset time is obtained through sliding mode design, including: according to the quadrotor drone model, an attitude error is obtained; according to the attitude error, a sliding membrane surface is constructed, wherein the sliding membrane surface is equal to or less than zero within the preset time; according to the sliding membrane surface, the first interference term within the preset time is obtained.

[0009] Through the technical solution of the embodiment of the present application, the sliding membrane surface can converge to the desired equilibrium point within a predetermined finite time during the control process by presetting the time. It can also be expressed as the sliding membrane surface is equal to or less than zero within the preset time, that is, to achieve fast and precise control of the attitude angle of the drone.

[0010] In some possible implementations, the preset time includes a first preset time and a second preset time, and obtaining a first interference term within the preset time according to the synovial surface includes: obtaining the first interference term within the preset time according to a first formula, and the first formula is:

[0011]

[0012] Where e is the attitude error, T c1 is the first preset time, T c2 is the second preset time, and T c1 <T c2 .

[0013] In some possible implementations, the method further includes: obtaining an attitude control rate of the UAV according to a second interference term to perform attitude control on the UAV, wherein the second interference term includes nonlinear interference.

[0014] Through the technical solution of the embodiment of the present application, by taking into account the nonlinear interference terms during the flight of the drone, the attitude control rate of the drone is obtained to accurately control the attitude of the drone.

[0015] In some possible implementations, the attitude control rate of the UAV is obtained according to the second interference term to perform attitude control on the UAV, including: fitting nonlinear interference through a fuzzy logic system.

[0016] In some possible implementations, fitting nonlinear interference through a fuzzy logic system includes: constructing a fuzzy logic system according to a quadrotor drone model to fit the nonlinear interference.

[0017] Through the technical solution of the embodiment of the present application, a fuzzy logic system is constructed according to the quadrotor drone model, and finally a quadrotor drone model with nonlinear interference is obtained.

[0018] In some possible implementations, a fuzzy logic system is constructed according to a quadrotor drone model, including: obtaining an output of the fuzzy logic system according to a second formula, where the second formula is:

[0019]

[0020] Among them, x i is a quad-rotor drone model, i is the number of propellers, is the fuzzy function, is the maximum value of the fuzzy function.

[0021] In some possible implementations, constructing a quad-rotor drone model includes: obtaining a quad-rotor drone model according to a third formula, where the third formula is:

[0022]

[0023] Among them, I x ,I y and I z is the inertia matrix of the x, y and z axes, μ θ and μ ψ are the rolling moment, yaw moment and pitch moment, l is the distance from the propeller axis to the center of mass of the UAV, θ and ψ are the roll angle, yaw angle, and pitch angle.

[0024] In some possible implementations, the adaptive term is determined according to a fuzzy logic system.

[0025] In some possible implementations, the adaptive term is determined according to a fuzzy logic system, including: determining the adaptive term according to a fourth formula, the fourth formula being:

[0026] Z=ΥS T ξ;

[0027] Among them, ξ is the basis function of the fuzzy system.

[0028] In some possible implementations, the method further includes: constructing a Lyapunov function; and performing a boundedness analysis on the attitude control rate of the UAV according to the Lyapunov function.

[0029] Through the technical solution of the embodiment of the present application, by constructing a suitable Lyapunov function, the boundedness analysis of the attitude control rate of the UAV is performed, and the stability analysis of the attitude control rate of the UAV proposed in the present application is performed through the boundedness analysis, and the convergence of the finite time is analyzed.

[0030] In a second aspect, a control device for a drone is provided, the control device comprising: a construction unit for constructing a quad-rotor drone model; a processing unit for obtaining a first interference term within a preset time according to the quad-rotor drone model; the processing unit is also used to obtain an attitude control rate of the drone according to the quad-rotor drone model, the first interference term and an adaptive term, so as to perform attitude control on the drone, wherein the first interference term includes uncertain interference of the quad-rotor drone model and external interference.

[0031] In a third aspect, a control device for an unmanned aerial vehicle is provided, the control device comprising: a processor and a memory, the memory being used to store a computer program, the processor being used to call and run the computer program stored in the memory to execute: a control method as in the first aspect or any possible implementation manner of the first aspect.

[0032] In a fourth aspect, a drone is provided, comprising: a computing device, and a control device as in the second aspect or the third aspect, the control device being used to generate instruction information on the computing device and execute the instruction information. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 A schematic flowchart of a method for controlling a drone provided in an embodiment of the present application is shown.

[0034] Figure 2 A flowchart of the pitch angle of a drone provided in an embodiment of the present application is shown.

[0035] Figure 3 A flowchart of the pitch angle of another drone provided in an embodiment of the present application is shown.

[0036] Figure 4 A schematic structural block diagram of a control device for a drone provided in an embodiment of the present application is shown.

[0037] Figure 5 A schematic structural block diagram of a control device for a drone provided in an embodiment of the present application is shown.

[0038] Figure 6 A schematic structural block diagram of a drone provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0039] The technical solution in this application will be described below in conjunction with the accompanying drawings.

[0040] The present application relates to the attitude angle control of a quadrotor drone. As a highly flexible and maneuverable aircraft, the quadrotor drone has been widely used in military, logistics, rescue, environmental monitoring and other fields. During the flight of the quadrotor drone, the attitude angle of the quadrotor drone is controlled to ensure that the quadrotor drone can fly stably and operate according to a predetermined trajectory or mission requirements.

[0041] In some solutions, attitude angle control is achieved through proportional-integral-derivative (PID) control, sliding mode control and other technologies. However, these control methods have many limitations when facing nonlinear dynamic systems during flight, especially when dealing with system parameter uncertainties and external disturbances. The robustness and stability of the system cannot be ensured.

[0042] In view of this, the present application proposes a control method for a drone, which controls the attitude of the drone more accurately and quickly by considering multiple interference factors of the drone during flight.

[0043] Figure 1 A schematic flowchart of a method 100 for controlling a drone provided in an embodiment of the present application is shown.

[0044] like Figure 1 As shown, the control method 100 of the drone includes the following steps.

[0045] S110: Build a quadrotor drone model.

[0046] S120: According to the quad-rotor UAV model, a first interference item of the UAV within a preset time is obtained.

[0047] S130: Obtaining an attitude control rate of the UAV according to the quad-rotor UAV model, a first interference term, and an adaptive term to perform attitude control on the UAV, wherein the first interference term includes uncertain interference of the quad-rotor UAV model and external interference.

[0048] The executor of the embodiment of the method is a control unit of a quad-rotor drone, such as a flight control system. The control unit may also be a server, such as a cloud server.

[0049] In the above step S110, the control unit obtains the quad-rotor drone model and constructs the quad-rotor drone model according to the third formula, which is:

[0050]

[0051] Among them, I x ,I y and Iz is the inertia matrix of the x, y and z axes, μ θ and μ ψ are the rolling moment, yaw moment and pitch moment, l is the distance from the propeller axis to the center of mass of the UAV, θ and ψ are the roll angle, yaw angle, and pitch angle.

[0052] It should be understood that in this application, the drone refers to a quad-rotor drone.

[0053] Specifically, the Newton-Euler formula shows that the quadcopter model can be described as:

[0054]

[0055] in, Represents three Euler angles, R 3×3 Represents the rotation matrix, which represents the coordinate transformation of the three attitude angles of the quadrotor drone model from the system to the inertial system. It represents the angular velocity of the three attitude angles, that is, the attitude angle is obtained by the first-order derivative. I=diag[I x ,I y ,I z ] represents the inertia matrix. The symbol × represents the cross product of matrices. τ∈R 3×1 represents the control torque, μ θ and μ ψ represents the rolling moment, yaw moment and pitch moment, so the relationship between the control input and the rotation speed of the four propellers can be approximated as:

[0056]

[0057] Among them, l, F b And d represents the distance from the propeller shaft to the center of mass of the aircraft, the propeller lift coefficient and the propeller torque coefficient. i represents the rotation speed of the i-th propeller. Finally, after sorting out, the attitude dynamics model of the quadrotor can be obtained as the fifth formula.

[0058] For the fifth formula, by representing the system state, and using to represent the control input. The attitude dynamics model of the quadrotor can be simplified as:

[0059]

[0060] In the above step S120, the control unit obtains a first interference item of the drone within a preset time according to the quad-rotor drone model, wherein the first interference item includes uncertain interference of the quad-rotor drone model and external interference.

[0061] Specifically, the control unit obtains the first interference term within a preset time through sliding mode design according to the quad-rotor drone model.

[0062] First, the control unit obtains the attitude error according to the quadrotor drone model. Specifically, the attitude error is obtained by the error dynamics equation obtained by the quadrotor drone model. In this application, x 1,d =[x 1.1.d ,x 1.2.d ,x 1.3.d ] and x 2,d =[x 2.1.d ,x 2.2.d ,x 2.3.d ] is expressed as the desired attitude angle and the desired attitude angular velocity. At the same time, define e1 = [e 1.1 ,e 1.2 ,e 1.3 ] T ∈R 3×1 and e2=[e 2.1 ,e 2.2 ,e 2.3 ] T ∈R 3×1 It represents the attitude angle tracking error and attitude angular velocity tracking error, that is, the error dynamic equation can be expressed as:

[0063]

[0064]

[0065] Among them, the error dynamics equation is reconstructed and differentiated to obtain:

[0066]

[0067] Among them, f(e1,e2) is a nonlinear function, and G(e1,e2) represents the control gain.

[0068] It should be understood that e1 is the attitude angle tracking error, that is, the attitude error in this application. After the attitude error is obtained through the quad-rotor drone model, the sliding membrane surface is constructed according to the attitude error.

[0069] Specifically, the first interference term is obtained through the sliding mode control algorithm. The sliding mode control algorithm is to construct a suitable sliding surface and its switching control law so that the state of the UAV system can slide on the sliding surface. First, the sliding film surface is defined as:

[0070]

[0071] in, Related to the preset time, it can be expressed as That is, by presetting the time, the synovial surface can be made to converge to a desired equilibrium point within a predetermined finite time during the control process. It can also be expressed as the synovial surface is equal to or less than zero within the preset time.

[0072] Optionally, a first interference term within a preset time is obtained according to the synovial surface, and the preset time includes a first preset time and a second preset time. When the synovial surface is equal to or less than zero within the preset time, the first interference term within the preset time is obtained according to a first formula, and the first formula is:

[0073]

[0074] Where e is the attitude error, T c1 is the first preset time, T c2 is the second preset time, and T c1 <T c2 For example, T c1 Set to 2s, T c2 It is set to 4s. During the control process through the sliding mode control algorithm, the attitude angle of the UAV is controlled quickly and accurately by making the sliding film surface less than or equal to zero between 2s and 4s.

[0075] It should be understood that in the above first formula or other formulas, the formulas not described are all control parameters.

[0076] Optionally, the control unit may also obtain an attitude control rate of the UAV according to a second interference term to perform attitude control on the UAV, wherein the second interference term includes nonlinear interference.

[0077] Specifically, the nonlinear interference is fitted by the fuzzy logic system (FLS).

[0078] Among them, FLS is a computational framework that imitates human reasoning and decision-making processes and is suitable for dealing with uncertainty and nonlinear problems. FLS consists of the following four basic parts: fuzzy rule base, fuzzification, fuzzy reasoning engine, and defuzzification.

[0079] Among them, the fuzzy rule base consists of a set of IF-THEN rules, which are in the following form:

[0080] IFx1 is As and in, and is a fuzzy function.

[0081] Then, by using a single-value fuzzifier, product inference, and central average defuzzification, in this application, a fuzzy logic system is constructed according to the quadcopter model to fit the nonlinear interference. That is, according to the second formula, the output of FLS is obtained, and the second formula is:

[0082]

[0083] Among them, x i is a quad-rotor drone model, i is the number of propellers, is the fuzzy function, is the maximum value of the fuzzy function.

[0084] More specifically, simplify the second formula above and let The fuzzy basis function is defined as follows:

[0085]

[0086] Among them, ξ(x)=[ξ1(x),ξ2(x),…,ξ N (x)] T , the second formula can be described as:

[0087]

[0088] Among them, W l is a free parameter of the fuzzy logic system, ξ l It is the basic function of the fuzzy logic system.

[0089] That is, in this application, the quadcopter drone model x i As the input of the fuzzy logic system, the nonlinear disturbance is fitted through the fuzzy logic system, and finally the quadrotor UAV model with nonlinear disturbance is obtained.

[0090] In the above step S130, the control unit obtains the attitude control rate of the drone according to the quad-rotor drone model, the first interference term and the adaptive term to perform attitude control on the drone.

[0091] Optionally, the attitude control of the UAV is performed by an adaptive term, wherein the adaptive term is determined according to a fuzzy logic system. The adaptive term is determined according to the fourth formula, which is:

[0092] Z=ΥS T ξ;

[0093] Among them, ξ is the basis function of the fuzzy system.

[0094] Specifically, the control unit obtains the attitude control rate of the UAV according to the quadrotor UAV model, the first interference term and the adaptive term, which can be described as the design of the controller, which can be described by the following formula:

[0095]

[0096] Among them, the calculation formula of the attitude control rate in the above formula is to subtract the first interference term from the quadrotor drone model and add the adaptive term, where, is an adaptive term, and the second interference term is included in In this way, the attitude of the UAV can be controlled accurately and quickly.

[0097] Through the technical solution of the embodiment of the present application, by considering multiple interference factors of the drone during flight and effectively controlling the drone within a preset time during the control process, the attitude of the drone can be controlled more accurately and quickly.

[0098] Optionally, after obtaining the attitude control rate of the UAV through the above control method, it is necessary to construct a Lyapunov function; based on the Lyapunov function, perform boundedness analysis on the attitude control rate of the UAV.

[0099] Specifically, the preset time in the attitude control rate is first analyzed to verify that the control method in this application can make the sliding surface converge to the desired equilibrium point within a predetermined finite time within the preset time. Construct the Lyapunov function 1, the formula is as follows:

[0100]

[0101] The formula obtained by derivation is as follows:

[0102]

[0103] The first interference term about T c1 Substituting the part into the above formula, we get the formula:

[0104]

[0105] Among them, e1 satisfies the predefined time control. Then construct Lyapunov function 2;

[0106]

[0107] Derivative the above formula, we get:

[0108]

[0109] Bring in the attitude control rate and adaptive terms:

[0110]

[0111] After processing, the following formula is obtained:

[0112]

[0113] After simplification, we get the following formula:

[0114]

[0115] Where b = s T ∈-k|s|>0,0<η2<1.

[0116] Through the above verification, the attitude control rate designed in the present application can be obtained, which can make the sliding membrane surface converge to the desired equilibrium point within a predetermined finite time within a preset time, and can accurately control the attitude of the UAV.

[0117] For example, the parameters in the formulas of the control methods in the above embodiments are given as examples to verify the limitations of the control methods of the present application.

[0118] Example 1, let α1=2; α2=2; β1=2; β2=2; eta1=0.5; eta1=0.5; k=0.1; T c1 =2; T c2 =4; Y = 0.3; I x =0.03; I y =0.05; I z =0.1; x 1.1.d =0.2cost;x 1.2.d =0.2cost;x 1.3.d =0.2cost;x 2.1.d =-0.2sint;x 2.2.d =-0.2sint;x 2.3.d = -0.2sint, at T c1 =2 and T c2 =4, if Figure 2 As shown, the real-time pitch angle and the expected pitch angle basically coincide with each other as they change over time, so it can be concluded that the control method in the embodiment of the present application can accurately adjust the posture of the drone to achieve the expected value.

[0119] Example 2: When other parameters remain unchanged, at T c1 =6 and T c2 =8, if Figure 3As shown, it can also be seen that the real-time pitch angle and the desired pitch angle basically coincide with each other as time changes, so it can be concluded that the control method in the embodiment of the present application can accurately adjust the attitude of the drone to achieve the desired value. In addition, by adjusting the preset time, the control method in the embodiment of the present application can achieve the attitude angle to be controlled within the preset time.

[0120] Combination of the above Figures 1 to 3 The method embodiment provided by the present application is described below. Figure 4 and Figure 5 The device embodiments provided in the present application are described. It is understandable that the device embodiments below may correspond to the method embodiments above, and the specific solutions may refer to the above description, and the repeated parts will not be described in detail.

[0121] Figure 4 A schematic structural block diagram of a control device 400 for an unmanned aerial vehicle provided in an embodiment of the present application is shown.

[0122] like Figure 4 As shown, the control unit 400 includes: a construction unit 410 and a processing unit 420 .

[0123] The construction unit 410 is used to construct a quad-rotor drone model.

[0124] The processing unit 420 is used to obtain a first interference term within a preset time according to the quad-rotor drone model.

[0125] The processing unit 420 is also used to obtain the attitude control rate of the drone according to the quadrotor drone model, the first interference term and the adaptive term to perform attitude control on the drone, wherein the first interference term includes uncertain interference and external interference of the quadrotor drone model.

[0126] Figure 5 A schematic structural block diagram of a control device 500 for a drone provided in an embodiment of the present application is shown.

[0127] like Figure 5 As shown, the control device 500 includes: a processor 510 and a memory 520, the memory 520 is used to store a computer program, and the processor 510 is used to call and run the computer program stored in the memory 520 to execute the above Figures 1 to 3 The control method of the drone provided in any embodiment.

[0128] The embodiment of the present application also provides a drone, Figure 6 A schematic structural block diagram of a drone 600 provided in an embodiment of the present application is shown.

[0129] like Figure 6As shown, the drone 600 includes: a computing device 610, and a control device 620, wherein the control device 620 is used to generate instruction information on the computing device 610 and execute the instruction information.

[0130] Optionally, the control device 620 may be Figure 4 or Figure 5 The control device 400 or the control device 500 shown.

[0131] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0132] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0133] It should be understood that the specific examples in this article are only intended to help those skilled in the art better understand the embodiments of the present application, rather than to limit the scope of the embodiments of the present application.

[0134] It should also be understood that in the various embodiments of the present application, the size of the serial number of each process does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0135] It should also be understood that the various implementation methods described in this specification can be implemented individually or in combination, and the embodiments of the present application are not limited to this.

[0136] Unless otherwise stated, all technical and scientific terms used in the embodiments of the present application are the same as the meanings generally understood by those skilled in the art of the technical field of the present application. The terms used in the present application are only for the purpose of describing specific embodiments and are not intended to limit the scope of the present application. The term "and / or" used in the present application includes any and all combinations of one or more related listed items. The singular forms of "a kind of", "above" and "the" used in the embodiments of the present application and the appended claims are also intended to include majority forms, unless the context clearly indicates other meanings. In addition, the terms "first", "second", "third" etc. are only used for description purposes and cannot be understood as indicating or suggesting relative importance.

[0137] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0138] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0139] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0140] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0141] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for controlling an unmanned aerial vehicle, characterized in that: include: Build a quadrotor drone model; According to the quadrotor drone model, a first interference term of the drone within a preset time is obtained; According to the quadrotor drone model, the first interference term and the adaptive term, an attitude control rate of the drone is obtained to perform attitude control on the drone. Among them, the first interference term includes uncertain interference and external interference of the quadrotor drone model.

2. The control method according to claim 1, characterized in that: The method of obtaining a first interference term within a preset time according to the quadrotor drone model includes: According to the quad-rotor UAV model, the first interference term within a preset time is obtained through sliding mode design.

3. The control method according to claim 2, characterized in that: The first interference term within a preset time is obtained by sliding mode design according to the quad-rotor drone model, including: According to the quadrotor drone model, an attitude error is obtained; constructing a sliding surface according to the posture error, wherein the sliding surface is equal to or less than zero within the preset time; A first interference term within the preset time is obtained according to the synovial surface.

4. The control method according to any one of claims 1 to 3, characterized in that: The preset time includes a first preset time and a second preset time. The obtaining, according to the synovial surface, a first interference term within the preset time includes: According to the first formula, a first interference term within the preset time is obtained, and the first formula is: Wherein, e is the posture error, T c1 is the first preset time, T c2 is the second preset time, and T c1 <T c2 .

5. The control method according to any one of claims 1 to 4, characterized in that: The method further comprises: According to the second interference term, the attitude control rate of the UAV is obtained to perform attitude control on the UAV. Wherein, the second interference term includes nonlinear interference.

6. The control method according to claim 5, characterized in that: The step of obtaining the attitude control rate of the UAV according to the second interference term to perform attitude control on the UAV includes: The nonlinear disturbance is fitted by a fuzzy logic system.

7. The control method according to claim 6, characterized in that: The step of fitting the nonlinear interference by using a fuzzy logic system comprises: According to the quadrotor drone model, the fuzzy logic system is constructed to fit the nonlinear interference.

8. The control method according to claim 7, characterized in that: The fuzzy logic system is constructed according to the quadrotor drone model, including: According to the second formula, the output of the fuzzy logic system is obtained, and the second formula is: Among them, x i is the quadrotor drone model, i is the number of propellers, is the fuzzy function, is the maximum value of the fuzzy function.

9. The control method according to any one of claims 1 to 8, characterized in that: The construction of the quad-rotor drone model includes: According to the third formula, the quad-rotor drone model is obtained, and the third formula is: Among them, I x ,I y and I z is the inertia matrix of the x, y and z axes, μ θ and μ ψ are the rolling moment, yaw moment and pitch moment, l is the distance from the propeller axis to the center of mass of the UAV, θ and ψ are the roll angle, yaw angle, and pitch angle.

10. The control method according to any one of claims 6 to 9, characterized in that: The adaptive term is determined according to the fuzzy logic system.

11. The control method according to claim 10, characterized in that: The adaptive term is determined according to the fuzzy logic system, including: According to the fourth formula, the adaptive term is determined, and the fourth formula is: Z=ΥS T ξ; Wherein, ξ is the basis function of the fuzzy system.

12. The control method according to claims 1 to 11, characterized in that: The method further comprises: Construct Lyapunov functions; According to the Lyapunov function, a boundedness analysis is performed on the attitude control rate of the UAV.

13. A control device for an unmanned aerial vehicle, characterized in that: include: A construction unit for building a quadrotor drone model; A processing unit, configured to obtain a first interference term within a preset time according to the quadrotor drone model; The processing unit is also used to obtain the attitude control rate of the drone according to the quadrotor drone model, the first interference term and the adaptive term, so as to perform attitude control on the drone, wherein the first interference term includes uncertain interference and external interference of the quadrotor drone model.

14. A control device for an unmanned aerial vehicle, characterized in that: include: A processor and a memory, wherein the memory is used to store a computer program, and the processor is used to call and run the computer program stored in the memory to execute: the control method according to any one of claims 1 to 12.

15. A drone, characterized in that: include: A computing device, and a control apparatus as claimed in claim 13 or 14, wherein the control apparatus is used to generate instruction information on the computing device and execute the instruction information.

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