Take-off operation stability method, device and equipment for aileron-free electric unmanned aerial vehicle and storage medium

Abstract

The invention provides an aileron-free electric unmanned aerial vehicle takeoff operation stability method, device and equipment and a storage medium, and the method comprises the steps: obtaining the overall parameter information of an unmanned aerial vehicle and the local atmospheric density information of the unmanned aerial vehicle, and determining the minimum constraint speed of the aileron-free electric unmanned aerial vehicle during takeoff according to the overall parameter information and the local atmospheric density information; the unmanned aerial vehicle is controlled to be accelerated to the minimum constraint speed from the initial speed according to preset acceleration time, and the propeller reverse torque and the rolling control torque under the thrust needed by the unmanned aerial vehicle are obtained; and taking an integral error absolute value of the reaction torque and the rolling control torque as an optimization target, taking a maximum torque value provided by a propeller as a constraint condition, performing loop iteration to obtain an optimal thrust and an optimal propeller rotating speed of the unmanned aerial vehicle, and stably controlling the unmanned aerial vehicle to take off according to the optimal thrust and the optimal propeller rotating speed. The reliability of the electric unmanned aerial vehicle is effectively improved and the system cost is reduced on the premise of meeting the takeoff stability control requirement.

Description

Technical Field

[0001] The present application belongs to the field of drone control technology, and in particular relates to a takeoff and stabilization method, device, equipment, and storage medium for a flybarless electric drone. Background Art

[0002] With the rapid development of drone technology, goals such as high reliability, integration, intelligence, and low cost have become the mainstream development trends of drones. Among them, electric drone technology has gradually become the preferred technical route for the research and development of low-cost micro drones due to its many advantages such as fast power response, simple power system, low noise level and low maintenance cost.

[0003] Traditional electric drones typically feature ailerons on their wings, particularly during takeoff. These effectively eliminate the effects of the high-speed propeller's counter-torque and provide stable roll control. This traditional design requires careful wing-aileron matching and the addition of a pair of servo hardware, increasing the weight, reducing payload, and resulting in insufficient overall performance. Summary of the Invention

[0004] In view of this, the present application aims to propose a flybarless electric UAV takeoff and stabilization method, device, equipment and storage medium, so as to improve the reliability of the electric UAV and reduce the system cost while meeting the takeoff stability control requirements.

[0005] To achieve the above objectives, the technical solution of this application is implemented as follows:

[0006] In a first aspect, the present application provides a method for taking off and stabilizing a flybarless electric drone, comprising:

[0007] Obtaining overall parameter information of the UAV and local atmospheric density information of the UAV, and determining a minimum constrained speed for takeoff of the flybarless electric UAV based on the overall parameter information and the local atmospheric density information;

[0008] Controlling the UAV to accelerate from an initial speed to the minimum constraint speed according to a preset acceleration time, and obtaining the propeller counter-torque and rolling control torque under the thrust required by the UAV;

[0009] The absolute value of the integral error between the counter-torque and the roll control torque is used as the optimization target, and the maximum torque provided by the propeller is used as the constraint condition. The optimal thrust and optimal propeller speed of the drone are obtained through cyclic iteration. The drone is then controlled to take off based on the optimal thrust and the optimal propeller speed.

[0010] In a second aspect, based on the same inventive concept, the present application also provides a takeoff and stabilization device for a flybarless electric UAV, comprising:

[0011] an information acquisition module configured to acquire overall parameter information of the UAV and local atmospheric density information of the UAV, and determine a minimum constrained speed for takeoff of the flybarless electric UAV based on the overall parameter information and the local atmospheric density information;

[0012] a data processing module configured to control the UAV to accelerate from an initial speed to the minimum constraint speed according to a preset acceleration time, and obtain a propeller counter-torque and a rolling control torque under a thrust required by the UAV;

[0013] The optimization iteration module is configured to use the absolute value of the integral error between the counter-torque and the roll control torque as the optimization target, and the maximum torque provided by the propeller as the constraint condition, to iteratively obtain the optimal thrust and optimal propeller speed of the drone, and to control the drone to take off based on the optimal thrust and the optimal propeller speed.

[0014] In a third aspect, based on the same inventive concept, the present application also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method described in the first aspect when executing the program.

[0015] In a fourth aspect, based on the same inventive concept, the present application also provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the method described in the first aspect.

[0016] Compared with the prior art, the flybarless electric UAV takeoff and stabilization method, device, equipment, and storage medium described in this application have the following beneficial effects:

[0017] The method, device, equipment and storage medium for takeoff stabilization of a flybarless electric UAV described in this application can achieve stabilization of the UAV during takeoff by designing the propeller speed control law during takeoff and relying on the UAV's full-motion horizontal tail to perform roll control while reducing the influence of the electric propeller's back torque. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings, which constitute part of this application, are intended to provide a further understanding of this application. The exemplary embodiments and descriptions of this application are intended to explain this application and do not constitute an improper limitation on this application. In the accompanying drawings:

[0019] Figure 1 This is a flow chart of a takeoff and stabilization method for a flybarless electric UAV according to an embodiment of the present application;

[0020] Figure 2This is a schematic diagram of a curve diagram showing the change of the all-moving horizontal tail roll control torque and propeller counter-torque over time according to an embodiment of the present application;

[0021] Figure 3 This is a schematic structural diagram of a takeoff and stabilization device for a flybarless electric UAV according to an embodiment of the present application;

[0022] Figure 4 This is a schematic diagram of the hardware structure of the electronic device described in an embodiment of the present application. DETAILED DESCRIPTION

[0023] In order to make the objectives, technical solutions and advantages of this application more clear, this application is further described in detail below in combination with specific embodiments and with reference to the accompanying drawings.

[0024] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the embodiments of the present application should have the usual meanings understood by people with ordinary skills in the field to which this application belongs. The "first", "second" and similar words used in the embodiments of the present application do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word cover the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0025] The embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0026] See also Figure 1 As shown, this embodiment provides a takeoff and stabilization method for a flybarless electric drone, which specifically includes the following steps:

[0027] Step S101: obtaining overall parameter information of the UAV and local atmospheric density information of the UAV, and determining the minimum constraint speed of the flybarless electric UAV during takeoff based on the overall parameter information and the local atmospheric density information;

[0028] Step S102: controlling the UAV to accelerate from an initial speed to a minimum constraint speed according to a preset acceleration time, and obtaining the propeller counter-torque and rolling control torque under the thrust required by the UAV;

[0029] Step S103: Using the absolute value of the integral error between the counter-torque and the roll control torque as the optimization target and the maximum torque provided by the propeller as the constraint, the optimal thrust and optimal propeller speed of the UAV are obtained through iterative looping. The UAV is then controlled to take off based on the optimal thrust and optimal propeller speed.

[0030] The method described in this embodiment is for an electric drone with a flybarless configuration. By designing a propeller speed control rule during the takeoff phase, the drone relies on its fully movable horizontal tail for roll control, while reducing the impact of the electric propeller's back torque, thereby achieving stable control of the drone during takeoff.

[0031] In some embodiments, the overall parameter information includes mass characteristic information, shape geometric characteristic information, aerodynamic characteristic information, and electric propeller power characteristic information;

[0032] Among them, the external geometric feature information includes at least the reference area information and reference length information of the UAV, the aerodynamic characteristic information includes at least the lift coefficient information, the drag coefficient information, the full-moving horizontal tail roll rudder effect information and the full-moving horizontal tail maximum rudder deflection angle information, and the electric propeller power characteristic information includes at least the thrust-speed characteristic information and the torque-thrust characteristic information.

[0033] In some embodiments, obtaining overall parameter information of the UAV and local atmospheric density information of the UAV, and determining the minimum constrained speed of the flybarless electric UAV during takeoff based on the overall parameter information and the local atmospheric density information, includes:

[0034] Based on mass characteristic information, lift coefficient information, reference area information and local atmospheric density information, and according to the minimum constraint speed algorithm, the minimum constraint speed that meets the take-off requirements of the flybarless electric UAV is calculated.

[0035] Specifically, in this embodiment, by obtaining the overall parameter information of the flybarless electric drone, including the drone mass information m (the drone mass in this embodiment is 30 kg, and the parameter values ​​are not specifically limited here, and the following parameter values ​​are also not specifically limited), the lift coefficient information C y (The lift coefficient information in this embodiment is 0.4) and the reference area information S (the reference area in this embodiment is 1m 2 ), and the local atmospheric density information ρ where the drone is located (the local atmospheric density in this embodiment is 1.2 kg / m 3 ), calculate the minimum constraint speed information V that meets the take-off requirements of the electric drone lim , the calculation method is as follows:

[0036]

[0037] When the overall parameters are known, this implementation can obtain the minimum constraint speed required for the electric drone to take off.

[0038] In some embodiments, controlling the UAV to accelerate from an initial speed to a minimum constrained speed according to a preset acceleration time to obtain the propeller counter-torque and rolling control torque under the thrust required by the UAV includes:

[0039] Based on the mass characteristic information and minimum constraint speed of the flybarless electric drone, the drone speed is accelerated from the initial speed to the minimum constraint speed at a constant acceleration within the set acceleration time;

[0040] Based on the mass characteristic information and the drag coefficient information, the thrust information applied by the electric propeller in the axial direction of the UAV during the acceleration time is obtained;

[0041] Based on the torque-thrust characteristic information of the electric propeller, the thrust information is mapped to the torque information generated by the electric propeller, and applied in the roll direction of the UAV body in the form of counter-torque, thereby obtaining the counter-torque applied by the electric propeller in the roll direction of the UAV body;

[0042] Based on the roll rudder effect information of the all-moving horizontal tail, the maximum rudder deflection angle information of the all-moving horizontal tail, the reference area information and the reference length information, and according to the roll control torque algorithm, the roll control torque of the all-moving horizontal tail within the acceleration time is obtained.

[0043] Specifically, in this embodiment, by obtaining the initial speed information V0 of the flybarless electric drone (the initial speed in this embodiment is 25m / s), based on the minimum constraint speed V lim (In this embodiment, the minimum constraint speed is 35 m / s). Set the initial time t1 to 2 seconds, and accelerate the drone from the initial speed to the minimum constraint speed with acceleration a. The calculation method for obtaining the constant acceleration a is as follows:

[0044]

[0045] Based on mass characteristic information m and drag coefficient information C d (The drag coefficient in this embodiment is 0.05), calculate the thrust information F that the electric propeller needs to apply to the UAV in the axial direction during time t1, considering that the UAV is affected by the aerodynamic drag D, given that the UAV's attitude during takeoff is close to horizontal, and ignoring the influence of gravity on the UAV's acceleration phase, in order to meet the UAV's acceleration a (the acceleration in this embodiment is 5m / s 2 ), the calculation method is as follows:

[0046]

[0047] When the overall parameters, local density and resistance information are known, KD is a constant. This implementation method accurately considers the aerodynamic drag information of the UAV and can obtain the thrust F required during the acceleration time of the UAV.

[0048] In this embodiment, by obtaining the torque-thrust characteristic information of the electric propeller, the thrust F required during the acceleration time of the drone is mapped to the torque information generated by the electric propeller, and at the same time applied in the roll direction of the drone body in the form of counter-torque, the counter-torque M applied by the electric propeller in the roll direction of the drone body during time t1 is calculated. rotor , the calculation method is as follows:

[0049] M rotor =K F ·F

[0050] =K F ma+K F K D (V0+at) 2

[0051] =c2t 2 +c1t+c0

[0052] It should be noted that the propeller torque-thrust characteristic is in a linear proportional relationship, and the proportional coefficient K F The proportional coefficient K in this embodiment is obtained through propeller torque-thrust test calibration. F Taking 0.03 can improve the accuracy of the electric propeller torque-thrust mapping relationship and increase the accuracy of the counter-torque calculation. This implementation method can obtain the counter-torque M applied by the electric propeller to the roll direction of the drone during the acceleration time of the drone. rotor , its changing rule is a quadratic function of time, such as Figure 2 shown.

[0053] In this embodiment, the maximum thrust constraint that the propeller can provide is F Max (The maximum thrust constraint in this embodiment is 200N), and the maximum propeller torque M is established based on the propeller torque-thrust mapping. rotorMax The constraint is 6Nm.

[0054] In the embodiment of the present disclosure, based on the full-motion horizontal tail roll steering effect information C ldx (The full-motion horizontal tail roll rudder effect in this embodiment is taken as 0.01), the maximum rudder deflection angle information of the full-motion horizontal tail δ xmax (The maximum rudder deflection angle of the fully movable horizontal stabilizer in this embodiment is 10°), reference area information S and reference length information L (the maximum rudder deflection angle of the fully movable horizontal stabilizer in this embodiment is 1m), calculate the roll control torque M that the fully movable horizontal stabilizer can provide within time t1 ctrl , the calculation method is as follows:

[0055]

[0056]

[0057] When the overall parameter information, local atmospheric density information, full-motion horizontal tail roll rudder effect information and full-motion horizontal tail maximum rudder deflection angle information are known, K ctrl is a constant, and this implementation method can obtain the rolling control torque M that the full-moving horizontal tail can provide during the acceleration time of the UAV. ctrl , and its changing law is a quadratic function of time.

[0058] In some embodiments, the optimal thrust and optimal propeller speed of the drone are obtained by iteratively looping, using the absolute value of the integrated error between the counter-torque and the roll control torque as the optimization target and the maximum torque provided by the propeller as the constraint, including:

[0059] According to the time for obtaining the roll control torque of the all-moving horizontal tail to offset the propeller anti-torque, the integral values ​​of the roll control torque and the anti-torque within the time are calculated respectively, and the absolute value of the integral error is obtained based on the two integral values;

[0060] The absolute value of the integral error is used as the optimization target, and a fixed-step iteration is performed based on the set acceleration time. The number of cycles is set, and the optimal thrust that satisfies the minimum absolute value of the integral error is recorded while ensuring the maximum torque and maximum thrust constraints.

[0061] Specifically, in this embodiment, when the minimum constraint speed V lim When the acceleration time t1 is determined, the acceleration a is determined, and the full-dynamic horizontal tail roll control torque M ctrl and propeller back torque M rotor are quadratic functions of time t, and the polynomial coefficients b and c are known. Calculate M rotor and M ctrl For the same time t2, the calculation method is as follows:

[0062] M rotor (t2) = M ctrl (t2)

[0063] (c2-b2)t 2 +(c1-b1)t+(c0-b0)=0

[0064] When the quadratic equation has a positive root t2, the implementation method can obtain the time t2 when the full-dynamic horizontal tail roll control torque offsets the propeller anti-torque (t2 is 0.94s at this time), and calculate the full-dynamic horizontal tail roll control torque M respectively. ctrl The integral value ∫M within 0 to 0.94s ctrl and counter torque M rotorThe integral value ∫M within t2 rotor , and calculate the absolute value of the integral error |Δ∫M|. The calculation method is as follows:

[0065]

[0066] Taking the minimum |Δ∫M| as the optimization goal, the optimal thrust F is found by iterating the acceleration time t1 opt , the specific implementation is:

[0067] 1) According to the minimum constraint speed information V lim , calculate the value of |Δ∫M| according to the above steps and record it as |Δ∫M| last , (remember |Δ∫M| in this embodiment last =0.64N·m);

[0068] 2) Let t1 = t1 + Δt1, where Δt1 is 0.1s. Calculate the value of |Δ∫M| according to the above steps and compare it with |Δ∫M| last Compare, if |Δ∫M|<|Δ∫M| last , then |Δ∫M| last =|Δ∫M|, and record F opt =F, otherwise keep |Δ∫M| last ;

[0069] 3) Repeat step 2), set the number of cycles to N (50 cycles are used as an example in this embodiment), and always keep the condition M rotor (t2)≤M rotorMax It should be noted that |Δ∫M| in this embodiment achieves a minimum value, that is, M rotor The maximum is 5.3N·m, satisfying ≤M rotorMax Conditions. At this time:

[0070]

[0071] Under this acceleration, the corresponding optimal thrust F opt The rule is:

[0072]

[0073] In some embodiments, further comprising:

[0074] Based on the optimal thrust law and combined with the thrust-speed characteristic information of the electric propeller, the optimal propeller speed law for the takeoff and stabilization phase of the UAV is generated.

[0075] Specifically, in this embodiment, the electric propeller thrust coefficient C is obtained. T is 0.01, according to the optimization result F opt, calculate the optimal propeller speed law Ω (r / s) during the takeoff and stabilization phase of the UAV. The specific calculation method is as follows:

[0076]

[0077] It should be noted that the above description is limited to some embodiments of the present application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in an order different from that described in the above embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0078] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments and methods, an embodiment of the present application further provides a takeoff and stabilization device for a flybarless electric UAV.

[0079] like Figure 3 As shown, the take-off and stabilization device of the flybarless electric UAV includes:

[0080] An information acquisition module 11 is configured to obtain overall parameter information of the UAV and local atmospheric density information of the UAV, and determine a minimum constrained speed for takeoff of the flybarless electric UAV based on the overall parameter information and the local atmospheric density information;

[0081] The data processing module 12 is configured to control the UAV to accelerate from an initial speed to a minimum constraint speed according to a preset acceleration time, and obtain the propeller counter-torque and rolling control torque under the thrust required by the UAV;

[0082] The optimization iteration module 13 is configured to use the absolute value of the integral error of the counter-torque and the roll control torque as the optimization target, and the maximum torque provided by the propeller as the constraint condition, to iteratively obtain the optimal thrust and optimal propeller speed of the UAV, and control the UAV to take off based on the optimal thrust and optimal propeller speed.

[0083] For the convenience of description, the above devices are described as being divided into various modules according to their functions. Of course, when implementing the embodiments of the present application, the functions of each module can be implemented in the same or multiple software and / or hardware.

[0084] The apparatus of the above embodiment is used to implement the corresponding method in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be described in detail here.

[0085] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments and methods, an embodiment of the present application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and runnable on the processor, wherein when the processor executes the program, the method described in any of the above embodiments is implemented.

[0086] Figure 4 10 is a schematic diagram showing a more specific hardware structure of an electronic device provided in this embodiment. The device may include: a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040, and a bus 1050. The processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040 are communicatively connected to each other within the device via the bus 1050.

[0087] The processor 1010 can be implemented using a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.

[0088] The memory 1020 can be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage devices, dynamic storage devices, etc. The memory 1020 can store an operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 1020 and is called and executed by the processor 1010.

[0089] The input / output interface 1030 is used to connect an input / output module to implement information input and output. The input / output module can be configured as a component in the device (not shown in the figure) or can be externally connected to the device to provide corresponding functions. Input devices may include a keyboard, mouse, touch screen, microphone, various sensors, etc., and output devices may include a display, speaker, vibrator, indicator light, etc.

[0090] The communication interface 1040 is used to connect to a communication module (not shown) to enable communication between the device and other devices. The communication module can communicate via a wired method (such as USB, network cable, etc.) or a wireless method (such as mobile network, WiFi, Bluetooth, etc.).

[0091] The bus 1050 comprises a path for transmitting information between the various components of the device (eg, the processor 1010 , the memory 1020 , the input / output interface 1030 , and the communication interface 1040 ).

[0092] It should be noted that although the above device only shows the processor 1010, the memory 1020, the input / output interface 1030, the communication interface 1040, and the bus 1050, in a specific implementation, the device may also include other components necessary for normal operation. In addition, it will be understood by those skilled in the art that the above device may only include the components necessary to implement the embodiments of this specification, and does not necessarily include all the components shown in the figure.

[0093] The electronic device of the above embodiment is used to implement the corresponding method in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be described in detail here.

[0094] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments and methods, the present application also provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the method described in any of the above embodiments.

[0095] The computer-readable media of this embodiment include permanent and non-permanent, removable and non-removable media that can be used to store information by any method or technology. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, read-only compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device.

[0096] The computer instructions stored in the storage medium of the above embodiment are used to enable the computer to execute the method described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0097] Those skilled in the art should understand that the discussion of any of the above embodiments is merely illustrative and is not intended to imply that the scope of the present application (including the claims) is limited to these examples. Within the scope of the present application, the technical features in the above embodiments or different embodiments may be combined, the steps may be implemented in any order, and there are many other variations of the different aspects of the embodiments of the present application as described above, which are not provided in detail for the sake of simplicity.

[0098] In addition, for simplicity of description and discussion, and in order not to make the embodiment of the application difficult to understand, the known power supply / ground connection with integrated circuit (IC) chip and other components may or may not be shown in the accompanying drawings provided. In addition, the device can be shown in the form of a block diagram to avoid making the embodiment of the application difficult to understand, and this also takes into account the following fact, that is, the details of the embodiment of these block diagram devices are highly dependent on the platform to be implemented in the embodiment of the application (that is, these details should be fully within the scope of understanding of those skilled in the art). When specific details (for example, circuit) are set forth to describe exemplary embodiments of the application, it will be apparent to those skilled in the art that the embodiment of the application can be implemented without these specific details or when these specific details are changed. Therefore, these descriptions should be considered to be illustrative rather than restrictive.

[0099] Although the present invention has been described in conjunction with specific embodiments thereof, many alternatives, modifications, and variations of these embodiments will be apparent to those skilled in the art based on the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may utilize the embodiments discussed.

[0100] The embodiments of the present application are intended to cover all such substitutions, modifications, and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of the present application should be included in the scope of protection of this application.

Claims

1. A flybarless electric drone takeoff and stabilization method, characterized in that: include: Obtaining overall parameter information of the UAV and local atmospheric density information of the UAV, and determining a minimum constrained speed for takeoff of the flybarless electric UAV based on the overall parameter information and the local atmospheric density information; Controlling the UAV to accelerate from an initial speed to the minimum constraint speed according to a preset acceleration time, and obtaining the propeller counter-torque and rolling control torque under the thrust required by the UAV; The absolute value of the integral error between the counter-torque and the roll control torque is used as the optimization target, and the maximum torque provided by the propeller is used as the constraint condition. The optimal thrust and optimal propeller speed of the drone are obtained through cyclic iteration. The drone is then controlled to take off based on the optimal thrust and the optimal propeller speed.

2. The method according to claim 1, wherein: The overall parameter information includes mass characteristic information, shape geometric characteristic information, aerodynamic characteristic information and electric propeller power characteristic information; Among them, the external geometric feature information includes at least reference area information and reference length information of the UAV, the aerodynamic characteristic information includes at least lift coefficient information, drag coefficient information, full-moving horizontal tail roll rudder effect information and full-moving horizontal tail maximum rudder deflection angle information, and the electric propeller power characteristic information includes at least thrust-speed characteristic information and torque-thrust characteristic information.

3. The method according to claim 2, characterized in that The obtaining of overall parameter information of the UAV and local atmospheric density information of the UAV, and determining the minimum constrained speed of the flybarless electric UAV during takeoff based on the overall parameter information and the local atmospheric density information, includes: Based on the mass characteristic information, lift coefficient information, reference area information and local atmospheric density information, and according to a minimum constraint speed algorithm, a minimum constraint speed that meets the take-off requirements of the flybarless electric drone is calculated.

4. The method according to claim 2, characterized in that The method of controlling the UAV to accelerate from the initial speed to the minimum constraint speed according to the preset acceleration time to obtain the propeller counter-torque and rolling control torque under the thrust required by the UAV includes: Obtaining the initial speed information of the UAV, and obtaining the acceleration measure from the initial speed to the minimum constraint speed according to the set acceleration time; Based on the mass characteristic information and the drag coefficient information, obtaining thrust information applied by the electric propeller in the axial direction of the drone during acceleration time; Based on the torque-thrust characteristic information of the electric propeller, the thrust information is mapped to the torque information generated by the electric propeller, and applied in the roll direction of the UAV body in the form of counter-torque to obtain the counter-torque applied by the electric propeller in the roll direction of the UAV body.

5. The method according to claim 4, characterized in that Also includes: Based on the all-moving horizontal tail roll rudder effect information, the all-moving horizontal tail maximum rudder deflection angle information, the reference area information and the reference length information, and according to a roll control torque algorithm, the all-moving horizontal tail roll control torque within the acceleration time is obtained.

6. The method according to claim 4, characterized in that The method uses the absolute value of the integral error between the counter torque and the roll control torque as the optimization target, and the maximum torque provided by the propeller as the constraint condition, and iterates to obtain the optimal thrust and optimal propeller speed of the UAV, including: calculating, based on the time for obtaining the roll control torque of the all-moving horizontal tail to offset the propeller counter-torque, the integral values ​​of the roll control torque and the counter-torque within the time, respectively, and obtaining the absolute value of the integral error based on the two integral values; The absolute value of the integral error is used as the optimization target, a fixed-step iteration is performed based on the set acceleration time, and the number of cycles is set. The optimal thrust that satisfies the minimum absolute value of the integral error is recorded while ensuring the maximum torque and maximum thrust constraints.

7. The method according to claim 6, characterized in that Also includes: Based on the optimal thrust law and combined with the thrust-speed characteristic information of the electric propeller, the optimal propeller speed law for the takeoff and stabilization phase of the UAV is generated.

8. A take-off and stabilization device for a flybarless electric drone, characterized in that: include: an information acquisition module configured to acquire overall parameter information of the UAV and local atmospheric density information of the UAV, and determine a minimum constrained speed for takeoff of the flybarless electric UAV based on the overall parameter information and the local atmospheric density information; a data processing module configured to control the UAV to accelerate from an initial speed to the minimum constraint speed according to a preset acceleration time, and obtain a propeller counter-torque and a rolling control torque under a thrust required by the UAV; The optimization iteration module is configured to use the absolute value of the integral error between the counter-torque and the roll control torque as the optimization target, and the maximum torque provided by the propeller as the constraint condition, to iteratively obtain the optimal thrust and optimal propeller speed of the drone, and to control the drone to take off based on the optimal thrust and the optimal propeller speed.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1 to 7 when executing the program.

10. A non-transitory computer-readable storage medium, characterized in that in, The non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to cause a computer to execute the method according to any one of claims 1 to 7.

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