Multi-rotor unmanned aerial vehicle online variable parameter control method, electronic equipment and storage medium

Abstract

The invention discloses an online variable parameter control method for a multi-rotor unmanned aerial vehicle, electronic equipment and a storage medium, and the method comprises the steps: S1, calculating and generating a dynamic coefficient table corresponding to each state through employing the state parameters, including the altitude, the flight speed and the weight center of gravity, of various flight states of the multi-rotor unmanned aerial vehicle; s2, according to the dynamic coefficient table, PID control parameter design is completed, control parameters are verified through linear control response simulation and multi-rotor unmanned aerial vehicle flight simulation, and control parameter tables corresponding to various flight states are formed; s3, in the flight process of the multi-rotor unmanned aerial vehicle, according to sensing data including the altitude, the flight speed and the weight gravity center change caused by load throwing, optimal control parameters are selected through the control parameter table. Compared with a traditional multi-rotor single-set parameter control method, independent control parameters can be designed for different flight states, so that the flight control precision and stability in each state can be optimal.

Description

Technical Field

[0001] This invention relates to the field of multi-rotor unmanned aerial vehicle (UAV) control, and more particularly to an online variable parameter control method, electronic device, and storage medium for multi-rotor UAVs. Background Technology

[0002] Multirotor UAV flight control refers to the process by which the flight controller (FC) generates electronic speed controller (ESC) control commands in real time based on attitude, velocity, and position information acquired from onboard sensors. These commands drive the brushless motors to adjust the rotor speed, thereby achieving attitude stabilization, velocity tracking, and position control of the UAV. This process involves the coordinated work of multiple stages, including sensor data acquisition, state estimation, control algorithm calculation, and power system execution. Its core objective is to ensure stable flight and accurate trajectory tracking of the UAV in complex environments.

[0003] Currently, the core algorithm for flight control of multi-rotor UAVs mainly adopts the linear PID control algorithm. The core principle is to determine a set of attitude, speed, and position control parameters through flight simulation and actual aircraft debugging to achieve flight control of the multi-rotor UAV. However, while determining a set of PID parameters for attitude, speed, and position control through flight simulation and actual aircraft debugging is simple to implement, a single set of parameters is difficult to adapt to different flight conditions. It is prone to loss of control under boundary conditions, making it difficult to guarantee high precision and stability of flight control, and thus has significant limitations. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the prior art and provide an online variable parameter control method, electronic device and storage medium for multi-rotor unmanned aerial vehicles.

[0005] The objective of this invention is achieved through the following technical solution: A first aspect of the present invention provides an online variable parameter control method for a multi-rotor unmanned aerial vehicle, comprising the following steps: S1: Calculate and generate a table of dynamic coefficients for each flight state using state parameters of the multi-rotor UAV, including altitude, flight speed, and center of gravity. S2: Based on the power coefficient table, complete the PID control parameter design, verify the control parameters through linearized control response simulation and multi-rotor UAV flight simulation, and form a control parameter table corresponding to various flight states; S3: During the flight of the multi-rotor UAV, the optimal control parameters are selected using the control parameter table based on sensor data including altitude, flight speed, and changes in the center of gravity caused by payload dropping.

[0006] Furthermore, in step S1, the state parameters, including altitude, flight speed, and center of gravity, correspond to dynamic coefficients including altitude channel coefficients. Rolling channel coefficient Pitch channel coefficient and yaw channel coefficient The calculation formulas are as follows: In the formula, This refers to the weight of the drone; The moment of inertia in the roll direction of the drone; The moment of inertia of the UAV in the pitch direction; The moment of inertia of the UAV in the yaw direction; This is the distance from the drone's center of gravity to the center of its rotor. The tensile force coefficient of the UAV power unit; This refers to the anti-torque coefficient of the UAV power unit; For motor constants; The rotor speed of the drone when it is hovering; in, , , , and Determined by the structure of the drone and the payload loading status, the payload load changes during flight due to the dropping action; , , and The condition of the drone's power unit will be determined by environmental factors, including altitude and flight speed.

[0007] Furthermore, in step S2, the PID control parameters include altitude channel PID control parameters, roll channel PID control parameters, pitch channel PID control parameters, and yaw channel PID control parameters, as detailed below: The height channel PID control parameters include: height control gain. Longitudinal speed control gain ; The PID control parameters for the roll channel include: roll angle control gain. Roll velocity control gain Right-hand position control gain Right-hand speed control gain ; The pitch channel PID control parameters include: pitch angle control gain. Pitch rate control gain Forward position control gain Forward speed control gain ; The PID control parameters for the yaw channel include: yaw angle control gain. yaw rate control gain .

[0008] Furthermore, in step S2, the design models corresponding to each PID control parameter in the control parameter table are divided into altitude channel design model, roll channel design model, pitch channel design model, and yaw channel design model, as detailed below: The height channel design model includes: The open-loop transfer function for the height channel PID control parameter design is as follows: In the formula, It is a high-biased quantity; s is the high-channel motor command bias, and s is a characteristic quantity obtained by performing the Laplace transform on the dynamic equation; The closed-loop transfer function for the height channel PID control parameter design is as follows: In the formula, For height control command bias; The roll channel design model includes: The open-loop transfer function for the PID control parameters of the roll channel is: In the formula, This is the rightward distance offset; This is the roll angle offset; This is the offset of the motor command for the roll channel; It is the acceleration due to gravity; The closed-loop transfer function for the PID control parameters of the roll channel is: In the formula, This is the roll angle command offset; This is the offset for the rightward distance command; The pitch channel design model includes: The open-loop transfer function for the pitch channel PID control parameters is as follows: In the formula, Forward distance bias; This is the pitch angle offset. This is the tilt channel motor command offset.

[0009] The closed-loop transfer function for the pitch channel PID control parameter design is as follows: In the formula, This is the pitch angle command offset; Forward distance command bias; The yaw channel design model includes: The open-loop transfer function for the yaw channel PID control parameters is as follows: In the formula, This is the yaw angle offset; This is the yaw channel motor command bias; The closed-loop transfer function for the yaw channel PID control parameter design is as follows: In the formula, This is the offset of the yaw angle command.

[0010] Further, in step S3, the step of selecting the optimal control parameters based on the control parameter table using sensor data including altitude, flight speed, and weight center of gravity changes caused by payload dropping includes: For weight and center of gravity changes caused by payload jettison during flight, two sets of control parameter tables are pre-stored for payload presence and payload absence, and the corresponding control parameters are selected based on the electrical detection signal indicating whether the payload has been jettisoned. For changes in altitude and speed during flight, a multi-dimensional control parameter table corresponding to different states is pre-stored. Based on the state parameters output by the navigation system, the corresponding control parameters are obtained by interpolation of the control parameter table.

[0011] A second aspect of the present invention provides an electronic device including a storage unit and a processing unit, wherein the storage unit stores computer instructions executable on the processing unit, and the processing unit executes the steps of an online variable parameter control method for a multi-rotor unmanned aerial vehicle as described in the first aspect when executing the computer instructions.

[0012] A third aspect of the present invention provides a storage medium storing computer instructions that, when executed, perform the steps of an online variable parameter control method for a multi-rotor unmanned aerial vehicle as described in the first aspect.

[0013] The beneficial effects of this invention are: In an exemplary embodiment of the present invention, compared with the traditional multi-rotor single-parameter control method, independent control parameters can be designed for different flight states, so that the flight control accuracy and stability can be optimized in each state; special control parameters can be designed for special flight states, such as dynamic take-off and landing, precise landing, and strong wind resistance, without affecting the flight control effect in normal states. Attached Figure Description

[0014] Figure 1 A flowchart of an online variable parameter control method for a multi-rotor unmanned aerial vehicle (UAV) provided as an exemplary embodiment of the present invention; Figure 2 A block diagram of the design loop for the height channel PID control parameters provided in an exemplary embodiment of the present invention; Figure 3 A block diagram of the design loop for the PID control parameters of the roll channel provided in an exemplary embodiment of the present invention; Figure 4 A block diagram of the pitch channel PID control parameter design loop provided for an exemplary embodiment of the present invention; Figure 5 A block diagram of the yaw channel PID control parameter design loop provided for an exemplary embodiment of the present invention. Detailed Implementation

[0015] The technical solution of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0016] In the description of this invention, it should be noted that the directions or positional relationships indicated by terms such as "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer" are based on the directions or positional relationships shown in the accompanying drawings and are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this invention. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0017] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "joining" should be interpreted broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; they can refer to mechanical connections or electrical connections; they can refer to direct connections or indirect connections through an intermediate medium; and they can refer to the internal communication between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0018] Furthermore, the technical features involved in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0019] See Figure 1 , Figure 1 The flowchart illustrates an exemplary embodiment of the present invention of an online variable parameter control method for a multi-rotor unmanned aerial vehicle, comprising the following steps: S1: Calculate and generate a table of dynamic coefficients for each flight state using state parameters of the multi-rotor UAV, including altitude, flight speed, and center of gravity. S2: Based on the power coefficient table, complete the PID control parameter design, verify the control parameters through linearized control response simulation and multi-rotor UAV flight simulation, and form a control parameter table corresponding to various flight states; S3: During the flight of the multi-rotor UAV, the optimal control parameters are selected using the control parameter table based on sensor data including altitude, flight speed, and changes in the center of gravity caused by payload dropping.

[0020] Specifically, in this exemplary embodiment, various flight states of the multi-rotor UAV are uniformly expressed as linearized dynamic coefficients, and a control parameter table is designed accordingly. The optimal control parameters are selected online during the flight of the multi-rotor UAV, which effectively improves the accuracy and stability of flight control under different flight states.

[0021] Compared to the traditional single-parameter control method for multi-rotors, this exemplary embodiment can design independent control parameters for different flight states, so that the flight control accuracy and stability can be optimized in each state. It can also design special control parameters for special flight states, such as dynamic take-off and landing, precise landing, and strong wind resistance, without affecting the flight control effect in normal states.

[0022] The following will describe in detail the specific implementation methods for each step: More preferably, in an exemplary embodiment, in step S1, the dynamic coefficients corresponding to the state parameters including altitude, flight speed, and center of gravity include the altitude channel coefficient. Rolling channel coefficient Pitch channel coefficient and yaw channel coefficient The calculation formulas are as follows: In the formula, This refers to the weight of the drone; The moment of inertia in the roll direction of the drone; The moment of inertia of the UAV in the pitch direction; The moment of inertia of the UAV in the yaw direction; The distance from the center of gravity of the drone to the center of the rotor (rotor arm length). This refers to the thrust coefficient of the UAV power unit (rotor thrust coefficient). This refers to the anti-torque coefficient (rotor torque coefficient) of the UAV power unit. This is the motor constant (slope from throttle to steady-state motor speed). The rotor speed of the drone when hovering (steady-state speed when hovering). in, , , , and Determined by the structure of the drone and the payload loading status, the payload load changes during flight due to the dropping action; , , and The condition of the drone's power unit will be determined by environmental factors, including altitude and flight speed.

[0023] In a specific exemplary embodiment, the model parameters of the multi-rotor UAV in a certain state are shown in the table below: Table 1. Parameters of Multi-rotor UAV Model Based on the height channel coefficient Rolling channel coefficient Pitch channel coefficient and yaw channel coefficient The calculation formula yields the specific numerical value: More preferably, in an exemplary embodiment, in step S2, the PID control parameters include altitude channel PID control parameters, roll channel PID control parameters, pitch channel PID control parameters, and yaw channel PID control parameters, as follows: The height channel PID control parameters include: height control gain. Longitudinal speed control gain ; The PID control parameters for the roll channel include: roll angle control gain. Roll velocity control gain Right-hand position control gain Right-hand speed control gain ; The pitch channel PID control parameters include: pitch angle control gain. Pitch rate control gain Forward position control gain Forward speed control gain ; The PID control parameters for the yaw channel include: yaw angle control gain. yaw rate control gain .

[0024] In a specific exemplary embodiment, based on the specific values ​​of the aforementioned power coefficients, PID control parameters are designed offline according to the design model of each channel, ultimately obtaining the values ​​of each PID control coefficient: It should be noted that there are multiple methods for designing the gain of each channel, such as the root locus method and the Bode plot method.

[0025] More preferably, in an exemplary embodiment, in step S2, the design models corresponding to each PID control parameter in the control parameter table are divided into altitude channel design model, roll channel design model, pitch channel design model, and yaw channel design model, as follows: like Figure 2 As shown, the height channel design model includes: The open-loop transfer function for the height channel PID control parameter design is as follows: In the formula, It is a high-biased quantity; s is the high-channel motor command bias, and s is a characteristic quantity obtained by performing the Laplace transform on the dynamic equation; The closed-loop transfer function for the height channel PID control parameter design is as follows: In the formula, For height control command bias; like Figure 3 As shown, the roll channel design model includes: The open-loop transfer function for the PID control parameters of the roll channel is: In the formula, This is the rightward distance offset; This is the roll angle offset; This is the offset of the motor command for the roll channel; It is the acceleration due to gravity; The closed-loop transfer function for the PID control parameters of the roll channel is: In the formula, This is the roll angle command offset; This is the offset for the rightward distance command; like Figure 4 As shown, the pitch channel design model includes: The open-loop transfer function for the pitch channel PID control parameters is as follows: In the formula, Forward distance bias; This is the pitch angle offset. This is the tilt channel motor command offset.

[0026] The closed-loop transfer function for the pitch channel PID control parameter design is as follows: In the formula, This is the pitch angle command offset; Forward distance command bias; like Figure 5 As shown, the yaw channel design model includes: The open-loop transfer function for the yaw channel PID control parameters is as follows: In the formula, This is the yaw angle offset; This is the yaw channel motor command bias; The closed-loop transfer function for the yaw channel PID control parameter design is as follows: In the formula, This is the offset of the yaw angle command.

[0027] It should be noted that the open-loop transfer function and the closed-loop transfer function are derived from the linearization of the UAV dynamics model.

[0028] Further, in step S3, the step of selecting the optimal control parameters based on the control parameter table using sensor data including altitude, flight speed, and weight center of gravity changes caused by payload dropping includes: For weight and center of gravity changes caused by payload jettison during flight, two sets of control parameter tables are pre-stored for payload presence and payload absence, and the corresponding control parameters are selected based on the electrical detection signal indicating whether the payload has been jettisoned. For changes in altitude and speed during flight, a multi-dimensional control parameter table corresponding to different states is pre-stored. Based on the state parameters output by the navigation system, the corresponding control parameters are obtained by interpolation of the control parameter table.

[0029] Having the same inventive concept as the above exemplary embodiments, another exemplary embodiment of the present invention provides an electronic device, including a storage unit and a processing unit, wherein the storage unit stores computer instructions that can be executed on the processing unit, and the processing unit executes the steps of the online variable parameter control method for a multi-rotor unmanned aerial vehicle when executing the computer instructions.

[0030] Electronic devices are manifested in the form of general-purpose computing devices. Components of electronic devices may include, but are not limited to: at least one processing unit, at least one storage unit, and a bus connecting different system components (including storage units and processing units).

[0031] The storage unit stores program code that can be executed by the processing unit, causing the processing unit to perform the steps described in the "Exemplary Methods" section above, based on various exemplary embodiments of the present invention. For example, the processing unit can perform actions such as... Figure 1 The method shown in the figure.

[0032] The storage unit may include readable media in the form of volatile storage units, such as random access memory (RAM) and / or cache storage units, and may further include read-only memory (ROM).

[0033] The storage unit may also include a program / utility having a set (at least one) of program modules, including but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of these examples may include an implementation of a network environment.

[0034] A bus can represent one or more of several types of bus structures, including a memory cell bus or memory cell controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus that uses any of the various bus structures.

[0035] The electronic device can also communicate with one or more external devices (e.g., keyboards, pointing devices, Bluetooth devices, etc.), one or more devices that enable a user to interact with the electronic device, and / or any device that enables the electronic device to communicate with one or more other computing devices (e.g., routers, modems, etc.). This communication can be performed via input / output (I / O) interfaces. Furthermore, the electronic device can communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via a network adapter. The network adapter communicates with other modules of the electronic device via a bus. It should be understood that other hardware and / or software modules can be used in conjunction with the electronic device, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0036] Through the above description, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solution according to this exemplary embodiment can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, terminal device, or network device, etc.) to execute the method according to this exemplary embodiment.

[0037] Having the same inventive concept as the above exemplary embodiments, another exemplary embodiment of the present invention provides a storage medium storing computer instructions, which, when executed, perform the steps of the online variable parameter control method for a multi-rotor unmanned aerial vehicle.

[0038] Based on this understanding, the technical solution of this embodiment, or the part that contributes to the prior art, or part of the technical solution, can be embodied in the form of a software product (program product). The computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention.

[0039] The program product may employ any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0040] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium, capable of sending, propagating, or transmitting programs for use by or in conjunction with an instruction execution system, apparatus, or device.

[0041] The program code contained on the readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination thereof.

[0042] Program code for performing the operations of this invention can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can execute entirely on the user's computing device, partially on the user's device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0043] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art can make other variations or modifications based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A method for online variable parameter control of a multi-rotor unmanned aerial vehicle, characterized in that: Includes the following steps: S1: Calculate and generate a table of dynamic coefficients for each flight state using state parameters of the multi-rotor UAV, including altitude, flight speed, and center of gravity. S2: Based on the power coefficient table, complete the PID control parameter design, verify the control parameters through linearized control response simulation and multi-rotor UAV flight simulation, and form a control parameter table corresponding to various flight states; S3: During the flight of the multi-rotor UAV, the optimal control parameters are selected using the control parameter table based on sensor data including altitude, flight speed, and changes in the center of gravity caused by payload dropping.

2. The online variable parameter control method for a multi-rotor unmanned aerial vehicle according to claim 1, characterized in that: In step S1, the state parameters, including altitude, flight speed, and center of gravity, correspond to dynamic coefficients, including altitude channel coefficients. Rolling channel coefficient Pitch channel coefficient and yaw channel coefficient The calculation formulas are as follows: ； In the formula, This refers to the weight of the drone; The moment of inertia in the roll direction of the drone; The moment of inertia of the UAV in the pitch direction; The moment of inertia of the UAV in the yaw direction; This is the distance from the drone's center of gravity to the center of its rotor. The tensile force coefficient of the UAV power unit; This refers to the anti-torque coefficient of the UAV power unit; For motor constants; The rotor speed of the drone when it is hovering; in, , , , and Determined by the structure of the drone and the payload loading status, the payload load changes during flight due to the dropping action; , , and The condition of the drone's power unit will be determined by environmental factors, including altitude and flight speed.

3. The online variable parameter control method for a multi-rotor unmanned aerial vehicle according to claim 2, characterized in that: In step S2, the PID control parameters include altitude channel PID control parameters, roll channel PID control parameters, pitch channel PID control parameters, and yaw channel PID control parameters, as detailed below: The height channel PID control parameters include: height control gain. Longitudinal speed control gain ; The PID control parameters for the roll channel include: roll angle control gain. Roll velocity control gain Right-hand position control gain Right-hand speed control gain ; The pitch channel PID control parameters include: pitch angle control gain. Pitch rate control gain Forward position control gain Forward speed control gain ; The PID control parameters for the yaw channel include: yaw angle control gain. yaw rate control gain .

4. The online variable parameter control method for a multi-rotor unmanned aerial vehicle according to claim 3, characterized in that: In step S2, the design models corresponding to each PID control parameter in the control parameter table are divided into altitude channel design model, roll channel design model, pitch channel design model, and yaw channel design model, as detailed below: The height channel design model includes: The open-loop transfer function for the height channel PID control parameter design is as follows: ； In the formula, It is a high-biased quantity; s is the high-channel motor command bias, and s is a characteristic quantity obtained by performing the Laplace transform on the dynamic equation; The closed-loop transfer function for the height channel PID control parameter design is as follows: ； In the formula, For height control command bias; The roll channel design model includes: The open-loop transfer function for the PID control parameters of the roll channel is: ； In the formula, This is the rightward distance offset; This is the roll angle offset; This is the offset of the motor command for the roll channel; It is the acceleration due to gravity; The closed-loop transfer function for the PID control parameters of the roll channel is: ； In the formula, This is the roll angle command offset; This is the offset for the rightward distance command; The pitch channel design model includes: The open-loop transfer function for the pitch channel PID control parameters is as follows: ； In the formula, Forward distance bias; This is the pitch angle offset. This is the pitch channel motor command offset; The closed-loop transfer function for the pitch channel PID control parameter design is as follows: ； In the formula, This is the pitch angle command offset; Forward distance command bias; The yaw channel design model includes: The open-loop transfer function for the yaw channel PID control parameters is as follows: ； In the formula, This is the yaw angle offset; This is the yaw channel motor command bias; The closed-loop transfer function for the yaw channel PID control parameter design is as follows: ； In the formula, This is the offset of the yaw angle command.

5. The online variable parameter control method for a multi-rotor unmanned aerial vehicle according to claim 1, characterized in that: In step S3, the selection of optimal control parameters based on sensor data including altitude, flight speed, and weight center of gravity changes caused by payload drop, using the control parameter table, includes: For weight and center of gravity changes caused by payload jettison during flight, two sets of control parameter tables are pre-stored for payload presence and payload absence, and the corresponding control parameters are selected based on the electrical detection signal indicating whether the payload has been jettisoned. For changes in altitude and speed during flight, a multi-dimensional control parameter table corresponding to different states is pre-stored. Based on the state parameters output by the navigation system, the corresponding control parameters are obtained by interpolation of the control parameter table.

6. An electronic device comprising a storage unit and a processing unit, wherein the storage unit stores computer instructions executable on the processing unit, characterized in that: When the processing unit executes the computer instructions, it performs the steps of the online variable parameter control method for a multi-rotor unmanned aerial vehicle as described in any one of claims 1 to 5.

7. A storage medium storing computer instructions thereon, characterized in that: When the computer instructions are executed, they perform the steps of the online variable parameter control method for a multi-rotor unmanned aerial vehicle as described in any one of claims 1 to 5.

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