Flight control method, device, equipment, storage medium and product

Abstract

The invention discloses a flight control method and device, equipment, a storage medium and a product, and relates to the technical field of computers.The flight control method comprises the steps that flight control is carried out based on an optimized target dynamic model in response to a flight control instruction, and the target dynamic model is constructed based on an optimized target weight control algorithm; the target weight control algorithm is obtained by combining an initial PID control algorithm and a fuzzy control algorithm. According to the invention, after the flight control instruction is obtained, flight control is carried out through the target weight control algorithm obtained by combining the initial PID control algorithm and the fuzzy control algorithm and the optimized target kinetic model obtained by construction, so that the problem that the flight control accuracy is reduced due to the respective use of the PID control algorithm and the fuzzy control algorithm can be avoided.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a flight control method, device, equipment, storage medium and product. Background Art

[0002] A VTOL (Vertical Takeoff and Landing) aircraft is an aircraft that can take off and land vertically and fly horizontally. It combines the vertical takeoff and landing capabilities of a helicopter with the efficient cruising performance of a fixed-wing aircraft. The flight control design of this type of aircraft is somewhat complex because it requires smooth switching between different flight modes and ensuring stability and controllability in each mode.

[0003] In the related technology, the commonly used vertical take-off fixed-wing flight control method is a gain scheduling method based on PID lookup table. This method has a better control effect when the model is relatively accurate. However, if the model is not accurate in the early design stage or is subject to uncertain disturbances during the flight, the accuracy of this method will drop significantly. Fuzzy control does not rely on the model but lacks integral control, and the steady-state error is difficult to eliminate, resulting in low steady-state accuracy of the system. Summary of the invention

[0004] The main purpose of this application is to provide a flight control method, device, equipment, storage medium and product, which aims to solve the technical problems that the accuracy of the gain scheduling based on PID lookup table will be greatly reduced when the model is not accurate in the early design stage or is subject to uncertain disturbances during the flight, and the fuzzy control does not rely on the model but lacks integral control, and the steady-state error is difficult to eliminate, resulting in low steady-state accuracy of the system.

[0005] To achieve the above objectives, the present application proposes a flight control method, which includes: In response to the flight control instruction, flight control is performed based on the optimized target dynamics model, wherein the target dynamics model is constructed based on the optimized target weight control algorithm, and the target weight control algorithm is obtained by combining an initial PID control algorithm and a fuzzy control algorithm.

[0006] In one embodiment, the step of performing flight control based on the optimized target dynamics model in response to the flight control instruction includes: Inputting error data of the initial dynamics model into a preset fuzzy control algorithm to obtain fuzzy control parameters corresponding to the error data, wherein the initial dynamics model is constructed based on the initial PID control algorithm; Based on the fidelity of the initial dynamics model, determining the target weight ratio corresponding to the initial control parameters of the initial dynamics model and the fuzzy control parameters; Determining a target control parameter based on the initial control parameter, the fuzzy control parameter and the target weight ratio; Based on the target control parameters, the initial dynamics model is optimized to obtain an optimized target dynamics model.

[0007] In one embodiment, the step of determining the target weight ratio corresponding to the initial control parameters of the initial dynamics model and the fuzzy control parameters based on the fidelity of the initial dynamics model includes: Based on a preset mapping relationship between the fidelity of the initial dynamics model and the target weight ratio, the initial control parameters of the initial dynamics model and the target weight ratio corresponding to the fuzzy control parameters are determined.

[0008] In one embodiment, the target weight ratio includes a first weight of the initial control parameter and a second weight of the fuzzy control parameter. If the fidelity is higher, the first weight of the initial control parameter is higher and the second weight of the fuzzy control parameter is lower. If the fidelity is lower, the first weight of the initial control parameter is lower and the second weight of the fuzzy control parameter is higher.

[0009] In one embodiment, the step of optimizing the initial dynamics model based on the target control parameter includes: Based on the target control parameters, the proportion of fuzzy rules in the initial dynamics model is optimized to obtain an optimized target dynamics model.

[0010] In one embodiment, the step of inputting the error parameter of the initial dynamics model into a preset fuzzy control algorithm to obtain the fuzzy control parameter corresponding to the error includes: Based on the initial PID control algorithm, the initial dynamics model is constructed; The initial dynamics model is iteratively trained, and a trained initial dynamics model that meets the accuracy requirement is determined.

[0011] In one embodiment, the error data includes error parameters and error differentials, and the step of inputting the error data of the initial dynamics model into a preset fuzzy control algorithm to obtain the fuzzy control parameters corresponding to the error data includes: Inputting the error parameters and error differentials of the initial dynamics model into a preset fuzzy control algorithm, mapping the error parameters and the error differentials through a preset membership function, and obtaining the membership values ​​corresponding to the error parameters and the error differentials respectively; Based on the membership value, determining the fuzzy variable subsets corresponding to the error parameter and the error differential respectively; The fuzzy output corresponding to the fuzzy variable subset is determined through a preset fuzzy rule table, and the fuzzy output is defuzzified to obtain fuzzy control parameters.

[0012] In addition, to achieve the above-mentioned purpose, the present application also proposes a flight control device, the flight control device comprising: A control module is used to respond to flight control instructions and perform flight control based on an optimized target dynamics model, wherein the target dynamics model is constructed based on an optimized target weight control algorithm, and the target weight control algorithm is obtained by combining an initial PID control algorithm and a fuzzy control algorithm.

[0013] In addition, to achieve the above-mentioned purpose, the present application also proposes a flight control device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the flight control method described above.

[0014] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the flight control method described above are implemented.

[0015] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the steps of the flight control method described above are implemented.

[0016] One or more technical solutions proposed in this application have at least the following technical effects: Compared with the related art, the commonly used vertical take-off fixed-wing flight control method is a gain scheduling method based on PID lookup table. This method has a better control effect when the model is relatively accurate, but the accuracy of this method will be greatly reduced when the model is not accurate in the early design stage or is subject to uncertain disturbances during the flight. In addition, fuzzy control does not rely on the model but lacks integral control, and the steady-state error is difficult to eliminate, resulting in low steady-state accuracy of the system. In comparison, the present application performs flight control based on an optimized target dynamics model in response to flight control instructions, wherein the target dynamics model is constructed based on an optimized target weight control algorithm, and the target weight control algorithm is obtained by combining an initial PID control algorithm and a fuzzy control algorithm. It can be understood that after obtaining the flight control instruction, the present application uses the target weight control algorithm obtained by combining the initial PID control algorithm and the fuzzy control algorithm to construct an optimized target dynamics model for flight control, which can avoid the problem that the use of the PID control algorithm and the fuzzy algorithm respectively will lead to a decrease in flight control accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0018] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0019] Figure 1 This is the overall flow chart of the flight control method of this application; Figure 2 The dynamic block diagram of the flight control method of this application; Figure 3 Generate a structure diagram for target control parameters of the flight control method of the present application; Figure 4 A schematic diagram of a flow chart provided for the second embodiment of the flight control method of the present application; Figure 5 This is an example diagram of the membership function of the flight control method of this application; Figure 6 This is an example diagram of fuzzy control rules for the flight control method of this application; Figure 7 This is a schematic diagram of the module structure of the flight control device according to an embodiment of the present application; Figure 8 Schematic diagram of the device structure of the hardware operating environment involved in the flight control method in the embodiment of the present application.

[0020] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0021] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0022] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0023] The main solution of the embodiment of the present application is: inputting the error data of the initial dynamic model into a preset fuzzy control algorithm to obtain fuzzy control parameters corresponding to the error data, wherein the initial dynamic model is constructed based on the PID control algorithm; based on the fidelity of the initial dynamic model, determining the initial control parameters of the initial dynamic model and the target weight ratio corresponding to the fuzzy control parameters; based on the initial control parameters, the fuzzy control parameters and the target weight ratio, determining the target control parameters; based on the target control parameters, optimizing the initial dynamic model, and performing flight control based on the optimized target dynamic model.

[0024] In the related technology, the commonly used vertical take-off fixed-wing flight control method is a gain scheduling method based on PID lookup table. This method has a better control effect when the model is relatively accurate. However, if the model is not accurate in the early design stage or is subject to uncertain disturbances during the flight, the accuracy of this method will drop significantly. Fuzzy control does not rely on the model but lacks integral control, and the steady-state error is difficult to eliminate, resulting in low steady-state accuracy of the system.

[0025] After obtaining the flight control instructions, the present application constructs an optimized target dynamics model for flight control through a target weight control algorithm obtained by combining the initial PID control algorithm and the fuzzy control algorithm, thereby avoiding the problem that the use of the PID control algorithm and the fuzzy algorithm respectively will lead to a decrease in flight control accuracy.

[0026] It should be noted that the execution subject of this embodiment can be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, etc. The following takes the flight control device as an example to illustrate this embodiment and the following embodiments.

[0027] Based on this, the present application embodiment provides a flight control method, referring to Figure 1 , Figure 1 This is the overall flow chart of the flight control method of this application.

[0028] In this embodiment, the flight control method includes step S100: In response to the flight control instruction, flight control is performed based on the optimized target dynamics model, wherein the target dynamics model is constructed based on the optimized target weight control algorithm, and the target weight control algorithm is obtained by combining an initial PID control algorithm and a fuzzy control algorithm.

[0029] It should be noted that the execution subject of this embodiment is the flight control device. The flight control device is provided with a dynamic model, referring to Figure 2 , Figure 2A dynamics block diagram is provided, and the dynamics model is built based on the PID control algorithm. After receiving the flight control command, the flight control device will perform flight control based on the optimized target dynamics model.

[0030] In a feasible implementation manner, the following steps are included before step S100: Inputting error data of the initial dynamics model into a preset fuzzy control algorithm to obtain fuzzy control parameters corresponding to the error data, wherein the initial dynamics model is constructed based on the initial PID control algorithm; It should be noted that the error data includes the error value and the error differential The error value is the error between the input signal and the expected value in the PID control algorithm, and the error differential is the rate of change of the error. The initial dynamic model is constructed based on the PID control algorithm without combining fuzzy rules. The flight control equipment calculates the error value of the PID control algorithm in the initial dynamic model. and the error differential After extraction, the fuzzy control parameters are input into the preset fuzzy control algorithm to obtain the fuzzy control parameters. Specifically, the PID control algorithm formula is as follows:

[0031] in, is the output of the controller, It is the error between the input signal of the controller and the expected value, Kp is the proportional coefficient or proportional gain, Ki is the integral coefficient or integral gain, and Kd is the differential coefficient or differential gain.

[0032] It is understandable that due to the large changes in overall parameters of the traditional PID algorithm, a large number of simulations are required for each situation in order to obtain the initial control parameters for different situations. The calculation is large and difficult to implement. Introducing fuzzy algorithm into the traditional PID algorithm can avoid the above problems and improve resource utilization.

[0033] Based on the fidelity of the initial dynamics model, determining the target weight ratio corresponding to the initial control parameters of the initial dynamics model and the fuzzy control parameters; It should be noted that fidelity is the result of the trust judgment of the initial dynamic model, and fidelity includes high fidelity, relatively high fidelity, general fidelity and low fidelity. Fuzzy control parameters are used to correct the gain of the PID controller. The target weight ratio determines the relative importance of the two control methods in the final control decision.

[0034] It is understandable that the flight control device determines the weight ratio of PID control parameters and fuzzy control parameters based on the confidence judgment result of the initial dynamic model. This ratio determines the relative importance of the two control methods in the final control decision.

[0035] Specifically, the definition of fidelity is as follows: High fidelity: The overall parameters and aerodynamic parameters of the model have been tested in wind tunnels or inherited from mature models, and have been verified by a large number of (>100) flight tests; Higher fidelity: Although the overall parameters of the model have not been flight tested, they have not changed much from the mature model and have been flight tested more than 50 times; General fidelity: The overall parameters and aerodynamic parameters of the model are simulation results. The model takes into account the lateral and longitudinal coupling. The model has been verified by more than 10 flight tests. Low fidelity: The overall parameters and aerodynamic parameters of the model are simulation results. The model does not consider the lateral and longitudinal coupling. The model has not been verified by flight tests and is a theoretical model.

[0036] Determining a target control parameter based on the initial control parameter, the fuzzy control parameter and the target weight ratio; It is understandable that the target control parameter is the control parameter for the final flight control. The flight control device performs weighted summation of the PID control parameter and the fuzzy control parameter according to the determined target weight ratio to obtain the final target control parameter, ensuring that the advantages of the two control methods can be fully utilized while avoiding the limitations of a single control method. By adjusting the weight ratio, the stability of PID control and the adaptability of fuzzy control can be flexibly balanced, thereby achieving a better control effect.

[0037] Specifically, refer to Figure 3 , Figure 3 Provides target control parameter generation structure diagram, target control parameter The formula is as follows:

[0038] in, is the weight of the PID control parameter, is the weight of the fuzzy control parameter.

[0039] Based on the target control parameters, the initial dynamics model is optimized to obtain an optimized target dynamics model.

[0040] It should be noted that the target dynamics model is a more accurate dynamics model. The flight control device applies the determined target control parameters to the initial dynamics model and optimizes it. The optimized model should be able to show better control performance under different working conditions, reduce errors and improve system stability. The optimized model can better cope with complex environments and uncertain factors, and provide more accurate and stable flight control.

[0041] In a feasible implementation manner, based on the fidelity of the initial dynamics model, determining the target weight ratio corresponding to the initial control parameters of the initial dynamics model and the fuzzy control parameters comprises the following steps: Based on a preset mapping relationship between the fidelity of the initial dynamics model and the target weight ratio, the initial control parameters of the initial dynamics model and the target weight ratio corresponding to the fuzzy control parameters are determined.

[0042] It is understandable that the target weight ratio is the weight ratio corresponding to the fidelity. After determining the fidelity of the initial dynamics model, the flight control device will directly determine the target weight ratio corresponding to the fidelity through a preset mapping relationship, as shown in Table 1, which is a corresponding relationship table between weight ratio and fidelity.

[0043] Table 1

[0044] In a feasible implementation manner, the target weight ratio includes a first weight of the initial control parameter and a second weight of the fuzzy control parameter. If the fidelity is higher, the first weight of the initial control parameter is higher and the second weight of the fuzzy control parameter is lower. If the fidelity is lower, the first weight of the initial control parameter is lower and the second weight of the fuzzy control parameter is higher.

[0045] It should be noted that the flight control device stores a preset mapping relationship between the fidelity of the initial dynamics model and the target weight ratio. From the corresponding relationship table between the weight ratio and the fidelity, it can be seen that the basic PID control weight a1 is negatively correlated with the fuzzy control weight a2.

[0046] In a feasible implementation manner, based on the target control parameter, the step of optimizing the initial kinetic model comprises the following steps: Based on the target control parameters, the proportion of fuzzy rules in the initial dynamics model is optimized to obtain an optimized target dynamics model.

[0047] It is understandable that the higher the trust in the initial dynamic model of the flight control device, the greater the proportion of PID control in flight control and the smaller the proportion of fuzzy control. Conversely, the lower the trust in the initial dynamic model, the smaller the proportion of PID control in flight control and the greater the proportion of fuzzy control. The proportion of PID control and fuzzy control in flight control is adjusted according to the trust in the initial dynamic model. Then, according to the proportion of PID control and fuzzy control, the optimized target dynamic model is obtained to improve the accuracy of flight control.

[0048] In this implementation, the flight control device selects different weight ratios based on the trustworthiness of the initial dynamics model to determine the proportion of fuzzy rules in the final control, thereby solving the problem that traditional gain scheduling requires a large amount of simulation calculations on the model and requires the model of the controlled aircraft to be highly accurate. However, for large vertical take-off fixed-wing aircraft, the model accuracy established in the early stage of design and without wind tunnel testing is not high, which has a great impact on the control effect of PID. By adding fuzzy control, better control effects can be obtained even when the model is not perfect or the overall parameters change greatly during the mission.

[0049] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction, and will not be described in detail later. Figure 4 Before step S100, the flight control method further includes steps A100 to A300: Step A100, inputting the error parameter and the error differential of the initial dynamics model into a preset fuzzy control algorithm, mapping the error parameter and the error differential through a preset membership function, and obtaining the membership values ​​corresponding to the error parameter and the error differential respectively; It should be noted that the membership function is a mathematical tool for defining membership values. It maps input variables to membership values ​​in the interval [0,1]. The membership function includes the triangular membership function (trimf), which is suitable for simple cases and has a triangular shape, and the Gaussian membership function (gaussmf), which is suitable for smooth transitions and has a Gaussian curve shape. Figure 5 , Figure 5 An example diagram of the membership function is provided. The membership value is used to describe the degree to which an element belongs to a fuzzy set. After receiving the error parameters and error differentials of the dynamic model, the preset fuzzy control algorithm in the flight control device maps the error parameters and error differentials through the preset membership function to obtain the degree to which they belong to a fuzzy set.

[0050] Specifically, before using the preset fuzzy control algorithm, it is necessary to select the domain range of the input and output variables.

[0051] Step A200, based on the membership value, determining the fuzzy variable subsets corresponding to the error parameter and the error differential respectively; It is understandable that the fuzzy variable subset includes NB, NM, NS, Z, PS, PM and PB. The flight control device determines the fuzzy variable subsets corresponding to the error parameters and the error differential according to their membership values.

[0052] Step A300, determining the fuzzy output corresponding to the fuzzy variable subset through a preset fuzzy rule table, and defuzzifying the fuzzy output to obtain fuzzy control parameters.

[0053] It should be noted that the fuzzy output is the output of the preset fuzzy control algorithm. The fuzzy control parameter Kf (Kf includes proportional gain Kpf, integral gain Kif and differential gain Kdf) is used to adjust the gain of the PID controller to improve the control performance. After obtaining the fuzzy variable subsets corresponding to the error parameter and the error differential, the flight control device determines the fuzzy output of the preset fuzzy control algorithm according to the preset fuzzy rule table, and defuzzifies the fuzzy output to obtain the fuzzy control parameter. Figure 6 , Figure 6 Example diagrams of fuzzy control rules are provided.

[0054] Specifically, the preset fuzzy rule table is shown in Table 2: Table 2

[0055] In particular, the flight control device sets an initial parameter for the initial PID control algorithm and builds an initial dynamic model based on the initial PID control algorithm. The flight control device can generate training data through actual flight tests, wind tunnel tests or high-fidelity simulations, and ensure that the training data covers various operating conditions, such as different flight speeds, altitudes and weather conditions, etc. The training data is input into the initial dynamic model for iterative training, and a differentiable objective function is selected to gradually adjust the PID parameters to minimize the error.

[0056] In this embodiment, the flight control device establishes an initial dynamic model based on the PID control algorithm and introduces fuzzy control parameters for the initial dynamic model to achieve better control effects even when the model is not perfect or the overall parameters change greatly during the mission. The fuzzy control parameters are introduced into the basic PID control parameters for optimization, thereby avoiding the shortcomings of fuzzy control and improving the accuracy of the overall flight control.

[0057] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the flight control method of the present application. More simple transformations based on this technical concept are all within the scope of protection of the present application.

[0058] This application also provides a flight control device, please refer to Figure 7 , the flight control device comprises: The control module 10 is used to respond to the flight control instruction and perform flight control based on the optimized target dynamics model, wherein the target dynamics model is constructed based on the optimized target weight control algorithm, and the target weight control algorithm is obtained by combining the initial PID control algorithm and the fuzzy control algorithm.

[0059] Optionally, the control module includes: The optimization submodule is used to input the error data of the initial dynamic model into a preset fuzzy control algorithm to obtain the fuzzy control parameters corresponding to the error data, wherein the initial dynamic model is constructed based on the initial PID control algorithm; based on the fidelity of the initial dynamic model, the initial control parameters of the initial dynamic model and the target weight ratio corresponding to the fuzzy control parameters are determined; based on the initial control parameters, the fuzzy control parameters and the target weight ratio, the target control parameters are determined; based on the target control parameters, the initial dynamic model is optimized to obtain the target dynamic model.

[0060] Optionally, the optimization submodule includes: A mapping unit is used to determine the target weight ratio corresponding to the initial control parameters of the initial dynamics model and the fuzzy control parameters based on a preset mapping relationship between the fidelity of the initial dynamics model and the target weight ratio.

[0061] Optionally, the target weight ratio includes a first weight of the initial control parameter and a second weight of the fuzzy control parameter. If the fidelity is higher, the first weight of the initial control parameter is higher and the second weight of the fuzzy control parameter is lower. If the fidelity is lower, the first weight of the initial control parameter is lower and the second weight of the fuzzy control parameter is higher.

[0062] Optionally, the optimization submodule includes: The model optimization unit is used to optimize the proportion of fuzzy rules in the initial dynamics model based on the target control parameters to obtain an optimized target dynamics model.

[0063] Optionally, the optimization submodule includes: The output unit is used to input the error parameters and error differentials of the initial dynamic model into a preset fuzzy control algorithm, map the error parameters and the error differentials through a preset membership function, and obtain the membership values ​​corresponding to the error parameters and the error differentials respectively; based on the membership values, determine the fuzzy variable subsets corresponding to the error parameters and the error differentials respectively; determine the fuzzy outputs corresponding to the fuzzy variable subsets through a preset fuzzy rule table, and defuzzify the fuzzy outputs to obtain fuzzy control parameters.

[0064] The flight control device provided by the present application adopts the flight control method in the above embodiment to solve the technical problem of flight control. Compared with the prior art, the beneficial effects of the flight control device provided by the present application are the same as the beneficial effects of the flight control method provided by the above embodiment, and other technical features in the flight control device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0065] The present application provides a flight control device, which includes: at least one processor; and a memory that is communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the flight control method in the above-mentioned embodiment one.

[0066] Reference below Figure 8 , which shows a schematic diagram of the structure of a flight control device suitable for implementing an embodiment of the present application. The flight control device in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptops, tablet computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PMPs (Portable Media Players), vehicle terminals (such as vehicle navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 8 The flight control device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0067] like Figure 8As shown, the flight control device may include a processing device 1001 (e.g., a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the flight control device are also stored. The processing device 1001, ROM1002, and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the flight control device to communicate with other devices wirelessly or by wire to exchange data. Although the figure shows a flight control device with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or provided instead.

[0068] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0069] The flight control device provided by the present application adopts the flight control method in the above embodiment to solve the technical problem of flight control. Compared with the prior art, the beneficial effects of the flight control device provided by the present application are the same as the beneficial effects of the flight control method provided by the above embodiment, and the other technical features in the flight control device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0070] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0071] 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.

[0072] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, wherein the computer-readable program instructions are used to execute the flight control method in the above-mentioned embodiment.

[0073] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM: Random Access Memory), a read-only memory (ROM: Read Only Memory), an erasable programmable read-only memory (EPROM: Erasable Programmable Read Only Memory or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM: CD-Read Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency: Radio Frequency), etc., or any suitable combination of the above.

[0074] The computer-readable storage medium may be included in the flight control device; or may exist independently without being assembled into the flight control device.

[0075] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by the flight control device, the flight control device: responds to the flight control instructions and performs flight control based on the optimized target dynamics model, wherein the target dynamics model is constructed based on the optimized target weight control algorithm, and the target weight control algorithm is obtained by combining the initial PID control algorithm and the fuzzy control algorithm.

[0076] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0077] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0078] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0079] The readable storage medium provided in this application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned flight control method, and can solve the technical problems of flight control. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as the beneficial effects of the flight control method provided in the above-mentioned embodiment, and will not be described in detail here.

[0080] The present application also provides a computer program product, comprising a computer program, which implements the steps of the above-mentioned flight control method when executed by a processor.

[0081] The computer program product provided by this application can solve the technical problems of flight control. Compared with the prior art, the beneficial effects of the computer program product provided by this application are the same as the beneficial effects of the flight control method provided by the above embodiment, which will not be repeated here.

[0082] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A flight control method, characterized in that: The flight control method comprises: In response to the flight control instruction, flight control is performed based on the optimized target dynamics model, wherein the target dynamics model is constructed based on the optimized target weight control algorithm, and the target weight control algorithm is obtained by combining an initial PID control algorithm and a fuzzy control algorithm.

2. The flight control method according to claim 1, characterized in that: The step of performing flight control based on the optimized target dynamics model in response to the flight control instruction includes: Inputting error data of the initial dynamics model into a preset fuzzy control algorithm to obtain fuzzy control parameters corresponding to the error data, wherein the initial dynamics model is constructed based on the initial PID control algorithm; Based on the fidelity of the initial dynamics model, determining the target weight ratio corresponding to the initial control parameters of the initial dynamics model and the fuzzy control parameters; Determining a target control parameter based on the initial control parameter, the fuzzy control parameter and the target weight ratio; Based on the target control parameters, the initial dynamics model is optimized to obtain an optimized target dynamics model.

3. The flight control method according to claim 2, characterized in that: The step of determining the target weight ratio corresponding to the initial control parameters of the initial dynamics model and the fuzzy control parameters based on the fidelity of the initial dynamics model comprises: Based on a preset mapping relationship between the fidelity of the initial dynamics model and the target weight ratio, the initial control parameters of the initial dynamics model and the target weight ratio corresponding to the fuzzy control parameters are determined.

4. The flight control method according to claim 2, characterized in that: The target weight ratio includes the first weight of the initial control parameter and the second weight of the fuzzy control parameter. If the fidelity is higher, the first weight of the initial control parameter is higher and the second weight of the fuzzy control parameter is lower. If the fidelity is lower, the first weight of the initial control parameter is lower and the second weight of the fuzzy control parameter is higher.

5. The flight control method according to claim 2, characterized in that: The step of optimizing the initial dynamics model based on the target control parameter comprises: Based on the target control parameters, the proportion of fuzzy rules in the initial dynamics model is optimized to obtain an optimized target dynamics model.

6. The flight control method according to claim 2, characterized in that: The step of inputting the error parameters and error differentials of the initial dynamics model into a preset fuzzy control algorithm to obtain fuzzy control parameters corresponding to the error parameters and error differentials comprises: Inputting the error parameters and error differentials of the initial dynamics model into a preset fuzzy control algorithm, mapping the error parameters and the error differentials through a preset membership function, and obtaining the membership values ​​corresponding to the error parameters and the error differentials respectively; Based on the membership value, determining the fuzzy variable subsets corresponding to the error parameter and the error differential respectively; The fuzzy output corresponding to the fuzzy variable subset is determined through a preset fuzzy rule table, and the fuzzy output is defuzzified to obtain fuzzy control parameters.

7. A flight control device, characterized in that: The device comprises: A control module is used to respond to flight control instructions and perform flight control based on an optimized target dynamics model, wherein the target dynamics model is constructed based on an optimized target weight control algorithm, and the target weight control algorithm is obtained by combining an initial PID control algorithm and a fuzzy control algorithm.

8. A flight control device, characterized in that: The device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the flight control method according to any one of claims 1 to 6.

9. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the flight control method according to any one of claims 1 to 6 are implemented.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the flight control method according to any one of claims 1 to 6 are implemented.

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