A control method and system for satellite navigation-based glide guidance

Abstract

This application relates to the field of glide guidance technology for intelligent unmanned aerial vehicles, and specifically relates to a control method and system for glide guidance based on satellite navigation. The method includes: determining the actual angle of attack of the intelligent unmanned aerial vehicle; determining the flight stability of the intelligent unmanned aerial vehicle at the current moment based on the extreme distribution of the actual flight speeds at all acquisition moments and combining the differences between the actual flight speeds at all adjacent acquisition moments; determining the lift change rate of the intelligent unmanned aerial vehicle at the current moment; determining the ideal angle of attack based on the flight stability, the lift change rate, and the actual angle of attack, and combining the PID control algorithm to adjust the angle of attack in glide guidance. This application improves the accuracy of angle of attack control during the glide guidance of intelligent unmanned aerial vehicles by comprehensively analyzing actual flight data and simulated flight data.

Description

Technical Field

[0001] This application relates to the technical field of glide guidance for intelligent unmanned aerial vehicles, and particularly to a control method and system for glide guidance based on satellite navigation. Background Art

[0002] The basic process of glide guidance for an intelligent unmanned aerial vehicle is to control the stable flight of the vehicle to reach a preset target end point under various process constraint conditions.

[0003] During the glide guidance process of an intelligent unmanned aerial vehicle, the control of the angle of attack is crucial for whether the vehicle can fly stably. During the climbing stage, too large or too small an angle of attack will affect the flight performance of the intelligent unmanned aerial vehicle. An overly large angle of attack easily leads to stall, and the vehicle may lose lift and be unable to maintain flight. At the same time, an overly large angle of attack will also cause an increase in induced drag and frictional drag, reducing the maneuverability and efficiency of the vehicle. An overly small angle of attack may result in insufficient lift to overcome gravity, causing the flight state of the vehicle to become unstable and affecting flight balance and control. When traditionally controlling the angle of attack, only the flight data during the actual flight of the intelligent unmanned aerial vehicle is used to control the angle of attack, lacking comparison with simulation data, and only considering the influence of a single factor of flight speed on the control of the angle of attack, reducing the accuracy of the angle of attack control of the intelligent unmanned aerial vehicle during the climbing stage of the glide guidance process. Summary of the Invention

[0004] In order to solve the above technical problems, the purpose of this application is to provide a control method and system for glide guidance based on satellite navigation, and the specific technical solutions adopted are as follows:

[0005] In the first aspect, an embodiment of this application provides a control method for glide guidance based on satellite navigation, and the method includes the following steps:

[0006] During the climbing stage of the intelligent unmanned aerial vehicle, obtain all types of actual flight data at each acquisition moment within a preset time period before the current moment and all types of flight data under multiple simulations. All types of flight data include the angle of attack, flight speed, and air pressure difference;

[0007] Based on the differences between various types of actual flight data within a preset time period before the current moment and any corresponding type of simulated flight data, determine the flight deviation degree between the actual flight and any simulated flight of the intelligent unmanned aerial vehicle at the current moment, and combine the angles of attack of all simulations at the current moment to determine the actual angle of attack of the intelligent unmanned aerial vehicle at the current moment;

[0008] Determine the flight stability of the intelligent unmanned aerial vehicle at the current moment based on the extreme distribution of the actual flight speeds at all acquisition moments before the current moment, and determine the flight smoothness of the intelligent unmanned aerial vehicle at the current moment in combination with the differences between the actual flight speeds at all adjacent acquisition moments before the current moment;

[0009] Based on the differences in the air pressure differences in any simulation between each acquisition moment before the current moment and the subsequent acquisition moment, determine the rate of change of the air pressure difference at each acquisition moment before the current moment of the intelligent unmanned aerial vehicle, and determine the rate of change of the lift of the intelligent unmanned aerial vehicle at the current moment in combination with the differences in the actual air pressure difference data at all adjacent acquisition moments before the current moment;

[0010] Based on the flight smoothness, the rate of change of the lift, and the actual angle of attack, determine the ideal angle of attack of the intelligent unmanned aerial vehicle at the current moment, and regulate the angle of attack in the climbing stage of the glide guidance in combination with the PID control algorithm.

[0011] Preferably, the method for determining the flight deviation degree between the actual flight and any simulation flight of the intelligent unmanned aerial vehicle at the current moment is as follows:

[0012] In the climbing stage of the intelligent unmanned aerial vehicle, take the sum of the differences between all types of actual flight data and the corresponding types of simulation flight data within a preset time period before the current moment as the flight deviation degree between the actual flight and any simulation flight of the intelligent unmanned aerial vehicle at the current moment in the climbing stage.

[0013] Preferably, the actual angle of attack of the intelligent unmanned aerial vehicle at the current moment is the mean value of the products of the angles of attack of all simulations at the current moment and the corresponding flight deviation degrees.

[0014] Preferably, the flight stability of the intelligent unmanned aerial vehicle at the current moment is the normalized value of the ratio of the minimum value to the range of the actual flight speeds at all acquisition moments before the current moment.

[0015] Preferably, the method for determining the flight smoothness of the intelligent unmanned aerial vehicle at the current moment is as follows:

[0016] Calculate the differences in the actual flight speeds between each acquisition moment before the current moment and the subsequent acquisition moment, calculate the mean value of the differences in the actual flight speeds at all acquisition moments, and take the ratio of the flight stability to the mean value as the flight smoothness of the intelligent unmanned aerial vehicle at the current moment.

[0017] Preferably, the expression for the rate of change of the air pressure difference at each acquisition moment before the current moment of the intelligent unmanned aerial vehicle is: In the formula, A i represents the rate of change of the air pressure difference at the acquisition moment i before the current moment of the intelligent unmanned aerial vehicle; B i,jIt represents the rate of change of the air pressure difference in the j-th simulation between the acquisition time i before the current moment and the next acquisition time; M represents the total number of simulations.

[0018] Preferably, the expression for the lift rate of change of the intelligent unmanned aircraft at the current moment is: In the formula, L represents the lift rate of change of the intelligent unmanned aircraft at the current moment; C i It represents the ratio of the difference between the actual air pressure difference between the acquisition time i before the current moment and the next acquisition time and the air pressure difference at the acquisition time i to the air pressure difference at the acquisition time i; N represents the number of all acquisition times within the preset duration before the current moment; norm() represents the normalization function.

[0019] Preferably, the expression for the ideal angle of attack of the intelligent unmanned aircraft at the current moment is: In the formula, S ′ represents the ideal angle of attack of the intelligent unmanned aircraft at the current moment; S represents the actual angle of attack of the intelligent unmanned aircraft at the current moment; W represents the flight stability of the intelligent unmanned aircraft at the current moment; L represents the lift rate of change of the intelligent unmanned aircraft at the current moment; σ represents the preset first threshold; ε represents the preset second threshold.

[0020] Preferably, the regulation of the angle of attack in the climbing stage of the glide guidance includes:

[0021] In the climbing stage of the glide guidance of the intelligent unmanned aircraft, the difference between the actual angle of attack and the ideal angle of attack of the intelligent unmanned aircraft at the current moment is used as the input of the PID control algorithm, and the angle of attack control signal at the current moment is obtained to regulate the angle of attack at the current moment. Second, the embodiment of the present application also provides a control system for glide guidance based on satellite navigation, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of the control method for glide guidance based on satellite navigation described in any one of the above.

[0022] The present application has at least the following beneficial effects:

[0023] Based on the differences between various actual flight data within the preset duration before the current moment and any corresponding type of simulated flight data, the present application determines the flight deviation degree between the actual flight and any simulated flight of the intelligent unmanned aircraft at the current moment, and combines the angles of attack of all simulations at the current moment to determine the actual angle of attack of the intelligent unmanned aircraft at the current moment. The beneficial effect is that by comparing the differences between the actual flight data and the simulated flight data, the actual flight state of the intelligent unmanned aircraft can be accurately determined, and the angle of attack can be adjusted accordingly, so that the intelligent unmanned aircraft can better adapt to the changing flight conditions and flight requirements;

[0024] Based on the extreme distribution of the actual flight speeds at all acquisition times before the current time, the present application determines the flight stability of the intelligent unmanned aerial vehicle at the current time, and combines the differences between the actual flight speeds at all adjacent acquisition times before the current time to determine the flight smoothness of the intelligent unmanned aerial vehicle at the current time. The beneficial effect is that it can more accurately evaluate the flight situation of the intelligent unmanned aerial vehicle at the current time, providing an important reference basis for more precisely regulating the angle of attack;

[0025] The present application determines the rate of change of the air pressure difference at each acquisition time before the current time by analyzing the differences in the air pressure differences of any simulation between each acquisition time before the current time and the subsequent acquisition time, and combines the differences in the actual air pressure difference data at all adjacent acquisition times before the current time to determine the rate of change of the lift of the intelligent unmanned aerial vehicle at the current time. The beneficial effect is that it can more precisely grasp the change of the lift of the intelligent unmanned aerial vehicle, thereby achieving more precise regulation of the angle of attack;

[0026] The present application determines the ideal angle of attack of the intelligent unmanned aerial vehicle at the current time based on the flight smoothness, the rate of change of the lift, and the actual angle of attack, and combines the PID control algorithm to regulate the angle of attack in glide guidance, improving the control accuracy of the angle of attack in the glide guidance process of the intelligent unmanned aerial vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0028] Figure 1 It is a flowchart of the steps of a control method for glide guidance based on satellite navigation provided by an embodiment of the present application;

[0029] Figure 2 It is a schematic diagram of the process of obtaining the actual angle of attack provided by an embodiment of the present application;

[0030] Figure 3 It is a schematic diagram of the process of extracting the flight smoothness provided by an embodiment of the present application;

[0031] Figure 4 It is a schematic diagram of the process of extracting the rate of change of the lift provided by an embodiment of the present application;

[0032] Figure 5 It is a schematic diagram of the process of obtaining the ideal angle of attack provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0033] In order to further elaborate on the technical means and effects adopted by this application to achieve the intended invention purpose, the following specifically describes, in conjunction with the accompanying drawings and preferred embodiments, a control method and system for satellite navigation-based glide guidance proposed according to this application, including its specific implementation manner, structure, features, and effects, as follows. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0034] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which this application belongs.

[0035] The following specifically describes, in conjunction with the accompanying drawings, the specific solution of a control method and system for satellite navigation-based glide guidance provided by this application.

[0036] Please refer to Figure 1 , which shows a step flow chart of a control method for satellite navigation-based glide guidance provided by an embodiment of this application. The method includes the following steps:

[0037] Step S1: During the climbing stage of the intelligent unmanned aerial vehicle, obtain all types of actual flight data and all types of multiple simulation flight data at each acquisition moment within a preset time period before the current moment.

[0038] When the intelligent unmanned aerial vehicle is flying, it is usually divided into two stages, namely the climbing stage and the gliding stage. The intelligent unmanned aerial vehicle first takes off from the launch platform and uses a booster or rocket engine to provide an initial velocity. When the intelligent unmanned aerial vehicle reaches the preset climbing height, it enters the gliding stage.

[0039] Since the flight process of the intelligent unmanned aerial vehicle is a sequential process, the stage from the start moment of the intelligent unmanned aerial vehicle to the moment when the power device is turned off is the climbing stage.

[0040] Due to the changes in air flow and wind speed in the actual environment, the flight process of the intelligent unmanned aerial vehicle cannot be consistent with the flight process in the simulation process. Therefore, in this embodiment, during the climbing stage of the intelligent unmanned aerial vehicle, all types of actual flight data and multiple all types of simulation flight data at each acquisition moment within a preset time period before the current moment are obtained. All types of flight data include the angle of attack, flight speed, and pressure difference. The angle of attack during the climbing process of the intelligent unmanned aerial vehicle is obtained through an angle-of-attack sensor, the flight speed during the climbing process of the intelligent unmanned aerial vehicle is obtained through a speed sensor, and the pressure difference during the climbing process of the intelligent unmanned aerial vehicle is obtained through a pressure sensor. Various simulation flight data during the simulation process of the intelligent unmanned aerial vehicle are obtained through X-Plane, where the sampling interval is set to T.

[0041] It should be noted that the values of the preset duration t and the sampling interval T are both artificially set. In this embodiment, the value of the preset duration t is 20 s, and the value of the sampling interval T is 1 s. Implementers can also set them by themselves according to specific situations, and this embodiment does not make special restrictions.

[0042] Step S2: Based on the differences between various types of actual flight data and any corresponding type of simulated flight data within the preset duration before the current moment, determine the flight deviation degree between the actual flight and any simulated flight of the intelligent unmanned aerial vehicle at the current moment, and combine the angles of attack of all simulations at the current moment to determine the actual angle of attack of the intelligent unmanned aerial vehicle at the current moment. During the glide guidance process of the intelligent unmanned aerial vehicle, the control of the angle of attack is crucial. An excessive or too small angle of attack will affect the flight performance of the intelligent unmanned aerial vehicle. An excessive angle of attack is likely to cause stall, and the aircraft may lose lift and be unable to maintain flight. At the same time, an excessive angle of attack will also lead to an increase in induced drag and frictional drag, reducing the maneuverability and efficiency of the aircraft. A too small angle of attack may result in insufficient lift to overcome gravity, causing the flight state of the aircraft to become unstable and affecting flight balance and control.

[0043] Due to the changes in airflows and wind speeds in the actual environment, the flight process of the intelligent unmanned aerial vehicle cannot be consistent with the flight process in the simulation process. Therefore, based on the differences between various types of actual flight data and any corresponding type of simulated flight data within the preset duration before the current moment, determine the flight deviation degree between the actual flight and any simulated flight of the intelligent unmanned aerial vehicle at the current moment, and combine the angles of attack of all simulations at the current moment to determine the actual angle of attack of the intelligent unmanned aerial vehicle at the current moment. Specifically:

[0044] During the climbing stage of the intelligent unmanned aerial vehicle, calculate the differences between the actual flight data and the flight data of any simulation among various types of flight data within the preset duration before the current moment, and take the cumulative sum of the differences between the flight data of all types of flight data as the flight deviation degree between the actual flight and any simulated flight of the intelligent unmanned aerial vehicle at the current moment during the climbing stage.

[0045] It should be noted that there are many methods to measure the differences between data groups. In this embodiment, the DTW distance between the actual flight data and the flight data of any simulation in the same type of flight data is calculated to measure the differences between the actual flight data and the corresponding simulated flight data. Implementers can also use other methods to measure the differences between data groups, such as Euclidean distance and Manhattan distance. This embodiment does not make special restrictions on the selection of methods for measuring the differences between data groups.

[0046] Among them, the calculation process of the DTW distance is a well-known technology, and its specific calculation steps will not be elaborated here.

[0047] Further, the actual angle of attack of the intelligent unmanned aerial vehicle at the current moment is the mean value of the products of the angles of attack of all sub-simulations at the current moment and the corresponding flight deviation degrees.

[0048] It can be understood from the actual angle of attack of the intelligent unmanned aerial vehicle at the current moment that the smaller the difference in various flight data between the actual flight and the simulated flight, the higher the accuracy of the actual angle of attack corresponding to the current moment; on the contrary, the larger the difference in various flight data between the actual flight and the simulated flight, the lower the accuracy of the actual angle of attack corresponding to the current moment.

[0049] Preferably, the schematic diagram of the process for obtaining the actual angle of attack provided in this embodiment is as Figure 2 shown.

[0050] Step S3: Based on the extreme distribution of the actual flight speeds at all acquisition moments before the current moment, determine the flight stability of the intelligent unmanned aerial vehicle at the current moment, and combine the differences between the actual flight speeds at all adjacent acquisition moments before the current moment to determine the flight smoothness of the intelligent unmanned aerial vehicle at the current moment.

[0051] The change in flight speed will change the characteristics of the airflow, thereby affecting lift and drag. At low speeds, the airflow is more likely to separate, which may lead to a sharp drop in lift and poor stability. At high speeds, the changes in aerodynamic forces and moments are more sensitive. Therefore, it is necessary to precisely control the angle of attack to maintain stable flight. Based on the extreme distribution of all actual flight speeds within a preset time period before the current moment, determine the flight stability of the intelligent unmanned aerial vehicle at the current moment, and combine the differences between the actual flight speeds at all adjacent acquisition moments within a preset time period before the current moment to determine the flight smoothness of the intelligent unmanned aerial vehicle at the current moment. Specifically:

[0052] (1) Calculate the normalized value of the ratio of the minimum value to the range of the actual flight speeds at all acquisition moments before the current moment, and denote it as the flight stability of the intelligent unmanned aerial vehicle at the current moment;

[0053] (2) Further, calculate the differences in the actual flight speeds at each acquisition moment before the current moment and the next acquisition moment, calculate the mean value of the differences in the actual flight speeds at all acquisition moments, and use the ratio of the flight stability to the mean value as the flight smoothness of the intelligent unmanned aerial vehicle at the current moment.

[0054] Furthermore, based on the flight stability of the intelligent unmanned aerial vehicle at the current moment, it can be understood that the flight stability reflects the degree of fluctuation of the flight speed within a preset period before the current moment. The greater the flight stability, the higher the speed maintained by the intelligent unmanned aerial vehicle for most of the time, with little speed change, relatively stable flight, and the smaller the difference in the actual flight speed at adjacent acquisition moments, indicating that the intelligent unmanned aerial vehicle flies more stably, and the greater the flight smoothness, indicating that the intelligent unmanned aerial vehicle has maintained a relatively stable and uniform flight speed within the preset duration without significant fluctuations or jitters; conversely, the smaller the flight stability, the greater the speed change, unstable flight, and the greater the difference in the actual flight speed at adjacent acquisition moments, indicating that the intelligent unmanned aerial vehicle flies more unstably, and the smaller the flight smoothness, indicating that the intelligent unmanned aerial vehicle has experienced a large speed change within the preset duration.

[0055] Preferably, the schematic diagram of the flight smoothness extraction process provided in this embodiment is as Figure 3 shown.

[0056] Step S4: Based on the difference in the air pressure difference of any simulation between each acquisition moment before the current moment and the next acquisition moment, determine the air pressure difference change rate of each acquisition moment before the current moment of the intelligent unmanned aerial vehicle, and combine the difference in the actual air pressure difference data at all adjacent acquisition moments before the current moment to determine the lift change rate of the intelligent unmanned aerial vehicle at the current moment.

[0057] When the air pressure difference changes, the lift force received by the intelligent unmanned aerial vehicle will also change accordingly. To maintain the stability and performance of the intelligent unmanned aerial vehicle in the air, it may be necessary to adjust the angle of attack to compensate for the change in air pressure difference, thereby maintaining the required lift level. The adjustment of the angle of attack can change the airflow velocity distribution on the upper and lower surfaces of the wing of the intelligent unmanned aerial vehicle, thereby affecting the magnitude of the air pressure difference.

[0058] Therefore, the precise control of the angle of attack is particularly important for the intelligent unmanned aerial vehicle. In order to enable the intelligent unmanned aerial vehicle to maintain the best flight state under different flight environments and mission requirements, based on the difference in the air pressure difference of any simulation between each acquisition moment within a preset duration before the current moment and the next acquisition moment, determine the air pressure difference change rate of each acquisition moment of the intelligent unmanned aerial vehicle at the current moment, and combine the difference in the actual air pressure difference data at all adjacent acquisition moments within a preset duration before the current moment to determine the lift change rate of the intelligent unmanned aerial vehicle at the current moment, so as to precisely control the angle of attack based on the change of the air pressure difference. Specifically:

[0059] (1) Determine the air pressure difference change rate of each acquisition moment before the current moment of the intelligent unmanned aerial vehicle.

[0060] The air pressure difference change rate A of the acquisition moment i before the current moment of the intelligent unmanned aerial vehicle iThe expression is as follows: In the formula, B i,j represents the change rate of the air pressure difference in the jth simulation between the acquisition time i before the current time and the next acquisition time; M represents the total number of simulations.

[0061] It can be understood from the change rate of the air pressure difference at each acquisition time of the intelligent unmanned aerial vehicle at the current time that the greater the change rate of the simulated air pressure difference between adjacent acquisition times, the greater the fluctuation amplitude of the air pressure difference. The greater the change rate of the air pressure difference, the flight efficiency can be improved by appropriately reducing the angle of attack; conversely, the smaller the change rate of the simulated air pressure difference between adjacent acquisition times, the smaller the fluctuation amplitude of the air pressure difference. The smaller the change rate of the air pressure difference, the flight efficiency can be improved by appropriately increasing the angle of attack.

[0062] Among them, the calculation process of the change rate is a well-known technology, and its specific calculation steps will not be elaborated here.

[0063] (2) Determine the change rate of the lift of the intelligent unmanned aerial vehicle at the current time.

[0064] The expression of the change rate of the lift L of the intelligent unmanned aerial vehicle at the current time is as follows: In the formula, C i represents the ratio of the difference between the air pressure difference between the acquisition time i before the current time and the next acquisition time and the actual air pressure difference at the acquisition time i; N represents the number of all acquisition times before the current time; norm() represents the normalization function.

[0065] It can be understood from the change rate of the lift of the intelligent unmanned aerial vehicle at the current time that the greater the change rate of the air pressure difference, the greater the ratio of the difference between the air pressure differences between any acquisition time and the next adjacent acquisition time to the air pressure difference at any acquisition time, then the greater the change rate of the lift of the intelligent unmanned aerial vehicle; conversely, the smaller the change rate of the air pressure difference, the smaller the ratio of the difference between the air pressure differences between any acquisition time and the next adjacent acquisition time to the air pressure difference at any acquisition time, then the smaller the change rate of the lift of the intelligent unmanned aerial vehicle. By combining the simulated flight data with the actual flight data, a more accurate change rate of the lift can be obtained, which helps to improve the accuracy of flight control.

[0066] Preferably, the schematic diagram of the process for extracting the change rate of the lift provided in this embodiment is as Figure 4 shown.

[0067] Step S5: Based on the flight stability, the change rate of the lift, and the actual angle of attack of the intelligent unmanned aerial vehicle at the current time, determine the ideal angle of attack of the intelligent unmanned aerial vehicle at the current time, and combine the PID control algorithm to adjust the angle of attack during the climbing stage in the glide guidance.

[0068] Calculate the ratio of the difference between the pressure difference data between each acquisition moment and the subsequent acquisition moment within a preset duration before the current moment to the pressure difference data at the corresponding acquisition moment, which is denoted as the pressure difference ratio. The lift change rate of the intelligent unmanned aerial vehicle at the current moment is the normalized value of the sum of all the above-mentioned pressure difference ratios before the current moment.

[0069] The expression for the ideal angle of attack of the intelligent unmanned aerial vehicle at the current moment is: In the formula, S ′ represents the ideal angle of attack of the intelligent unmanned aerial vehicle at the current moment; S represents the actual angle of attack data of the intelligent unmanned aerial vehicle at the current moment; W represents the flight stability of the intelligent unmanned aerial vehicle at the current moment; L represents the lift change rate of the intelligent unmanned aerial vehicle at the current moment; σ represents a preset first threshold; ε represents a preset second threshold.

[0070] It should be noted that the values of the preset first threshold and the preset second threshold are both set manually. In this embodiment, the value of the preset first threshold is 0.8, and the value of the preset second threshold is 0.7. Implementers can also set them according to specific situations by themselves, and this embodiment does not make special restrictions.

[0071] Furthermore, in the climbing stage of the gliding guidance of the intelligent unmanned aerial vehicle, the difference between the actual angle of attack and the ideal angle of attack of the intelligent unmanned aerial vehicle at the current moment is used as the input of the PID control algorithm to obtain the angle of attack control signal at the current moment to regulate the angle of attack at the current moment.

[0072] Preferably, the schematic diagram of the process for obtaining the ideal angle of attack provided in this embodiment is as Figure 5 shown.

[0073] Based on the same inventive concept as the above method, an embodiment of the present application also provides a control system for gliding guidance based on satellite navigation, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any one of the above methods for the control method of gliding guidance based on satellite navigation.

[0074] It should be noted that: the above sequence of the embodiments of the present application is only for description and does not represent the superiority or inferiority of the embodiments. And the above describes specific embodiments of this specification. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0075] Each embodiment in this specification is described in a progressive manner. The same or similar parts among the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments.

[0076] The above are only the preferred embodiments of the present application, and are not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present application shall be included within the protection scope of the present application.

Claims

1. A control method for satellite navigation-based glide guidance, characterized in that, The method includes the following steps: During the climbing stage of the intelligent unmanned aerial vehicle, obtain all types of actual flight data at each acquisition moment within a preset duration before the current moment and all types of flight data under multiple simulations. All types of flight data include angle of attack, flight speed, and air pressure difference; Based on the differences between various types of actual flight data within a preset duration before the current moment and any corresponding type of simulated flight data, determine the flight deviation degree between the actual flight and any simulated flight of the intelligent unmanned aerial vehicle at the current moment. Combine the angles of attack of all simulations at the current moment to determine the actual angle of attack of the intelligent unmanned aerial vehicle at the current moment; Based on the extreme distribution of the actual flight speeds at all acquisition moments before the current moment, determine the flight stability of the intelligent unmanned aerial vehicle at the current moment. Combine the differences between the actual flight speeds at all adjacent acquisition moments before the current moment to determine the flight smoothness of the intelligent unmanned aerial vehicle at the current moment; Based on the differences in the air pressure differences of any simulation between each acquisition moment before the current moment and the next acquisition moment, determine the rate of change of the air pressure difference at each acquisition moment before the current moment. Combine the differences in the actual air pressure difference data at all adjacent acquisition moments before the current moment to determine the rate of change of the lift of the intelligent unmanned aerial vehicle at the current moment; Based on the flight smoothness, the rate of change of the lift, and the actual angle of attack, determine the ideal angle of attack of the intelligent unmanned aerial vehicle at the current moment. Combine the PID control algorithm to regulate the angle of attack during the climbing stage of the glide guidance; The expression for the ideal angle of attack of the intelligent unmanned aerial vehicle at the current moment is as follows: In the formula, S ′ represents the ideal angle of attack of the intelligent unmanned aerial vehicle at the current moment; S represents the actual angle of attack of the intelligent unmanned aerial vehicle at the current moment; W represents the flight stability of the intelligent unmanned aerial vehicle at the current moment; L represents the lift change rate of the intelligent unmanned aerial vehicle at the current moment; σ represents a preset first threshold; ε represents a preset second threshold.

2. The control method for satellite navigation-based glide guidance according to claim 1, characterized in that, The method for determining the flight deviation degree between the actual flight and any simulated flight of the intelligent unmanned aerial vehicle at the current moment is: During the climbing stage of the intelligent unmanned aerial vehicle, take the sum of the differences between all types of actual flight data and the corresponding type of simulated flight data within a preset duration before the current moment as the flight deviation degree between the actual flight and any simulated flight of the intelligent unmanned aerial vehicle at the current moment during the climbing stage.

3. A control method for satellite navigation-based glide guidance according to claim 1, characterized in that, The actual angle of attack of the intelligent unmanned aerial vehicle at the current moment is the mean value of the product of the angles of attack of all simulations at the current moment and the corresponding flight deviation degrees.

4. A control method for satellite navigation-based glide guidance according to claim 1, characterized in that, The flight stability of the intelligent unmanned aerial vehicle at the current moment is the normalized value of the ratio of the minimum value to the range of the actual flight speeds at all acquisition moments before the current moment.

5. A control method for satellite navigation-based glide guidance according to claim 1, characterized in that The method for determining the flight smoothness of the intelligent unmanned aerial vehicle at the current moment is: Calculate the differences in the actual flight speeds between each acquisition moment before the current moment and the next acquisition moment. Calculate the mean value of the differences in the actual flight speeds at all acquisition moments. Take the ratio of the flight stability to the mean value as the flight smoothness of the intelligent unmanned aerial vehicle at the current moment.

6. A control method for satellite navigation-based glide guidance according to claim 1, characterized in that, The expression for the rate of change of air pressure difference at each acquisition moment before the current moment of the intelligent unmanned aerial vehicle is as follows: In the formula, A i represents the rate of change of air pressure difference at the acquisition moment i before the current moment of the intelligent unmanned aerial vehicle; B i,j represents the rate of change of air pressure difference at the jth simulation between the acquisition moment i before the current moment and the subsequent acquisition moment; M represents the total number of simulations.

7. A control method for satellite navigation-based glide guidance according to claim 6, characterized in that, The expression for the lift change rate of the intelligent unmanned aerial vehicle at the current moment is as follows: In the formula, L represents the lift change rate of the intelligent unmanned aerial vehicle at the current moment; C i represents the ratio of the difference between the actual air pressure difference between the acquisition moment i before the current moment and the subsequent acquisition moment and the air pressure difference at the acquisition moment i; N represents the number of all acquisition moments within the preset duration before the current moment; norm() represents the normalization function.

8. A control method for satellite navigation-based glide guidance according to claim 1, characterized in that, The regulation of the angle of attack during the climbing stage of the glide guidance includes: During the climbing stage of the glide guidance of the intelligent unmanned aerial vehicle, take the difference between the actual angle of attack and the ideal angle of attack of the intelligent unmanned aerial vehicle at the current moment as the input of the PID control algorithm, and obtain the angle of attack control signal at the current moment to regulate the angle of attack at the current moment.

9. A control system for satellite navigation-based glide guidance, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the control method for glide guidance based on satellite navigation according to any one of claims 1-8.

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