Gliding guidance control method and system based on satellite navigation

Abstract

The invention relates to the technical field of gliding guidance of intelligent unmanned aerial vehicles, in particular to a gliding guidance control method and system based on satellite navigation, and the method comprises the steps: determining an actual attack angle of an intelligent unmanned aerial vehicle; determining the flight stability of the intelligent unmanned aerial vehicle at the current moment by combining the difference between the actual flight speeds at all adjacent collection moments based on the extreme distribution condition of the actual flight speeds at all collection moments; determining the lift force change rate of the intelligent unmanned aerial vehicle at the current moment; and determining an ideal attack angle based on the flight stability, the lift force change rate and the actual attack angle, and regulating and controlling the attack angle in gliding guidance in combination with a PID control algorithm. According to the method, the actual flight data and the simulated flight data are comprehensively analyzed, so that the attack angle control precision in the gliding guidance process of the intelligent unmanned aerial vehicle is improved.

Description

Technical Field

[0001] The present application relates to the technical field of gliding guidance of intelligent unmanned aerial vehicles, and in particular to a control method and system for gliding guidance based on satellite navigation. Background Art

[0002] The basic process of gliding guidance of intelligent unmanned aerial vehicles is to control the aircraft to fly stably to reach the preset target end point while satisfying various process constraints.

[0003] During the gliding guidance process of intelligent unmanned aerial vehicles, the control of the angle of attack is crucial to whether the aircraft can fly stably. During the climbing phase, an angle of attack that is too large or too small will affect the flight performance of the intelligent unmanned aerial vehicle. An angle of attack that is too large can easily lead to stalling, and the aircraft may lose lift, resulting in the inability to maintain flight. At the same time, an excessively large angle of attack will also increase induced drag and friction drag, reducing the maneuverability and efficiency of the aircraft. An angle of attack that is too small may result in insufficient lift to overcome gravity, causing the flight state of the aircraft to become unstable, affecting the balance and control of the flight. Traditionally, the angle of attack is controlled only based on the flight data of the intelligent unmanned aerial vehicle during actual flight, lacking comparison with simulation data, and only considering the influence of the single factor of flight speed on the angle of attack control, which reduces the accuracy of the intelligent unmanned aerial vehicle's angle of attack control during the climbing phase of the gliding 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 gliding guidance based on satellite navigation. The technical solutions adopted are as follows:

[0005] In a first aspect, an embodiment of the present application provides a control method for gliding guidance based on satellite navigation, the method comprising the following steps:

[0006] During the climbing phase of the intelligent unmanned aerial vehicle, all types of actual flight data at each collection moment within a preset time before the current moment and all types of flight data under multiple simulations are obtained, and all types of flight data include angle of attack, flight speed and pressure difference;

[0007] Based on the difference between various types of actual flight data and any corresponding type of simulated flight data within a preset time before the current moment, the flight deviation between the actual flight of the intelligent unmanned aerial vehicle at the current moment and any simulated flight is determined, and the actual angle of attack of the intelligent unmanned aerial vehicle at the current moment is determined by combining the angles of attack of all simulations at the current moment;

[0008] Based on the extreme distribution of the actual flight speeds at all the collection moments before the current moment, the flight stability of the intelligent unmanned aerial vehicle at the current moment is determined, and combined with the difference between the actual flight speeds at all adjacent collection moments before the current moment, the flight stability of the intelligent unmanned aerial vehicle at the current moment is determined;

[0009] Based on the difference in the pressure difference of any simulation between each collection moment before the current moment and the next collection moment, determine the pressure difference change rate of the intelligent unmanned aerial vehicle at each collection moment before the current moment, and combine the difference in the actual pressure difference data at all adjacent collection moments before the current moment to determine the lift change rate of the intelligent unmanned aerial vehicle at the current moment;

[0010] Based on the flight stability, the lift change rate and the actual angle of attack, the ideal angle of attack of the intelligent unmanned aerial vehicle at the current moment is determined, and the angle of attack in the climbing stage of gliding guidance is regulated in combination with a PID control algorithm.

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

[0012] During the climbing phase of the intelligent unmanned aerial vehicle, the cumulative sum of the differences between all types of actual flight data and the corresponding types of simulated flight data within a preset time before the current moment is taken as the flight deviation degree between the actual flight at the current moment and any simulated flight during the climbing phase of the intelligent unmanned aerial vehicle.

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

[0014] Preferably, the flight stability of the intelligent unmanned aerial vehicle at the current moment is a 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 stability of the intelligent unmanned aerial vehicle at the current moment is:

[0016] The difference in actual flight speed between each collection moment before the current moment and the next collection moment is calculated, the average of the difference in actual flight speed at all collection moments is calculated, and the ratio of the flight stability to the average is used as the flight stability of the intelligent unmanned aerial vehicle at the current moment.

[0017] Preferably, the expression of the change rate of the air pressure difference at each collection time before the current time of the intelligent unmanned aerial vehicle is: In the formula, A i B represents the rate of change of the air pressure difference at the time i collected by the intelligent unmanned aerial vehicle before the current time; i,jIt represents the rate of change of the pressure difference of the jth simulation between the acquisition time i before the current moment and the acquisition time after it; M represents the total number of simulations.

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

[0019] Preferably, the expression of 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 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 the preset first threshold; ε represents the preset second threshold.

[0020] Preferably, the controlling of the angle of attack during the climbing phase of the gliding guidance comprises:

[0021] In the climbing phase of the gliding guidance of the intelligent unmanned aerial vehicle, the difference between the actual angle of attack of the intelligent unmanned aerial vehicle at the current moment and the ideal angle of attack is used as the input of the PID control algorithm, and the angle of attack control signal at the current moment is obtained to adjust the angle of attack at the current moment. In a second aspect, 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, and when the processor executes the computer program, the steps of the control method for gliding guidance based on satellite navigation described in any one of the above are implemented.

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

[0023] The present application determines the flight deviation between the actual flight of the intelligent unmanned aerial vehicle at the current moment and any simulated flight based on the difference between various types of actual flight data and any corresponding type of simulated flight data within a preset time period before the current moment, and determines the actual angle of attack of the intelligent unmanned aerial vehicle at the current moment in combination with the angle of attack of all simulations at the current moment. The beneficial effect is that by comparing the difference between the actual flight data and the simulated flight data, the actual flight state of the intelligent unmanned aerial vehicle is accurately determined, and the angle of attack is adjusted accordingly, so that the intelligent unmanned aerial vehicle can better adapt to the changing flight conditions and flight requirements;

[0024] This application determines the flight stability of the intelligent unmanned aerial vehicle at the current moment based on the extreme distribution of the actual flight speed at all acquisition moments before the current moment, and determines the flight stability of the intelligent unmanned aerial vehicle at the current moment by combining the difference between the actual flight speeds at all adjacent acquisition moments before the current moment. The beneficial effect is that the flight situation of the intelligent unmanned aerial vehicle at the current moment can be more accurately evaluated, providing an important reference for more precise control of the angle of attack;

[0025] The present application determines the pressure difference change rate of the intelligent unmanned aerial vehicle at each collection moment before the current moment by analyzing the difference in the pressure difference of any simulation between each collection moment before the current moment and the next collection moment, and determines the lift change rate of the intelligent unmanned aerial vehicle at the current moment by combining the difference in the actual pressure difference data at all adjacent collection moments before the current moment. The beneficial effect is that the lift change of the intelligent unmanned aerial vehicle can be more accurately grasped, thereby achieving more precise control of the angle of attack;

[0026] The present application determines the ideal angle of attack of the intelligent unmanned aerial vehicle at the current moment based on the flight stability, the lift change rate and the actual angle of attack, and adjusts the angle of attack in gliding guidance in combination with a PID control algorithm, thereby improving the accuracy of angle of attack control during the gliding 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 drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0028] Figure 1 A flowchart of a control method for gliding guidance based on satellite navigation provided in one embodiment of the present application;

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

[0030] Figure 3 A schematic diagram of a flight stability extraction process provided by an embodiment of the present application;

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

[0032] Figure 5 A schematic diagram of the ideal angle of attack acquisition process provided for one embodiment of the present application. DETAILED DESCRIPTION

[0033] In order to further explain the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the following is a detailed description of the control method and system of gliding guidance based on satellite navigation proposed in the present application, its specific implementation method, structure, features and effects, in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0034] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0035] The following is a detailed description of a specific solution of a gliding guidance control method and system based on satellite navigation provided by the present application in conjunction with the accompanying drawings.

[0036] See also Figure 1 , which shows a flow chart of the steps of a control method of gliding guidance based on satellite navigation provided by an embodiment of the present application, the method comprising the following steps:

[0037] Step S1: During the climbing phase of the intelligent unmanned aerial vehicle, all types of actual flight data and all types of multiple simulated flight data at each collection time within a preset time period before the current time are obtained.

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

[0039] Since the flight process of the intelligent unmanned aerial vehicle is a time sequence process, the stage from the moment the intelligent unmanned aerial vehicle is started to the moment the power device of the intelligent unmanned aerial vehicle is shut down is the climbing stage.

[0040] Due to the changes in airflow 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 the climbing stage of the intelligent unmanned aerial vehicle, this embodiment obtains all types of actual flight data and multiple types of simulated flight data at each collection time within a preset time before the current moment. All types of flight data include angle of attack, flight speed and air pressure difference. The angle of attack during the climbing process of the intelligent unmanned aerial vehicle is obtained through the angle of attack sensor, the flight speed during the climbing process of the intelligent unmanned aerial vehicle is obtained through the speed sensor, and the air pressure difference during the climbing process of the intelligent unmanned aerial vehicle is obtained through the air pressure sensor. Various types of simulated flight data in the simulation process of the intelligent unmanned aerial vehicle are obtained through X-Plane, wherein the sampling interval is set to T.

[0041] It should be noted that the values ​​of the preset time length t and the sampling interval T are both manually set. In this embodiment, the value of the preset time length t is 20s, and the value of the sampling interval T is 1s. The implementer can also set them according to the specific situation. This embodiment does not impose any special restrictions.

[0042] Step S2: Based on the difference between various types of actual flight data and any corresponding type of simulated flight data within a preset time before the current moment, determine the flight deviation between the actual flight of the intelligent unmanned aerial vehicle at the current moment and any simulated flight, 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. In the gliding guidance process of the intelligent unmanned aerial vehicle, the control of the angle of attack is crucial. Too large or too small an angle of attack will affect the flight performance of the intelligent unmanned aerial vehicle. Too large an angle of attack can easily lead to stalling, and the aircraft may lose lift, resulting in the inability to maintain flight. At the same time, too large an angle of attack will also lead to an increase in induced drag and friction drag, reducing the maneuverability and efficiency of the aircraft. Too small an angle of attack may result in insufficient lift to overcome gravity, causing the flight state of the aircraft to become unstable, affecting the balance and control of the flight.

[0043] Due to the changes in airflow 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, according to the difference between various types of actual flight data and any corresponding type of simulated flight data within the preset time before the current moment, the flight deviation between the actual flight of the intelligent unmanned aerial vehicle at the current moment and any simulated flight is determined. Combined with the angle of attack of all simulations at the current moment, the actual angle of attack of the intelligent unmanned aerial vehicle at the current moment is determined, specifically:

[0044] During the climbing phase of the intelligent unmanned aerial vehicle, the difference between the actual flight data and any simulated flight data in various types of flight data within a preset time period before the current moment is calculated, and the cumulative sum of the differences between the flight data of all types of flight data is used as the flight deviation degree between the actual flight at the current moment and any simulated flight during the climbing phase of the intelligent unmanned aerial vehicle.

[0045] It should be noted that there are many methods for measuring the differences between data groups. In this embodiment, the difference between the actual flight data and the corresponding simulated flight data is measured by calculating the DTW distance between the actual flight data and any simulated flight data in the same type of flight data. The implementer may also use other methods for measuring the differences between data groups, such as Euclidean distance and Manhattan distance. This embodiment does not impose any special restrictions on the selection of methods for measuring the differences between data groups.

[0046] The calculation process of the DTW distance is a well-known technology, and the specific calculation steps are not repeated here.

[0047] Furthermore, the actual angle of attack of the intelligent unmanned aerial vehicle at the current moment is the average of the products of all simulated angles of attack at the current moment and the corresponding flight deviation.

[0048] According to the actual angle of attack of the intelligent unmanned aerial vehicle at the current moment, it can be understood that the smaller the difference between various flight data between the actual flight and the simulated flight, the higher the accuracy of the actual angle of attack at the current moment; conversely, the greater the difference between various flight data between the actual flight and the simulated flight, the lower the accuracy of the actual angle of attack at the current moment.

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

[0050] Step S3: Based on the extreme distribution of the actual flight speeds at all collection 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 collection moments before the current moment to determine the flight stability of the intelligent unmanned aerial vehicle at the current moment.

[0051] Changes in flight speed will change the characteristics of airflow, thereby affecting lift and drag. At low speeds, airflow is more likely to separate, which may cause a sharp drop in lift and poor stability. At high speeds, changes in aerodynamic force and torque are more sensitive, so it is necessary to accurately control the angle of attack to maintain stable flight. According to the extreme distribution of all actual flight speeds within the preset time before the current moment, the flight stability of the intelligent unmanned aerial vehicle at the current moment is determined. Combined with the difference between the actual flight speeds at all adjacent collection moments within the preset time before the current moment, the flight stability of the intelligent unmanned aerial vehicle at the current moment is determined. Specifically:

[0052] (1) Calculate the normalized value of the minimum value and the range ratio of the actual flight speed at all acquisition times before the current time, and record it as the flight stability of the intelligent unmanned aerial vehicle at the current time;

[0053] (2) Further, the difference between the actual flight speed at each collection moment before the current moment and the next collection moment is calculated, the average of the actual flight speed differences at all collection moments is calculated, and the ratio of the flight stability to the average is used as the flight stability of the intelligent unmanned aerial vehicle at the current moment.

[0054] Furthermore, according to 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 in the preset time period before the current moment. The greater the flight stability, the intelligent unmanned aerial vehicle has maintained a higher speed for most of the time, and the speed does not change much, the flight is relatively stable, and the smaller the difference in actual flight speeds at adjacent collection moments, the more stable the flight of the intelligent unmanned aerial vehicle, the greater the flight stability, indicating that the intelligent unmanned aerial vehicle has maintained a relatively stable and uniform flight speed within the preset time period without violent fluctuations or jitters; conversely, the smaller the flight stability, the greater the speed change, the flight is unstable, and the greater the difference in actual flight speeds at adjacent collection moments, the more unstable the flight of the intelligent unmanned aerial vehicle, the smaller the flight stability, indicating that the intelligent unmanned aerial vehicle has experienced a large speed change within the preset time period.

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

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

[0057] When the pressure difference changes, the lift on the smart unmanned aerial vehicle will also change. In order to maintain the stability and performance of the smart unmanned aerial vehicle in the air, it may be necessary to compensate for the change in the pressure difference by adjusting the angle of attack to maintain the required lift level. Adjusting the angle of attack can change the airflow velocity distribution on the upper and lower surfaces of the smart unmanned aerial vehicle's wings, thereby affecting the size of the pressure difference.

[0058] Therefore, precise control of the angle of attack is particularly important for intelligent unmanned aerial vehicles. In order to enable the intelligent unmanned aerial vehicle to maintain the best flight state under different flight environments and mission requirements, the pressure difference change rate of the intelligent unmanned aerial vehicle at each collection moment at the current moment is determined based on the difference in any simulated pressure difference between each collection moment within the preset time length before the current moment and the next collection moment, and the lift change rate of the intelligent unmanned aerial vehicle at the current moment is determined in combination with the difference in actual pressure difference data at all adjacent collection moments within the preset time length before the current moment, so as to accurately control the angle of attack based on the change in pressure difference. Specifically:

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

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

[0061] According to the pressure difference change rate of the intelligent unmanned aerial vehicle at each collection moment at the current moment, it can be understood that the greater the change rate of the simulated pressure difference between adjacent collection moments, the greater the pressure difference fluctuation amplitude and the greater the pressure difference change rate, and the flight efficiency can be improved by appropriately reducing the angle of attack; conversely, the smaller the change rate of the simulated pressure difference between adjacent collection moments, the smaller the pressure difference fluctuation amplitude and the smaller the pressure difference change rate, and the flight efficiency can be improved by appropriately increasing the angle of attack.

[0062] The calculation process of the change rate is a well-known technology, and the specific calculation steps are not repeated here.

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

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

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

[0066] Preferably, the lift change rate extraction process schematic diagram provided in this embodiment is as follows: Figure 4 shown.

[0067] Step S5: Based on the flight stability, lift change rate and actual angle of attack of the intelligent unmanned aerial vehicle at the current moment, determine the ideal angle of attack of the intelligent unmanned aerial vehicle at the current moment, and adjust the angle of attack in the climbing phase of the gliding guidance in combination with the PID control algorithm.

[0068] The ratio of the difference in pressure difference data between each collection moment and the next collection moment within a preset time period before the current moment to the pressure difference data at the corresponding collection moment is calculated and recorded 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 cumulative sum of all the pressure difference ratios before the current moment.

[0069] The ideal angle of attack of the intelligent unmanned aerial vehicle at the current moment is expressed as: In the formula, S ′ It 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 the preset first threshold value; ε represents the preset second threshold value.

[0070] It should be noted that the values ​​of the preset first threshold and the preset second threshold are both manually set. In this embodiment, the head office presets the value of the first threshold to be 0.8, and the value of the preset second threshold to be 0.7. The implementer can also set them according to the specific situation. This embodiment does not impose any special restrictions.

[0071] Furthermore, in the climbing phase of the gliding guidance of the intelligent unmanned aerial vehicle, the difference between the actual angle of attack of the intelligent unmanned aerial vehicle at the current moment and the ideal angle of attack 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.

[0072] Preferably, the schematic diagram of the ideal angle of attack acquisition process provided in this embodiment is as follows: 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, and when the processor executes the computer program, the steps of any one of the above-mentioned methods for gliding guidance based on satellite navigation are implemented.

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

[0075] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0076] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present application should be included in the protection scope of the present application.

Claims

1. A control method for gliding guidance based on satellite navigation, characterized in that: The method comprises the following steps: During the climbing phase of the intelligent unmanned aerial vehicle, all types of actual flight data at each collection moment within a preset time before the current moment and all types of flight data under multiple simulations are obtained, and all types of flight data include angle of attack, flight speed and pressure difference; Based on the difference between various types of actual flight data and any corresponding type of simulated flight data within a preset time before the current moment, the flight deviation between the actual flight of the intelligent unmanned aerial vehicle at the current moment and any simulated flight is determined, and the actual angle of attack of the intelligent unmanned aerial vehicle at the current moment is determined by combining the angles of attack of all simulations at the current moment; Based on the extreme distribution of the actual flight speeds at all the collection moments before the current moment, the flight stability of the intelligent unmanned aerial vehicle at the current moment is determined, and combined with the difference between the actual flight speeds at all adjacent collection moments before the current moment, the flight stability of the intelligent unmanned aerial vehicle at the current moment is determined; Based on the difference in the pressure difference of any simulation between each collection moment before the current moment and the next collection moment, determine the pressure difference change rate of the intelligent unmanned aerial vehicle at each collection moment before the current moment, and combine the difference in the actual pressure difference data at all adjacent collection moments before the current moment to determine the lift change rate of the intelligent unmanned aerial vehicle at the current moment; Based on the flight stability, the lift change rate and the actual angle of attack, the ideal angle of attack of the intelligent unmanned aerial vehicle at the current moment is determined, and the angle of attack in the climbing stage of gliding guidance is regulated in combination with a PID control algorithm.

2. A control method for gliding guidance based on satellite navigation as claimed in claim 1, characterized in that: The method for determining the flight deviation between the actual flight of the intelligent unmanned aerial vehicle at the current moment and any simulated flight is as follows: During the climbing phase of the intelligent unmanned aerial vehicle, the cumulative sum of the differences between all types of actual flight data and the corresponding types of simulated flight data within a preset time before the current moment is taken as the flight deviation degree between the actual flight at the current moment and any simulated flight during the climbing phase of the intelligent unmanned aerial vehicle.

3. The control method of gliding guidance based on satellite navigation as claimed in claim 1, characterized in that: The actual angle of attack of the intelligent unmanned aerial vehicle at the current moment is the average of the products of all simulated angles of attack at the current moment and the corresponding flight deviation.

4. The control method of gliding guidance based on satellite navigation as claimed in 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 extreme difference of the actual flight speed at all acquisition moments before the current moment.

5. The control method of gliding guidance based on satellite navigation as claimed in claim 1, characterized in that: The method for determining the flight stability of the intelligent unmanned aerial vehicle at the current moment is: The difference in actual flight speed between each collection moment before the current moment and the next collection moment is calculated, the average of the difference in actual flight speed at all collection moments is calculated, and the ratio of the flight stability to the average is used as the flight stability of the intelligent unmanned aerial vehicle at the current moment.

6. The control method of gliding guidance based on satellite navigation as claimed in claim 1, characterized in that: The expression of the change rate of the air pressure difference at each collection time before the current time of the intelligent unmanned aerial vehicle is: In the formula, A i B represents the rate of change of the air pressure difference at the time i collected by the intelligent unmanned aerial vehicle before the current time; i,j It represents the rate of change of the pressure difference of the jth simulation between the acquisition time i before the current moment and the acquisition time after it; M represents the total number of simulations.

7. A control method for gliding guidance based on satellite navigation as claimed in claim 6, characterized in that: The expression of the lift change rate of the intelligent unmanned aerial vehicle at the current moment is: Where, L represents the lift change rate of the intelligent unmanned aerial vehicle at the current moment; C i It represents the ratio of the difference between the actual air pressure difference at the acquisition time i before the current moment and the next acquisition time to the air pressure difference at the acquisition time i; N represents the number of all acquisition times within the preset time before the current moment; norm() represents the normalization function.

8. The control method of gliding guidance based on satellite navigation as claimed in claim 1, characterized in that: The expression of 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 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 the preset first threshold; ε represents the preset second threshold.

9. The control method of gliding guidance based on satellite navigation as claimed in claim 1, characterized in that: The control of the angle of attack during the climbing phase of the gliding guidance comprises: In the climbing phase of the gliding guidance of the intelligent unmanned aerial vehicle, the difference between the actual angle of attack of the intelligent unmanned aerial vehicle at the current moment and the ideal angle of attack is used as the input of the PID control algorithm to obtain the current angle of attack control signal to regulate the current angle of attack.

10. A gliding guidance control system based on satellite navigation, 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, the steps of the control method of gliding guidance based on satellite navigation as described in any one of claims 1-9 are implemented.

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