High-speed stable flight control method for long-endurance variant unmanned aerial vehicle

Abstract

The invention discloses a high-speed stable flight control method for a long-endurance variant unmanned aerial vehicle, and relates to the field of unmanned aerial vehicle control. According to the method, a longitudinal nonlinear kinetic equation after deformation of the variant unmanned aerial vehicle is firstly established, then the longitudinal nonlinear kinetic equation is represented in a nonlinear system form, and then speed and attitude decoupling is performed on a nonlinear control model of the variant unmanned aerial vehicle represented in the nonlinear system form based on a superhelix algorithm. And controlling the deformed variant unmanned aerial vehicle by using the speed control sub-model and the attitude control sub-model obtained by decoupling. According to the method, the aerodynamic performance change after the deformation of the variant unmanned aerial vehicle is accurately described by establishing the longitudinal nonlinear kinetic equation, and the high-speed stable control problem after the deformation of the variant unmanned aerial vehicle is solved through the speed control sub-model and the attitude control sub-model based on the superhelix algorithm; according to the invention, high-speed stable control after deformation of the variant unmanned aerial vehicle is realized.

Description

Technical Field

[0001] The present application relates to the field of unmanned aerial vehicle control, and in particular to a high-speed and stable flight control method for a long-flight variant unmanned aerial vehicle. Background Art

[0002] A morphing UAV is an unmanned aerial vehicle that changes its entire configuration through materials, structures, mechanisms, advanced flow and flight control to adapt to different mission requirements and achieve optimal performance under different flight conditions. The main way for a morphing UAV to deform is to change the shape of the wing. Common forms include telescopic wings, folding wings, inflatable wings and "sliding skins". Among them, the telescopic wing-shaped morphing UAV has a more outstanding ability to change the wing area and aspect ratio, and has a significant impact on the aircraft's endurance performance. It is one of the main development directions of morphing technology. The morphing UAV can adjust the wing area, aspect ratio, and sweep angle parameters through the deformation of structures such as wings to adapt to different flight speeds, thereby meeting the design requirements of expanding the speed range of the UAV. The deformation of a morphing UAV will cause a significant change in its aerodynamic characteristics. The deformation process has highly nonlinear characteristics. The existing control method cannot achieve high-speed and stable control of the morphing UAV after deformation. Summary of the invention

[0003] The purpose of this application is to provide a high-speed and stable flight control method for a long-flight variant UAV, so as to achieve high-speed and stable control of the variant UAV after deformation.

[0004] To achieve the above objectives, this application provides the following solutions.

[0005] The present application provides a high-speed and stable flight control method for a long-flight variant UAV, comprising the following steps.

[0006] Construct the longitudinal nonlinear dynamic equations of the deformed UAV.

[0007] The longitudinal nonlinear dynamic equation is expressed in the form of a nonlinear system to obtain a nonlinear control model of the variant UAV.

[0008] Based on the super-helix algorithm, the nonlinear control model of the variant UAV is decoupled into a speed control sub-model and an attitude control sub-model.

[0009] The deformed variant UAV is controlled according to the speed control sub-model and the attitude control sub-model.

[0010] According to the specific embodiments provided in this application, this application has the following technical effects.

[0011] The present application provides a method for high-speed and stable flight control of a long-flight variant UAV. The present application first establishes a longitudinal nonlinear dynamic equation of the variant UAV after deformation, and then expresses the longitudinal nonlinear dynamic equation in the form of a nonlinear system to obtain a nonlinear control model of the variant UAV. Then, based on a superhelix algorithm, the speed and attitude of the nonlinear control model of the variant UAV are decoupled, and the speed control sub-model and attitude control sub-model obtained by decoupling are used to control the deformed variant UAV. The present application establishes a longitudinal nonlinear dynamic equation to accurately describe the change in aerodynamic performance of the variant UAV after deformation, and designs a speed control sub-model and an attitude control sub-model based on the superhelix algorithm for achieving high-speed and stable flight of the UAV after the mode transition, thereby solving the problem of high-speed and stable control of the variant UAV after deformation. The present application realizes high-speed and stable control of the variant UAV after deformation. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] 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 will be 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 paying creative work.

[0013] Figure 1 A flowchart of a high-speed and stable flight control method for a long-flight variant UAV provided in one embodiment of the present application.

[0014] Figure 2 A schematic diagram of a high-speed and stable flight control method for a long-flight variant UAV provided in one embodiment of the present application. DETAILED DESCRIPTION

[0015] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0016] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0017] In an exemplary embodiment, in order to overcome the nonlinear system control problem caused by the change of aerodynamic characteristics after the deformation of the deformable UAV, the present invention proposes a high-speed and stable flight control method for a long-flight deformable UAV, such as Figure 1 and Figure 2As shown, the process includes the following steps 101 to 104.

[0018] Step 101, constructing the longitudinal nonlinear dynamic equation of the deformed UAV.

[0019] Step 102: The longitudinal nonlinear dynamic equation is expressed in a nonlinear system form to obtain a nonlinear control model of the variant UAV.

[0020] Step 103, based on the super helix algorithm, decouple the nonlinear control model of the variant UAV into a speed control sub-model and an attitude control sub-model.

[0021] Step 104: Control the deformed variant UAV according to the speed control sub-model and the attitude control sub-model.

[0022] Implementing the above steps 101 to 104 can achieve high-speed stable control of the deformed UAV after deformation.

[0023] In an exemplary embodiment, based on the traditional UAV dynamics equation and combined with the additional torque caused by the change in aerodynamic performance of the variant UAV after deformation, the longitudinal nonlinear dynamics equation of the variant UAV after deformation is derived, that is, the longitudinal nonlinear dynamics equation constructed in the above step 101.

[0024] The longitudinal nonlinear dynamic equation is shown in equation (1).

[0025] (1).

[0026] in, is the flight speed of the variant drone; for The first derivative of , characterizes the flight acceleration of the variant UAV; for The first derivative of is the flight altitude of the variant drone; is the pitch angle of the variant drone, for The first derivative of ; is the angle of attack of the variant drone, for The first derivative of ; is the pitch angular velocity of the variant drone, for The first derivative of ; is the resistance of the variant drone during flight. is the deformation parameter of the variant drone, is the engine thrust of the variant drone, , is the engine inference coefficient of the variant UAV, Indicates the throttle amount. is the quality of the variant drone, is the acceleration due to gravity, is the flight path angle of the variant drone, For the transformation process of the variant drone Inertial force generated by the shaft; is the lift of the variant UAV during flight. For the transformation process of the variant drone Inertial force generated by the shaft; is the pitch axis inertia moment of the variant UAV, for The first derivative of For variant drones Static moment of the shaft, is the pitch moment of the variant UAV during flight, For the transformation process of the variant drone The moment of inertia of the axis, This is the engine axis position of the variant UAV.

[0027] Among the above parameters, the flight acceleration of the variant drone Measured by a three-axis accelerometer; flight speed of the variant drone Obtained by integrating acceleration data; Flight altitude of variant drone Measured by the barometric altimeter; pitch angular velocity of the variant drone Measured by a three-axis gyroscope; the flight angle of attack of the variant drone , Pitch angle and flight path angle Obtained by integrating the angular acceleration data measured by the three-axis gyroscope; Variant UAV mass , pitch axis moment of inertia of variant drone , Engine axis position of variant UAV And the static moment of the variant drone These are all UAV design parameters.

[0028] The variant drone in formula (1) is deformed during the deformation process. Inertial force generated by the shaft , the variant drone is around during the deformation process Inertial force generated by the shaft And the variant drone is around during the deformation process Moment of inertia of the axis The additional force and additional torque on the UAV after the deformation of the variant UAV are characterized and can be calculated using formula (2).

[0029] (2).

[0030] in, for The first derivative of for The second derivative of .

[0031] Variant of formula (1) Lift of the drone during flight , resistance of the variant drone during flight And the pitch moment of the variant drone during flight It can be calculated by formula (3).

[0032] (3).

[0033] in, is the atmospheric density, is the wing area of ​​the variant UAV, For the deformation parameters of the variant drone The lift coefficient, For the deformation parameters of the variant drone The drag coefficient, For the deformation parameters of the variant drone The pitching moment coefficient, is the average aerodynamic chord length of the variant UAV.

[0034] Among the above parameters, and These are the design parameters of variant UAVs; It is about the flight altitude of the variant drone The function can be used to change the flight height of the drone Calculated; It can represent the wingspan, sweep angle, etc., which can be determined based on the deformation characteristics of the actual variant UAV.

[0035] Furthermore, in the above formula (3) , and According to the deformation parameters of the variant drone Taking the variable-sweep UAV as an example, the deformation parameters of the variant UAV It can be specifically quantified as the sweep angle of the variant drone ,at this time, , as well as The calculation formula is shown in formula (4).

[0036] (4).

[0037] in, Indicates the sweep angle of the variant drone, , is the lift coefficient of the variant UAV when the angle of attack is 0, is the first-order coefficient of the lift coefficient, is the drag coefficient of the variant UAV when the angle of attack is 0, is the first-order coefficient of the resistance coefficient, is the quadratic coefficient of the drag coefficient, The angle of attack of the variant drone 、Pitch rudder angle and pitch angular velocity The pitching moment coefficient when both are 0, is the angle of attack term of the pitching moment coefficient, is the pitching rudder angle term coefficient of the pitching moment coefficient, is the pitching angular velocity term coefficient of the pitching moment coefficient, is the average aerodynamic chord length of the variant UAV.

[0038] In the above formula (4), the deformation parameters of the variant drone are The lift coefficient Linearized into a variant drone angle of attack A linear function; about the deformation parameters of the variant drone The drag coefficient Fitted into a variant drone angle of attack Quadratic function of; about the deformation parameters of the variant drone The pitch moment coefficient is fitted to the variant UAV angle of attack 、Pitch rudder deflection angle and pitch angular velocity A composite function of . Among them, , , , , , , , , These are all coefficient terms in the aerodynamic parameters of variant UAVs. These parameters are all functions of the sweep angle. The specific values ​​of the parameters can be obtained through wind tunnel tests or CFD (Computational Fluid Dynamics) calculations according to different sweep angles.

[0039] In another exemplary embodiment, step 102 of the present application expresses the longitudinal dynamics of the variant UAV established in step 101, i.e., equation (1), in the form of a nonlinear system to obtain a nonlinear control model of the variant UAV, as shown in equation (5).

[0040] (5).

[0041] in, is the system state variable, , for The first derivative of is the system status output, is the flight speed of the variant drone, is the angle of attack of the variant drone, is the pitch angle of the variant drone, is the pitch angular velocity of the variant drone, is the flight altitude of the variant drone, and the superscript T indicates transposition. Represents the system input variable, , represents the pitch rudder angle, Indicates the throttle amount. The interference term represents the uncertainty in the modeling process, is the system function matrix; is the system gain matrix.

[0042] The specific form of the system function matrix is ​​shown in formula (6).

[0043] (6).

[0044] In the formula, is the quality of the variant drone, is the atmospheric density, is the wing area of ​​the variant UAV, For the deformation parameters of the variant drone The drag coefficient, For variant drones Static moment of the shaft, for The first derivative of for The first derivative of for The second-order derivative of For the deformation parameters of the variant drone The lift coefficient, is the acceleration due to gravity, is the flight path angle of the variant drone.

[0045] The specific form of the system gain matrix is ​​shown in equation (7).

[0046] (7).

[0047] In the formula, is the engine inference coefficient of the variant UAV.

[0048] In formula (5) to formula (7), Depends on the engine model.

[0049] In another exemplary embodiment, in step 103 of the present application, based on the variant drone nonlinear control model established in step 102 above, the system state variable The flight speed of the variant drone The speed control sub-model of the variant UAV is established as shown in formula (8).

[0050] (8).

[0051] in, is the expected flight speed of the variant drone, is the flight speed of the variant drone, is the tracking error between the velocity and the desired velocity, is the sliding mode variable of the speed control sub-model, It is an intermediate variable of the speed control sub-model and has no practical significance. for The first derivative of for The first derivative of and These are the adaptive parameters of the speed control sub-model designed for the super-helical controller. for The first derivative of and are the two observer functions for speed control, for The first derivative of , t is the time variable, For the quality of the variant drone, is the static gain, , , are all normal numbers preset in the speed control sub-model. For judging A small positive number of absolute value, It is a preset parameter, which can be selected based on experience. is the control quantity of the speed control sub-model, Indicates the throttle amount. is the system function matrix, is the system gain matrix, is the deformation parameter of the variant drone, is the system state variable.

[0052] In formula (8), Used to determine the sign of the sliding surface and the expected flight speed of the variant drone is the flight speed of the variant UAV defined by the user, which can be taken within the flight envelope determined when designing the variant UAV; the design parameters related to the sliding mode algorithm can be obtained by iteration in the simulation, and the initial assignment can be determined by referring to typical examples.

[0053] In another exemplary embodiment, in step 103 of the present application, based on the variant drone nonlinear control model established in step 102 above, the system state variable The pitch angular velocity , establish the posture control sub-model, as shown in formula (9).

[0054] (9).

[0055] in, is the desired pitch angle of the variant drone, is the pitch angle of the variant drone, is the tracking error between the pitch angle and the desired pitch angle, is the tracking error between the pitch angular velocity and the desired pitch angular velocity, for The first derivative of for The second-order derivative of is the pitch angular velocity of the variant drone, is the sliding mode variable of the attitude control sub-model, for The first derivative of is the intermediate variable of the attitude control sub-model, and Design parameters for the sliding surface; is the intermediate function, , is the average synovial surface, , and are the first intermediate variable and the second intermediate variable respectively, , , For judging A small positive number of absolute value, is a positive real number between 0 and 1, for The first derivative of and These are the adaptive parameters of the attitude control sub-model designed for the super-helical controller. for The first derivative of and are the two observer functions for attitude control, is the sign function in the sliding mode control law, For the quality of the variant drone, is the static gain, for The first derivative of , and are all positive constants preset in the speed control sub-model. For judging A small positive number of absolute value, is the control quantity of the attitude control sub-model, is the preset parameter, represents the pitch rudder angle, is the system function matrix, is the system gain matrix, is the deformation parameter of the variant drone, is the system state variable.

[0056] In another exemplary embodiment, the above-mentioned step 104 controls the stable flight of the variant UAV based on the speed control sub-model and the attitude control sub-model in step 103. First, the system state variables are obtained based on the onboard sensors of the variant UAV. Then, the throttle amount is determined according to the system state variables using the speed control sub-model. The pitch rudder angle is determined according to the system state variables using the attitude control sub-model. Then, the flight speed and flight attitude of the variant UAV are controlled according to the throttle amount and the pitch rudder angle.

[0057] Exemplarily, the speed control sub-model and attitude control sub-model obtained in the above embodiments can be deployed on the flight control system of the variant UAV to realize the control of the long-flight variant UAV. The flight control system mainly includes: a main control unit, servo equipment and various types of sensors.

[0058] The main control unit optimizes and controls the flight performance of the variant UAV through an integrated and designed control algorithm; the servo equipment implements specific control instructions by receiving control signals from the main control unit; various types of sensors collect various flight data of the variant UAV, mainly including: a three-axis rate gyroscope for collecting the flight angular velocity of the variant UAV, a three-axis accelerometer for measuring the acceleration of the variant UAV in three-dimensional space, a barometric altimeter for measuring the flight altitude of the variant UAV, and an airspeed sensor for measuring the flight speed of the variant UAV.

[0059] The above step 104 specifically includes the following steps 201 to 204.

[0060] Step 201, obtaining the system state variables of the variant drone through the variant drone airborne sensor .

[0061] Step 202: Calculate the tracking error based on the system state variables , and .

[0062] Step 203: calculate the tracking error , and The input is into the main control unit of the flight control system of the variant UAV, and the control instructions of the throttle amount and pitch rudder angle of the variant UAV are planned according to the control algorithm (speed control sub-model and attitude control sub-model) deployed on the main control unit.

[0063] Step 204, sending control instructions to the engine and control surface actuators of the variant UAV to adjust the flight speed and flight attitude of the variant UAV to complete stable control.

[0064] According to the specific embodiments provided in this application, this application has the following technical effects.

[0065] The high-speed stable flight control method for a long-flight variant UAV provided in the above embodiments of the present application can be used to solve the high-speed stable flight control problem of the variant UAV after the mode transition. The longitudinal nonlinear dynamic equation established in the present application can accurately describe the change in aerodynamic performance of the variant UAV after deformation. The control method based on the sliding surface (i.e., the super-helical algorithm) in the present application enables the system state variables to converge quickly, making the system more robust and having better anti-interference ability. The present application provides a universal control method for various variant UAVs based on wing structure deformation, and provides a theoretical and practical basis for engineering applications.

[0066] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0067] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A high-speed and stable flight control method for a long-flight variant UAV, characterized in that: include: Construct the longitudinal nonlinear dynamic equations of the deformed UAV; The longitudinal nonlinear dynamic equation is expressed in a nonlinear system form to obtain a nonlinear control model of the variant UAV; Based on the super-helix algorithm, the nonlinear control model of the variant UAV is decoupled into a speed control sub-model and an attitude control sub-model; The deformed variant UAV is controlled according to the speed control sub-model and the attitude control sub-model.

2. The high-speed stable flight control method for a long-flight variant UAV according to claim 1 is characterized in that: The longitudinal nonlinear dynamic equation is: ； in, is the flight speed of the variant drone; for The first derivative of , characterizes the flight acceleration of the variant UAV; for The first derivative of is the flight altitude of the variant drone; is the pitch angle of the variant drone, for The first derivative of ; is the angle of attack of the variant drone, for The first derivative of ; is the pitch angular velocity of the variant drone, for The first derivative of ; is the resistance of the variant drone during flight. is the deformation parameter of the variant drone, is the engine thrust of the variant drone, , is the engine inference coefficient of the variant UAV, Indicates the throttle amount. is the quality of the variant drone, is the acceleration due to gravity, is the flight path angle of the variant drone, For the transformation process of the variant drone Inertial force generated by the shaft; is the lift of the variant UAV during flight. For the transformation process of the variant drone Inertial force generated by the shaft; is the pitch axis inertia moment of the variant UAV, for The first derivative of For variant drones Static moment of the shaft, is the pitch moment of the variant UAV during flight, For the transformation process of the variant drone The moment of inertia of the axis, This is the engine axis position of the variant UAV.

3. The high-speed stable flight control method for a long-flight variant UAV according to claim 2 is characterized in that: The variant drone is circling during the transformation process Inertial force generated by the shaft , the variant drone is around during the deformation process Inertia force generated by the shaft And the variant drone is around during the deformation process Moment of inertia of the axis The calculation formula is as follows: ； in, for The first derivative of for The second derivative of .

4. The high-speed stable flight control method for a long-flight variant UAV according to claim 2 is characterized in that: The calculation formulas for the drag, lift and pitch moment of the variant UAV during flight are as follows: ； in, is the atmospheric density, is the wing area of ​​the variant UAV, For the deformation parameters of the variant drone The lift coefficient, For the deformation parameters of the variant drone The drag coefficient, For the deformation parameters of the variant drone The pitching moment coefficient, is the average aerodynamic chord length of the variant UAV.

5. The high-speed stable flight control method for a long-flight variant UAV according to claim 4 is characterized in that: The deformation parameter of the variant drone is the sweep angle of the variant drone. The calculation formulas for the lift coefficient, drag coefficient and pitching moment coefficient are as follows: ； in, Indicates the sweep angle of the variant drone, , is the lift coefficient of the variant UAV when the angle of attack is 0, is the first-order coefficient of the lift coefficient, is the drag coefficient of the variant UAV when the angle of attack is 0, is the first-order coefficient of the resistance coefficient, is the quadratic coefficient of the drag coefficient, The angle of attack of the variant drone 、Pitch rudder angle and pitch angular velocity The pitching moment coefficient when both are 0, is the angle of attack term of the pitching moment coefficient, is the pitching rudder angle term coefficient of the pitching moment coefficient, is the pitching angular velocity term coefficient of the pitching moment coefficient, is the average aerodynamic chord length of the variant UAV.

6. The high-speed stable flight control method for a long-flight variant UAV according to claim 1 is characterized in that: The nonlinear control model of the variant UAV is: ； in, is the system state variable, , for The first derivative of is the system status output, is the flight speed of the variant drone, is the angle of attack of the variant drone, is the pitch angle of the variant drone, is the pitch angular velocity of the variant drone, is the flight altitude of the variant drone, and the superscript T indicates transposition. Represents the system input variable, , represents the pitch rudder angle, Indicates the throttle amount. The interference term represents the uncertainty in the modeling process, is the system function matrix; is the system gain matrix; ； is the quality of the variant drone, is the atmospheric density, is the wing area of ​​the variant UAV, For the deformation parameters of the variant drone The drag coefficient, For variant drones Static moment of the shaft, for The first derivative of for The first derivative of for The second-order derivative of For the deformation parameters of the variant drone The lift coefficient, is the acceleration due to gravity, is the flight path angle of the variant drone; ； is the engine inference coefficient of the variant UAV.

7. The high-speed stable flight control method for a long-flight variant UAV according to claim 1, characterized in that: The speed control sub-model is: ； in, is the expected flight speed of the variant drone, is the flight speed of the variant drone, is the tracking error between the velocity and the desired velocity, is the sliding mode variable of the speed control sub-model, is the intermediate variable of the speed control sub-model, for The first derivative of for The first derivative of and These are the adaptive parameters of the speed control sub-model designed for the super-helical controller. for The first derivative of and are the two observer functions for speed control, for The first derivative of is the time variable, is the sign function in the sliding mode control law, For the quality of the variant drone, is the static gain, , , are all normal numbers preset in the speed control sub-model. For judging A small positive number of absolute value, is the preset parameter, is the control quantity of the speed control sub-model, Indicates the throttle amount. is the system function matrix, is the system gain matrix, is the deformation parameter of the variant drone, is the system state variable.

8. The high-speed stable flight control method for a long-flight variant UAV according to claim 1 is characterized in that: The posture control sub-model is: ； in, is the desired pitch angle of the variant drone, is the pitch angle of the variant drone, is the tracking error between the pitch angle and the desired pitch angle, is the tracking error between the pitch angular velocity and the desired pitch angular velocity, for The first derivative of for The second-order derivative of is the pitch angular velocity of the variant drone, is the sliding mode variable of the attitude control sub-model, for The first derivative of is the intermediate variable of the attitude control sub-model, and Design parameters for the sliding surface; is the intermediate function, , is the average synovial surface, , and are the first intermediate variable and the second intermediate variable respectively, , , For judging A small positive number of absolute value, is a positive real number between 0 and 1; for The first derivative of and These are the adaptive parameters of the attitude control sub-model designed by the super-helical controller. for The first derivative of and are the two observer functions for attitude control, is the sign function in the sliding mode control law, For the quality of the variant drone, is the static gain, for The first derivative of , and are all normal numbers preset in the speed control sub-model. For judging A small positive number of absolute value, is the preset parameter, is the control quantity of the attitude control sub-model, represents the pitch rudder angle, is the system function matrix, is the system gain matrix, is the deformation parameter of the variant drone, is the system state variable.

9. The high-speed stable flight control method for a long-flight variant UAV according to claim 1, characterized in that: Controlling the deformed variant UAV according to the speed control sub-model and the attitude control sub-model specifically includes: Obtain system state variables based on the variant UAV's onboard sensors; Determine the throttle amount using the speed control sub-model according to the system state variable; Determining the pitch rudder deflection angle using the attitude control sub-model according to the system state variables; The flight speed and flight attitude of the variant UAV are controlled according to the throttle amount and the pitch rudder deflection angle.

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