A fixed-wing unmanned aerial vehicle anti-interference adaptive flight control method based on dynamic shear mapping

Abstract

The application discloses a kind of fixed-wing unmanned aerial vehicle based on dynamic shear mapping anti-interference adaptive flight control method, this method will outermost ring PID controller replace the PID controller based on dynamic shear mapping, by introducing preset performance constraint, the anti-interference ability and tracking accuracy of system are promoted, finally realize the tracking control ability of three independent channels of air speed, height and yaw rate;The dynamic shear mapping has the following characteristics: in normal flight state, keep close to the error convergence constraint of preset performance control;When encountering external disturbance or flight state changes greatly, the risk of singularity of traditional rigid error transformation near the constraint boundary can be reduced, so that the controller can be defined and bounded first, and then gradually restore the error constraint effect.The application provides reliable robustness guarantee for multiple types of disturbance environment, and meets the control requirements of fixed-wing unmanned aerial vehicle in rapid maneuvering and complex disturbance adaptive smooth flight.

Description

Technical Field

[0001] This invention relates to the field of fixed-wing unmanned aerial vehicle (UAV) flight control technology, and specifically to a disturbance-resistant adaptive flight control method for fixed-wing UAVs based on dynamic shear mapping. Background Technology

[0002] Fixed-wing unmanned aerial vehicles (UAVs) have been widely used in environmental monitoring, emergency search and rescue, and other fields due to their advantages such as high cruising speed, long flight time, and wide coverage. The performance of the flight controller directly determines the trajectory tracking accuracy, anti-interference capability, and flight safety of fixed-wing UAVs in complex mission environments. In actual flight, fixed-wing UAVs frequently face external disturbances such as gusts and turbulence, coupled with multi-channel endogenous coupling interference caused by rapid and high-maneuver flight, making it difficult to maintain accurate and stable flight control.

[0003] Classic PID controllers are widely used in the flight control of fixed-wing UAVs due to their simple structure, convenient parameter tuning, and lack of reliance on precise models. However, conventional PID controllers have fixed gains and limited adaptability to internal and external disturbances. When the flight state changes drastically or encounters sudden strong disturbances, they are prone to problems such as increased tracking error, deterioration of dynamic response, and even instability, making it difficult to meet the robust control requirements under rapid maneuvering and complex disturbance conditions.

[0004] To improve disturbance rejection capability while ensuring transient and steady-state performance, a pre-defined performance control method has been introduced into flight control design. This method applies a pre-defined convergence constraint to the tracking error, ensuring that the error converges to a specified accuracy range within a specified time, effectively reducing peak and steady-state errors. However, traditional pre-defined performance control relies on a rigid error transformation function. When the aircraft encounters significant disturbances or rapid changes in state causing the error to approach the constraint boundary, this transformation function is prone to infinity, leading to control law singularities, compromising the definition and boundedness of the control system, and even causing flight accidents. To mitigate this problem, existing solutions often employ threshold protection, trigger-based switching, or adaptive adjustment of constraint boundaries, but all of these methods increase controller complexity to varying degrees, or sacrifice constraint accuracy and response speed while suppressing singularity risks, lacking practical engineering application capabilities. Therefore, there is an urgent need for a flight control method that can leverage the advantages of pre-defined performance constraints while effectively avoiding singularity risks at error boundaries, balancing constraint accuracy and robust safety to meet the engineering application needs of fixed-wing UAVs under rapid maneuvers and complex disturbances. Summary of the Invention

[0005] The purpose of this invention is to provide a disturbance-resistant adaptive flight control method for fixed-wing unmanned aerial vehicles based on dynamic shear mapping.

[0006] The technical solution to achieve the purpose of this invention is: a disturbance-resistant adaptive flight control method for fixed-wing unmanned aerial vehicles based on dynamic shear mapping, comprising the following steps:

[0007] Step 1: Set the flight controller parameters and initialize the controller;

[0008] Step 2: Obtain real-time control commands, including desired airspeed, altitude, and yaw rate;

[0009] Step 3: Collect various flight status information using sensors;

[0010] Step 4: Calculate the error transformation results for each channel based on dynamic shearing mapping;

[0011] Step 5: Calculate the throttle control amount from the airspeed channel;

[0012] Step 6: Calculate the elevator control quantity from the altitude channel;

[0013] Step 7: Calculate the aileron control parameters from the yaw rate channel;

[0014] Step 8: Input the calculated throttle control, elevator control, and aileron control values ​​into the actuators of the fixed-wing UAV;

[0015] Step 9: Check the autopilot status of the flight controller. If the autopilot remains active, proceed to step 2; otherwise, end the autopilot and switch to manual channel mapping mode.

[0016] A computer device includes a memory and one or more processors, wherein the memory stores executable code, and the processors, when executing the executable code, implement the steps of the method described above.

[0017] Compared with existing technologies, the significant advantages of this invention are as follows: This invention proposes a preset performance PID control method based on dynamic shear mapping and applies it to the field of flight control. By organically embedding preset performance constraints into the PID control law, peak error and steady-state error are effectively reduced under normal flight conditions, improving trajectory tracking accuracy. A dynamic shear mapping mechanism is designed, which can suppress the singular trend of traditional rigid error transformation near the constraint boundary when encountering external disturbances or significant changes in flight state. This allows the controller to prioritize maintaining defined and bounded conditions and then gradually restore error constraints, significantly enhancing the robustness, safety, and reliability of the control system. This control method balances high constraint accuracy and strong anti-disturbance capability without excessively increasing complexity, and can reliably support the adaptive and stable flight of fixed-wing UAVs under rapid maneuvering and complex disturbance conditions, demonstrating good engineering practical value. Attached Figure Description

[0018] Figure 1This is a flowchart of a disturbance-resistant adaptive flight control method for fixed-wing unmanned aerial vehicles based on dynamic shear mapping, according to the present invention.

[0019] Figure 2 This is a schematic diagram of the airspeed channel control loop of the present invention.

[0020] Figure 3 This is a schematic diagram of the height channel control loop of the present invention.

[0021] Figure 4 This is a schematic diagram of the yaw rate channel control loop of the present invention.

[0022] Figure 5 This is a schematic diagram of the Dynamic Shear Mapping PID Controller (DSMPID Controller) of the present invention.

[0023] Figure 6 This is a schematic diagram of a continuous, rapid, high-mobility test scenario (Scenario 1) considered in the embodiment.

[0024] Figure 7 This is a schematic diagram of the continuous gust disturbance test scenario (Scenario 2) considered in the embodiment.

[0025] Figure 8 The simulation test results are for the continuous high-speed high-mobility test scenario (Scenario 1) considered in the embodiments.

[0026] Figure 9 The simulation test results are for the continuous gust disturbance test scenario (Scenario 2) considered in the embodiment. Detailed Implementation

[0027] This invention proposes a disturbance-resistant adaptive flight control method for fixed-wing unmanned aerial vehicles (UAVs) based on dynamic shear mapping, which effectively solves the problem of insufficient robustness of flight control for fixed-wing UAVs under rapid maneuvers and complex disturbances. In a common flight control architecture, this method replaces the outermost PID controller with a PID controller based on dynamic shear mapping (DSMPID controller). By introducing preset performance constraints, it improves the system's disturbance resistance and tracking accuracy, ultimately achieving tracking control capabilities for three independent channels: airspeed, altitude, and yaw rate. The dynamic shear mapping has the following characteristics: under normal flight conditions, it maintains error convergence constraints close to the preset performance control, which helps reduce peak and steady-state errors; when encountering external disturbances or significant changes in flight state, it reduces the risk of singularities appearing near the constraint boundaries in traditional rigid error transformations, allowing the controller to prioritize definition and boundedness before gradually restoring the error constraint effect, thus enhancing flight robustness and safety. This invention is an effective extension of fixed-wing UAV flight control methods, providing reliable robustness guarantees for various disturbance environments and meeting the control requirements of fixed-wing UAVs for adaptive and stable flight under rapid maneuvers and complex disturbances.

[0028] like Figure 1 As shown, a disturbance-resistant adaptive flight control method for fixed-wing unmanned aerial vehicles based on dynamic shear mapping includes the following steps:

[0029] Step 1 involves setting the flight controller parameters, including the control parameters of all dynamic shear mapping performance functions in the three channels of airspeed, altitude, and yaw rate, the proportional / integral / derivative gain coefficients of each PID controller, and the safety constraint ranges of each control variable. Simultaneously, the controller is initialized, including setting the initial time of the dynamic shear mapping performance functions to the current time and initializing each PID controller.

[0030] Specifically, the schematic diagram of the airspeed channel control loop is as follows: Figure 2 As shown, a schematic diagram of the height channel control loop is as follows: Figure 3 As shown, the schematic diagram of the yaw rate channel control loop is as follows: Figure 4 As shown, a schematic diagram of the Dynamic Shear Mapping PID Controller (DSMPID Controller) in each channel is as follows: Figure 5 As shown.

[0031] In step 2, real-time control commands from external input of the fixed-wing UAV are obtained, including the desired airspeed. ,high and yaw rate The flight controller will calculate the required throttle control quantity (normalized to 0~1), elevator control quantity (normalized to -1~1), and aileron control quantity (normalized to -1~1) in real time based on the above three control commands to achieve the required flight state.

[0032] In step 3, sensors are used to collect real-time flight status information, including the current flight time. ,airspeed ,high Vertical velocity Angle of attack Roll angle With roll rate .

[0033] Step 4 involves calculating the error transformation results for each channel based on dynamic shearing mapping, specifically including the following steps:

[0034] Step 4.1: Calculate the direct deviations between the airspeed, altitude, and yaw rate channels in the flight controller and the actual values, where the airspeed deviation... Height deviation For the yaw rate channel, this controller uses a coordinated turn method to control the UAV's steering, that is, by changing the form of the roll angle (bank) to achieve the turning process. In this case, the expected yaw rate is equivalent to the roll angle command. Specifically ,in If the acceleration due to gravity is used, then the direct deviation of the yaw rate channel is equivalent to the roll angle deviation. Subsequently, steps 4.2-4.5 are used to calculate the dynamic shearing mapping transformation results of the channel deviation under the performance function constraint for each of the above channels.

[0035] Step 4.2, calculate the intermediate variables of the deviation under the performance function constraints. ,in Let be the tracking deviation at time t. The performance function is specifically chosen in the following exponential form:

[0036] (1)

[0037] in Let be the initial value of the performance function. The final value of the performance function. Let be the convergence rate of the performance function. This represents the convergence start time of the performance function.

[0038] In order to make the adjustment of deviation conform to the constraint process of the performance function, when the deviation is greater than The performance function will be manually reset and adjusted with initial values ​​as constraints (i.e., coarse deviation adjustment). Performance constraints will be applied again when the deviation enters the range of the initial value of the performance function (i.e., fine deviation adjustment). The specific procedure is as follows: Before calculating formula (1), if Then set The current time t is used to force the performance function to remain in its initial state.

[0039] Step 4.3, introduce the mapping function Variable transformation is performed, and the specific mapping function is selected in the following form:

[0040] (2)

[0041] This mapping function can be used to map constrained intermediate variables. Convert to unconstrained variables However, in practical applications, non-ideal factors such as improper selection of the sampling period, input limitations, or strong external interference can lead to... This leads to mapping singularities, causing the transformation function to lose its mathematical definition, ultimately resulting in controller failure or even instability. Therefore, it is necessary to introduce dynamic shearing mapping and... Solve for the intermediate variables without singularity Finally obtained Corresponding unconstrained variables .

[0042] Step 4.4, introduce dynamic shear mapping This mapping can be viewed as a generalized extension of the original mapping function, and its matrix form is:

[0043] (3)

[0044] in, The original coordinate point has... ; The corresponding point after mapping; Let be the shear angle function, and it has the following definition:

[0045] (4)

[0046] in, It is the preset maximum shear angle. These are two preset thresholds. , , ,in and These are the dynamic shear angle functions located in the positive and negative transition intervals, respectively. It ensures that the dynamic shear angle reaches the preset maximum shear angle at the endpoint of the transition range. The normalized coefficient; For the integration variable. A schematic diagram of the specific dynamic shear mapping form is shown below. Figure 5 As shown.

[0047] In the designed dynamic shearing mapping, when When the tracking deviation is within the preset safety range and far from the constraint boundary, Equation (3) degenerates into At this time, the system maintains the traditional preset performance constraint characteristics; when When the tracking deviation approaches or exceeds the constraint boundary, the transformation effectively extends the domain to the entire real number space, thus eliminating the mapping singularity problem at its root.

[0048] Step 4.5: Solve for intermediate variables without singular constraints based on dynamic shearing mapping. and unconstrained variables Combining the proposed dynamic shear mapping equation (3) with equation (2), we have:

[0049] (5)

[0050] (6)

[0051] Equations (5) and (6) together constitute the core relation of the proposed dynamic shearing mapping strategy, where the unconstrained variables... From intermediate variables Uniquely determined. Therefore, by substituting... The implicit equation (6) can be solved to find the intermediate variable without singularity. Then, the unconstrained variables are obtained from equation (5). That is, the deviation was achieved. In performance function Dynamic shearing mapping transformation under constraints. Specifically, the solution to implicit equation (6) can be based on... It is divided into two forms: when in strict constraint mode, i.e. ,have At this point, equation (6) degenerates into a simple linear relationship. The computational burden is negligible; when At that time, that is Dynamic shear mapping requires solving nonlinear equations using Newton's method or bisection method (6), and such tracking deviations approaching or exceeding constraint boundaries only occur when encountering large disturbances during flight, accounting for a small proportion in the solution. Therefore, the proposed method avoids singularity problems while ensuring the real-time operation of the control system.

[0052] In step 5, the throttle control quantity is calculated from the airspeed channel, that is, the throttle control quantity is obtained by inputting the airspeed deviation after error transformation into the PID controller. Specifically:

[0053] (7)

[0054] in, for The error transformation results after dynamic shearing mapping in steps 4.2-4.5, For throttle PID controller, The function limits the value to a specified minimum and maximum range. The PID controller in equation (7) takes the following form: ,in For proportional, integral, and differential coefficients, express First-order differential.

[0055] In step 6, the elevator control input is calculated using the height channel. First, the desired vertical speed is obtained by inputting the height deviation (after error transformation) into the PID controller. Specifically:

[0056] (8)

[0057] in, for Error transformation result after dynamic shear mapping It is a vertical speed PID controller. The maximum vertical velocity is constrained. Next, the vertical velocity deviation is input into the PID controller to obtain the desired angle of attack. Specifically:

[0058] (9)

[0059] in, For angle-of-attack PID controller, The maximum angle of attack is constrained. Finally, the angle of attack deviation is input into the PID controller to obtain the elevator control quantity. Specifically:

[0060] (10)

[0061] in, This is a PID controller for the elevator.

[0062] In step 7, the aileron control input is calculated from the yaw rate channel. First, the desired roll rate is obtained by inputting the roll angle deviation after error transformation into the PID controller. Specifically:

[0063] (11)

[0064] in, for Error transformation result after dynamic shear mapping For roll rate PID controller, The maximum roll rate is constrained. Finally, the roll rate deviation is input into the PID controller to obtain the aileron control input. Specifically:

[0065] (12)

[0066] in, It is a PID controller for the aileron.

[0067] In step 8, the calculated throttle control quantity is... elevator control quantity and aileron control Input the throttle, elevator, and aileron actuators corresponding to the fixed-wing UAV to achieve real-time adjustment of the flight status.

[0068] In step 9, check the autopilot status of the flight controller. If the autopilot remains active, proceed to step 2 to read externally input control commands in real time and achieve dynamic tracking of control commands by the fixed-wing UAV; otherwise, end the autopilot status and switch to manual channel mapping mode.

[0069] The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0070] Example

[0071] To verify the performance of the method of this invention, a flight simulation platform was used to test the command tracking capability of the flight controller under two flight scenarios: continuous high-speed high-maneuverability flight and continuous gust wind disturbance. In this embodiment, the flight simulation platform simulated a fixed-wing UAV with a weight of 1000 kg and a wing area of ​​40 m². 2 The large fixed-wing UAV has an engine with a maximum thrust of 10,000 N. The controller design for the airspeed, altitude, and yaw rate channels of the flight controller is as follows: Figures 2-5 As shown, the flight controller was set to a maximum yaw rate of 20° / s, a maximum vertical speed of 5m / s, a maximum angle of attack of 10°, and a maximum roll rate of 90° / s. All other controller parameters were adjusted to their optimal values ​​for best flight control. In the control group, the flight controllers of the UAVs had the dynamic shear mapping component removed, and ordinary PID controllers were used in each control loop, with their parameters also adjusted to their corresponding optimal values ​​for best flight control.

[0072] Test Scenario 1 compared the command tracking performance of two flight controllers on a fixed-wing UAV during continuous, rapid, and highly maneuverable flight. Specifically, the UAV maintained an altitude of 100m and an airspeed of 45m / s, and made rapid maneuvers to the right at flight time T=75s and to the left at flight time T=100s. A schematic diagram of the test scenario is shown below. Figure 6 As shown, the test results are as follows: Figure 8 As shown. From Figure 8 It can be seen that the disturbance-resistant adaptive flight controller based on dynamic shear mapping proposed in this invention can quickly adjust the engine to maintain the given desired airspeed during continuous, fast, and highly maneuverable flight, with lower steady-state tracking error. In the altitude channel, this method can effectively maintain flight altitude, and in the yaw rate (specifically reflected in the tracking of roll angle) channel, this method has better roll angle tracking accuracy. Test scenario 2 compares the command tracking performance of the two flight controllers on a fixed-wing UAV under continuous gust disturbances. Specifically, the UAV maintains an altitude of 100m, an airspeed of 45m / s, and a northward flight direction. At T=75s, it is subjected to a continuous gust of wind from the left, and at T=100s, the wind direction changes to a continuous gust of wind from the right. A schematic diagram of the test scenario is shown below. Figure 7 As shown, the test results are as follows: Figure 9 As shown. From Figure 9 As can be seen, the disturbance-resistant adaptive flight controller based on dynamic shear mapping proposed in this invention exhibits better tracking accuracy in all three channels under continuous gust disturbances, is less affected by external disturbances, and does not show significant chattering caused by endogenous coupling interference in the roll angle curve compared to traditional PID. In summary, compared with traditional PID, the method of this invention has higher control accuracy, can effectively cope with mode changes, and has stronger adaptive adjustment and anti-interference capabilities.

[0073] The specific embodiments described in this invention are merely illustrative of the spirit of the invention. Those skilled in the art can make various modifications or additions to the described specific embodiments or use similar methods to replace them, without departing from the spirit of the invention or exceeding the scope defined by the appended claims.

Claims

1. A disturbance-resistant adaptive flight control method for fixed-wing unmanned aerial vehicles based on dynamic shear mapping, characterized in that, Includes the following steps: Step 1: Set the flight controller parameters and initialize the controller; Step 2: Obtain real-time control commands, including desired airspeed, altitude, and yaw rate; Step 3: Collect various flight status information using sensors; Step 4: Calculate the error transformation results for each channel based on dynamic shearing mapping; Step 5: Calculate the throttle control amount from the airspeed channel; Step 6: Calculate the elevator control quantity from the altitude channel; Step 7: Calculate the aileron control parameters from the yaw rate channel; Step 8: Input the calculated throttle control, elevator control, and aileron control values ​​into the actuators of the fixed-wing UAV; Step 9: Check the autopilot status of the flight controller. If the autopilot remains active, proceed to step 2; otherwise, end the autopilot and switch to manual channel mapping mode.

2. The method according to claim 1, characterized in that, In step 1, the flight controller parameters are set, including the control parameters of all dynamic shear mapping performance functions in the three channels of airspeed, altitude and yaw rate in the flight controller, the proportional / integral / derivative gain coefficients of each PID controller, and the safety constraint range of each control variable; at the same time, the controller is initialized, including setting the initial time of the dynamic shear mapping performance function to the current time and initializing each PID controller.

3. The method according to claim 1, characterized in that, In step 2, real-time control commands from external input of the fixed-wing UAV are obtained, including the desired airspeed. ,high and yaw rate The flight controller will calculate the required throttle, elevator, and aileron control values ​​in real time based on the above three control commands to achieve the desired flight state.

4. The method according to claim 3, characterized in that, In step 3, sensors are used to collect real-time flight status information, including the current flight time. ,airspeed ,high Vertical velocity Angle of attack Roll angle With roll rate .

5. The method according to claim 4, characterized in that, Step 4 involves calculating the error transformation results for each channel based on dynamic shearing mapping, and includes the following steps: Step 4.1: Calculate the direct deviations between the airspeed, altitude, and yaw rate channels in the flight controller and the actual values, including the airspeed deviation. Height deviation For the yaw rate channel, the controller uses a coordinated turn method to control the UAV's steering, that is, by changing the form of the roll angle to achieve the turning process. In this case, the desired yaw rate is equivalent to the roll angle command. Specifically ,in If the acceleration due to gravity is used, then the direct deviation of the yaw rate channel is equivalent to the roll angle deviation. ; Step 4.2, calculate the intermediate variables of the deviation under the performance function constraints. ,in Let be the tracking deviation at time t. The performance function is specifically chosen in the following exponential form: （1） in Let be the initial value of the performance function. The final value of the performance function. Let be the convergence rate of the performance function. This represents the convergence start time of the performance function; When the deviation is greater than The performance function will be manually reset and adjusted with initial values ​​as constraints. Performance constraints will be applied again when the deviation falls within the range of the initial values ​​of the performance function. Specifically, before calculating formula (1), if Then set For the current time t, the performance function is forced to remain in its initial state; Step 4.3, introduce the mapping function Variable transformation is performed, and the specific mapping function is selected in the following form: （2） This mapping function will be used to define the constrained intermediate variables. Convert to unconstrained variables ; Step 4.4, introduce dynamic shear mapping This mapping can be viewed as a generalized extension of the original mapping function, and its matrix form is as follows: （3） in, The original coordinate point has... ; The corresponding point after mapping; Let be the shear angle function, and it has the following definition: （4） in, It is the preset maximum shear angle. These are two preset thresholds. , , ,in and These are the dynamic shear angle functions located in the positive and negative transition intervals, respectively. It ensures that the dynamic shear angle reaches the preset maximum shear angle at the endpoint of the transition range. The normalized coefficient, For integration variables; Step 4.5: Solve for intermediate variables without singular constraints based on dynamic shearing mapping. and unconstrained variables Combining equation (3) with equation (2), we have: （5） （6） Equations (5) and (6) together constitute the core relation of the dynamic shearing mapping strategy, where the unconstrained variables... From intermediate variables Uniquely determined; therefore, by substitution The implicit equation (6) can be solved to find the intermediate variable without singularity. Then, the unconstrained variables are obtained from equation (5). That is, the deviation was achieved. In performance function Dynamic shearing mapping transformation under constraints.

6. The method according to claim 5, characterized in that, In step 5, the throttle control quantity is calculated from the airspeed channel, that is, the throttle control quantity is obtained by inputting the airspeed deviation after error transformation into the PID controller. Specifically: （7） in, for Error transformation result after dynamic shear mapping For throttle PID controller, The function limits the value to a specified minimum and maximum range.

7. The method according to claim 6, characterized in that, In step 6, the elevator control quantity is calculated from the height channel; firstly, the desired vertical speed is obtained by inputting the height deviation after error transformation into the PID controller. Specifically: （8） in, for Error transformation result after dynamic shear mapping It is a vertical speed PID controller. The maximum vertical velocity is constrained; secondly, the vertical velocity deviation is input into the PID controller to obtain the desired angle of attack. Specifically: （9） in, For angle-of-attack PID controller, To constrain the maximum angle of attack; finally, the angle of attack deviation is input into the PID controller to obtain the elevator control quantity. Specifically: （10） in, This is a PID controller for the elevator.

8. The method according to claim 7, characterized in that, In step 7, the aileron control input is calculated from the yaw rate channel; firstly, the desired roll rate is obtained by inputting the roll angle deviation after error transformation into the PID controller. Specifically: （11） in, for Error transformation result after dynamic shear mapping For roll rate PID controller, The maximum roll rate is constrained; then, the roll rate deviation is input into the PID controller to obtain the aileron control quantity. Specifically: （12） in, It is a PID controller for the aileron.

9. The method according to claim 8, characterized in that, In step 8, the calculated throttle control quantity is... elevator control quantity and aileron control Input the throttle, elevator, and aileron actuators corresponding to the fixed-wing UAV to achieve real-time adjustment of the flight status.

10. A computer device comprising a memory and one or more processors, wherein the memory stores executable code, characterized in that... When the processor executes the executable code, it implements the steps of the method as described in any one of claims 1 to 9.

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