Crossed double-rotor unmanned aerial vehicle gust adaptive stabilization control system

Abstract

The application belongs to the technical field of unmanned aerial vehicle control systems, and particularly relates to a cross double-rotor unmanned aerial vehicle gust adaptive stability control system, which comprises: a flight state sensing module, which is used for collecting flight state parameters in real time; a gust identification module, which is used for identifying external gust disturbance states according to the flight state parameters, establishing gust characteristic parameters, extracting gust disturbance characteristic frequencies, combining the gust characteristic parameters and the gust disturbance characteristic frequencies, estimating gust directions and action positions, and outputting gust identification results; and a rotor coupling state analysis module, which is used for analyzing coupling vibration states between rotors and wake interference characteristics. The application dynamically identifies disturbance characteristics through gust identification and rotor coupling analysis, and uses an artificial intelligence algorithm to online optimize pitch, roll, yaw gains, thrust distribution and feedforward compensation coefficients, so that adaptive adjustment of control parameters is realized.

Description

Technical Field

[0001] This invention belongs to the field of unmanned aerial vehicle (UAV) control system technology, specifically relating to a cross-rotor UAV gust adaptive stability control system. Background Technology

[0002] In the drone manufacturing industry, the "brain" of a drone is its flight control system, which is responsible for sensing the environment, making decisions, and driving the motors to perform actions. A flight control system generally includes a perception layer, a decision-making layer, and an execution layer, and may be equipped with communication and power management modules as needed. By collecting information about the drone's status and the external environment, and processing it through control algorithms, it calculates the commands required for the drone to fly stably or perform specific actions.

[0003] Most existing UAV flight control systems employ traditional PID control, fixed parameter control, or compensation methods based on empirical models. Their control parameters typically depend on preset operating conditions, making it difficult to adjust the control strategy in real time according to gust disturbances. Under complex and unsteady wind field conditions, existing flight control systems suffer from problems such as response lag, insufficient disturbance rejection capability, and weak ability to identify rotor coupled vibrations.

[0004] Therefore, there is an urgent need to propose a cross-rotor UAV gust adaptive stability control system that can sense gust disturbances in real time, adaptively identify rotor coupling state, and dynamically adjust flight control parameters, so as to improve its stable flight capability and environmental adaptability in complex wind fields. Summary of the Invention

[0005] The purpose of this invention is to provide a gust-adaptive stability control system for a cross-rotor unmanned aerial vehicle (UAV), which can dynamically identify disturbance characteristics through gust recognition and rotor coupling analysis, and utilize... Artificial intelligence algorithms optimize pitch, roll, and yaw gains, thrust distribution, and feedforward compensation coefficients online, enabling adaptive adjustment of control parameters.

[0006] The specific technical solution adopted by this invention is as follows: A cross-rotor UAV gust adaptive stability control system includes: The flight status perception module is used to collect flight status parameters in real time; The gust identification module is used to identify the external gust disturbance state based on flight status parameters, establish gust characteristic parameters, extract gust disturbance characteristic frequencies, combine gust characteristic parameters and gust disturbance characteristic frequencies, estimate the gust direction and location, and output gust identification results. The rotor coupling state analysis module is used to analyze the coupled vibration state and wake interference characteristics between rotors, and to determine whether it has entered a resonance enhancement state or an unstable flight state. The state estimation and prediction module is used to establish the current state and gust model, integrate the current state and gust model with flight state parameters, gust identification results and rotor coupling state results, solve the current complete flight state, and predict the future flight path; The adaptive control module is used to build an artificial intelligence model, input gust recognition results and rotor coupling state results, dynamically adjust flight control parameters, generate control commands, and realize flight stability control in gust environments. The flight execution module is used to execute the control commands generated by the adaptive control module.

[0007] As an optional solution, the gust identification module includes using joint time-domain and frequency-domain analysis to perform fast Fourier transform analysis on the body vibration signal and extract the characteristic frequency of gust disturbance.

[0008] As an optional solution, the gust identification module includes: The wind field fluctuation analysis unit is used to analyze flight state parameters and extract the amplitude and period of gust changes. The vibration spectrum analysis unit is used to perform fast Fourier transform analysis on the vibration signal of the machine body and extract the characteristic frequency of gust disturbance. The transient energy change analysis unit is used to monitor transient energy changes in attitude and velocity parameters of flight status. The gust level determination unit is used to establish a gust level model. It inputs the output data of the wind field fluctuation analysis unit, vibration spectrum analysis unit, and transient energy change analysis unit into the gust level model, determines and outputs the gust level.

[0009] As an optional solution, the rotor coupling state analysis module includes: The rotor phase analysis unit is used to extract the rotor's phase difference and synchronization status. The vibration energy flow analysis unit is used to establish a rotor coupled energy flow model and identify the transmission state of vibration energy between rotors. The rotor wake coupling analysis unit is used to analyze the aerodynamic interference between the downwash and the upwash. The nonlinear vibration identification unit is used to identify nonlinear vibration characteristics such as higher-order harmonics and subharmonics.

[0010] As an optional solution, the rotor coupling state analysis module extracts rotor speed, torque, vibration data, coupling frequency, harmonic characteristics and energy distribution during the analysis of the coupled vibration state and wake interference characteristics between rotors, which are used to calculate rotor aerodynamic force and thrust fluctuations. Analysis of rotor phase difference and synchronization state based on rotor aerodynamic and thrust fluctuations; When entering an unstable flight state, the coupling interference features are extracted to assess the coupling interference level and output the coupling state results. The coupling state output includes coupling strength coefficient, disturbance characteristic frequency set, vibration energy transfer direction and amplitude, providing multiple inputs for the adaptive control module to dynamically adjust flight control parameters in order to improve flight attitude stability.

[0011] As an optional approach, the state estimation and prediction module uses extended Kalman filtering or unscented Kalman filtering to fuse flight state parameters, gust identification results, and rotor coupling state results when calculating the current complete flight state. This calculates the accurate 12-dimensional state vector of the cross-rotor UAV, which is used to improve the accuracy of the current state and gust model in predicting future flight paths.

[0012] As an optional solution, the adaptive control module includes: Thrust distribution control unit, used to adjust the thrust distribution ratio of the twin rotors; The rotor speed adjustment unit is used to adjust the speed of each rotor. Phase synchronization control unit is used to control the rotor phase difference to reduce coupled vibration; Attitude stabilization compensation unit is used to compensate for attitude deviations caused by gusts of wind; Nonlinear vibration suppression control unit, used to suppress nonlinear vibration.

[0013] As an optional solution, the adaptive control module performs flight stability control in gust winds, specifically including the following steps: Once the control objective is determined, the adaptive control module dynamically determines the control priority based on the gust identification results and the rotor coupling status results. Design a controller that linearizes the current state with the gust model near the equilibrium point; Parameters are optimized online using a genetic algorithm; Output control commands and evaluate the effectiveness of flight control.

[0014] As an optional approach, the online parameter optimization using a genetic algorithm specifically includes the following steps: Establish parameter mapping relationships, mapping the control gain parameters to the weight matrix and feedforward matrix; Establish optimized coding, using real numbers to encode chromosomes; Establish a fitness function, comprehensively consider control accuracy and energy consumption under gust scenarios, and calculate the fitness value; Control commands are generated based on feedforward and feedback; Establish preset correction conditions, compare the feedback data with the preset correction conditions, and evaluate the flight control effect based on the comparison results.

[0015] A cross-rotor unmanned aerial vehicle (UAV) employing the cross-rotor UAV gust adaptive stability control system as described above, includes a fuselage, on which rotors and a tail are mounted, characterized in that it further includes: Millimeter-wave radar, vision camera, and vibration sensor are spaced apart at the bottom of the fuselage; A barometric altimeter, a GNSS antenna, a wind speed and direction sensor, and a gust sensor are installed at intervals on the top of the fuselage; A first rotational speed sensor, an IMU (Inertial Measurement Unit), and a second rotational speed sensor are mounted alternately on the rotor. The control surface position sensor and the tail attitude sensor are installed at intervals on the tail fin.

[0016] The technical effects achieved by this invention are as follows: This invention provides a control system that dynamically identifies disturbance characteristics through gust identification and rotor coupling analysis, and utilizes... Artificial intelligence algorithms optimize pitch, roll, and yaw gains, thrust distribution, and feedforward compensation coefficients online, enabling adaptive adjustment of control parameters.

[0017] This invention provides a control system based on Artificial intelligence algorithms optimize flight control parameters online, effectively suppressing the coupling vibration between gust disturbances and rotors, significantly improving flight attitude stability and trajectory tracking accuracy, and enhancing the flight safety and robustness of UAVs in complex wind field environments.

[0018] This invention provides a control system that can identify gust disturbances in complex low-altitude wind fields in real time when dealing with the impact of gusts from a cross-rotor UAV, thereby improving the UAV's environmental perception capabilities.

[0019] This invention provides a control system that can reduce airframe vibration and attitude fluctuations and improve the working accuracy of airborne mission payloads when dealing with the impact of gusts from cross-rotor UAVs. Attached Figure Description

[0020] Figure 1 This is a schematic diagram of the structure of a cross-rotor unmanned aerial vehicle according to Embodiment 1 of the present invention; Figure 2 This is a schematic diagram of a cross-rotor UAV gust adaptive stability control system according to Embodiment 2 of the present invention; Figure 3 This is the invention Figure 2 A schematic diagram of the gust detection module; Figure 4 This is the invention Figure 2 A schematic diagram of the rotor coupling state analysis module; Figure 5This is the invention Figure 2 A schematic diagram of the adaptive control module; Figure 6 This is the invention Figure 2 A schematic diagram of the flight execution module.

[0021] The attached diagram lists the components represented by each number as follows: 1. Fuselage; 2. Rotor; 3. Tail; 4. Millimeter-wave radar; 5. Visual camera; 6. Vibration sensor; 7. Barometric altimeter; 8. GNSS antenna; 9. Wind speed and direction sensor; 10. Gust sensor; 11. First rotational speed sensor; 12. IMU (Inertial Measurement Unit); 13. Second rotational speed sensor; 14. Control surface position sensor; 15. Tail attitude sensor. Detailed Implementation

[0022] To make the objectives and advantages of this invention clearer, the invention will be specifically described below with reference to embodiments. It should be understood that the following text is merely used to describe one or more specific embodiments of the invention and does not strictly limit the scope of protection specifically claimed by the invention.

[0023] Example 1: like Figure 1 As shown, a cross-rotor drone is controlled by a flight control system. It includes a fuselage 1, with two rotors 2 mounted on the top of the fuselage 1 via a pivot. Each rotor 2 is driven by a motor to provide lift, enabling the cross-rotor drone to take off and hover. A tail fin 3 is mounted on the tail of the fuselage 1 via a drive shaft. When the tail fin 3 rotates under the drive of the engine, it generates a rearward airflow, providing forward thrust to the fuselage 1, enabling the cross-rotor drone to fly at high speed.

[0024] It should be noted that the rotors of the two rotors 2 will partially overlap when rotating. Driven by the two motors, they rotate synchronously and in opposite directions. One rotor rotates clockwise and the other rotor rotates counterclockwise. The counter-torques generated by the two rotors are equal in magnitude and opposite in direction, canceling each other out in the air. Therefore, the cross-rotor UAV does not need to be equipped with an additional tail rotor to specifically resist the counter-torque, allowing rotor 2 to focus on generating lift and improving drive efficiency.

[0025] like Figure 1As shown, a Linpowave U300 millimeter-wave radar 4 and an OpenMV4 H7 Plus vision camera 5 are mounted on the bottom of the fuselage 1 using bolt and nut kits. The millimeter-wave radar 4 is used to acquire real-time ground height data, and the vision camera 5 is used to acquire real-time obstacle data. A Kistler Type 8640A vibration sensor 6 is mounted on the side of the fuselage 1 using bolt and nut kits. The vibration sensor 6 is used to acquire real-time vibration data.

[0026] like Figure 1 As shown, the top of the fuselage 1 is equipped with an MS5611 barometric altimeter 7, an HX-28-GNF GNSS antenna 8, an FT205 wind speed and direction sensor 9, and an FT742-SM gust sensor 10 via bolt and nut kits. During operation, the barometric altimeter 7 is used to acquire real-time altitude data, the GNSS antenna 8 is used to acquire real-time absolute position data, the wind speed and direction sensor 9 is used to acquire real-time turbulence disturbance data, and the gust sensor 10 is used to acquire real-time gust disturbance data.

[0027] like Figure 1 As shown, a first rotation speed sensor 11 of model LUYOR ROLS-5PW, an IMU inertial measurement unit 12 of model QMI8658A, and a second rotation speed sensor 13 of model LUYOR ROLS-5PW are installed on rotor 2 by bolt and nut assembly. The first rotation speed sensor 11 and the second rotation speed sensor 13 are used to acquire real-time rotation speed data of the two rotors 2. The IMU inertial measurement unit 12 is used to acquire real-time flight attitude data of the cross-rotor UAV. The flight attitude data includes the attitude angle, angular velocity, flight speed and real-time ground altitude data of the fuselage 1.

[0028] like Figure 1 As shown, a control surface position sensor 14 (e.g., a rotary potentiometer) and a tail attitude sensor 15 (refer to the IMU inertial measurement unit 12 of model QMI8658A) are mounted on the tail fin 3 by bolt and nut assembly. The control surface position sensor 14 is used to acquire real-time orientation data of the tail fin 3, and the tail attitude sensor 15 is used to acquire real-time attitude angle of the tail fin 3.

[0029] Example 2: like Figures 2-6 As shown, a cross-rotor UAV gust adaptive stability control system is used to control the cross-rotor UAV as provided in Embodiment 1, including: The flight status perception module is used to collect flight status parameters of the cross-rotor UAV in real time, providing a data foundation for upper-level analysis and control; The flight status parameters can be acquired in real time using the millimeter-wave radar 4, visual camera 5, vibration sensor 6, barometric altimeter 7, GNSS antenna 8, wind speed and direction sensor 9, gust sensor 10, first rotational speed sensor 11, IMU inertial measurement unit 12, second rotational speed sensor 13, control surface position sensor 14, and tail attitude sensor 15 provided in Example 1. Specifically, the data includes the following: Attitude angle information, including pitch angle Roll angle Yaw angle ; Location information, including position in the x-axis direction of the ground coordinate system. Position along the y-axis Position in the z-axis direction ; Angular velocity information, including roll angular velocity pitch angular velocity yaw rate ; The body vibration acceleration information includes the acceleration along the x, y, and z axes of the ground coordinate system; Motor speed information, including the speeds of both motors. and ; Flight speed information, including ground speed and airspeed, with the speeds along the x, y, and z axes of the ground coordinate system denoted as follows: , , ; Information on airflow disturbances, including relative wind speed and wind direction.

[0030] The gust identification module identifies external gust disturbances based on flight status parameters, establishes gust characteristic parameters (amplitude of sudden changes, period, and duration), and performs a fast Fourier transform on the airframe vibration signal using a joint time-domain and frequency-domain analysis method. The analysis extracts the characteristic frequencies of gust disturbances. Simultaneously, by analyzing changes in the aircraft vibration spectrum, rotor load fluctuations, and attitude deviation characteristics, the direction and location of the gusts are estimated, and the gust identification results are output. (See [link to relevant documentation]). Figure 3 Specifically, it includes the following parts: Wind field fluctuation analysis unit: Analyzes time-series data from wind speed sensors to extract the amplitude and period of sudden gusts; Vibration spectrum analysis unit: performs fast Fourier transform analysis on the body vibration signal to extract the characteristic frequency of gust disturbance; Transient Energy Change Analysis Unit: Monitors transient energy changes in attitude / velocity; Gust level determination unit: Determines the gust level by combining the outputs of the aforementioned units; The gust identification output includes gust direction, gust intensity level, and disturbance frequency type, as detailed below: Gust direction, horizontal angle (0°~360°) and vertical component; Gust intensity levels include: (1) No gusts (Level 0, wind speed < 3 m / s); (2) Slight gusts (Level 1, wind speed 3m / s~8m / s); (3) Moderate gusts (Level 2, wind speed 8m / s~15m / s); (4) Strong gusts (level 3, wind speed 15m / s~25m / s); (5) Extremely strong gusts (level 4, wind speed > 25 m / s); Disturbance frequency types include: Pulse gusts, high-frequency transient impacts (triggered by gusts of wind no less than moderate gusts, impact interval <3s). Gradual gusts, with continuous changes in low to medium frequency (triggered by gusts below moderate and impact intervals > 3 seconds). Turbulent gusts, broadband random disturbances (triggered by gusts of wind no less than moderate and impact intervals > 3s).

[0031] The rotor coupling state analysis module analyzes the coupled vibration state and wake interference characteristics between the crossed rotors to determine whether the crossed-rotor UAV has entered a state of enhanced resonance or unstable flight. (See also...) Figure 4 It includes the following parts: Rotor phase analysis unit: used to extract the phase difference and synchronization status of the two rotors; Vibration energy flow analysis unit: used to establish a rotor coupled energy flow model and identify the transmission state of vibration energy between the two rotors; Rotor wake coupling analysis unit: used to analyze the aerodynamic interference between the downwash and the upwash; Nonlinear vibration identification unit: used to identify nonlinear vibration characteristics such as higher-order harmonics and subharmonics; The specific steps for analyzing the coupled vibration state and wake interference characteristics between the intersecting rotors are as follows: Data extraction: Extract rotor speed, torque, vibration data, coupling frequency, harmonic characteristics, and energy distribution. Aerodynamic calculations: Calculate rotor aerodynamic forces and thrust fluctuations; Phase analysis: Analyzes rotor phase difference and synchronization status; Airframe stress calculation: Calculate the stress and torque coupling on the airframe of the cross-rotor UAV; Perform a current state check; If the resonance enhancement state is entered, repeat the above steps and reanalyze; If the flight enters an unstable state, the coupling interference characteristics are extracted, the coupling interference level is evaluated, and the coupling state result is output. Specifically, the coupling state results output includes: (a) Coupling strength coefficient ,in, Indicates no coupling. Indicates fully coupled resonance, when Greater than When this time comes, it indicates that you have entered a danger zone; (b) Set of interference characteristic frequencies ; (c) Direction and amplitude of vibration energy transfer.

[0032] The state estimation and prediction module establishes a current state and gust model to fuse flight state parameters, gust identification results, and rotor coupling state results. It calculates the current complete flight state of the cross-rotor UAV and predicts its future flight path, specifically including the following steps: Establish a model of the current state and gusts; The flight status parameters acquired by the flight status perception module, the gust recognition results output by the gust recognition module, and the coupling status results output by the rotor coupling status analysis module are combined. Multi-source data fusion is performed using either Extended Kalman Filter (EKF) or Unscented Kalman Filter (UKF) to calculate the accurate 12-dimensional state vector of the cross-rotor UAV. ,in, Indicates the preset duration; State prediction is performed, based on the current state and the gust model, to recursively predict the future of the cross-rotor UAV. The flight trajectory within seconds provides forward-looking information for the adaptive control module.

[0033] The adaptive control module is used to adjust the gust control based on the gust identification results and the rotor coupling state results. An artificial intelligence model dynamically adjusts flight control parameters and generates optimal control commands to achieve stable flight control in gust winds. (See also...) Figure 5 It includes the following parts: Thrust distribution control unit: Automatically adjusts the thrust distribution ratio of the twin rotors, including the thrust distribution coefficient. , ; Rotor speed control unit: Independently adjusts the speed of each rotor, including yaw gain. , ; Phase synchronization control unit: controls the phase difference between the two rotors to reduce coupled vibrations, including roll gain. , , ; Attitude stabilization compensation unit: compensates for attitude deviations caused by gusts, including pitch gain. , , ; Nonlinear vibration suppression control unit: suppresses nonlinear vibrations, including feedforward compensation coefficients. , ; The adaptive control module implements flight stability control in gust winds, specifically including the following steps: Control target determination: Based on the gust identification results and rotor coupling status results, the adaptive control module dynamically determines the control priority; Among them, if the gust intensity is no greater than level 1, the trajectory tracking control target is given priority; if the gust intensity is no less than level 2 or the coupling state is abnormal, the attitude stabilization control target is given priority. design The controller linearizes the current state and the gust model near the equilibrium point. The controller aims to minimize the quadratic performance index. The parameters are optimized online using a genetic algorithm. The specific steps are as follows: Step 1: Establish parameter mapping relationships, mapping the control gain parameters to... weight matrix , The feedforward matrix and the specific mapping relationship are shown in Table 1 below; Table 1 Mapping Relationships

[0034] Step II: Establish GA optimized coding; Chromosomes are encoded using real numbers ; Step 3: Establish the fitness function; Taking into account both control accuracy and energy consumption in gust scenarios, the fitness value is calculated. Under gust conditions, the fitness function is set to include an additional weighted attitude deviation integral. Meanwhile, the following improvement strategies are given: (d) Optimal individual retention: The optimal chromosome from each generation is directly retained to the next generation; (e) Adaptive crossover / mutation: crossover probability and mutation probability Adaptive adjustment with each generation of evolution; (f) Initial population optimization: The initial population is generated using the Lyapunov stability condition; Step IV: Implement combined feedforward and feedback control; The final control command is generated based on feedforward and feedback. Step V: Output control commands and evaluate the flight control effect; Among them, it generates and outputs control commands, including thrust distribution commands, rotor speed commands, and servo deflection commands; The flight control performance is evaluated under the following preset correction conditions: steady-state attitude angle error ≤3°, maximum attitude angle deviation ≤5°, adjustment time ≤2s, and position tracking error ≤0.1m. If the preset correction conditions are met, the current flight attitude is maintained; If the preset correction conditions are not met, GA optimization coding is triggered, and optimization is performed again.

[0035] The flight execution module executes the control commands generated by the adaptive control module to adjust the UAV's flight status. See [link / reference]. Figure 6 It includes the following parts: Motor drive unit: converts speed commands into PWM signals to drive the brushless motor; Rotor actuator: Enables independent speed and pitch adjustment of the two rotors; Servo control unit: controls the periodic variable pitch servo; Flight control output unit: coordinates the timing and synchronization of various execution units.

[0036] In summary, this invention dynamically identifies disturbance characteristics through gust identification and rotor coupling analysis, and utilizes... Artificial intelligence algorithms optimize pitch, roll, and yaw gains, thrust distribution, and feedforward compensation coefficients online, enabling adaptive adjustment of control parameters. This effectively suppresses gust disturbances and rotor-coupled vibrations, significantly improving flight attitude stability and trajectory tracking accuracy, and enhancing the flight safety and robustness of UAVs in complex wind field environments.

[0037] The above description is merely an optional embodiment of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention. Structures, devices, and operating methods not specifically described or explained in this invention, unless otherwise specified or limited, shall be implemented according to conventional means in the art.

Claims

1. A cross-rotor UAV gust adaptive stability control system, characterized in that, include: The flight status perception module is used to collect flight status parameters in real time; The gust identification module is used to identify the external gust disturbance state based on flight status parameters, establish gust characteristic parameters, extract gust disturbance characteristic frequencies, combine gust characteristic parameters and gust disturbance characteristic frequencies, estimate the gust direction and location of action, and output the gust identification result. The rotor coupling state analysis module is used to analyze the coupled vibration state and wake interference characteristics between rotors, and to determine whether it has entered a resonance enhancement state or an unstable flight state. The state estimation and prediction module is used to establish the current state and gust model, integrate the current state and gust model with flight state parameters, gust identification results and rotor coupling state results, solve the current complete flight state, and predict the future flight path; The adaptive control module is used to build an artificial intelligence model, input gust recognition results and rotor coupling state results, dynamically adjust flight control parameters, generate control commands, and realize flight stability control in gust environments. The flight execution module is used to execute the control commands generated by the adaptive control module.

2. The cross-rotor UAV gust adaptive stabilization control system according to claim 1, characterized in that: The gust identification module employs a combination of time-domain and frequency-domain analysis to perform fast Fourier transform analysis on the body vibration signal and extract the characteristic frequencies of gust disturbances.

3. The cross-rotor UAV gust adaptive stability control system according to claim 1, characterized in that, The gust identification module includes: The wind field fluctuation analysis unit is used to analyze flight state parameters and extract the amplitude and period of gust changes. The vibration spectrum analysis unit is used to perform fast Fourier transform analysis on the vibration signal of the machine body and extract the characteristic frequency of gust disturbance. The transient energy change analysis unit is used to monitor transient energy changes in attitude and velocity parameters of flight status. The gust level determination unit is used to establish a gust level model. It inputs the output data of the wind field fluctuation analysis unit, vibration spectrum analysis unit, and transient energy change analysis unit into the gust level model, determines and outputs the gust level.

4. The cross-rotor UAV gust adaptive stability control system according to claim 1, characterized in that, The rotor coupling state analysis module includes: The rotor phase analysis unit is used to extract the rotor's phase difference and synchronization status. The vibration energy flow analysis unit is used to establish a rotor coupled energy flow model and identify the transmission state of vibration energy between rotors. The rotor wake coupling analysis unit is used to analyze the aerodynamic interference between the downwash and the upwash. The nonlinear vibration identification unit is used to identify nonlinear vibration characteristics such as higher-order harmonics and subharmonics.

5. The cross-rotor UAV gust adaptive stabilization control system according to claim 1, characterized in that: The rotor coupling state analysis module extracts rotor speed, torque, vibration data, coupling frequency, harmonic characteristics and energy distribution during the analysis of the coupled vibration state and wake interference characteristics between rotors, which are used to calculate rotor aerodynamic force and thrust fluctuations. Analysis of rotor phase difference and synchronization state based on rotor aerodynamic and thrust fluctuations; When entering an unstable flight state, the coupling interference features are extracted to assess the coupling interference level and output the coupling state results. The coupling state output includes coupling strength coefficient, disturbance characteristic frequency set, vibration energy transfer direction and amplitude, providing multiple inputs for the adaptive control module to dynamically adjust flight control parameters in order to improve flight attitude stability.

6. The cross-rotor UAV gust adaptive stability control system according to claim 1, characterized in that, When the state estimation and prediction module calculates the current complete flight state, it uses extended Kalman filtering or unscented Kalman filtering to fuse flight state parameters, gust identification results and rotor coupling state results, and calculates the accurate 12-dimensional state vector of the cross-rotor UAV to improve the accuracy of the current state and gust model in predicting the future flight path.

7. The cross-rotor UAV gust adaptive stability control system according to claim 1, characterized in that, The adaptive control module includes: Thrust distribution control unit, used to adjust the thrust distribution ratio of the twin rotors; The rotor speed adjustment unit is used to adjust the speed of each rotor. Phase synchronization control unit is used to control the rotor phase difference to reduce coupled vibration; Attitude stabilization compensation unit is used to compensate for attitude deviations caused by gusts of wind; Nonlinear vibration suppression control unit, used to suppress nonlinear vibration.

8. The cross-rotor UAV gust adaptive stability control system according to claim 1, characterized in that, The adaptive control module performs flight stability control in gust winds, specifically including the following steps: Once the control objective is determined, the adaptive control module dynamically determines the control priority based on the gust identification results and the rotor coupling status results. Design a controller that linearizes the current state with the gust model near the equilibrium point; Parameters are optimized online using a genetic algorithm; Output control commands and evaluate the effectiveness of flight control.

9. A cross-rotor UAV gust adaptive stabilization control system according to claim 8, characterized in that: The online parameter optimization using a genetic algorithm specifically includes the following steps: Establish parameter mapping relationships, mapping the control gain parameters to the weight matrix and feedforward matrix; Establish optimized coding, using real numbers to encode chromosomes; Establish a fitness function, comprehensively consider control accuracy and energy consumption under gust scenarios, and calculate the fitness value; Control commands are generated based on feedforward and feedback; Establish preset correction conditions, compare the feedback data with the preset correction conditions, and evaluate the flight control effect based on the comparison results.

10. A cross-rotor unmanned aerial vehicle (UAV) employing the cross-rotor UAV gust adaptive stability control system as described in any one of claims 1-9, comprising a fuselage (1), wherein a rotor (2) and a tail fin (3) are disposed on the fuselage (1), characterized in that, Also includes: Millimeter-wave radar (4), vision camera (5) and vibration sensor (6) are installed at intervals on the bottom of the fuselage (1); A barometric altimeter (7), a GNSS antenna (8), a wind speed and direction sensor (9), and a gust sensor (10) are installed at intervals on the top of the fuselage (1); The first rotational speed sensor (11), the IMU inertial measurement unit (12), and the second rotational speed sensor (13) are installed at intervals on the rotor (2); The control surface position sensor (14) and the tail attitude sensor (15) are installed at intervals on the tail fin (3).

Images