A stable posture wind resistance control method for a resource recycling scheduling and distribution unmanned aerial vehicle

Abstract

The application discloses a kind of unmanned aerial vehicle for recycling resource scheduling distribution stable posture wind resistance control method, this method is combined with the relative air speed estimated wind speed, and then calculate wind disturbance;Based on proportionality coefficient, acceleration coefficient and wind force compensation coefficient, wind force compensation amount is solved, which is superimposed with preset conventional control amount to obtain output control amount, and the driving motor PWM instruction is updated to offset wind disturbance.Simultaneously, through the data acquisition of speed and power measurement unit, speed / torque mode adaptive switching and emergency landing protection under extreme working condition are realized.The application improves the attitude stability and transportation accuracy of unmanned aerial vehicle in complex wind field, ensures the efficiency and equipment safety of recycling resource distribution, and is suitable for lightweight recycling resource mountain, tunnel transportation scene.The application aims to solve the problem of unstable attitude of unmanned aerial vehicle when transporting recycling resources in complex scenes such as rural tunnels and rugged mountain roads.

Description

Technical Field

[0001] This invention relates to the field of unmanned aerial vehicle (UAV) flight control technology, specifically to a method for stabilizing attitude and resisting wind in a UAV used for dispatching and distributing renewable resources. Background Technology

[0002] In rural alleyways and rugged mountain roads where traditional transportation methods are difficult to penetrate, the recycling and transportation of lightweight recyclable resources such as cardboard and plastic bottles have long relied on manual collection and handling. These scenarios not only have poor access conditions, making it difficult for vehicles to enter, but also result in low efficiency and high labor intensity for manual transportation. Furthermore, recyclable resources are prone to moisture damage and contamination due to untimely transfer.

[0003] In some areas, drones have been deployed for the transportation of recycled resources. Personnel collect recycled materials such as cardboard and plastic bottles, then load them onto drones for transport to designated locations, reducing the need for manual labor in the process. However, wind often interferes with drone operations in rural alleyways and rugged mountain roads, necessitating optimization of drone attitude stabilization and wind resistance control. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a method for stabilizing attitude and resisting wind for unmanned aerial vehicles (UAVs) used for dispatching and distributing renewable resources.

[0005] The technical solution adopted by this invention to solve the above-mentioned technical problems is: a method for attitude stabilization and wind resistance control of a drone used for dispatching and distributing renewable resources, comprising the following steps: S1, Estimated wind speed V wind : ; This refers to the actual speed of the drone; The preset speed of the drone relative to the air; S2, The UAV's control unit calculates wind disturbance F wind : ; in, air density; This is the drag coefficient; For windward area; S3. The UAV's control unit calculates the wind compensation amount u. wind : ; in, For the desired speed; This refers to the actual speed of the drone; For the desired acceleration; This refers to the actual acceleration of the drone; This is the proportionality coefficient; The acceleration coefficient; This is the wind compensation coefficient; S4. The UAV control unit calculates and outputs the control quantity u: ; This is the preset standard control value; The drone's control unit updates the PWM command of the drone's drive motor based on the output control quantity u.

[0006] Preferably, the UAV is equipped with a rotational speed measurement unit and a power measurement unit; The speed measurement unit collects the real-time speed value S of the drive motor of the UAV. z The power measurement unit collects the real-time power value S of the drone's drive motor. gl ; N real-time rotation speed values ​​S are collected according to the time period. z Create a real-time speed dataset, and obtain cleaned real-time speed data based on the real-time speed dataset. ; and, collect N real-time power values ​​according to a time period. Create a real-time power dataset, and obtain cleaned real-time power data from the real-time power dataset. ; Calculate the angular velocity J of the motor sd The angular velocity J of the motor sd The algorithm expression is as follows: ; Calculate motor torque D jnj ; The motor torque D jnj The algorithm expression is as follows: ; In the formula, Indicates the efficiency of the drive motor; The angular velocity J of the motor sd and the preset motor angular velocity threshold J sdyz In comparison, when the motor angular velocity J sd Greater than the preset motor angular velocity threshold J sdyz At this time, the drone's drive motor switches to speed control mode; Motor torque D jnj and motor torque threshold D jnjyz In comparison, when the motor torque D jnj Greater than the preset motor torque threshold D jnjyz At this time, the drone's drive motor switches to torque control mode; When the motor angular velocity J sdGreater than the preset motor angular velocity threshold J sdyz When and when the motor torque D jnj Greater than the preset motor torque threshold D jnjyz At that time, the drone's control unit controls the drone to perform a landing maneuver.

[0007] Preferably, the real-time rotation speed data after cleaning The algorithm expression is as follows:

[0008] The expression for the real-time rotational speed dataset is: , This represents the total number of data points in the real-time speed dataset. In This means that the calculation starts from the first data point in the real-time speed dataset. Begin calculation. This indicates that the calculation up to the first [number]th [item] in the dataset is performed. Up to the last data point, that is, until the calculation is completed. Up to this point, N in the denominator represents the number of data points in the dataset. Data.

[0009] Preferably, the real-time power data after cleaning The algorithm expression is as follows:

[0010] The expression for the real-time power dataset is: , This represents the total number of data points in the real-time speed dataset. In This means that the calculation starts from the first data point in the real-time speed dataset. Begin calculation. This indicates that the calculation up to the first [number]th [item] in the dataset is performed. Up to the last data point, that is, until the calculation is completed. Up to this point, N in the denominator represents the number of data points in the dataset. Data.

[0011] The beneficial effects of this invention are as follows: The attitude stabilization and wind resistance control method for UAVs used for renewable resource dispatch and distribution of this invention estimates wind speed by combining a preset relative air speed, and then calculates wind disturbance; based on the proportional coefficient, acceleration coefficient, and wind compensation coefficient, the wind compensation amount is solved, and this is superimposed with a preset conventional control amount to obtain the output control amount, which updates the PWM command of the drive motor to counteract wind disturbance. Simultaneously, data is collected through the speed and power measurement unit to achieve adaptive switching of speed / torque modes and emergency landing protection under extreme conditions.

[0012] This invention directly calculates compensation for wind field disturbances through wind speed estimation, wind disturbance quantification, and feedforward compensation mechanisms. It does not require waiting for speed or acceleration deviations to accumulate, resulting in fast response and significantly improved flight stability in complex wind field environments. Attached Figure Description

[0013] Figure 1 This is a flowchart of the control method of the present invention. Detailed Implementation

[0014] The present invention will now be described in further detail with reference to the accompanying drawings and preferred embodiments. These drawings are simplified schematic diagrams, illustrating only the basic structure of the invention, and therefore only show the components relevant to the invention.

[0015] The following provides a detailed description of the attitude stabilization and wind resistance control method for the unmanned aerial vehicle (UAV) used for the dispatch and distribution of renewable resources according to the present invention. In this embodiment, the UAV used for the dispatch and distribution of renewable resources is a 30KG payload UAV.

[0016] The hardware modules carried by the heavy-duty drone include: GPS module: Obtains the actual speed V of the drone meas ; IMU (Inertial Measurement Unit): Acquires the actual acceleration of the UAV. ; Speed ​​measurement unit: Employs a magnetoelectric speed sensor with a measurement range of 0-6000 r / min and an accuracy of ±1 r / min; Power measurement unit: Employs a three-phase power sensor, with a measurement range of 0-20kW and an accuracy of ±0.5W; Control unit: Selected from STM32H7 series, which has floating-point operation acceleration function and can complete multi-parameter parallel calculation, mode switching logic judgment and PWM instruction output; Drive motor: Equipped with a high-power brushless DC motor (rated power 15kW), it supports speed / torque mode switching, with a starting torque ≥50N・m and a continuous operating torque ≥40N・m, meeting the payload flight requirements of 30KG of recycled resources (such as cardboard bundles and plastic bottle packages).

[0017] The following parameters are preset: Air density ρ = 1.225 kg / m³ 3 ; The windward area of ​​the drone is A = 1.8m. 2 ; The drag coefficient C = 0.92; proportionality coefficient K p =8.0; acceleration coefficient K d =4.0; Wind compensation coefficient K f =7.5; Motor angular velocity threshold J sdyz =350rad / s; avoid overload and overspeed; Motor torque threshold D jnjyz =40 N·m; The efficiency of the drive motor is ω=0.93; The data acquisition period is T=0.08s, and N=15 speed data and N=15 power data are acquired in each period to ensure the integrity and anti-interference of the dataset.

[0018] Specific control process: (I) Data Acquisition and Preprocessing Speed ​​and power data acquisition and cleaning: The speed measurement unit and power measurement unit acquire N=15 real-time speed values ​​S according to a period T. z (Forming a dataset) ) and N=15 real-time power values ​​S gl (Forming a dataset) ).

[0019] The control unit uses a mean filtering method to clean the data and remove outliers caused by vibration during heavy-load flight. The calculation formula is as follows: Real-time rotation speed data after cleaning The algorithm expression is as follows: ; Real-time power data after cleaning The algorithm expression is as follows: .

[0020] (II) Calculation of wind disturbance and solution of compensation amount, such as Figure 1 As shown: Wind disturbance F wind calculate: The actual speed V of the drone relative to the ground is collected by the GPS module configured on the drone. meas Decomposed into horizontal x-axis component V mean_x =7.5m / s, horizontal y-axis component V mean_y =2.1m / s, vertical z-axis component V mean_z =0.1m / s, the sampling frequency is consistent with the data processing period T=0.08s. V mean = ≈7.79m / s.

[0021] Based on the preset V air Decomposed into horizontal x-axis component V air_x =1.9m / s, horizontal y-axis component Vair_y =-2.1m / s, vertical z-axis component V air_z =0.1m / s.

[0022] Calculate the components of wind speed: V wind_x =V mean_x -V air_x = 5.6m / s; V wind_y =V mean_y -V air_y =4.2m / s; V wind_z =V mean_z -V air_z =0m / s; Final synthesis V wind = =7m / s; The control unit estimates the wind speed V wind And based on preset parameters, the disturbance of wind force on the heavy-load drone is calculated using a formula: ; When estimating wind speed V wind When F = 7m / s wind =2×1.225×0.92×1.8×7=28.4004N, which reflects the estimated intensity of wind interference on the flight attitude of the UAV.

[0023] Wind compensation amount u wind Calculation: The control unit obtains the actual speed V of the drone via GPS. meas The actual acceleration is obtained through the IMU inertial measurement unit. Determine the desired speed based on the pre-set flight mission (such as constant speed transport). and expected acceleration Substitute into the compensation formula: ; like =7m / s, V meas =7.79m / s =0.5m / s 2 , =0.3m / s 2 F wind =28.4004N, then u wind =8.0×(7-7.79)+4.0×(0.5-0.3)+7.5×28.4004=207.483; Output control quantity u calculation: Preset normal control quantity U nominal (U-shaped flight under heavy load conditions) nominal =300), and the final control quantity is obtained by superimposing the compensation amount: u=Unominal +u wind By using feedforward compensation to offset wind field disturbances, wind resistance is improved.

[0024] Using the example above, u=300+207.483=507.483. The control unit converts this value into a PWM command (duty cycle range 0-100%) and outputs it to the drive motor. By adjusting the motor output power, the wind disturbance is counteracted, ensuring stable flight attitude under a 30KG load.

[0025] In other embodiments, In this implementation, only the scaling factor K is set. p and acceleration coefficient K d .

[0026] Unadded At that time, compensation only depends on Compensation should only be initiated after wind disturbance causes a deviation in speed / acceleration. However, the 30KG drone has a large inertia, and by the time the deviation accumulates to a detectable level, there is already a significant attitude shift (such as a decrease in speed when facing headwinds). The compensation lag will exacerbate the fluctuations.

[0027] join in After that, F wind It is a direct quantification of wind disturbance. As soon as wind disturbance occurs, the compensation term responds immediately without waiting for the deviation to accumulate, thereby improving the wind resistance response speed and reducing hysteresis error.

[0028] K f Calibration can be performed based on the drone's payload inertia (m=30kg), for example, wind disturbance of 13.7N, via K. f =0.2 can directly output a compensation amount of 2.74, reducing system oscillation and improving flight stability under heavy load.

[0029] Motor status monitoring and mode switching: Motor angular velocity J sd Calculation: Based on rotational speed data after cleaning The real-time angular velocity of the motor is calculated using the following formula: .

[0030] like =2850.67 r / min, then J sd =(2×3.14×2850.67) / 60≈309rad / s; Motor torque D jnj Calculation: Calculate the real-time torque of the motor using the formula:

[0031] like =12010W, ω=0.93, J sd≈309rad / s, then D jnj =(12010×0.93) / 309≈36.1N・m.

[0032] Mode switching and security control: When J sd When the speed exceeds 350 rad / s (e.g., due to sudden strong winds causing motor overspeed), the control unit immediately switches the drive motor to speed control mode. By limiting the PWM duty cycle, the speed is stabilized within the threshold to prevent motor overload and burnout. The drive motor speed is quickly adjusted to counteract speed fluctuations caused by the wind.

[0033] When D jnj When the torque exceeds 40 N·m (e.g., when climbing a hill against the wind, causing the torque to exceed the limit), switch the drive motor to torque control mode. Control the torque output through current limiting to protect the motor transmission system, limit the drive motor output, and avoid overload damage.

[0034] If J is satisfied at the same time sd >350 rad / s and D jnj If the temperature exceeds 40 N·m (e.g., in extreme wind and steep slope conditions), the control unit will initiate an emergency landing procedure: first, adjust the drone's attitude to a horizontal position (roll and pitch angles ≤ 3°), then slowly descend to the nearest safe area (e.g., on flat ground) at a descent speed of 0.5 m / s to avoid the loaded drone from losing control and crashing.

[0035] This embodiment conducts a transportation test of 30KG of recycled resources (plastic bottle packages, volume 0.8m×0.5m×0.4m) in a rugged mountain road scenario (wind speed 0-10m / s, including gusts), comparing the performance of the method of this invention with that of traditional heavy-load UAV control methods: Attitude stability: The method of this invention shows no significant yaw deviation at a wind speed of 7 m / s.

[0036] Wind-resistant transportation precision: There is no risk of shaking or falling of recycled resources along the entire 1.5km transportation route.

[0037] Power system protection: No overload or overheating occurred; the emergency landing was smooth, and neither the equipment nor the regenerative resources were damaged.

[0038] This invention relates to a wind-resistant attitude control method for unmanned aerial vehicles (UAVs) used for the dispatch and delivery of recyclable resources. The method aims to address the issue of attitude instability caused by wind interference during UAV transport of recyclable resources in complex scenarios such as rural alleyways and rugged mountain roads. The method estimates wind speed based on a preset relative air velocity, then calculates wind disturbance. Based on proportional coefficients, acceleration coefficients, and wind compensation coefficients, it calculates the wind compensation amount, which is then superimposed with a preset conventional control amount to obtain the output control amount. This output control amount updates the PWM command of the drive motor to counteract wind disturbance. Simultaneously, data is collected through speed and power measurement units to achieve adaptive switching between speed / torque modes and emergency landing protection under extreme conditions. This invention improves the attitude stability and transport accuracy of UAVs in complex wind fields, ensuring the efficiency of recyclable resource delivery and equipment safety. It is suitable for transporting lightweight recyclable resources in mountainous and alleyway scenarios. The adaptive switching between speed control and torque control modes can specifically limit motor overspeed and over-torque operation, preventing drive motor overload burnout or transmission system damage. The emergency landing procedure under extreme conditions ensures the safe landing of the UAV and its loaded recyclable resources, reducing equipment wear and cargo loss risks.

[0039] This invention directly calculates compensation for wind field disturbances through wind speed estimation, wind disturbance quantification, and feedforward compensation mechanisms. It does not require waiting for speed or acceleration deviations to accumulate, resulting in fast response and significantly improved flight stability in complex wind field environments.

[0040] By combining proportional control, acceleration control, and wind-specific compensation control logic, the drone can still track the preset route even under windy conditions without manual intervention to adjust its attitude. This reduces the time spent on transporting recycled resources and improves the delivery efficiency of lightweight recycled resources.

[0041] The above description is merely a specific embodiment of the present invention. Various examples and illustrations do not constitute a limitation on the substantive content of the present invention. Those skilled in the art can modify or transform the specific embodiments described above after reading the specification without departing from the essence and scope of the invention.

Claims

1. A method for attitude stabilization and wind resistance control of a drone used for dispatching and distributing renewable resources, characterized in that: Includes the following steps: S1, Estimated wind speed V wind : ; This refers to the actual speed of the drone; The preset speed of the drone relative to the air; S2, The UAV's control unit calculates wind disturbance F wind : Calculate among them, air density; This is the drag coefficient; For windward area; S3. The UAV's control unit calculates the wind compensation amount u. wind : ； in, For the desired speed; This refers to the actual speed of the drone; For the desired acceleration; This refers to the actual acceleration of the drone; This is the proportionality coefficient; The acceleration coefficient; This is the wind compensation coefficient; S4. The UAV control unit calculates and outputs the control quantity u: ； This is the preset standard control value; The drone's control unit updates the PWM command of the drone's drive motor based on the output control quantity u.

2. The attitude stabilization and wind resistance control method for a drone used for dispatching and distributing renewable resources according to claim 1, characterized in that: The UAV is equipped with a rotation speed measurement unit and a power measurement unit; The speed measurement unit collects the real-time speed value S of the drive motor of the UAV. z The power measurement unit collects the real-time power value S of the drone's drive motor. gl ; N real-time rotation speed values ​​S are collected according to the time period. z Create a real-time speed dataset, and obtain cleaned real-time speed data based on the real-time speed dataset. ; and, collect N real-time power values ​​according to a time period. Create a real-time power dataset, and obtain cleaned real-time power data from the real-time power dataset. ; Calculate the angular velocity J of the motor sd The angular velocity J of the motor sd The algorithm expression is as follows: ； Calculate motor torque D jnj ; The motor torque D jnj The algorithm expression is as follows: ； In the formula, Indicates the efficiency of the drive motor; The motor angular velocity J sd and the preset motor angular velocity threshold J sdyz In comparison, when the motor angular velocity J sd Greater than the preset motor angular velocity threshold J sdyz At this time, the drone's drive motor switches to speed control mode; Motor torque D jnj and motor torque threshold D jnjyz In comparison, when the motor torque D jnj Greater than the preset motor torque threshold D jnjyz At this time, the drone's drive motor switches to torque control mode; When the motor angular velocity J sd Greater than the preset motor angular velocity threshold J sdyz When and when the motor torque D jnj Greater than the preset motor torque threshold D jnjyz At that time, the drone's control unit controls the drone to perform a landing maneuver.

3. The attitude stabilization and wind resistance control method for a drone used for dispatching and distributing renewable resources according to claim 1, characterized in that: Real-time rotation speed data after cleaning The algorithm expression is as follows: ； The expression for the real-time rotational speed dataset is: , This represents the total number of data points in the real-time speed dataset. In This means that the calculation starts from the first data point in the real-time speed dataset. Begin calculation. This indicates that the calculation up to the first [number]th [item] in the dataset is performed. Up to the last data point, that is, until the calculation is completed. Up to this point, N in the denominator represents the number of data points in the dataset. Data points.

4. The attitude stabilization and wind resistance control method for a drone used for dispatching and distributing renewable resources according to claim 1, characterized in that: Real-time power data after cleaning The algorithm expression is as follows: ； The expression for the real-time power dataset is: , This represents the total number of data points in the real-time speed dataset. In This means that the calculation starts from the first data point in the real-time speed dataset. Begin calculation. This indicates that the calculation up to the first [number]th [item] in the dataset is performed. Up to the last data point, that is, until the calculation is completed. Up to this point, N in the denominator represents the number of data points in the dataset. Data points.

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