Control method and system of air guide rope, computer equipment and medium

Abstract

The invention relates to the technical field of aircraft control, in particular to an air guide rope control method and system, computer equipment and a medium. The method comprises the steps that the hook body opening angle, the guide rope separation distance and the swing angular velocity of a guide rope during unhooking are obtained, and a hook body unlocking speed off-rail result is generated; when the guide rope deviates from the set track, performing weighted calculation according to the instantaneous rate difference and the accumulated offset to obtain a plurality of deviation index values; if the inertia abnormal condition of the guide rope is met, a regulation and control instruction signal is output; and according to the current opening angle of the hook body, the separation distance of the guide rope and the swing angular velocity, the working state parameters of the unlocking mechanism and / or the mechanical damping stabilizing device are / is adjusted. By means of the mode, the technical problem that the unlocking speed and swing control dynamic balance cannot be achieved in the complex airflow environment through an existing aerial guide rope control technology is solved, and the guide rope unhooking accuracy and stability are improved.

Description

Technical Field

[0001] This invention relates to the field of aircraft control technology, and in particular to a control method, system, computer equipment, and medium for an aerial guide rope. Background Technology

[0002] With the rapid development of drone technology in key areas such as material delivery, rescue missions, and precision operations, remote control technology using guide ropes, as a core means of achieving precise remote control, directly impacts mission efficiency and flight safety. This technology connects the drone to the target object via a guide rope, enabling precise release and control, and has become an indispensable part of modern aviation operations. Currently, most uncoupling control schemes employ fixed operating modes with preset parameters, revealing significant adaptability deficiencies when facing the complex and ever-changing high-altitude flight environment. Traditional methods cannot adaptively adjust to dynamic conditions such as real-time airflow disturbances. Especially when encountering sudden turbulence, static control strategies struggle to simultaneously optimize uncoupling efficiency and operational stability, their fundamental limitation being the lack of real-time response to environmental changes.

[0003] In the field of guide rope sway suppression and control, existing technologies have established a certain foundation. Existing technology (application publication number CN119336057A) discloses a method for suppressing swaying of a suspended object from an unmanned helicopter. This method collects attitude motion information of the sling box and the adapter plate, calculates the sway-suppressing acceleration, and outputs a control angle to achieve rapid suppression of the suspended object's swaying. While this method improves stability during suspended flight, it primarily targets steady-state sway control and does not specifically address the challenge of balancing the guide rope release speed and swaying dynamics during unhooking. Specifically, existing technologies have two prominent problems: First, sway suppression control relies on overall attitude measurement of the suspended object, lacking specific monitoring of the guide rope separation distance, hook opening angle, and swaying angular velocity at the moment of unhooking, making it difficult to effectively capture unexpected swaying trends caused by airflow disturbances. Second, the control strategy does not integrate a real-time control mechanism for the unlocking mechanism, failing to resolve the inherent contradiction between increased unlocking speed and inertial swaying under anti-entanglement requirements. When a drone encounters sudden turbulence during high-altitude operations, the hook release needs to be accelerated to prevent the guide rope from becoming entangled. However, increased speed exacerbates the inertial force generated by the weight of the guide rope, causing it to swing uncontrollably during release. This not only affects release accuracy but may also impact the drone's flight stability. Operators cannot perceive deviations from the expected trajectory of the guide rope in real time, nor can they adjust the unlocking parameters online. Therefore, existing technologies suffer from insufficient controllability of the release process and an inability to achieve a dynamic balance between unlocking speed and swing control in complex airflow environments. Summary of the Invention

[0004] To address the aforementioned shortcomings or deficiencies, this invention provides a control method, system, computer equipment, and medium for aerial guide ropes, which can solve the technical problem that existing aerial guide rope control technologies cannot achieve a dynamic balance between unlocking speed and swing control in complex airflow environments.

[0005] This invention provides a control method for an aerial guidance rope, which is based on a status monitoring module and a control execution module deployed in an aircraft guidance rope system, including: The status monitoring module obtains the hook opening angle, guide rope separation distance, and swing angular velocity when the guide rope is unhooked.

[0006] Based on the calculation results of the hook unlocking speed according to the hook opening angle, and the auxiliary judgment features generated by the guide rope separation distance and swing angular velocity, the hook unlocking speed deviation result is generated.

[0007] The result of the hook unlocking speed deviation indicates that the guide rope has deviated from the set trajectory. Based on the instantaneous rate difference and cumulative offset in the result of the hook unlocking speed deviation, multiple deviation index values ​​are obtained by weighted calculation.

[0008] In response to any deviation index value satisfying the preset guide rope inertia anomaly condition, a control command signal is output. The guide rope inertia anomaly condition includes the swing amplitude growth rate exceeding the preset growth rate threshold obtained from the time-series characteristic analysis based on the deviation index value, the swing frequency change slope being positive, and the cumulative phase offset value exceeding the preset offset range.

[0009] In response to the control command signal, based on the hook opening angle, guide rope separation distance and swing angular velocity currently acquired by the status monitoring module, the working status parameters of the unlocking mechanism and / or mechanical damping stabilizing device are adjusted by the control execution module.

[0010] According to a second aspect, the present invention provides a control system for an aerial guide rope, comprising: The status monitoring module is configured to acquire the hook opening angle, guide rope separation distance, and swing angular velocity when the guide rope is unhooked.

[0011] The deviation analysis module is configured to calculate the hook unlocking speed based on the hook opening angle and the auxiliary judgment features generated by the guide rope separation distance and swing angular velocity, and generate the hook unlocking speed deviation result.

[0012] The index calculation module is configured to perform weighted calculations based on the instantaneous rate difference and cumulative offset in the hook unlocking speed deviation result when the guide rope has deviated from the set trajectory, to obtain multiple deviation index values.

[0013] The decision control module is configured to output a control command signal when any deviation index value meets the preset guide rope inertia anomaly conditions. The guide rope inertia anomaly conditions include the swing amplitude growth rate exceeding the preset growth rate threshold obtained from the time-series characteristic analysis of the deviation index value, the swing frequency change slope being positive, and the cumulative phase offset exceeding the preset offset range.

[0014] The execution adjustment module is configured to, upon receiving a control command signal, adjust the working status parameters of the unlocking mechanism and / or the mechanical damping stabilizing device by controlling the execution module based on the hook opening angle, guide rope separation distance, and swing angular velocity currently acquired by the status monitoring module.

[0015] According to a third aspect, the present invention provides a computer device comprising: At least one processor; and a memory communicatively connected to the at least one processor; The memory stores instructions that can be executed by the at least one processor, which, when executed by the at least one processor, enables the at least one processor to perform any of the aerial guide rope control methods in the embodiments of the present invention.

[0016] According to another aspect of the present invention, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to cause a computer to execute any of the aerial guide rope control methods in the embodiments of the present invention.

[0017] The present invention provides a remote control method for a guide rope, which is achieved through five core steps: real-time acquisition of state parameters, determination of unlocking speed deviation, analysis of inertial anomaly characteristics, generation of control commands, and dynamic adjustment of actuator parameters. Specifically, the system employs a status monitoring module to acquire the hook opening angle, guide rope separation distance, and swing angular velocity during disengagement, extracting dynamic features of the disengagement process from real-time sensor data. Based on the temporal variation of the hook opening angle, the system calculates the hook unlocking speed and, combined with auxiliary judgment features generated from the guide rope separation distance and swing angular velocity, generates a hook unlocking speed deviation result for early detection of unlocking anomalies. Responding to the hook unlocking speed deviation result indicating that the guide rope has deviated from the set trajectory, multiple deviation index values ​​are obtained through weighted calculation based on the instantaneous rate difference and cumulative offset, quantifying the swing risk intensity. If any deviation index value meets the preset guide rope inertial anomaly condition, a control command signal is output to trigger control intervention. In response to the control command signal, based on the hook opening angle, guide rope separation distance, and swing angular velocity currently acquired by the status monitoring module, the control execution module adjusts the working state parameters of the unlocking mechanism and / or mechanical damping stabilization device, achieving dynamic optimization of driving force and damping force.

[0018] In this technical solution, addressing the lack of dynamic adjustment capability in the static control mode described in the background technology, a step of real-time acquisition of state parameters and discrimination of unlocking speed deviation is introduced. This enables continuous monitoring and anomaly identification of the hook unlocking speed, providing a data foundation for real-time control and overcoming the shortcomings of traditional methods that cannot adapt to airflow changes due to fixed parameter operation. Regarding the contradiction between unlocking speed and swing stability, an inertial anomaly feature analysis step is used to comprehensively judge the trend of excessive inertia under multi-dimensional conditions, constructing an evaluation mechanism that balances anti-entanglement and swing control. This solves the drawback of swing loss of control caused by simply adjusting the unlocking speed in existing technologies. Addressing the lack of real-time response during the unhooking process, a closed-loop control cycle based on sensor feedback is established through steps of generating control commands and dynamically adjusting the parameters of the actuator. This achieves rapid response from monitoring to execution, overcoming the deficiency of operators being unable to intervene in a timely manner in the background technology. Therefore, the technical solution of this invention solves the technical problem that existing aerial guide rope control technology cannot achieve dynamic balance between unlocking speed and swing control in complex airflow environments, improving the accuracy and stability of guide rope unhooking. Attached Figure Description

[0019] Figure 1 This is a flowchart of a control method for an aerial guide rope according to an embodiment of the present invention; Figure 2 This is a flowchart illustrating a remote control method for a guide rope according to another embodiment of the present invention. Figure 3 This is a schematic diagram illustrating the real-time feedback adjustment process performed by the mechanical damping stabilizing device in response to an increased oscillation tendency, according to another embodiment of the present invention. Figure 4 This diagram illustrates the operation flow of performing closed-loop convergence judgment and termination control in a remote control method for a guide rope according to another embodiment of the present invention. Figure 5 This is a schematic diagram of the control system of an aerial guide rope according to an embodiment of the present invention; Figure 6 This is a block diagram of a computer device for implementing embodiments of the present invention. Detailed Implementation

[0020] The following description, in conjunction with the accompanying drawings, illustrates exemplary embodiments of the present invention, including various details to aid understanding. These details should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope of the invention. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0021] During the development of this invention, researchers conducted numerous experiments and data analysis, revealing the intrinsic relationship between the hook unlocking speed, the inertial oscillation of the guide rope, and airflow disturbance: when sudden airflow occurs, the hook unlocking speed needs to be increased to avoid rope entanglement, but an excessively fast unlocking speed can cause unexpected oscillation due to the inertia of the guide rope's weight, creating a contradiction between unlocking efficiency and oscillation stability. Based on this relationship, this invention innovatively proposes this technical solution, utilizing a state monitoring module to acquire the hook opening angle, guide rope separation distance, and oscillation angular velocity in real time. By analyzing these data in real time, the unlocking speed deviation result is generated, and combined with the control execution module, the working parameters of the unlocking mechanism and the mechanical damping stabilization device are dynamically adjusted, thereby achieving precise and controllable unhooking process, embodying the core concept of "monitoring-judgment-regulation" closed-loop control.

[0022] Specifically, through comparative experiments, the invention team discovered three major technical defects in traditional fixed-parameter control methods: first, they cannot adjust the unlocking speed in real time according to environmental changes, leading to entanglement or swaying under sudden airflow changes; second, they lack a real-time monitoring and early warning mechanism for the swaying trend of the guide rope, increasing the risk of instability during the unhooking process; and third, the control strategy is disconnected from the actuator, making dynamic compensation difficult. These technical defects result in low unhooking accuracy and poor safety for UAV guide ropes. However, the state-aware dynamic control method proposed in this invention can improve unhooking stability and adaptability; by introducing deviation index values ​​and inertial anomaly conditions (such as the sway amplitude growth rate exceeding a preset threshold, the slope of the sway frequency change being positive, and the cumulative value of the phase offset exceeding the range), early identification and suppression of swaying risks can be achieved; and by adjusting the driving force and damping parameters in real time, the unhooking process can remain controllable under complex airflow conditions.

[0023] Therefore, this invention provides a control method for an aerial guide rope based on the first aspect. This method is based on a status monitoring module and a control execution module deployed in the aircraft guide rope system and can be applied to a remote control system for a UAV guide rope (hereinafter referred to as the "system"). The system can operate on an onboard flight control computer through real-time control or adaptive adjustment to complete the uncoupling process control in payload delivery missions. Specifically, this system can be deployed in various hardware environments, including but not limited to: a payload delivery UAV platform equipped with a Hall angle sensor, an ultrasonic ranging sensor, and a gyroscope; a control execution unit integrating an unlocking mechanism motor and a mechanical damping stabilization device; and a data processing and feedback loop implemented by an embedded processor. This flexible deployment architecture allows the system to meet both high-precision and high-reliability control requirements and adapt to complex flight conditions such as sudden airflow changes.

[0024] like Figure 1 As shown, the method may include: Step S110: Obtain the hook opening angle, guide rope separation distance, and swing angular velocity of the guide rope when it is unhooked through the status monitoring module.

[0025] The status monitoring module refers to an integrated system composed of multiple sensors, used to collect physical quantity data in real time during the guide rope unhooking process; the hook opening angle refers to the actual angle value of the hook rotating from the closed state to the open state, in degrees. The guide rope separation distance is the straight-line distance between the guide rope connection point and the hook fixing point, in meters (m). ); angular velocity refers to the rate of change of angle per unit time during the swing of the guide rope, expressed in degrees per second (°C / s). ).

[0026] Specifically, the system can acquire voltage signals and convert them into angle data through a Hall angle sensor installed at the hook hinge, measure spatial distance using an ultrasonic ranging sensor, and detect angular velocity signals using a gyroscope sensor. All data are combined into an initial state dataset after being timestamped according to a unified clock reference.

[0027] For example, the system uses a sensitivity of 10 millivolts per degree (mV). The Hall sensor, when the hook is fully closed, has a calibrated zero-point reference voltage of 2.5 volts. When the hook body is opened to 30 degrees, the output voltage difference is 300 millivolts. The ultrasonic sensor emits at 40 kHz ( The pulse, when separated at a distance of 0.5 meters, had a time difference of 1.47 milliseconds. ); The gyroscope uses a microelectromechanical system (MEMS). MEMS (Micro-Mechanical Systems) structure, with an angular velocity of 5 degrees per second ( ). When the output digital signal value is 5, the output value is 5.

[0028] Step S120: Based on the calculation result of the hook unlocking speed based on the hook opening angle, and the auxiliary judgment feature generated by the guide rope separation distance and swing angular velocity, generate the hook unlocking speed deviation result.

[0029] The hook unlocking speed refers to the rate of change of the hook opening angle over time, reflecting the release rate of the guide rope, and is measured in meters per second. The auxiliary judgment features refer to the characteristic parameters derived from the instantaneous change rate of the separation distance of the guide rope and the fluctuation amplitude of the swing angular velocity, which are used to enhance the reliability of the judgment; the hook unlocking speed deviation result refers to the binary conclusion (0 indicates normal, 1 indicates deviation) or quantitative indicator for judging whether the unlocking speed deviates from the set trajectory.

[0030] Specifically, the system can obtain the instantaneous unlocking speed sequence by dividing the difference in the hook opening angle between adjacent sampling moments by the sampling time interval. It then combines the differential value of the separation distance (i.e., the rate of change of distance) and the variance of the swing angular velocity as auxiliary features, and after smoothing with a sliding window, compares the result with the upper limit of the preset threshold to generate the off-track result.

[0031] For example, the system uses 100 For the sampling period, the instantaneous unlocking speed when the hook opening angle increases from 0 degrees to 10 degrees is calculated to be 0.1 meters per second. The preset threshold upper limit is 0.15 meters per second based on a wind speed of 10 meters per second and an altitude of 500 meters; if the 5-point sliding average of the instantaneous velocity sequence is 0.18 meters per second, the output deviation result is 1.

[0032] Step S130: In response to the result of the hook unlocking speed deviation indicating that the guide rope has deviated from the set trajectory, multiple deviation index values ​​are obtained by weighted calculation based on the instantaneous rate difference and cumulative offset in the result of the hook unlocking speed deviation.

[0033] The instantaneous rate difference refers to the instantaneous difference between the actual unlocking speed and the target unlocking speed, measured in meters per second (m / s). The cumulative offset refers to the cumulative error obtained by integrating the instantaneous rate difference over time, and the unit is meters; the deviation index value refers to the scalar value obtained by weighted calculation, which is used to quantify the degree of deviation and has no unit.

[0034] Specifically, the system can trigger the calculation process by reading the deviation result; the instantaneous speed difference is calculated by subtracting the target speed (e.g., 0.2) from the actual speed. The cumulative offset is obtained by performing trapezoidal numerical integration on the instantaneous rate difference sequence. The weighted calculation uses the formula: Deviation index value = instantaneous rate difference × first weight coefficient + cumulative offset × second weight coefficient, where the first weight coefficient is set to 0.6 and the second weight coefficient is set to 0.4.

[0035] For example, when the instantaneous rate difference is When the cumulative offset is 0.02 meters, the deviation index value is calculated as follows: .

[0036] Step S140: In response to any deviation index value satisfying the preset guide rope inertia anomaly condition, output control command signal.

[0037] Among them, the abnormal conditions of guide rope inertia include: the growth rate of swing amplitude exceeding the preset growth rate threshold obtained from the time-series characteristic analysis of deviation index value; the slope of the swing frequency change being positive; and the cumulative value of phase offset exceeding the preset offset range; the swing amplitude growth rate refers to the growth rate of deviation index value per unit time, with the unit being per second ( The slope of the oscillation frequency change refers to the rate of change of the dominant frequency over time, extracted by the Fast Fourier Transform (FFT), and is measured in Hertz per second (Hz). The cumulative phase offset value refers to the sum of the initial phase angle differences of the main frequency, in degrees. The preset growth rate threshold is set to 0.1 per second. The frequency change slope threshold is set to 0.05. The offset range is set to .

[0038] Specifically, the system can perform time series analysis on the deviation index value sequence, calculate the average growth rate within the sliding window as the swing amplitude growth rate, use linear regression to fit the frequency time series to obtain the change slope, and calculate the phase offset by accumulating the phase angle difference. If all conditions are met at the same time, the system outputs a control command signal (such as binary flag 1).

[0039] For example, when the deviation indicator value increases from 0.02 to 0.12 within 5 seconds, the swing amplitude increases by 0.02%. ; frequency from Increase to The slope of the time variation is 0.06. The phase offset is accumulated as Because the growth rate exceeded the threshold of 0.1 If the slope is positive and the offset is out of range, the system outputs a control command signal.

[0040] Step S150: In response to the control command signal, based on the hook opening angle, guide rope separation distance and swing angular velocity currently acquired by the status monitoring module, the working status parameters of the unlocking mechanism and / or mechanical damping stabilizing device are adjusted by the control execution module.

[0041] Among them, the control execution module refers to the hardware unit consisting of a motor driver and a damping controller, which is used to adjust the execution parameters; the working status parameters refer to the driving force output level of the unlocking mechanism (such as the motor duty cycle, in percentage %) or the damping coefficient of the mechanical damping stabilizing device (unitless).

[0042] Specifically, the system can calculate the driving force adjustment through a proportional-integral-derivative (PID) control algorithm, or set the damping coefficient by querying a damping parameter table, while monitoring the status data feedback in real time to ensure the effectiveness of the adjustment.

[0043] For example, when the control command signal is triggered, the system reads that the current hook opening angle is 25 degrees. The separation distance is 0.6 meters, and the swing angular velocity is 8 degrees per second. The driving force can be adjusted from 50% to 30% via PID calculation, or the mechanical damping stabilization device can be activated and the damping coefficient set to 0.7; after adjustment, the oscillation angular velocity will decrease. This indicates that the optimization of the working status parameters is effective.

[0044] In other embodiments, such as Figure 2 The diagram shows a flowchart of the remote control method for the guide rope. This method can be applied to rescue material delivery missions to illustrate the workflow and actual effects of this technical solution. In this embodiment, the drone is flying at an altitude of 1500 meters, the ambient wind speed is 8 meters per second, and the guide rope detachment control needs to be performed on the suspended rescue materials.

[0045] The UAV control system first executes step S101 to acquire the opening angle of the payload delivery UAV hook, the separation distance of the guide rope, and the swing angular velocity to obtain the initial state dataset. Specifically, the Hall angle sensor measures that the hook is in the initial closed position (0 degrees), the ultrasonic ranging sensor measures that the separation distance of the guide rope is 0.1 meters, and the MEMS gyroscope measures that the swing angular velocity is close to 0 degrees per second. The system adds a unified timestamp to these three data points and packages them to form the initial state dataset.

[0046] Subsequently, the system executes step S102, determining whether the hook unlocking speed deviates from the set trajectory based on the initial state dataset. If the unlocking speed exceeds the preset threshold upper limit, it indicates a preliminary sign of an unexpected swinging trend in the guide rope at the moment of disengagement, and outputs a deviation index value based on this judgment. If the unlocking speed does not exceed the preset threshold upper limit, it indicates that the guide rope disengagement process is normal, with no signs of unexpected swinging trend, and outputs a normal state index value. The control system begins to unlock the hook according to the command. Within 0.5 seconds after the start of disengagement, the average value of the instantaneous unlocking speed sequence calculated by the system and smoothed through a sliding window is 0.22 meters per second. Based on the current flight altitude and wind speed, the speed threshold upper limit obtained from the preset configuration table is 0.18 meters per second. Since 0.22 meters per second > 0.18 meters per second, the system determines that the unlocking speed has deviated from the set trajectory, indicating a preliminary sign of an unexpected swinging trend, and outputs a non-zero deviation index value (e.g., 0.15). If the speed does not exceed the threshold, a zero value is output as a normal state index value.

[0047] Next, in step S103, the swing trend characteristics are extracted based on the time-series changes in the deviation index value. After filtering out noise interference using a Kalman filter algorithm, smoothed trend data is obtained. The system then determines whether the smoothed trend data indicates excessive guide rope inertia. If so, a control command signal is output and subsequent adjustments are initiated; otherwise, a maintenance command signal is output to keep the current control parameters unchanged. The system performs Kalman filtering on the deviation index values ​​for multiple consecutive cycles to obtain smoothed trend data. Analysis of this trend data reveals that the swing amplitude growth rate, frequency change slope, and cumulative phase offset all show an increasing trend, indicating a clear signal of "excessive guide rope inertia." Therefore, the system outputs a control command signal to initiate the subsequent adjustment process. If the "excessive inertia" condition is not met, the system outputs a maintenance command signal to keep the current control parameters unchanged.

[0048] Upon receiving the control command signal, the system executes step S104. Based on the control command signal, it obtains the current driving force output level. Using the deviation signal between the actual unlocking speed and the target unlocking speed, it calculates the required torque compensation amount using a proportional-integral-derivative (PID) control algorithm, generating the adjusted driving force output parameters. The system reads the current driving force output level and, based on the real-time calculated deviation signal between the actual unlocking speed and the target unlocking speed (0.18 m / s), calculates the required torque compensation amount using a PID control algorithm. Assuming the current deviation is 0.04 m / s, the torque compensation amount obtained after PID calculation is... Newton-meters (negative values ​​indicate a need to reduce output). Based on this, the system corrects the current drive force output level, generates adjusted drive force output parameters (e.g., reducing the target motor torque from 5.0 Newton-meters to 4.5 Newton-meters), and sends them to the motor driver of the unlocking mechanism for execution.

[0049] In step S105, the activation conditions of the mechanical damping stabilization device are determined from the adjusted driving force output parameters. When the adjusted driving force output parameters indicate that the oscillation trend continues to increase, the auxiliary mechanical damping stabilization device is activated. The oscillation intensity level of the guide rope is analyzed, and a stable control sequence is generated according to the damping parameters and control timing corresponding to the oscillation intensity level. After adjusting the driving force, the system continues to monitor the oscillation angular velocity. If the peak angular velocity continues to climb from 10 degrees per second to 15 degrees per second within the next 2 seconds, it indicates that the oscillation trend continues to increase even after adjusting the driving force alone. The system then activates the auxiliary mechanical damping stabilization device. The system analyzes the current oscillation intensity level (for example, judging it as "moderate" oscillation based on the peak angular velocity of 15 degrees per second), queries the preset parameter table, obtains the damping coefficient corresponding to the "moderate" level as 0.7, and the duration of action as 3 seconds, and generates a stable control sequence containing the application time, magnitude, and duration of the damping force, and sends it to the damping device controller.

[0050] Finally, the system executes step S106, which monitors the change in the hook opening angle in real time according to the stable control sequence, updates the guide rope separation distance and swing angular velocity, obtains the updated state dataset, and compares it with the initial state dataset to determine the convergence of the closed-loop control system. Based on the system's convergence, it confirms that the entire unhooking process is under control, terminates the control cycle via this signal, and records log data. The system compares this updated dataset with the initial state dataset and calculates the comprehensive deviation value. If the comprehensive deviation value continuously decreases for five consecutive sampling periods (each period being 100 milliseconds), and the latest value is lower than the preset convergence threshold (e.g., 0.1), it is determined that the closed-loop control system for the entire guide rope unhooking process has converged and is under control. The system then generates a control termination signal, terminates the current control cycle, and records the state data, control commands, and timestamps of the entire control process into a log file in non-volatile memory for subsequent analysis.

[0051] Therefore, according to the above implementation method, the system obtains the hook opening angle, guide rope separation distance, and swing angular velocity of the guide rope during unhooking through the state monitoring module, which is used to extract the dynamic characteristics of the unhooking process from real-time sensor data; the hook unlocking speed is calculated based on the time-series change of the hook opening angle, and the auxiliary judgment features generated by the guide rope separation distance and swing angular velocity are combined to generate the hook unlocking speed deviation result, which is used to realize the early detection of abnormal unlocking status; in response to the hook unlocking speed deviation result indicating that the guide rope has deviated from the set trajectory, multiple deviation index values ​​are obtained by weighted calculation based on the instantaneous rate difference and cumulative offset, which are used to quantify the swing risk intensity; in response to any deviation index value satisfying the preset guide rope inertial anomaly condition, a control command signal is output to trigger control intervention; in response to the control command signal, based on the hook opening angle, guide rope separation distance, and swing angular velocity currently obtained by the state monitoring module, the working state parameters of the unlocking mechanism and / or mechanical damping stabilization device are adjusted by the control execution module to realize the dynamic optimization of driving force and damping force.

[0052] Specifically, in this embodiment, addressing the lack of dynamic adjustment capability in the static control mode described in the background technology, a step of real-time acquisition of state parameters and deviation judgment of unlocking speed is introduced. This enables continuous monitoring and anomaly identification of the hook unlocking speed, providing a data foundation for real-time control and solving the deficiency of traditional methods that cannot adapt to airflow changes due to fixed parameter operation. Regarding the contradiction between unlocking speed and swing stability, an inertial anomaly feature analysis step is used to comprehensively judge the trend of excessive inertia under multi-dimensional conditions, constructing an evaluation mechanism that balances anti-entanglement and swing control, thus solving the drawback of swing loss of control caused by simply adjusting the unlocking speed in existing technologies. Addressing the lack of real-time response during the unhooking process, a closed-loop control cycle based on sensor feedback is established through steps of generating control commands and dynamically adjusting the parameters of the actuator. This achieves rapid response from monitoring to execution, overcoming the deficiency of operators being unable to intervene in a timely manner in the background technology. Therefore, the technical solution of this invention solves the technical problem that existing aerial guide rope control technology cannot achieve dynamic balance between unlocking speed and swing control in complex airflow environments, improving the accuracy and stability of guide rope unhooking.

[0053] In other embodiments, such as Figure 3 This diagram illustrates the real-time feedback adjustment process of a mechanically damped stabilizing device in response to an increasing swaying tendency. The process details the closed-loop control flow from receiving control commands to dynamically adjusting damping parameters for precise anti-sway control. Specifically, in a guide rope unhooking scenario, once the system determines that the swaying tendency is continuously increasing and issues a command to activate the mechanically damped stabilizing device, it enters this real-time adjustment cycle. First, the system sends a pulse width modulation (PWM) signal to the electromagnetic braking unit of the damping device according to the damping parameters specified in the control command (e.g., a damping coefficient of 0.7). This signal is a 1 kHz PWM wave with a 70% duty cycle, used to precisely control the average current flowing into the electromagnetic coil. Next, the system uses a current sensor for closed-loop feedback to stabilize the coil current at a target value. For example, if the target current is set to 2.0 amperes (A), the system uses a proportional-integral (PI) regulator to precisely maintain the actual current at... Within the range of A. A stable current causes the electromagnetic braking unit to generate braking force and record it. According to the electromagnetic force formula, the coil generates a braking torque in the magnetic field that is proportional to the current. For example, at a current of 2.0 A, approximately 5.0 Newton-meters can be generated (…). The system simultaneously records the braking torque, current value, and timestamp into a buffer queue. This is based on real-time monitoring of the guide rope's angular velocity (e.g., ) Given the target's deflection angle and separation distance, the system calculates the target's deflection angle. This calculation may employ model-based feedforward control or a lookup table method. For example, based on a pre-set aerodynamic model mapping table, for the current... Based on the angular velocity and the separation distance of 0.8 meters (m), the deflection angle of the target wing was found to be 15 degrees. After the calculation is completed, the system drives the airfoil to the target angle. The system receives the target angle command (15 degrees) via a servo motor and moves at a maximum angular velocity of 30°. The system rotates, driving the blade from 0 degrees to 15 degrees within 0.5 seconds, and locks the position via encoder feedback upon reaching the target. Simultaneously, the system collects tension data and calculates the gradient. Multiple tension sensors (e.g., three) distributed on the guide rope collect data in real time, and the system calculates the rate of change of the difference between adjacent sensor readings as the tension gradient. For example, if three sensor readings are 100 Newtons (N), 115 N, and 105 N, the calculated gradient sequence is as follows: The system then determines whether the threshold has been exceeded. The calculated absolute value of the maximum tension gradient (e.g., ...) is then used. ) and preset safety thresholds (such as The comparison is then performed. Finally, the control parameters are adjusted based on the judgment result. If the threshold is not exceeded ( The system maintains the current PWM duty cycle (70%) and vane angle (15 degrees). If the threshold is exceeded, the control parameters are dynamically adjusted upwards according to the proportion of the exceedance. For example, if the gradient reaches... Exceeding the threshold If the system proportionally increases the PWM duty cycle to 80%, it will recalculate a larger target vane deflection angle (e.g., 18 degrees) and initiate a new adjustment cycle. This closed-loop process continues until the overall deviation value meets the convergence condition, at which point the system exits the adjustment cycle.

[0054] In other embodiments, such as Figure 4 The diagram illustrates the operation flowchart for closed-loop convergence judgment and termination control in the remote control method for guide ropes. This flowchart specifically describes how, after the control execution module completes parameter adjustments, the system iteratively monitors and judges to ultimately determine that the unhooking process has reached a stable and controllable state and automatically terminates control. A typical scenario for this process in practical applications is the state assessment and closed-loop termination of a UAV after completing a unhooking maneuver. After the system initiates this process, it first executes the step "Read Hook Angle Periodically." Specifically, the system reads the latest hook opening angle value from the angle sensing unit via the Controller Area Network (CAN) bus at fixed control cycles (e.g., 100 milliseconds). For example, at 3.0 seconds after the start of the unhooking maneuver, the system reads the hook opening angle as 30 degrees (…). Following this, the system executes the steps of "acquiring guide rope distance" and "acquiring swing angular velocity" in parallel. Within the same control cycle, the system acquires guide rope separation distance data (e.g., 0.9 meters) from the ultrasonic ranging sensor via the Serial Peripheral Interface (SPI), and simultaneously acquires swing angular velocity data (e.g., ...) from the microelectromechanical system (MEMS) gyroscope via an analog-to-digital converter (ADC). Subsequently, the system executes the step of "aligning and combining data." Because there may be slight time differences between data acquisition and transmission from different sensors, the system timestamps the three sets of data using a unified high-precision clock source, employing linear interpolation to ensure they correspond to the same sampling time. Then, the system combines the aligned angle, distance, and angular velocity data into a data unit with the same structure as the initial state dataset, for example: Upon entering the core judgment stage, the system executes the step "calculate three types of deviation values". The system compares this data unit with the initial state dataset used as a reference, and calculates the angle deviation respectively. ), distance deviation ( ) and angular velocity deviation ( For example, if the initial angle is 50 degrees, the initial distance is 0.8 meters, and the initial angular velocity is 5 degrees per second, then the current deviation value is: Spend, rice, The system calculates the overall deviation value per second. Then, the system executes the step "determine if the deviation has converged." The system not only calculates the overall deviation value for the current period (e.g., 0.25 calculated using the normalized Euclidean distance formula), but also groups the overall deviation values ​​of the most recent N consecutive periods (e.g., N=5) into a sequence. The system determines whether this sequence meets the conditions of continuously decreasing (i.e., each subsequent value is less than the previous value) and the latest value is below a preset convergence threshold (e.g., threshold = 0.1). If it only meets the condition of decreasing but not below the threshold, or if the value fluctuates, it is determined to be non-converged, and the process returns to the initial step to continue monitoring the next period. When the deviation value sequence of 5 consecutive periods (e.g., ...) The system determines convergence when it simultaneously satisfies the conditions of monotonically decreasing and the latest value (0.08) being lower than the threshold (0.1). After convergence is determined, the system executes the step "generate termination control signal". The system outputs a specific level transition signal (e.g., from low level 0 to high level 1) through a digital input / output (DIO) port. This signal is received by the controller of the unlocking mechanism and the mechanical damping stabilization device as an instruction to stop receiving new control commands and maintain the current operating parameters. Finally, the system executes the step "record data to log". Before exiting the control loop, the system packages and writes the raw data collected in all cycles during this closed-loop judgment process, the calculated deviation value sequence, the convergence judgment time point, and the finally generated termination control signal into a designated log file in airborne non-volatile memory (e.g., flash memory) in chronological order and a predefined binary format, completing a complete control loop record and providing data support for task analysis and system optimization.

[0055] In some embodiments, the state monitoring module is configured with an angle sensing unit, a distance measurement unit, and an angular velocity detection unit; the state monitoring module acquires the hook opening angle, guide rope separation distance, and swing angular velocity of the guide rope during unhooking, including: The voltage signal of the hook hinge during rotation is collected by the angle sensing unit. The difference between the voltage signal and the preset zero-position reference voltage is calculated, and the calculated voltage difference is converted into hook opening angle data according to the sensor sensitivity coefficient.

[0056] The angle sensing unit refers to a magnetic field sensing device based on the Hall effect principle, used to convert the mechanical rotation angle of the hook into a measurable electrical signal; the preset zero-position reference voltage refers to the calibrated voltage value output by the angle sensing unit when the hook is in a fully closed state, in volts (V). The sensor sensitivity coefficient refers to the change in output voltage corresponding to a unit change in angle, with units of millivolts per degree. ) Specifically, the system can store the zero-point reference voltage in non-volatile memory, use a differential amplifier circuit to calculate the difference between the real-time voltage and the reference voltage, and divide the voltage difference by a sensitivity coefficient to obtain the angle value. For example, the system uses a sensitivity of 10 millivolts per degree (mV / °C). The Hall sensor detects when the hook body moves from the zero-point reference voltage. Rotate until the output voltage is At that time, the voltage difference was 500 millivolts. The corresponding hook opening angle is 50 degrees. .

[0057] The distance measurement unit receives the echo signal, and the spatial distance between the guide rope connection point and the hook fixing point is calculated based on the signal transmission time difference of the echo signal to obtain the guide rope separation distance.

[0058] Among them, the distance measurement unit refers to an active ranging device based on the ultrasonic ranging principle, which consists of an ultrasonic transmitter and a receiver; the echo signal refers to the sound wave signal reflected back after the ultrasonic wave encounters the guide rope connection point; the signal transmission time difference refers to the time interval from ultrasonic wave transmission to reception, and the unit is milliseconds (ms).

[0059] Specifically, the system can record the time difference between the transmitted and received pulses using a timer module, calculate the spatial distance using the formula "distance = speed of sound × time difference / 2", and compensate for fluctuations in the speed of sound caused by temperature changes in real time. For example, the system transmits a 40 kHz ultrasonic pulse at an ambient temperature of 25 degrees Celsius. The speed of sound is 346 meters per second. The measured time difference was 1.47 ms, therefore the guide rope separation distance was... Meter (m).

[0060] The angular velocity detection unit detects the change in angular velocity of the guide rope during its swing and outputs detection data to characterize the instantaneous angular velocity of the guide rope.

[0061] The angular velocity detection unit refers to a gyroscope sensor based on microelectromechanical systems (MEMS) used to measure the angular velocity of an object rotating around an axis; the angular velocity change signal is the angular velocity time series data obtained by integrating the angular acceleration generated during the swing of the guide rope.

[0062] Specifically, the system can convert the analog voltage signal output by the gyroscope into a digital value using an analog-to-digital converter, eliminate high-frequency noise using a digital filtering algorithm, and convert the voltage value into an angular velocity value using a calibration coefficient. For example, the range of a MEMS gyroscope is ±100 degrees per second (…). The sensitivity is 12.5 millivolts per second. When the output voltage is 625 millivolts ( At that time, the corresponding angular velocity value is 50 degrees per second. The system uses a low-pass filter with a cutoff frequency of 10 Hz to eliminate high-frequency vibration interference.

[0063] Add a preset unified timestamp to the hook opening angle data, guide rope separation distance data, and swing angular velocity signal to obtain the hook opening angle, guide rope separation distance, and swing angular velocity during the unhooking process.

[0064] Among them, the unified timestamp refers to the synchronous time stamp added to the multi-source sensor data using a high-precision system clock, with a timestamp accuracy of microseconds (µs). )class.

[0065] Specifically, the system can generate a reference time signal through a global clock source, trigger data acquisition from each sensor using hardware interrupts, and align the sampling times of different sensors using a time interpolation algorithm. For example, the system generates a timestamp at a clock frequency of 1 MHz, when the angle sensor is at 172,500,000 microseconds (… Data was collected, and the distance sensor was at 172500050. During data collection, distance data was aligned to 172,500,000 using linear interpolation. At any given moment, a three-dimensional data array with unified timestamps is ultimately formed. .

[0066] Therefore, according to the above implementation method, the system can realize the synchronous acquisition and fusion of multi-sensor data, providing an accurate initial state dataset for subsequent decoupling control.

[0067] In some embodiments, the auxiliary judgment features include the stability features of the guide rope separation distance and the fluctuation features of the swing angular velocity; based on the calculation result of the hook unlocking speed according to the hook opening angle, and the auxiliary judgment features generated by the guide rope separation distance and the swing angular velocity, the hook unlocking speed deviation result is generated, including: The angle values ​​of continuous sampling points are extracted from the time-series data of the hook opening angle, and the instantaneous unlocking speed sequence of the hook is calculated based on the sampling time interval.

[0068] Among them, time-series data refers to the set of hook opening angle values ​​arranged in chronological order; sampling time interval refers to the fixed time difference between two consecutive data acquisitions, in milliseconds (ms); instantaneous unlocking speed sequence refers to the ordered set of hook opening angular velocities corresponding to each sampling moment, in meters per second (m / s).

[0069] Specifically, the system can convert angular velocity into linear velocity by dividing the angle difference between adjacent sampling points by the sampling time interval and then multiplying it by the equivalent rotation radius of the hook hinge using a differential calculation method. For example, if the system continuously collects hook opening angle values ​​of 10°, 15°, and 22° with a sampling period of 100 milliseconds (ms), and the hinge rotation radius is 0.1 meters (m), then the instantaneous unlocking speed at the second sampling point is... The instantaneous unlocking speed of the third sampling point is This constitutes an instantaneous unlocking speed sequence. meters per second (m / s).

[0070] The upper limit of the speed threshold is obtained by querying the preset configuration table based on the current flight environment parameters of the aircraft.

[0071] Among them, flight environment parameters refer to real-time sensed or received flight altitude and wind speed data; preset configuration table refers to a two-dimensional lookup table that is pre-calibrated through experiments and associates different altitude ranges with wind speed levels and recommended speed threshold upper limits; speed threshold upper limit refers to the maximum unlocking speed of the hook body allowed under the current environment to avoid unexpected swinging of the guide rope, in meters per second (m / s).

[0072] Specifically, the system can obtain the current flight altitude and wind speed through an altitude sensor and an anemometer, mapping the continuous values ​​of altitude and wind speed to discrete interval levels, and then indexing a preset configuration table to obtain the corresponding upper limit of the speed threshold. For example, if the current flight altitude is 800 meters (m) and the wind speed is 8 meters per second (m / s), the system maps the altitude to the "500~1000 meters" interval and the wind speed to the "5~10 meters per second" level, and queries the preset configuration table to obtain the upper limit of the speed threshold for this combination as 0.18 meters per second (m / s).

[0073] The instantaneous unlocking speed sequence of the hook is smoothed using a sliding window method, and the arithmetic mean of the speed data within the window is calculated as the estimated unlocking speed at the current moment.

[0074] Among them, the sliding window method refers to a data processing technique that defines a fixed-length subsequence (i.e., window) on the data sequence, and slides the window point by point along the sequence to calculate the data within the window; the arithmetic mean refers to the average value obtained by dividing the sum of all velocity data within the window by the number of data.

[0075] Specifically, the system can set a sliding window containing 5 sampling points, calculate the sum of all instantaneous velocity values ​​within the window and divide by 5 to obtain a smoothed estimate of the unlocking speed; simultaneously, the Grubbs criterion can be used ( Outlier detection (OV) is a statistical hypothesis testing method used to detect the presence of outliers in a univariate dataset. It involves removing anomalous abrupt changes within a window. For example, the five instantaneous velocity values ​​within the current sliding window... The system detected 0.25. Outliers are identified and removed. The arithmetic mean of the remaining four values ​​is calculated. This value is the estimated unlocking speed at the current moment.

[0076] If the estimated unlocking speed exceeds the upper limit of the threshold, the ratio of the excess to the upper limit of the threshold is multiplied by a preset weighting coefficient to obtain a deviation index value used to characterize the intensity of the guide rope's unexpected swing trend; otherwise, a zero value is output as the normal state index value.

[0077] Among them, the deviation index value is a dimensionless scalar, and the larger the value, the higher the risk of deviating from the set trajectory; the preset weight coefficient is a multiplier factor that is dynamically adjusted according to the guide rope length and load mass, and is used to quantify the sensitivity of inertial influence under different configurations.

[0078] Specifically, the system can calculate the deviation index value using the formula: "Deviation Index Value = ((Estimated Unlock Speed ​​- Upper Speed ​​Threshold) / Upper Speed ​​Threshold) × Weighting Coefficient". The weighting coefficient can be linearly mapped based on the product of the guide rope length (meters) and the load mass (kilograms), for example, coefficient = 0.5 + 0.01 × length × mass. For example, if the estimated unlock speed is 0.20 m / s, the upper speed threshold is 0.18 m / s, and the weighting coefficient is 0.8, then the deviation index value = ((0.20 - 0.18) / 0.18) × 0.8 ≈ 0.089. If the estimated value does not exceed the upper threshold, the normal state index value of 0 is output.

[0079] Based on stability and fluctuation characteristics, the deviation index value or normal state index value is corrected to generate the hook unlocking speed deviation result.

[0080] Among them, the stability feature refers to the standard deviation of the guide rope separation distance, which is used to measure the smoothness of the separation process; the fluctuation feature refers to the variance of the swing angular velocity, which is used to quantify the severity of the swing; the correction refers to the use of auxiliary features to weight and adjust the preliminary calculated index values ​​to improve the accuracy of the judgment; the hook unlocking speed deviation result is the final judgment conclusion, which can be a binary result (0 normal / 1 deviation) or a quantitative value with confidence level.

[0081] Specifically, the system can calculate the standard deviation of the guide rope separation distance and the variance of the swing angular velocity within a recent time window. If the standard deviation is greater than threshold 1 (e.g., 0.05 meters) or the variance is greater than threshold 2 (e.g., ... If the initial deviation index value is 0, the initial deviation index value is multiplied by a gain coefficient greater than 1 (e.g., 1.2); otherwise, it remains unchanged. If the initial index value is 0 (normal state), the auxiliary feature is only used for log recording and does not change the result. Finally, if the corrected deviation index value is greater than a set threshold (e.g., 0.1), a deviation result of 1 is generated; otherwise, a deviation result of 0 is generated. For example, if the initial deviation index value is 0.089, the calculated separation distance standard deviation is 0.08 meters (greater than the threshold of 0.05 meters), and the angular velocity variance is... The corrected deviation index value is .because The system ultimately generates a hook unlocking speed deviation result of 1 (indicating deviation).

[0082] Therefore, according to the above implementation method, the system can combine the direct calculation of the hook unlocking speed with the auxiliary characteristics of the guide rope dynamics to generate a more robust and accurate hook unlocking speed deviation result.

[0083] In some embodiments, the step of weighting the instantaneous rate difference and cumulative offset in the hook unlocking speed deviation result to obtain multiple deviation index values ​​includes: Based on the instantaneous rate difference sequence extracted from the hook unlocking speed deviation result, the instantaneous rate of change is calculated, and the cumulative summation of the instantaneous rate of change is used to obtain the swing amplitude growth rate.

[0084] The instantaneous rate difference sequence refers to the set of differences between the actual unlocking speed and the target unlocking speed at each sampling moment, arranged in chronological order, with units of [unit missing]. Instantaneous rate of change refers to the difference in instantaneous rates between two adjacent sampling points, reflecting how fast the rate difference changes, and is measured in meters per second squared (m²). The oscillation amplitude growth rate refers to the cumulative sum of instantaneous rates of change per unit time, used to quantify the rate of increase in the oscillation trend, and is measured in seconds ( ). ).

[0085] Specifically, the system can calculate the instantaneous rate of change using the first-order difference method. This involves subtracting the instantaneous rate difference from the previous instant from the instantaneous rate difference at the next instant, and then dividing by the sampling time interval. Subsequently, all instantaneous rates of change within a specified time window are algebraically summed, and the sum is divided by the window length to obtain the average oscillation amplitude growth rate within that window. For example, within a time window of 0.5 seconds (s), with a sampling frequency of 100 Hz, the instantaneous rate of change sequence of 50 sampling points is as follows: meters per second squared ( The system calculates the algebraic sum of all values ​​in the sequence to be 0.75. Therefore, the growth rate of the swing amplitude is 0.75 / 0.5 = 1.5 seconds. ).

[0086] The dominant frequency component of the instantaneous rate difference sequence is extracted by frequency domain transformation, and the phase offset is determined based on the initial phase angle of the dominant frequency component in the time domain.

[0087] In this context, frequency domain transformation refers to the technique of converting time-domain signals to the frequency domain for analysis; in this embodiment, it specifically refers to Fast Fourier Transform (FFT). The dominant frequency component refers to the frequency component with the largest amplitude in the spectrum after FFT transformation, measured in Hertz (Hz). The initial phase angle refers to the phase angle of this dominant frequency component at the starting point in the time domain, measured in degrees (°). Phase offset refers to the change in initial phase angle calculated over a continuous time window, used to characterize the stability of the oscillation mode, and is measured in degrees. ).

[0088] Specifically, the system can perform an FFT operation on the instantaneous rate difference sequence within a time window to find the frequency corresponding to the maximum value point in the amplitude spectrum, which is the dominant frequency; the argument of the complex value corresponding to this frequency component is the initial phase angle; the initial phase angles of adjacent time windows are calculated consecutively, and the difference is the phase offset. For example, the system performs an FFT on the instantaneous rate difference sequence of 1024 sampling points (sampling rate 100Hz) and finds that the maximum amplitude point is at a frequency of 1.5 Hz, and the complex value of this point is... The initial phase angle is The initial phase angle calculated in the next time window is: Then the phase offset is .

[0089] A state estimation algorithm is used to perform vector recursive estimation on the state vector consisting of the swing amplitude growth rate, the main frequency component, and the phase offset to generate smooth trend data.

[0090] Among them, the state estimation algorithm refers to the algorithm used to estimate the internal state of a system from noisy observation data. In this embodiment, Kalman filtering is used. (This refers to an optimal recursive digital processing algorithm for estimating the internal state of a dynamic system from a series of noisy observation data); the state vector refers to a column vector composed of three state variables: the oscillation amplitude growth rate, the dominant frequency component, and the phase offset; vector recursive estimation refers to the recursive prediction and updating of the state vector based on the system model and observation data; smoothed trend data refers to the slowly changing state estimate obtained after filtering to remove high-frequency noise.

[0091] Specifically, the system can establish a state-space model, defining the process noise covariance matrix Q and the observation noise covariance matrix R. In each recursive step, state prediction is performed first, then the state is updated using the new observations, and finally, a smoothed state vector estimate is output. For example, the process noise covariance matrix Q is set as follows: A diagonal matrix, with diagonal elements as follows: The observation noise covariance matrix R is The identity matrix. The initial state vector is After Kalman filtering and recursive estimation, the output smoothed trend data is: .

[0092] Based on the oscillation amplitude growth rate, frequency change slope, and phase offset cumulative value in the smoothed trend data, multiple deviation index values ​​are calculated through weighted coefficient allocation.

[0093] The frequency change slope refers to the slope obtained by linearly fitting the smoothed trend data of the main frequency components, reflecting the frequency change trend over time, and is measured in Hertz per second (Hz). The cumulative phase offset refers to the total offset obtained by algebraically summing all phase offsets over a certain period of time, and the unit is degrees. Weighted coefficient allocation refers to assigning a weight coefficient to each feature quantity for calculating the comprehensive index.

[0094] Specifically, the system can use the least squares method to linearly fit the smoothed values ​​of the dominant frequency over the most recent N time moments to obtain the frequency change slope. The cumulative phase offset value is obtained by summing the phase offsets over consecutive time windows. Multiple deviation index values ​​can be calculated using the following formula: First deviation indicator = W1 * Swing amplitude growth rate; Second deviation index = W2 * frequency change slope; The third deviation indicator = W3 * cumulative phase offset. Where W1, W2, and W3 are preset weighting coefficients. For example, the smoothing trend value of the oscillation amplitude growth rate is... The slope of the frequency change is The cumulative phase offset is 25°. Weighting coefficients are set as W1=0.5, W2=2.0, and W3=0.04. The calculated deviation index values ​​are: First deviation index = 0.5 * 1.48 = 0.74; Second deviation index = 2.0 * 0.05 = 0.10; Third deviation index = 0.04 * 25 = 1.00.

[0095] Therefore, according to the above implementation method, the system can quantify the swing deviation trend of the guide rope from multiple dimensions in the time domain and frequency domain, and generate a set of deviation index values ​​that characterize different risk aspects, providing multi-dimensional decision-making basis for subsequent precise control.

[0096] In some embodiments, based on the hook opening angle, guide rope separation distance, and swing angular velocity currently acquired by the state monitoring module, the operating state parameters of the unlocking mechanism and / or mechanical damping stabilizing device are adjusted by the control execution module, including: The actual unlocking speed is calculated based on the currently acquired hook opening angle, and the deviation signal between the actual unlocking speed and the target unlocking speed is obtained. The target unlocking speed is determined by a preset parameter configuration table.

[0097] The actual unlocking speed refers to the instantaneous linear velocity calculated by differentiation based on the latest hook opening angle data, in meters per second (m / s); the target unlocking speed refers to the ideal release speed preset according to the current flight mission requirements and environmental conditions, in m / s; and the deviation signal refers to the difference between the actual unlocking speed and the target unlocking speed, in m / s.

[0098] Specifically, the system can calculate the actual unlocking speed by performing differential calculations on the hook opening angle values ​​of two consecutive sampling periods, and then multiplying the result by the equivalent rotation radius of the hook hinge; the target unlocking speed is obtained by querying a preset parameter configuration table based on the current flight altitude and wind speed; the deviation signal is calculated by subtracting the target unlocking speed from the actual unlocking speed. For example, if the hook opening angle at the current sampling moment is 30 degrees (…), The angle at the previous sampling time was 25 degrees. The sampling period is 0.1 seconds (s), and the hinge radius is 0.1 meters (m). The actual unlocking speed is... The target unlocking speed, as determined by the parameter configuration table, is 0.4 meters per second (m / s). Therefore, the deviation signal is... .

[0099] Based on the deviation signal, the torque compensation amount is calculated using a deviation control algorithm.

[0100] Among them, the deviation control algorithm refers to the proportional-integral-derivative (PID) control algorithm; the torque compensation amount refers to the amount of adjustment required to the output torque of the unlocking mechanism drive motor in order to eliminate speed deviation, and the unit is Newton-meter (N·m).

[0101] Specifically, the system can process the deviation signal using a PID controller, where the proportional term (P) is the current deviation multiplied by a proportional coefficient. The integral term (I) is the sum of historical deviations multiplied by the integral coefficient. The differential term (D) is the rate of change of deviation multiplied by the differential coefficient. The sum of these three terms is the initial torque compensation. For example, setting... The current deviation is 0.1 m / s, the cumulative historical deviation is 0.3 m, and the deviation change rate is 0.02%. Then the torque compensation amount Newton meter (N·m).

[0102] Based on the torque compensation amount, the current driving force output level is corrected to obtain the corrected driving force output level.

[0103] The current driving force output level refers to the current output torque or power setting value of the unlocking mechanism drive motor, usually expressed as a percentage (%) or an absolute value; correction refers to algebraically adding the torque compensation amount to the current driving force output level.

[0104] Specifically, the system can read the current torque setting value of the motor controller, add the calculated torque compensation amount to this setting value, and obtain the corrected drive force output level. Typically, upper and lower limits are applied to the correction result to prevent over-adjustment. For example, if the current drive force output level is 5.0 Newton-meters (Nm),... Torque compensation amount is (If the deviation is negative, the compensation amount is negative). The corrected driving force output level is: The system has a limited range. Newton's rice ( The correction value is within this range, therefore it is valid.

[0105] The corrected driving force output level is converted into the adjusted driving force output parameter of the unlocking mechanism and output, so as to adjust the working state parameter of the unlocking mechanism.

[0106] The adjusted drive force output parameter refers to the control signal that can directly drive the actuator of the unlocking mechanism, such as the target speed of the motor (revolutions per minute). ), target torque (Newton-meters, ) or pulse width modulation (PWM) duty cycle (percentage, %).

[0107] Specifically, the system can use a pre-calibrated lookup table or linear mapping relationship to output the corrected driving force level (Newton-meters). This is converted into instruction parameters that the motor controller can recognize and sent to the motor driver via a communication bus (such as a CAN bus). For example, the corrected drive force output level is... According to the lookup table, this torque value corresponds to a target motor current of 2.5 amps (A) and a PWM duty cycle of 60%. The system then sends the target current value of 2.5A and / or the PWM duty cycle of 60% as the adjusted drive force output parameters to the motor driver of the unlocking mechanism.

[0108] In response to the adjusted driving force output parameters indicating a continued strengthening of the oscillation trend, a control command is sent to the mechanical damping stabilizing device to adjust its operating parameters.

[0109] Among them, the continued strengthening of the swing trend refers to the state in which the swing amplitude is still increasing, as determined by the monitored guide rope separation distance and swing angular velocity, even though the driving force of the unlocking mechanism has been adjusted; the control command refers to a digital or analog signal containing parameters such as the target damping coefficient and the duration of action.

[0110] Specifically, the system can calculate the peak value or variance of the guide rope's angular velocity over a period of time after adjusting the driving force. If this value exceeds a preset threshold and shows an upward trend, it is determined that the oscillation trend is continuously strengthening. Subsequently, the system generates corresponding control commands based on the oscillation intensity level and sends them to the controller of the mechanical damping stabilization device via a digital input / output module or an analog output module. For example, after adjusting the driving force, if the peak angular velocity of the oscillation increases from 8 degrees per second within 2 seconds (s), the system can detect this change. (Rising to 12) It exceeded the threshold of 10. The system determined that the moderate oscillation trend was increasing, and then sent a control command to the mechanical damping stabilizing device: set the damping coefficient to 0.7 and the duration to 3 seconds (s).

[0111] Therefore, according to the above implementation method, the system can achieve precise closed-loop adjustment of the driving force of the unlocking mechanism, and promptly activate the auxiliary stabilizing device when the adjustment effect is insufficient, forming a coordinated control, thereby effectively suppressing the unintended swing of the guide rope.

[0112] In some embodiments, after obtaining multiple deviation index values ​​by weighting the instantaneous rate difference and cumulative offset in the hook unlocking speed deviation result, the method further includes: In response to multiple deviation index values ​​failing to meet the guide rope inertia anomaly conditions, a maintenance control signal is output to maintain the current operating parameters of the unlocking mechanism and mechanical damping stabilization device.

[0113] Among them, the maintenance control signal refers to a specific digital or logical signal used to indicate that the control system does not need to adjust the working parameters of any current actuators and maintains the existing operating state; the guide rope inertia anomaly condition refers to the logical judgment condition set based on the time-series characteristic analysis of deviation index values, which has been defined in detail in the preface of the document.

[0114] Specifically, the system can compare multiple calculated deviation index values ​​(such as the first deviation index, the second deviation index, and the third deviation index) with preset corresponding thresholds. If all index values ​​are lower than their respective thresholds, it is determined that the inertial anomaly condition has not been met, and a high-level signal (such as 5VTTL logic '1') is output through a specific address port of the control bus as a maintenance control signal. For example, the calculated first deviation index is 0.6 (threshold 0.8), the second deviation index is 0.08 (threshold 0.15), and the third deviation index is 0.9 (threshold 1.0). Since all index values ​​are less than the thresholds, the system's condition is not met, and a continuous high-level signal is output through channel 1 of the digital input / output (DIO) module. The signal is interpreted by the controller of the unlocking mechanism and the damping stabilizing device as a "maintain current state" command.

[0115] Based on the maintenance control signal, real-time monitoring data of the hook opening angle, guide rope separation distance, and swing angular velocity are continuously obtained through the status monitoring module.

[0116] Real-time monitoring data refers to the physical quantity data stream that the status monitoring module continuously collects and reports at a fixed sampling frequency during the period when the system is in a maintenance state.

[0117] Specifically, the system can keep the power supply and data acquisition circuits of each sensor in the state monitoring module (such as Hall angle sensors, ultrasonic ranging sensors, and MEMS gyroscopes) active during the period when the control signal is valid. It then cyclically reads sensor data at a preset sampling period (e.g., 100 milliseconds) and transmits the data to the main controller via a communication interface such as the controller area network bus or serial peripheral interface. For example, during the 5 seconds when the control signal is active, the system reads the data every 100 milliseconds. The sensor data was read once, and a total of 50 sets of real-time monitoring data were obtained. Each set of data included three values: hook opening angle (unit: degrees), guide rope separation distance (unit: meters), and swing angular velocity (unit: degrees / second).

[0118] When any parameter among the hook opening angle, guide rope separation distance, or swing angular velocity exceeds the preset safety threshold, the process of generating the hook unlocking speed deviation result is re-triggered.

[0119] Among them, the preset safety threshold refers to the independent safety operation boundary value set for each monitoring parameter, which is used to quickly identify sudden abnormalities in the maintenance state; re-triggering refers to interrupting the current maintenance state cycle and calling the complete algorithm process to generate the hook unlocking speed deviation result.

[0120] Specifically, upon receiving new real-time monitoring data, the system immediately compares the hook opening angle with an angle safety threshold (e.g., 90 degrees), the guide rope separation distance with a distance safety threshold (e.g., 1.5 meters), and the swing angular velocity with an angular velocity safety threshold (e.g., 30 degrees / second). If any parameter exceeds its corresponding threshold, the system immediately clears the maintenance control signal and jumps to the starting point of step S120 (or an equivalent process), restarting the entire process from calculating the instantaneous unlocking speed sequence to generating the deviation result. For example, in the maintenance state, if the system detects that the swing angular velocity suddenly increases to 35 degrees / second at a certain moment, exceeding the preset angular velocity safety threshold of 30 degrees / second, the system immediately stops outputting the maintenance control signal and re-executes the process of "calculating the hook unlocking speed based on the hook opening angle and the auxiliary judgment features generated by the guide rope separation distance and swing angular velocity to generate the hook unlocking speed deviation result."

[0121] Therefore, according to the above implementation method, the system can enter a low-intervention monitoring mode to save control resources when it is determined that the current state does not need to be adjusted, while having the ability to respond quickly to sudden abnormal situations, and ensuring the timeliness and security of the control strategy by re-triggering the evaluation process.

[0122] In some embodiments, after adjusting the operating state parameters of the unlocking mechanism and / or the mechanical damping stabilizing device through the control execution module, the method further includes: Based on the monitoring results of the hook opening angle change by the status monitoring module, the guide rope separation distance and swing angular velocity are updated to generate an updated status dataset.

[0123] The updated state dataset refers to the new dataset generated after the control adjustment action is performed, based on the hook opening angle, guide rope separation distance and swing angular velocity data collected in the latest monitoring cycle, and in the same format and timing rules as the initial state dataset.

[0124] Specifically, at the end of each fixed control cycle (e.g., 100 milliseconds), the system synchronously reads the latest measurement values ​​from the angle sensor, distance sensor, and gyroscope, appends new timestamps to these data that are consecutive to the initial dataset timestamps, and encapsulates them according to the structure [angle value, distance value, angular velocity value] to form an updated state dataset. For example, 1.5 seconds after the control adjustment, the system collects a hook opening angle of 55 degrees (…). The guide rope separation distance is 0.85 meters (m), and the swing angular velocity is 6 degrees per second (m). The system appends a timestamp of 1500 milliseconds to this dataset. Generate an updated status data record: Records from multiple consecutive periods constitute the updated state dataset.

[0125] The updated state dataset is compared with the hook opening angle, guide rope separation distance, and swing angular velocity during the unhooking process to calculate the comprehensive deviation value.

[0126] Here, the hook opening angle, guide rope separation distance, and swing angular velocity during the unhooking process specifically refer to the initial state dataset used as a comparison benchmark; the comprehensive deviation value refers to a scalar value used to quantify the overall difference between the updated state dataset and the initial state dataset, which is obtained by calculating the normalized Euclidean distance of the deviations of each parameter.

[0127] Specifically, the system can calculate the differences between the updated dataset and the initial dataset in three parameters: hook opening angle, guide rope separation distance, and swing angular velocity, i.e., angular deviation. Distance deviation and angular velocity deviation Then, each deviation is normalized (divided by the nominal value of the parameter, such as the nominal angle). Degrees, nominal distance meters, nominal angular velocity (degrees / second), and finally calculate the square root of the sum of squares of the normalized deviations as the comprehensive deviation value (E): .

[0128] For example, the initial state data is The current updated status data is .but Spend, rice, Degrees per second. Assuming... Spend, rice, Degrees per second. The overall deviation value is: .

[0129] If the overall deviation value continues to decrease and falls below the preset convergence threshold over multiple consecutive sampling periods, it is determined that the unhooking process of the guide rope is under control, and a control termination signal is generated to stop the updating of the working status parameters.

[0130] Among them, "continuous sampling cycles" refers to a preset number of sequentially arranged control cycles; "continuous decrease" means that within the current cycle and a specific number of cycles prior to it, the comprehensive deviation value of each subsequent cycle is less than the comprehensive deviation value of the previous cycle; "preset convergence threshold" refers to a pre-set small value threshold (such as 0.1) that indicates that the system state is sufficiently stable and acceptable; and "control termination signal" refers to a specific digital or logical signal used to notify the control system to stop the adjustment action of the current cycle.

[0131] Specifically, the system can maintain a queue of composite deviation values ​​of length N (e.g., N=5). Each time a new composite deviation value is calculated, it is added to the tail of the queue, and the old value at the head of the queue is removed. Then, it is checked whether the N values ​​in the queue satisfy a strictly monotonically decreasing order (i.e., ...). ,for arrive The system is considered to have converged if and only if the last value at the end of the queue (i.e., the latest value) is less than the preset convergence threshold. If both conditions are met, the system is considered to have converged, and a control termination signal is generated by setting a specific register or outputting a specific level (e.g., changing from low level 0 to high level 1). For example, the preset number of consecutive cycles N=5, and the convergence threshold is 0.1. The queue of the comprehensive deviation values ​​for the most recent 5 cycles is... The queue value is monotonically decreasing, and the latest value is 0.09 < 0.1. The system determines that the convergence condition is met and then generates a control termination signal (such as a high-level output from the digital output port).

[0132] Therefore, according to the above implementation method, the system can evaluate the control effect in real time through a closed-loop feedback mechanism, and automatically terminate the control after confirming that the unhooking process is stable and controllable, so as to avoid over-adjustment and achieve efficient and precise guide rope release control.

[0133] Figure 5 This is a structural block diagram of the control system for an aerial guide rope according to an embodiment of the present invention.

[0134] like Figure 5 As shown, the control system of the aerial guide rope includes: The status monitoring module 210 is configured to acquire the hook opening angle, guide rope separation distance and swing angular velocity when the guide rope is unhooked.

[0135] The deviation analysis module 220 is configured to generate the hook unlocking speed deviation result based on the hook opening angle calculation result and the auxiliary judgment feature generated by the guide rope separation distance and swing angular velocity.

[0136] The index calculation module 230 is configured to perform weighted calculations based on the instantaneous rate difference and cumulative offset in the hook unlocking speed deviation result when the guide rope has deviated from the set trajectory, to obtain multiple deviation index values.

[0137] The decision control module 240 is configured to output a control command signal when any deviation index value meets the preset guide rope inertia anomaly conditions. The guide rope inertia anomaly conditions include the swing amplitude growth rate obtained from the time-series characteristic analysis of the deviation index value exceeding the preset growth rate threshold, the swing frequency change slope being positive, and the cumulative value of phase offset exceeding the preset offset range.

[0138] The execution adjustment module 250 is configured to, upon receiving a control command signal, adjust the working status parameters of the unlocking mechanism and / or the mechanical damping stabilizing device by controlling the execution module based on the hook opening angle, guide rope separation distance, and swing angular velocity currently acquired by the status monitoring module.

[0139] The specific functions and examples of each module and submodule of the device in this embodiment of the invention can be found in the relevant descriptions of the corresponding steps in the above method embodiments, and will not be repeated here.

[0140] According to embodiments of the present invention, the above-described method of the present invention can be applied to a computer device and a readable storage medium.

[0141] Figure 6 A schematic block diagram of an example computer device 600 that can be used to implement embodiments of the present invention is shown. The computer device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The computer device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0142] like Figure 6 As shown, the computer device 600 includes a computing unit 601, which can perform various appropriate actions and processes based on a computer program stored in a read-only memory (ROM) 602 or a computer program loaded from a storage unit 608 into a random access memory (RAM) 603. The RAM 603 may also store various programs and data required for the operation of the computer device 600. The computing unit 601, ROM 602, and RAM 603 are interconnected via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0143] Multiple components in computer device 600 are connected to I / O interface 605, including: input unit 606, such as keyboard, mouse, etc.; output unit 607, such as various types of monitors, speakers, etc.; storage unit 608, such as disk, optical disk, etc.; and communication unit 609, such as network card, modem, wireless transceiver, etc. Communication unit 609 allows computer device 600 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0144] The computing unit 601 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 601 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 601 performs the various methods and processes described above, such as a method for controlling an aerial guide rope. For example, in some embodiments, a method for controlling an aerial guide rope may be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 608. In some embodiments, part or all of the computer program may be loaded and / or installed on the computer device 600 via ROM 602 and / or communication unit 609. When the computer program is loaded into RAM 603 and executed by the computing unit 601, one or more steps of the method for controlling an aerial guide rope described above may be performed. Alternatively, in other embodiments, the computing unit 601 may be configured to perform a control method for an aerial guide rope by any other suitable means (e.g., by means of firmware).

[0145] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0146] The program code used to implement the methods of the present invention can be written in any combination of one or more programming languages. This program code can be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing device, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code can be executed entirely on the machine, partially on the machine, as a standalone software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0147] In the context of this invention, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. Machine-readable media can include, but are not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0148] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0149] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0150] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact via communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other. Servers can be cloud servers, servers in distributed systems, or servers incorporating blockchain technology.

[0151] It should be understood that the various forms of processes shown above can be used to reorder, add, or delete steps. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this invention can be achieved, and this is not limited herein.

[0152] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for controlling an aerial guide rope, characterized in that, The method is based on a status monitoring module and a control execution module deployed in the aircraft's guidance rope system, including: The status monitoring module obtains the hook opening angle, guide rope separation distance, and swing angular velocity when the guide rope is unhooked. Based on the calculation result of the hook unlocking speed according to the hook opening angle, and the auxiliary judgment feature generated by the guide rope separation distance and swing angular velocity, the hook unlocking speed deviation result is generated. In response to the hook unlocking speed deviation result indicating that the guide rope has deviated from the set trajectory, multiple deviation index values ​​are obtained by weighted calculation based on the instantaneous rate difference and cumulative offset in the hook unlocking speed deviation result. In response to any of the deviation index values ​​satisfying the preset guide rope inertia anomaly conditions, an adjustment command signal is output. The guide rope inertia anomaly conditions include the swing amplitude growth rate exceeding the preset growth rate threshold obtained from the time-series characteristic analysis of the deviation index values, the swing frequency change slope being positive, and the cumulative phase offset exceeding the preset offset range. In response to the control command signal, based on the hook opening angle, guide rope separation distance and swing angular velocity currently acquired by the status monitoring module, the working status parameters of the unlocking mechanism and / or mechanical damping stabilizing device are adjusted by the control execution module.

2. The method according to claim 1, characterized in that, The status monitoring module is equipped with an angle sensing unit, a distance measurement unit, and an angular velocity detection unit; the acquisition of the hook opening angle, guide rope separation distance, and swing angular velocity during unhooking via the status monitoring module includes: The angle sensing unit collects the voltage signal of the hook hinge when it rotates, calculates the difference between the voltage signal and the preset zero-position reference voltage, and converts the calculated voltage difference into the hook opening angle data according to the sensor sensitivity coefficient. The distance measurement unit receives the echo signal, and calculates the spatial distance between the guide rope connection point and the hook fixing point based on the signal transmission time difference of the echo signal to obtain the guide rope separation distance. The angular velocity detection unit detects the angular velocity change signal of the guide rope during swinging and outputs detection data to characterize the instantaneous angular velocity of the guide rope. A preset unified timestamp is added to the hook opening angle data, guide rope separation distance data, and swing angular velocity signal to obtain the hook opening angle, guide rope separation distance, and swing angular velocity of the guide rope during the unhooking process.

3. The method according to claim 1, characterized in that, The auxiliary judgment features include the stability features of the guide rope separation distance and the fluctuation features of the swing angular velocity; the hook unlocking speed calculation result based on the hook opening angle, and the auxiliary judgment features generated by the guide rope separation distance and the swing angular velocity, generate the hook unlocking speed deviation result, including: The angle values ​​of continuous sampling points are extracted from the time-series data of the hook opening angle, and the instantaneous unlocking speed sequence of the hook is calculated based on the sampling time interval; The upper limit of the speed threshold is obtained by querying the preset configuration table based on the current flight environment parameters of the aircraft. The instantaneous unlocking speed sequence of the hook is smoothed using a sliding window method, and the arithmetic mean of the speed data within the window is calculated as the estimated unlocking speed at the current moment. If the estimated unlocking speed exceeds the upper limit of the threshold, the ratio of the excess to the upper limit of the threshold is multiplied by a preset weighting coefficient to obtain a deviation index value used to characterize the intensity of the guide rope's unexpected swing trend; otherwise, a zero value is output as the normal state index value. Based on the stability characteristics and the fluctuation characteristics, the deviation index value or the normal state index value is corrected to generate the hook unlocking speed deviation result.

4. The method according to claim 1, characterized in that, The step of calculating multiple deviation index values ​​by weighting the instantaneous rate difference and cumulative offset in the hook unlocking speed deviation result includes: Based on the instantaneous rate difference sequence extracted from the hook unlocking speed deviation result, the instantaneous rate of change is calculated, and the cumulative summation of the instantaneous rate of change is performed to obtain the swing amplitude growth rate. The main frequency component of the instantaneous rate difference sequence is extracted by frequency domain transformation, and the phase offset is determined based on the initial phase angle of the main frequency component in the time domain. A state estimation algorithm is used to perform vector recursive estimation on the state vector composed of the swing amplitude growth rate, the main frequency component and the phase offset to generate smooth trend data. Based on the oscillation amplitude growth rate, frequency change slope, and phase offset cumulative value in the smoothed trend data, the multiple deviation index values ​​are calculated by weighting coefficient allocation.

5. The method according to claim 1, characterized in that, The adjustment of the working status parameters of the unlocking mechanism and / or the mechanical damping stabilizing device by the control execution module based on the hook opening angle, guide rope separation distance, and swing angular velocity currently acquired by the status monitoring module includes: The actual unlocking speed is calculated based on the currently acquired hook opening angle, and the deviation signal between the actual unlocking speed and the target unlocking speed is obtained. The target unlocking speed is determined by a preset parameter configuration table. Based on the deviation signal, the torque compensation amount is calculated and generated using a deviation control algorithm. Based on the torque compensation amount, the current driving force output level is corrected to obtain the corrected driving force output level; The corrected driving force output level is converted into the adjusted driving force output parameter of the unlocking mechanism and output, so as to adjust the working state parameter of the unlocking mechanism; In response to the adjusted driving force output parameters indicating a continued increase in the oscillation trend, a control command is sent to the mechanical damping stabilizing device to adjust its operating parameters.

6. The method according to claim 1, characterized in that, After obtaining multiple deviation index values ​​by weighting the instantaneous rate difference and cumulative offset in the hook unlocking speed deviation result, the method further includes: In response to the fact that none of the multiple deviation index values ​​meet the guide rope inertia anomaly condition, a maintenance control signal is output to maintain the current working state parameters of the unlocking mechanism and the mechanical damping stabilization device; Based on the maintenance control signal, the real-time monitoring data of the hook opening angle, guide rope separation distance and swing angular velocity are continuously obtained through the status monitoring module. When any parameter among the hook opening angle, guide rope separation distance, or swing angular velocity is detected to exceed a preset safety threshold, the process of generating the hook unlocking speed deviation result is re-triggered.

7. The method according to claim 1, characterized in that, After adjusting the operating parameters of the unlocking mechanism and / or the mechanical damping stabilizing device through the control execution module, the method further includes: Based on the monitoring results of the hook opening angle change by the status monitoring module, the guide rope separation distance and swing angular velocity are updated to generate an updated status dataset; The updated state dataset is compared with the hook opening angle, guide rope separation distance and swing angular velocity of the guide rope during the unhooking process, and the comprehensive deviation value is calculated. If the overall deviation value continues to decrease and falls below the preset convergence threshold over multiple consecutive sampling periods, it is determined that the unhooking process of the guide rope is under control, and a control termination signal is generated to stop the updating of the working status parameters.

8. A control system for an aerial guide rope, characterized in that, include: The status monitoring module is configured to acquire the hook opening angle, guide rope separation distance and swing angular velocity of the guide rope when it is unhooked. The deviation analysis module is configured to generate the hook unlocking speed deviation result based on the hook opening angle calculation result and the auxiliary judgment feature generated by the guide rope separation distance and swing angular velocity. The index calculation module is configured to perform a weighted calculation based on the instantaneous rate difference and cumulative offset in the hook unlocking speed deviation result when the hook unlocking speed deviation result indicates that the guide rope has deviated from the set trajectory, and obtain multiple deviation index values. The decision control module is configured to output a control command signal when any of the deviation index values ​​meets the preset guide rope inertia anomaly conditions. The guide rope inertia anomaly conditions include the swing amplitude growth rate exceeding the preset growth rate threshold obtained from the time-series characteristic analysis of the deviation index values, the swing frequency change slope being positive, and the cumulative phase offset exceeding the preset offset range. The adjustment module is configured to, upon receiving the control command signal, adjust the working status parameters of the unlocking mechanism and / or the mechanical damping stabilizing device through the control execution module based on the hook opening angle, guide rope separation distance, and swing angular velocity currently acquired by the status monitoring module.

9. A computer device, characterized in that, include: At least one processor; and a memory that is communicatively connected to the at least one processor; The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-7.

10. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, in, Computer instructions are used to cause a computer to perform the method according to any one of claims 1-7.

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