Envelope adaptive based inspection unmanned aerial vehicle parachute control method and system

Abstract

The application discloses an envelope self-adaptive-based inspection unmanned plane parachute control method and system, relates to the unmanned plane landing control technical field, and the method comprises the following steps: triggering through the unmanned plane landing instruction, collecting the flight state parameters and the meteorological environment parameters, and calculating the predicted landing trajectory of the unmanned plane; a landing envelope region containing an outer envelope surface and an inner envelope surface is constructed, and the inner and outer envelope surfaces respectively represent the safety range and the fault tolerance space of the landing flight trajectory; when the real-time flight trajectory is monitored, if the trajectory deviates from the inner envelope surface and is still located in the outer envelope surface, the inner envelope deviation amplitude is calculated through a first calibration model, the parachute rope winding and unwinding calibration quantity is generated, and then the intervention instruction is sent to activate the landing parachute auxiliary control module to accurately adjust. Therefore, through the parallel design of the flight control system and the auxiliary control module, it is ensured that the unmanned plane can stably and accurately land in a complex environment, and the stability of the flight landing control is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of unmanned aerial vehicle landing control, and particularly relates to a patrol unmanned aerial vehicle parachute control method and system based on envelope self-adaptation. BACKGROUND

[0002] Unmanned aerial vehicles have gradually become the preferred tool for power companies to inspect facilities such as power transmission lines and substations due to their flexibility, efficiency and low cost. Unmanned aerial vehicle inspection can efficiently check high-altitude power equipment, reducing the high risk and high cost of manual inspection. However, the existence of complex power grid environments such as high-voltage power lines and iron towers poses many challenges to unmanned aerial vehicle inspection.

[0003] In these complex environments, the patrol unmanned aerial vehicle often needs to fly in a relatively narrow space and is easily affected by external factors such as electromagnetic interference and weather changes, resulting in fluctuations in the positioning accuracy of the patrol unmanned aerial vehicle or deviations in the flight path. These unstable factors may cause the unmanned aerial vehicle to collide during flight, even more serious loss of control or crash accidents, causing damage to equipment, and even threatening the safety of surrounding personnel.

[0004] To address this problem, current unmanned aerial vehicles mainly use the flight control system to automatically determine the flight state and deploy the parachute to reduce the risk of unmanned aerial vehicle crashes. However, once the flight control system fails, it may not be able to determine the flight state in time, or even cause misjudgment, affecting the safe landing of the patrol unmanned aerial vehicle. SUMMARY

[0005] The present application provides a patrol unmanned aerial vehicle parachute control method and system based on envelope self-adaptation, a storage medium, a computer program product and an electronic device to at least solve the problem of loss of control during unmanned aerial vehicle landing and inability to achieve safe landing due to flight control system failure or misjudgment in the current related technology.

[0006] In a first aspect, the embodiments of the present application provide a parachute control method for a patrol unmanned aerial vehicle based on envelope self-adaptation, which comprises: collecting flight state parameters and meteorological environment parameters of the unmanned aerial vehicle based on triggering of a landing instruction of the unmanned aerial vehicle; the flight state parameters include position and speed of the unmanned aerial vehicle, and the meteorological environment parameters include environmental wind speed; calculating a predicted landing trajectory of the unmanned aerial vehicle according to the flight state parameters and the meteorological environment parameters; constructing a landing envelope region according to the predicted landing trajectory; the landing envelope region includes an outer envelope surface and an inner envelope surface, the inner envelope surface and the outer envelope surface are cylindrical surfaces with the predicted landing trajectory as the center and with envelope radii of an inner envelope radius and an outer envelope radius respectively, and the outer envelope radius is greater than the inner envelope radius; monitoring a real-time flight trajectory of the unmanned aerial vehicle in a landing process, and when the real-time flight trajectory is not within the coverage of the inner envelope surface and is within the coverage of the outer envelope surface, processing an inner envelope deviation amplitude between the real-time flight trajectory and the inner envelope surface according to a first calibration model to calculate a corresponding first parachute rope winding and unwinding calibration quantity; generating a first parachute rope winding and unwinding intervention instruction according to the first parachute rope winding and unwinding calibration quantity to activate a parachute auxiliary control module to assist in winding and unwinding control of a parachute rope of a parachute of the unmanned aerial vehicle; and the parachute auxiliary control module and a flight control system module of the unmanned aerial vehicle are connected to a power module in parallel.

[0007] In a second aspect, the embodiments of the present application provide a parachute control system for a patrol unmanned aerial vehicle based on envelope self-adaptation, which comprises: a parameter collection unit configured to collect flight state parameters and meteorological environment parameters of the unmanned aerial vehicle based on triggering of a landing instruction of the unmanned aerial vehicle; the flight state parameters include position and speed of the unmanned aerial vehicle, and the meteorological environment parameters include environmental wind speed; a trajectory calculation unit configured to calculate a predicted landing trajectory of the unmanned aerial vehicle according to the flight state parameters and the meteorological environment parameters; an envelope construction unit configured to construct a landing envelope region according to the predicted landing trajectory; the landing envelope region includes an outer envelope surface and an inner envelope surface, the inner envelope surface and the outer envelope surface are cylindrical surfaces with the predicted landing trajectory as the center and with envelope radii of an inner envelope radius and an outer envelope radius respectively, and the outer envelope radius is greater than the inner envelope radius; a calibration quantity calculation unit configured to monitor a real-time flight trajectory of the unmanned aerial vehicle in a landing process, and when the real-time flight trajectory is not within the coverage of the inner envelope surface and is within the coverage of the outer envelope surface, process an inner envelope deviation amplitude between the real-time flight trajectory and the inner envelope surface according to a first calibration model to calculate a corresponding first parachute rope winding and unwinding calibration quantity; and an auxiliary winding and unwinding control unit configured to generate a first parachute rope winding and unwinding intervention instruction according to the first parachute rope winding and unwinding calibration quantity to activate a parachute auxiliary control module to assist in winding and unwinding control of a parachute rope of a parachute of the unmanned aerial vehicle; and the parachute auxiliary control module and a flight control system module of the unmanned aerial vehicle are connected to a power module in parallel.

[0008] In a third aspect, an electronic device is provided, which includes at least one processor, and a memory connected to the at least one processor in communication, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the steps of the envelope adaptive inspection UAV parachute control method of any of the embodiments of the present application.

[0009] In a fourth aspect, the embodiments of the present application provide a storage medium having a computer program stored thereon, characterized in that the program, when executed by a processor, implements the steps of the envelope adaptive inspection UAV parachute control method of any of the embodiments of the present application.

[0010] In a fifth aspect, the embodiments of the present application provide a computer program product, which includes computer programs / instructions, and the computer programs / instructions, when executed by a processor, implement the steps of the envelope adaptive inspection UAV parachute control method of any of the embodiments of the present application.

[0011] The envelope adaptive inspection UAV parachute control method and system provided by the present application can at least produce the following technical effects:

[0012] (1) By introducing the landing envelope region constructed around the predicted landing trajectory, composed of inner and outer envelope surfaces, forming a double-layer cylindrical surface structure, to distinguish the degree of flight deviation, effectively realizing the spatial dynamic boundary constraint control of the UAV landing state. The inner envelope surface is the allowable deviation range of the ideal landing path, while the outer envelope surface is the limit control boundary of the maximum tolerable deviation. The "buffer interval" formed by setting the envelope radius difference improves the recognition sensitivity of the landing flight trajectory deviation.

[0013] (2) The parachute rope retraction control mechanism based on the envelope deviation amplitude is introduced, that is, when the real-time trajectory is located in the region between the inner and outer envelopes, the inner envelope deviation amplitude is dynamically calculated, and a first parachute rope retraction calibration quantity is generated accordingly, and then converted into the corresponding intervention control instruction. Thus, according to different deviation degrees, differential control is implemented, with explicit response criteria and quantitative control capability, so that the landing parachute has more directional and control accuracy in the correction behavior of the UAV attitude and trajectory.

[0014] (3) The landing parachute auxiliary control module and the flight control system module are connected in parallel to the power module, and through the parallel architecture design, it is ensured that in the case of failure or abnormal power failure of the flight control system, the landing parachute auxiliary control module can still independently intervene in the landing process in real time, and through the redundant control structure, the influence of flight path deviation and external environmental disturbance on the landing stability of the UAV is reduced, effectively reducing the risk of crashing and the probability of equipment damage.

[0015] By the technical solution, the traditional passive parachute control is changed into a self-adaptive control system with early warning ability and active intervention ability through the coupling of space constraint and umbrella rope adjustment mechanism, and the landing stability and operation safety of the unmanned aerial vehicle in a complex power environment are improved. BRIEF DESCRIPTION OF DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0017] Figure 1 A flow chart of an example of a patrol unmanned aerial vehicle parachute control method based on envelope self-adaptation according to an embodiment of the present application is shown;

[0018] Figure 2 A principle schematic diagram of an example of a parachute flight control planning based on envelope line constraint according to an embodiment of the present application is shown;

[0019] Figure 3 A structure connection schematic diagram of an example of a parachute power supply system of an unmanned aerial vehicle according to an embodiment of the present application is shown;

[0020] Figure 4 An operation flow chart of an example of calculating a predicted landing trajectory of an unmanned aerial vehicle according to flight state parameters and meteorological environment parameters according to an embodiment of the present application is shown;

[0021] Figure 5 A simulation effect schematic diagram of an example of a parachute predicted trajectory in an ideal state is shown;

[0022] Figure 6 A simulation trajectory schematic diagram of an example of a non-controlled parachute descent in the presence of interference is shown;

[0023] Figure 7 A simulation effect schematic diagram of an example of a non-controlled parachute landing point distribution in the presence of interference is shown;

[0024] Figure 8 A simulation trajectory schematic diagram of an example of a controllable parachute descent according to an embodiment of the present application in the presence of interference is shown;

[0025] Figure 9 A simulation effect schematic diagram of an example of a controllable parachute landing point distribution according to an embodiment of the present application in the presence of interference is shown;

[0026] Figure 10 A structural block diagram of an example of an envelope self-adaptive inspection unmanned aerial vehicle parachute control system according to an embodiment of the present application is shown. DETAILED DESCRIPTION

[0027] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described below in connection with the drawings in the embodiments of the present application. Obviously, the described embodiments are only some, but not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0028] It should be noted that the research direction of some experts and scholars on the unmanned aerial vehicle parachute control system at present mainly focuses on the automatic parachute deployment technology based on the flight control system. Specifically, the flight state is monitored through the flight control system of the unmanned aerial vehicle, and the parachute deployment is automatically triggered when an abnormality occurs. Therefore, the height, speed, attitude, and other information of the unmanned aerial vehicle need to be obtained in real time through various sensors (such as a gyroscope, an accelerometer, an air pressure sensor, etc.) of the flight control system. When the flight control system detects that the unmanned aerial vehicle has failed or lost control (for example, the vertical speed is too high, the tilt angle is too large, etc.), the parachute system is automatically started to ensure that the unmanned aerial vehicle can land in a relatively safe manner.

[0029] However, the judgment ability of the flight control system directly depends on the accuracy of the sensor data. If the sensor fails or has an error, the judgment of the flight control system may deviate, thereby leading to an incorrect control decision. Especially in a high-voltage power grid environment, electromagnetic interference may affect the signal quality of the sensor, thereby leading to a misjudgment of the flight state of the unmanned aerial vehicle, and further failing to timely start the parachute. Secondly, the automatic parachute deployment of the flight control system is usually based on a fixed threshold setting, such as triggering the parachute when the vertical speed of the aircraft exceeds a certain preset value. Therefore, it is unable to flexibly cope with different flight states and external environment changes, such as sudden strong winds or air flow changes, leading to the inability to deploy the parachute at the best opportunity, thereby affecting the landing accuracy and safety, and lacking sufficient adaptability in the face of complex and dynamically changing power grid environments.

[0030] It should be understood that the above description of the prior art is only intended to facilitate the public to better understand the inventive spirit and motivation of the present application, and is not considered as a limitation of the present application. In addition, the technical solutions described in the above prior art may not be prior art, but also may be undisclosed technical solutions, such as solutions under research or in the laboratory stage.

[0031] The collection, storage, use, processing, transmission, provision and disclosure of user personal information in the technical solutions of the present application comply with relevant laws and regulations and do not violate public order and good customs.

[0032] Figure 1 A flowchart of an example of the envelope self-adaptive inspection unmanned aerial vehicle parachute control method according to an embodiment of the present application is shown.

[0033] The execution subject of the method of the present application can be any controller or processor with computing or processing capability, and specifically can be a processor coupled with the parachute drive motor of the unmanned aerial vehicle, such as a parachute auxiliary control module. By deeply integrating the dynamic landing envelope area with the adaptive parachute rope winding and unwinding intervention mechanism and improving the overall safety guarantee capability through parallel fault-tolerant architecture, the fine safety control of the landing process of the inspection unmanned aerial vehicle is realized, and the landing stability and operation safety of the unmanned aerial vehicle in complex power grid scenarios are significantly improved.

[0034] In some examples, it can be integrated and configured in an electronic device or terminal in a software, hardware or software and hardware combined manner, and the type of terminal or electronic device can be diversified, such as a mobile phone, a tablet computer or a desktop computer, etc.

[0035] As shown in FIG. 1, Figure 1 In step S110, based on the triggering of the unmanned aerial vehicle landing instruction, the flight state parameters and meteorological environment parameters of the unmanned aerial vehicle are collected.

[0036] During the flight of the unmanned aerial vehicle, the triggering of the landing instruction means that the unmanned aerial vehicle will enter a landing preparation state. Specifically, the unmanned aerial vehicle landing instruction can be issued by a flight control system, a remote control operator or an automatic task planning system, which should not be limited here.

[0037] In the collection of the flight state parameters, the flight state parameters can include the position and speed of the unmanned aerial vehicle. Specifically, they can be provided in real time by the inertial measurement unit (IMU) and GPS system installed on the unmanned aerial vehicle. The IMU is used to accurately measure the acceleration and angular velocity of the unmanned aerial vehicle, and the GPS provides the three-dimensional spatial position (longitude, latitude, height) and speed of the unmanned aerial vehicle, thereby describing the current flight dynamic state of the unmanned aerial vehicle.

[0038] In step S120, the predicted landing trajectory of the unmanned aerial vehicle is calculated according to the flight state parameters and meteorological environment parameters.

[0039] Here, based on the flight state parameters (position and speed) and meteorological environment parameters (environmental wind speed) at the time of triggering landing, the landing path of the UAV is predicted, and can be realized by means of various trajectory prediction models, such as a trajectory prediction model based on a machine learning model or a track tracking model. Exemplarily, the motion characteristics of the UAV and the influencing factors of the external environment are comprehensively considered, and a state estimation algorithm such as Kalman filtering or particle filtering is used to predict the landing trajectory of the UAV. Thus, by comprehensively considering the state parameters of the UAV and the environmental factors, an accurate predicted landing trajectory from the triggering landing position to the ground is constructed.

[0040] In step S130, a landing envelope region is constructed according to the predicted landing trajectory.

[0041] Here, the landing envelope region contains an outer envelope surface and an inner envelope surface, and the inner envelope surface and the outer envelope surface are cylindrical surfaces with the predicted landing trajectory as the center and with envelope radii of inner envelope radius and outer envelope radius respectively, and the outer envelope radius is greater than the inner envelope radius.

[0042] Specifically, the landing envelope region is a three-dimensional space region composed of the inner envelope surface and the outer envelope surface, the inner envelope surface represents the minimum range of the safe trajectory, and the outer envelope surface is the maximum range that tolerates possible trajectory deviation, forming a "protection circle" around the predicted landing trajectory, for evaluating the landing deviation of the UAV and providing the basis for landing intervention. For example, if the UAV trajectory does not fall into the region covered by the inner envelope surface, it can be considered that the UAV has deviated from the trajectory and needs to take control measures to correct it.

[0043] Regarding the outer envelope radius and the inner envelope radius, in one example of the embodiments of the present application, the outer envelope radius and the inner envelope radius can both adopt fixed preset values. In another example of the embodiments of the present application, the inner envelope radius can adopt a fixed value to provide a constraint range for fine control, and the outer envelope radius adopts a dynamic radius to support a larger deviation range of the UAV in the early stage of landing, and at the same time, as the landing process proceeds, the envelope region is gradually tightened to realize more accurate trajectory control.

[0044] Figure 2 A principle schematic diagram of one example of the landing parachute flight control planning based on the envelope line constraint according to the embodiments of the present application is shown.

[0045] It should be noted that parachutes rely on aerodynamic drag for deceleration, and their descent trajectory is highly sensitive to wind. Therefore, this embodiment proposes using the extension and retraction of parachute lines to alter the parachute's descent trajectory. However, due to limited control capabilities, this results in a certain lag in trajectory changes. The goal is to ensure that the actual parachute flight trajectory follows the predicted trajectory as closely as possible, thereby guaranteeing that the landing point meets the requirements. Due to limitations in parachute control capabilities and uncertainties during descent, the actual descent trajectory cannot perfectly coincide with the predicted trajectory.

[0046] To ensure that the parachute lands along a predetermined path or at a predetermined landing point, a large envelope radius can be set with the predicted trajectory as the center. , With flight altitude The radius gradually decreases. This forms an outer envelope that gradually converges towards the predicted trajectory. This outer envelope can be used as a critical surface for controlling the parachute, thereby limiting its flight range. Similarly, an inner envelope is introduced, with a radius... A fixed value should be taken, the magnitude of which should be determined based on the aerodynamic characteristics of the parachute and the accuracy requirements of the landing point on the ground. Control is considered complete when the parachute enters the inner envelope. When the actual parachute deployment point deviates from the predetermined deployment point by a distance greater than [a certain value], [the control is considered complete]. At this time, the control box generates control force by extending and retracting the parachute lines, causing the parachute to return to the inner envelope. After the parachute enters the inner envelope, the control box restores the line length, bringing the parachute back to normal. If the parachute drifts from the inner envelope to the outer envelope due to wind or other forces, control is applied again to bring the parachute back to the inner envelope, and this process is repeated until landing.

[0047] like Figure 2 As shown, the predicted trajectory is used as the baseline for the ideal landing path of the UAV. The outer envelope is established with the predicted trajectory as the center and adopts a dynamic radius that gradually shrinks as the altitude decreases. This limits the maximum allowable deviation range of the actual trajectory of the UAV, ensuring sufficient safety redundancy even under large disturbances. The inner envelope radius is fixed and used as the convergence criterion for fine control. When the actual trajectory enters this range, the parachute control can be determined to be in a stable state, avoiding excessive intervention. During free fall and controlled descent, the actual trajectory deviates from the predicted trajectory. When the trajectory touches the outer envelope, control intervention is triggered, adjusting the parachute lines to return it to the inner envelope range. This achieves zoned and progressive control of the landing process, ensuring that the UAV landing combines flexibility and high precision.

[0048] In step S140, the real-time flight trajectory of the UAV during landing is monitored, and when the real-time flight trajectory is not within the coverage of the inner envelope surface and is within the coverage of the outer envelope surface, the inner envelope deviation amplitude between the real-time flight trajectory and the inner envelope surface is processed according to the first calibration model to calculate a corresponding first parachute line retraction calibration amount.

[0049] Here, after the UAV starts landing, the real-time flight trajectory of the UAV will be continuously monitored. If it is found that the flight trajectory deviates from the predetermined inner envelope surface, the corresponding intervention mechanism is started, and the calibration amount of the parachute line retraction is calculated through the calibration model, so as to adjust the working state of the parachute, thereby correcting the landing trajectory of the UAV in real time.

[0050] Specifically, the deviation amplitude of the trajectory can be calculated by comparing the real-time flight trajectory with the trajectory of the inner envelope surface. If the flight trajectory is outside the inner envelope surface but still within the outer envelope surface, the deviation amplitude is further calculated and processed through the first calibration model to obtain the parachute line retraction calibration amount that needs to be adjusted, and a corresponding control instruction is generated, thereby providing a dynamic response mechanism based on the real-time trajectory deviation degree.

[0051] The first calibration model is mainly used to process the deviation amplitude between the real-time flight trajectory and the inner envelope surface, so as to calculate the retraction calibration amount of the parachute line. The specific model type can be diversified and should not be limited here. For example, a regression analysis model or a neural network model is selected for calibration amount calculation, and the corresponding calibration amount is obtained through learning of historical flight data.

[0052] In step S150, a first parachute line retraction intervention instruction is generated according to the first parachute line retraction calibration amount, so as to activate the landing parachute auxiliary control module to assist in controlling the parachute line of the landing parachute of the UAV.

[0053] Here, the landing parachute auxiliary control module and the flight control system module of the UAV are connected in parallel to the power module. The function of the landing parachute auxiliary control module is to accurately control the parachute line retraction, which can independently execute the intervention of the parachute line retraction from the flight control system, realize the precise adjustment of the parachute line, enhance the fault tolerance of the system, and make the deployment and retraction of the UAV landing parachute adapt to the real-time flight state, thereby ensuring the safe landing of the UAV.

[0054] Figure 3 A structure connection schematic diagram of an example of a landing parachute power supply system of a UAV according to an embodiment of the present application is shown.

[0055] As Figure 3As shown, in terms of power supply, considering the weight of the multi-rotor unmanned aerial vehicle, the parachute control system is not provided with a power supply independently, and a low-voltage battery can be used to supply power to the unmanned aerial vehicle + parachute system as a whole, so that the control circuit can still work normally in an emergency when the high-voltage battery is used to supply power to the rotors of the multi-rotor unmanned aerial vehicle. In addition, the receiver circuit, the flight control system circuit (or flight control system module) and the parachute steering engine circuit (or parachute auxiliary control module) are connected in parallel, so that when the unmanned aerial vehicle flight control system fails, the parachute can still be opened normally. Through the redundant design, it can be ensured that even if the flight control system fails, the parachute can still work normally, and the stable landing of the unmanned aerial vehicle is ensured.

[0056] In some examples of the embodiments of the present application, when the real-time flight trajectory is within the coverage range of the inner envelope surface, the parachute auxiliary control module remains in an inactive state to avoid interfering with the original parachute rope winding and unwinding control strategy of the flight control system module.

[0057] Here, when the real-time flight trajectory is within the coverage range of the inner envelope surface, it indicates that the landing process of the unmanned aerial vehicle is still within the ideal trajectory range, and the flight control system can effectively maintain a stable landing path. Therefore, the inactive state of the parachute auxiliary control module is maintained at this time, so that the flight control system can independently complete the landing control task, effectively avoiding redundant operations when the flight trajectory is normal and stable, and also reducing the complexity and computational burden of the system, so that the unmanned aerial vehicle can land stably.

[0058] In some examples of the embodiments of the present application, the first calibration model adopts a PID (Proportional-Integral-Derivative) control algorithm, and takes the inner envelope deviation amplitude as input, and dynamically adjusts the proportional coefficient, integral coefficient and differential coefficient, so that the first parachute rope winding and unwinding calibration quantity remains smooth within a continuous time period, thereby performing fine winding and unwinding control on the parachute rope of the parachute of the unmanned aerial vehicle.

[0059] Specifically, the PID control algorithm includes three control terms: proportional term (P), integral term (I) and differential term (D). In the proportional term (P), the deviation between the real-time flight trajectory and the inner envelope surface is calculated based on the current trajectory deviation, that is, the greater the deviation, the greater the output of the proportional term, so that the adjustment amount of the parachute rope is larger, helping to quickly correct the flight trajectory. In the integral term (I), the integral term is mainly used to eliminate the cumulative error caused by the long-term small deviation of the system, and integrates the persistent deviation to ensure that the slow error can be gradually corrected. In the differential term (D), the differential term generates a correction amount based on the change rate of the inner envelope deviation amplitude, to suppress the rapid change of the deviation and avoid being too sensitive to sudden changes, while maintaining sufficient response speed.

[0060] By introducing the fine PID control algorithm, the deviation between the real-time flight trajectory and the inner envelope surface can be accurately adjusted, ensuring that the parachute rope control can be smoothly transitioned, and avoiding the rapid adjustment leading to the dramatic change of the unmanned aerial vehicle landing trajectory. Thus, the unmanned aerial vehicle can maintain a relatively stable landing process under a small deviation of the flight trajectory, thereby improving the accuracy and safety of the landing. In addition, the introduction of the PID control algorithm also enhances the adaptability of the system to unstable factors, ensuring the smooth landing of the unmanned aerial vehicle in complex environments.

[0061] On the other hand, when the real-time flight trajectory is not within the coverage of the outer envelope surface, the outer envelope deviation amplitude between the real-time flight trajectory and the outer envelope surface is processed according to the second calibration model to calculate the corresponding second parachute rope winding and unwinding calibration quantity. Further, the second parachute rope winding and unwinding intervention instruction is generated according to the second parachute rope winding and unwinding calibration quantity to activate the landing parachute auxiliary control module to assist in winding and unwinding control of the parachute rope of the unmanned aerial vehicle.

[0062] Here, the second calibration model adopts a control algorithm based on proportional gain amplification, taking the outer envelope deviation amplitude as the input, and defining the second parachute rope winding and unwinding calibration quantity as a proportional gain amount to the outer envelope deviation amplitude, thereby rapidly winding and unwinding the parachute rope of the unmanned aerial vehicle.

[0063] Specifically, when the real-time flight trajectory is not within the coverage of the outer envelope surface, the second calibration model will take effect. Unlike the first calibration model, the second calibration model is based on a proportional gain amplification control algorithm for rapid adjustment of the parachute rope. When the real-time flight trajectory of the unmanned aerial vehicle deviates from the outer envelope surface, it indicates that the unmanned aerial vehicle has deviated significantly, and the landing parachute auxiliary control module needs to intervene more quickly and forcefully. According to the input of the outer envelope deviation amplitude, a proportional gain amount is generated, and rapid parachute rope winding and unwinding control is performed to prevent further deviation from causing loss of control.

[0064] Regarding the details of the proportional gain amplification algorithm, the deviation amount is amplified in proportion to the control increment by amplifying the outer envelope deviation amplitude, thereby generating the second parachute rope winding and unwinding calibration quantity. Specifically, the larger the outer envelope deviation, the higher the proportional gain, and the more intense the winding and unwinding adjustment of the parachute rope. Thus, the flight trajectory of the unmanned aerial vehicle can be corrected more quickly, reducing the duration and amplitude of the deviation.

[0065] According to the calculated second parachute rope winding and unwinding calibration quantity, the second parachute rope winding and unwinding intervention instruction is generated to activate the landing parachute auxiliary control module to control the winding and unwinding of the parachute rope of the unmanned aerial vehicle. Unlike the relatively gentle and gradual response strategy of the PID control algorithm, the second calibration model ensures that the unmanned aerial vehicle can timely recover to a safe landing trajectory when a large deviation occurs through more direct and rapid adjustment.

[0066] By employing a proportional gain amplification control method, the system can respond rapidly when the drone deviates from its outer envelope, and ensure a stable landing through quick parachute line deployment and retraction. In particular, it provides faster intervention than conventional PID control in response to sudden changes in extreme weather conditions such as strong winds, ensuring the drone can quickly correct significant trajectory deviations and guarantee a safe landing.

[0067] Therefore, by introducing the PID control algorithm of the first calibration model and the proportional gain amplification algorithm of the second calibration model, the adaptive parachute control strategy switching during the UAV landing process was realized. On the one hand, when the flight trajectory deviates slightly from and remains within the outer envelope, the PID control algorithm processes trajectory changes over continuous time periods and dynamically adjusts the parachute extension and retraction, making the UAV parachute extension and retraction control process smooth and precise, ensuring stability during landing. On the other hand, when the flight trajectory deviates significantly and has left the outer envelope, such as in the event of sudden wind speed fluctuations during landing, the proportional gain amplification control algorithm provides a stronger control input than the PID control algorithm, which can quickly reduce the trajectory deviation, enabling the UAV to complete trajectory correction in a shorter time, enhancing the safety and adaptability of the UAV landing under adverse weather conditions. This ensures multi-level stability during the landing process of the inspection UAV.

[0068] Regarding the method for setting the radius of the landing envelope region, in some implementations, the inner envelope radius... A pre-set landing area radius is used, which represents the area within which the parachute can precisely land. During the drone's descent, the landing area radius is a fixed value and can be determined by mission requirements, the drone's flight performance, and safety zone requirements. For example, the landing area radius defines the area within which the drone must remain during descent to ensure a safe landing and avoid collisions with surrounding obstacles (such as power lines, trees, etc.).

[0069] The outer envelope radius gradually decreases as the UAV's flight altitude decreases, and remains larger than the inner envelope radius. By dynamically adjusting the outer envelope radius, the intervention range on the drone's flight trajectory can be adjusted according to the real-time flight altitude.

[0070] Equation (1)

[0071] In the formula, Indicates the real-time flight altitude of the drone. At the real-time flight altitude of the drone The outer envelope radius below, It is the preset maximum deviation radius. represents the inner envelope radius, which adopts the landing area radius; represents the maximum flight height of the UAV at the initial moment when the UAV receives the landing instruction; is an influence index, representing the degree of influence of the flight height change on the radius reduction; is a wind speed disturbance influence factor, is a wind speed change amount, representing the difference corresponding to the environmental wind speed at the continuous signal sampling moment.

[0072] is the maximum control radius of the UAV at the initial landing time (the highest flight height ), reflecting the maximum tolerable deviation range of the parachute at the initial flight. The influence of the flight height change on the radius reduction can be controlled, and the value can be 1-2. Specifically, a larger makes the height change more sensitive to the outer envelope radius, so that the radius change during the descent process is more rapid.

[0073] In formula (1), a wind speed fluctuation compensation term is also introduced to adjust the outer envelope radius in real time through wind speed compensation. When the UAV encounters wind speed changes during flight, the outer envelope radius is adjusted according to the real-time monitored wind speed data, and the landing envelope area is adaptively adjusted. Specifically, when the wind speed changes greatly, the stability of the UAV landing is easily affected, and the wind speed fluctuation compensation term is used to expand the outer envelope radius to expand the intervention range of the fine control algorithm (i.e., the PID algorithm), so that the UAV can maintain a relatively stable landing trajectory under unstable wind speed conditions.

[0074] Through the embodiments of the present application, the gradually reduced outer envelope surface and the fixed inner envelope surface are designed, effectively balancing the flexibility and precision of parachute control. In the initial landing period, due to the large change in flight trajectory, a larger outer envelope radius provides sufficient fault tolerance range, and the flight trajectory is finely adjusted in a wider range, with a larger fault tolerance intervention range. As the flight height decreases, the outer envelope surface gradually decreases and gradually fits the inner envelope surface of the accurate landing path, ensuring that the parachute can meet the landing accuracy requirements when approaching the ground.

[0075] Figure 4 An operation flowchart of an example of calculating the predicted landing trajectory of the UAV according to flight state parameters and meteorological environment parameters according to the embodiments of the present application is shown. In the embodiments of the present application, a physical dynamics model based on numerical integration is adopted, and after receiving the landing instruction, the initial flight state and meteorological environment parameters of the UAV are obtained, and the complete ideal trajectory from the initial landing moment to landing is deduced through the Runge-Kutta integration method.

[0076] Specifically, as shown in step S410, based on the flight state parameters and meteorological environment parameters at the initial moment of receiving the unmanned aerial vehicle landing instruction, the dynamic prediction model is initialized. Figure 4

[0077] It should be noted that the unmanned aerial vehicle landing process is a nonlinear dynamic process under multi-force coupling. The dominant external forces such as gravity, aerodynamic resistance, wind disturbance, etc. are modeled to ensure that all integral steps are physically consistent and realistic.

[0078] Equation (2)

[0079] In the formula, M represents the total mass of the unmanned aerial vehicle, g represents the gravity acceleration vector, which is vertically downward; v represents the unmanned aerial vehicle velocity vector, t represents the time variable, a represents the derivative of the unmanned aerial vehicle velocity vector with respect to time, i.e. the acceleration vector of the unmanned aerial vehicle; D represents the aerodynamic resistance component, which is opposite to the relative airflow direction of the unmanned aerial vehicle; W represents the wind disturbance component, which simulates the pushing and offsetting effect of the wind on the whole machine.

[0080] In the dynamic prediction model, the gravity component dominates the overall acceleration to ensure the basic logic of the unmanned aerial vehicle continuously sinking. The aerodynamic resistance component mainly consumes the falling kinetic energy, limiting the falling speed of the unmanned aerial vehicle (especially after opening the parachute). The wind disturbance component determines the horizontal trajectory drift of the unmanned aerial vehicle, which is the main source of uncertainty in the safe landing scenario.

[0081] In step S420, the Runge-Kutta method is used to recursively solve the dynamic prediction model with a fixed step size to predict the motion state of the unmanned aerial vehicle at each integral step.

[0082] Since the dynamic model cannot be solved directly, a discrete time step numerical integration method can be used to "discretize" the theoretical trajectory and recursively predict the flight state at each time, thereby forming a complete, detailed and realistic landing trajectory.

[0083] Specifically, the step size can be predefined and can be selected according to the wind speed environment or the falling speed of the unmanned aerial vehicle. The value range can be 10-100 ms to balance the accuracy and computational load. For the iteration termination condition, it can be that the height of the unmanned aerial vehicle reaches the ground threshold.

[0084] The prediction of each integral step includes:

[0085] Calculate the acceleration​

[0086] Equation (3)

[0087] At this time, the net acceleration after the synthesis of three forces is affected by aerodynamic and wind disturbance in real time in direction and size.

[0088] Update speed

[0089] Equation (4)

[0090] At this time, the current speed is corrected by the acceleration just calculated, reflecting the immediate superposition effect of aerodynamic disturbance and gravity influence.

[0091] Update position

[0092] Equation (5)

[0093] In the equation, is the index of the integral step, indicating the th integral step; , and respectively represent the acceleration, position and speed of the UAV at the th integral step, and respectively represent the position and speed of the UAV at the th integral step, and respectively represent the aerodynamic drag component and wind disturbance component of the th integral step.

[0094] Here, the position calculation is performed using the speed recursion result, ensuring that each step of the physical process and trajectory point is physically interpretable.

[0095] The aerodynamic drag component is modeled as:

[0096] Equation (6)

[0097] Equation (7)

[0098] In the equation, represents the air density, represents the relative airflow speed, is the flight speed of the UAV at the th integral step, is the environmental wind speed vector at the th integral step, is the parachute drag coefficient, is the parachute windward area.

[0099] Here, the vector direction of the aerodynamic resistance component is consistent with the relative airflow of the parachute, and the amplitude is proportional to the square of the speed, highlighting the essence of the dramatic increase in aerodynamic resistance at high speed.

[0100] The wind disturbance component is modeled as:

[0101] Equation (8)

[0102] In the equation, is a preset wind coupling sensitivity coefficient.

[0103] Here, the wind disturbance component is weighted by the wind coupling sensitivity coefficient , and the relative airflow impact is directly reflected as a wind-induced disturbance force, capturing the overall shift of the falling parachute due to the dynamic pulsation of the wind.

[0104] The above prediction operation is repeated step by step with a step size until the flight height of the UAV is less than the set landing height threshold.

[0105] Here, all state variables (acceleration, velocity, position) are sampled and stored with the step size, and the recursive loop can automatically run on the onboard high-performance computing platform of the UAV, without human intervention during the prediction period. The discrete numerical integration method ensures high consistency between theoretical physical modeling and engineering implementation.

[0106] In step S430, the positions of the UAV at each integration step are concatenated in order to form a complete predicted trajectory from the triggering of the landing instruction to the landing.

[0107] Specifically, each predicted position point is output in time sequence to form a complete predicted trajectory from the triggering of the landing instruction to the landing. In this way, through one-time high-density trajectory prediction, it is efficient and accurate, saving resource consumption of real-time recursion.

[0108] Through the embodiments of the present application, the gravity, aerodynamic resistance and wind disturbance are modeled as dominant force terms using the dynamics equation, forming a complete mathematical model describing the actual physical motion of the UAV. By discretely propagating the dynamics equation set using the Runge-Kutta high-order integration method, the ideal flight trajectory from receiving the landing instruction to contacting the ground can be calculated sequentially under the premise of known initial state and environmental parameters. In this way, the initial flight state and real-time meteorological data are used to comprehensively evolve each dominant physical force, ensuring the continuity and physical consistency of the trajectory prediction, fully reflecting the actual superposition effect of each influencing factor during the landing process, and improving the credibility and practicality of the landing trajectory prediction.

[0109] In some examples of the embodiments of the present application, the first calibration model uses an adaptive PID control algorithm, and the adjustment gain parameter is adaptively updated.

[0110] , formula (9)

[0111] In the formula, denotes the time output umbrella rope calibration control amount, , and respectively denote the dynamic proportional coefficient, dynamic integral coefficient and dynamic differential coefficient at time , denotes the inner envelope deviation amplitude at time , denotes the integral time variable, denotes the system deviation at the integral time variable , denotes the cumulative deviation integral term, denotes the deviation change rate at time .

[0112] The above formula (9) shows the normalized PID control equation, but in the normalized PID control, each adjustment gain parameter (P, I, D) is usually a fixed value set manually. In the embodiments of the present application, each adjustment gain parameter is self-adaptively updated, for example, automatically adjusted according to the actual working condition, so as to realize self-adaptive PID control.

[0113] More specifically, the dynamic proportional coefficient is self-adaptively designed by the following formula:

[0114] , formula (10)

[0115] In the formula, denotes the basic proportional gain, denotes the proportional deviation response sensitivity coefficient, denotes the convergence speed adjustment coefficient, denotes the inner envelope radius, denotes the minimum deviation amount in the adjacent historical window at time , denotes the window time length of the historical window.

[0116] In formula (10), is dynamically calculated, which is adaptively amplified by the real-time deviation and the minimum error in the past time window . When there is a long time wandering (slow convergence) under disturbance, The item-driven proportional coefficient increases to accelerate the center of the regression envelope. Therefore, the proportional coefficient is dynamically amplified by the normalization of the current error and the convergence speed, ensuring that when the UAV trajectory deviates greatly from the target envelope center or cannot quickly converge for a long time, the system can immediately improve the response speed and convergence strength, effectively suppress large drift, and achieve fast return under large disturbance.

[0117] The dynamic integral coefficient is adaptively designed by the following formula:

[0118] Equation (11)

[0119] In the formula, Kp represents the basic integral gain, Ki represents the integral amplification coefficient, Kth represents the integral activation threshold proportional coefficient, T represents the window time length of the history window, t represents the time variable.

[0120] In equation (11), when the average error in the past seconds is lower than the threshold , the adaptive integral is activated; otherwise, the integral term is dynamically suppressed (directly set to zero). The adaptive amplification coefficient of the integral term is amplified with the increase of the window integral mean, and is limited by the activation condition to ensure that there is no “false compensation” in the large error or high disturbance stage. The real-time integral result is integrated in the actuator to limit the amplitude or prevent overflow protection to avoid excessive control action.

[0121] The integral coefficient is identified by the threshold judgment of the historical average error, and the integral term is activated and appropriately amplified only when the small error is continuously accumulated. The integral term is suppressed in the large error or high-frequency disturbance to prevent invalid or excessive compensation. In this way, the integral saturation in the traditional PID and the integral storm caused by wind field fluctuations can be effectively prevented, while the static error of the system can be compensated. Specifically, on the one hand, it can effectively suppress the long-term static deviation caused by the long-term static deviation of the UAV parachute adjustment and the stable drift of the wind field, and improve the long-term effect of the parachute fine adjustment; on the other hand, the integral term is cleared in the extreme disturbance or error burst period, thereby preventing saturation effect and large-scale over-regulation or loss of control phenomenon, and improving the stability of the overall control.

[0122] The dynamic differential coefficient is adaptively designed by the following formula:

[0123] Equation (12)

[0124] In the formula, Kp represents the basic differential gain, Kd represents the fluctuation suppression coefficient, Kt represents the differential response adjustment coefficient, t represents the time variable. the variance of the deviation rate within the adjacent history window; is an exponential decay factor, wherein represents a natural constant. The window length of the history window and the size of the damping coefficient can be set according to the specific platform response speed.

[0125] In formula (12), changes with the real-time error rate adaptive amplification, when the system is affected by environmental disturbances such as sudden wind, vortex, etc., causing trajectory mutation, it can quickly suppress overshoot; history window error variance large (i.e. the system is in a high-frequency disturbance or jitter environment), through the exponential suppression term to automatically reduce the differential coefficient and reduce high-frequency noise interference.

[0126] Therefore, the differential coefficient adopts the design of combining the real-time response to the error rate with the exponential suppression of the history variance, which can automatically increase the gain of the differential term to enhance the overshoot suppression ability in the stage of sudden large disturbance or drastic trajectory change. When the system is in a high-frequency noise or drastic bias jitter state, the exponential suppression mechanism timely weakens the differential action to prevent control instability caused by high-frequency signal amplification. Therefore, the unmanned aerial vehicle parachute has stronger adaptive suppression ability to dynamic disturbance, and the landing process is more smooth and stable, which greatly improves the stability of the unmanned aerial vehicle landing process.

[0127] In order to further demonstrate the technical superiority of the embodiments of the present application, the content of the experimental part will be expanded below.

[0128] Figure 5 A simulation effect schematic diagram of an example of a parachute predicted trajectory in an ideal state is shown.

[0129] Specifically, the optimization algorithm is used to accurately back-propagate the landing site position and velocity information. The predicted trajectory is calculated by considering the wind. At the same time, the landing point of the predicted trajectory is taken as the predetermined landing point. Here, it is assumed that the specific numerical value of the parachute opening point state (u0, v0, w0, X0, Y0, Z0) is (-3, 2, 15, 0, 0, 300), wherein the unit of velocity is m / s and the unit of distance is m.

[0130] It should be pointed out that the opening point refers to the starting point of the parachute after it is deployed. If the deployment process is considered, the release point state can be corrected on this basis. By gradually integrating the dynamic prediction model, the predicted trajectory of the parachute can be obtained, as shown in Figure 5 On this basis, the and Given the inner and outer envelope surfaces, the predicted landing point P0 obtained from the simulation has the coordinates (211.50, -154.71, 0) in the O-XYZ space.

[0131] Figure 6 A simulated trajectory diagram of an example of an uncontrolled parachute descent under interference conditions is shown. Figure 7 A simulation diagram illustrating an example of the impact point distribution of an uncontrolled parachute under interference conditions is shown.

[0132] Considering the inevitable influence of various disturbances in actual landing missions, the main disturbance factors considered in the simulation are: parachute descent speed deviation, altitude deviation, aerodynamic parameter deviation, and wind field measurement deviation. All deviations are taken as random numbers within 10% of their original values. Under the above simulation conditions, a Monte Carlo simulation of the uncontrolled parachute descent trajectory at 1000 sample points is presented, and the results are as follows. Figure 6 and Figure 7 As shown.

[0133] Figure 8 A schematic diagram of a simulated trajectory of an example of a controlled parachute descent according to an embodiment of this application under conditions of interference is shown. Figure 9 A simulation diagram illustrating an example of the controllable parachute landing point distribution according to an embodiment of this application under conditions of interference is shown.

[0134] Depend on Figure 8 and Figure 9 It can be seen that when the parachute is out of control, the initial state error and external disturbances have a significant impact on its descent trajectory, and the landing points are widely distributed, which approximately follows a normal distribution pattern, which is consistent with the actual flight test results.

[0135] right Figure 7 Statistical analysis of the data shows that the average absolute deviation relative to the predicted landing point in the X direction is 32.43 m, with a maximum absolute deviation of 133.03 m. The average absolute deviation in the Y direction is 25.90 m, with a maximum absolute deviation of 114.00 m. The average distance between the landing point and the predicted landing point is 46.03 m, with a maximum distance of 144.49 m.

[0136] Under the same simulation conditions, 1000 Monte Carlo simulations were performed on the controllable parachute, and the results are as follows. Figure 9 As shown, after adopting parachute line control, the parachute descent trajectories showed convergence after 1000 drops; in other words, the parachute descent trajectory approached the predicted trajectory. Figure 9The data is counted, and the average absolute deviation of the landing point in the X direction is 3.94 m, and the maximum absolute deviation is 19.55 m; the average absolute deviation in the Y direction is 3.54 m, and the maximum absolute deviation is 12.56 m; the average distance between the landing point after control and the predicted landing point is 6.16 m, and the farthest is 19.59 m.

[0137] As can be seen, when the parachute is additionally provided with the parachute rope auxiliary winding and unwinding control capability provided in the embodiments of the present application, the landing point accuracy of the unmanned aerial vehicle is significantly improved.

[0138] It should be noted that, for the foregoing method embodiments, in order to simply describe, they are all expressed as a series of actions, but those skilled in the art should know that the present application is not limited by the order of the described actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should know that the embodiments described in the specification all belong to preferred embodiments, and the actions and modules involved are not necessarily required by the present application. In the above embodiments, the description of each embodiment is focused on, and the parts not described in detail in a certain embodiment can be referred to the related description of other embodiments.

[0139] Figure 10 A structural block diagram of an example of a patrol unmanned aerial vehicle parachute control system based on envelope adaptation according to an embodiment of the present application is shown.

[0140] As Figure 10 shown, the envelope adaptation-based patrol unmanned aerial vehicle parachute control system 1000 includes a parameter acquisition unit 1010, a trajectory calculation unit 1020, an envelope construction unit 1030, a calibration quantity calculation unit 1040, and an auxiliary winding and unwinding control unit 1050.

[0141] The parameter acquisition unit 1010 is configured to acquire flight state parameters and meteorological environment parameters of the unmanned aerial vehicle based on triggering of an unmanned aerial vehicle landing instruction; the flight state parameters include the position and speed of the unmanned aerial vehicle, and the meteorological environment parameters include the environmental wind speed.

[0142] The trajectory calculation unit 1020 is configured to calculate a predicted landing trajectory of the unmanned aerial vehicle according to the flight state parameters and the meteorological environment parameters.

[0143] The envelope construction unit 1030 is configured to construct a landing envelope region according to the predicted landing trajectory; the landing envelope region includes an outer envelope surface and an inner envelope surface, the inner envelope surface and the outer envelope surface are cylindrical surfaces with the predicted landing trajectory as the center and envelope radii of inner envelope radius and outer envelope radius, respectively, and the outer envelope radius is greater than the inner envelope radius.

[0144] The calibration quantity calculation unit 1040 is configured to monitor a real-time flight trajectory of the UAV during landing, and when the real-time flight trajectory is not within the coverage of the inner envelope surface and is within the coverage of the outer envelope surface, process an inner envelope deviation range between the real-time flight trajectory and the inner envelope surface according to a first calibration model to calculate a corresponding first parachute line winding and unwinding calibration quantity.

[0145] The auxiliary winding and unwinding control unit 1050 is configured to generate a first parachute line winding and unwinding intervention instruction according to the first parachute line winding and unwinding calibration quantity, so as to activate a landing parachute auxiliary control module to assist in winding and unwinding control of a parachute line of a landing parachute of the UAV; wherein the landing parachute auxiliary control module and a flight control system module of the UAV are connected to a power module in parallel.

[0146] In some embodiments, the embodiments of the present application provide a non-volatile computer readable storage medium, wherein one or more programs including execution instructions are stored in the storage medium, the execution instructions can be read and executed by an electronic device (including but not limited to a computer, a server, or a network device, etc.) to execute the steps of any one of the above envelope adaptive inspection UAV parachute control methods.

[0147] In some embodiments, the embodiments of the present application also provide a computer program product, which includes a computer program stored on a non-volatile computer readable storage medium, the computer program includes program instructions, when the program instructions are executed by a computer, the computer executes the steps of any one of the above envelope adaptive inspection UAV parachute control methods.

[0148] In some embodiments, the embodiments of the present application also provide an electronic device, which includes at least one processor, and a memory connected to the at least one processor in communication, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the steps of the envelope adaptive inspection UAV parachute control method.

[0149] The above products can execute the methods provided by the embodiments of the present application, and have the corresponding function modules and beneficial effects of executing the methods. Technical details not described in detail in the embodiments can be referred to the methods provided by the embodiments of the present application.

[0150] The electronic device of the embodiments of the present application exists in various forms, including but not limited to: a mobile communication device, an ultra-mobile personal computer device, a portable entertainment device, or other on-board electronic devices with data interaction function.

[0151] The device embodiments described above are merely illustrative, wherein the units described as separate components can or can not be physically separate, and the components displayed as units can or can not be physical units, i.e., can be located in one place, or can be distributed to multiple network units. Part or all of the modules can be selected according to actual needs to achieve the purpose of the embodiment scheme.

[0152] Through the description of the above embodiments, those skilled in the art can clearly understand that the embodiments can be implemented by means of software plus a general hardware platform, and of course can also be implemented by hardware. Based on such understanding, the above technical solutions can be embodied in the form of a software product, which can be stored in a computer readable storage medium, such as a ROM / RAM, a magnetic disk, an optical disk, etc., and includes a plurality of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute the methods described in each embodiment or some parts of the embodiments.

[0153] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for part of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. An envelope-based adaptive inspection unmanned aerial vehicle parachute control method, characterized in that, The method comprises: Based on the triggering of the unmanned aerial vehicle landing instruction, the flight state parameters and the meteorological environment parameters of the unmanned aerial vehicle are collected; the flight state parameters include the position and speed of the unmanned aerial vehicle, and the meteorological environment parameters include the environmental wind speed; According to the flight state parameters and the meteorological environment parameters, the predicted landing trajectory of the unmanned aerial vehicle is calculated; According to the predicted landing trajectory, a landing envelope region is constructed; the landing envelope region includes an outer envelope surface and an inner envelope surface, the inner envelope surface and the outer envelope surface are cylindrical surfaces with the predicted landing trajectory as the center and the envelope radii are inner envelope radius and outer envelope radius respectively, and the outer envelope radius is greater than the inner envelope radius; The real-time flight trajectory of the unmanned aerial vehicle in the landing process is monitored, and when the real-time flight trajectory is not within the coverage range of the inner envelope surface and is within the coverage range of the outer envelope surface, the inner envelope deviation amplitude between the real-time flight trajectory and the inner envelope surface is processed according to a first calibration model to calculate a corresponding first parachute line retraction calibration quantity; A first parachute line retraction intervention instruction is generated according to the first parachute line retraction calibration quantity to activate a landing parachute auxiliary control module to assist in controlling the parachute line of the landing parachute of the unmanned aerial vehicle; wherein the landing parachute auxiliary control module and the flight control system module of the unmanned aerial vehicle are connected to the power module in parallel.

2. The method of claim 1, wherein, After monitoring the real-time flight trajectory of the unmanned aerial vehicle in the landing process, the method further comprises: When the real-time flight trajectory is within the coverage range of the inner envelope surface, the landing parachute auxiliary control module remains in an inactive state to avoid interfering with the original parachute line retraction control strategy of the flight control system module.

3. The method of claim 1, wherein, The first calibration model adopts a PID control algorithm, takes the inner envelope deviation amplitude as input, and dynamically adjusts the proportional coefficient, integral coefficient and differential coefficient, so that the first parachute line retraction calibration quantity remains smooth within a continuous time period, thereby performing fine retraction control on the parachute line of the landing parachute of the unmanned aerial vehicle.

4. The method of claim 1, wherein, After monitoring the real-time flight trajectory of the unmanned aerial vehicle in the landing process, the method further comprises: When the real-time flight trajectory is not within the coverage range of the outer envelope surface, the outer envelope deviation amplitude between the real-time flight trajectory and the outer envelope surface is processed according to a second calibration model to calculate a corresponding second parachute line retraction calibration quantity; wherein the second calibration model adopts a control algorithm based on proportional gain amplification, takes the outer envelope deviation amplitude as input, defines the second parachute line retraction calibration quantity as a proportional gain to the outer envelope deviation amplitude, thereby performing rapid retraction control on the parachute line of the landing parachute of the unmanned aerial vehicle; A second parachute line retraction intervention instruction is generated according to the second parachute line retraction calibration quantity to activate the landing parachute auxiliary control module to assist in controlling the parachute line of the landing parachute of the unmanned aerial vehicle.

5. The method according to any one of claims 1-4, characterized in that, The inner envelope radius adopts a pre-set landing area radius; the outer envelope radius gradually decreases as the flight height of the unmanned aerial vehicle decreases, and is always greater than the inner envelope radius; ， In the formula, represents the real-time flight height of the UAV, is the outer envelope radius when the real-time flight height of the UAV is is the preset maximum deviation radius, represents the inner envelope radius, which adopts the landing area radius; represents the maximum flight height of the UAV at the initial moment when the UAV landing instruction is received; is an influence index, which represents the influence degree of the flight height change on the radius reduction; is a wind speed disturbance influence factor, is a wind speed change amount, which represents the difference value corresponding to the environmental wind speed at the continuous signal sampling moment.​ 6. The method according to any one of claims 1-4, characterized in that, The calculation of the predicted landing trajectory of the unmanned aerial vehicle according to the flight state parameters and the meteorological environment parameters comprises: The dynamic prediction model is initialized based on flight state parameters and meteorological environment parameters at an initial moment when the UAV receives the landing instruction: ， wherein denotes the total mass of the drone, denotes the gravity acceleration vector; denotes the drone velocity vector, is a time variable, denotes the derivative of the drone velocity vector with respect to time, i.e. the drone acceleration vector; denotes the aerodynamic drag component, denotes the wind disturbance component; The Runge-Kutta method is used to solve the dynamic prediction model according to a fixed step size The dynamic prediction model is solved recursively to predict the motion state of the UAV at each integration step. The prediction of each integration step includes: Calculate the acceleration ， Update the speed ， Update the position ， wherein, is the index of the integration step, indicating the th integration step; , and respectively represent the acceleration, position and velocity of the UAV at the th integration step, and respectively represent the position and velocity of the UAV at the th integration step, and respectively represent the aerodynamic drag component and the wind disturbance component at the th integration step; The aerodynamic resistance component is modeled as: ， ， wherein denotes the air density, denotes the relative air flow speed, is the UAV flight speed for the th integration step, is the environmental wind speed vector for the th integration step, is the parachute drag coefficient, is the parachute frontal area; The wind disturbance component is modeled as: ， In the formula, is a preset wind coupling sensitivity coefficient; According to the step size The above prediction operation is repeated step by step until the flight height of the UAV is less than a set landing height threshold. The positions of the UAV in each integration step are concatenated in order to form a complete predicted trajectory from triggering the landing instruction to landing.

7. The method of claim 3, wherein, The first calibration model adopts an adaptive PID control algorithm, and the adjustment gain parameters are adaptively updated; ， wherein denotes the time instant the output umbilical cord calibration control quantity, , and denote the dynamic proportional, dynamic integral and dynamic derivative coefficients at the time instant , denotes the inner envelope deviation at the time instant , denotes the integration time variable, denotes the system deviation at the integration time variable , denotes the cumulative deviation integral term, denotes the deviation rate of change at the time instant ; The dynamic proportional coefficient is adaptively designed by the following formula: ， wherein, represents a base proportional gain, represents a proportional deviation response sensitivity coefficient, represents a convergence speed adjustment coefficient, represents an inner envelope radius, represents a time of a minimum deviation within a neighboring history window of the time represents a window time length of the history window; The dynamic integral coefficient is adaptively designed by the following formula: ， wherein denotes a base integral gain, denotes an integral amplification factor, denotes an integral activation threshold proportionality factor, denotes a window time length of the history window, is a time variable; The dynamic differential coefficient is adaptively designed by the following formula: ， wherein represents a base differential gain, represents a fluctuation suppression coefficient, represents a differential response adjustment coefficient, represents a time of a variance of a deviation change rate within a neighboring history window of the time is an exponential decay factor, where represents a natural constant.

8. An envelope-based adaptive inspection drone parachute control system, comprising: The system comprises: A parameter acquisition unit configured to acquire flight state parameters and meteorological environment parameters of the UAV based on triggering of a UAV landing instruction; the flight state parameters include the position and speed of the UAV, and the meteorological environment parameters include the environmental wind speed; A trajectory calculation unit configured to calculate a predicted landing trajectory of the UAV according to the flight state parameters and the meteorological environment parameters; An envelope construction unit configured to construct a landing envelope region according to the predicted landing trajectory; the landing envelope region includes an outer envelope surface and an inner envelope surface, the inner envelope surface and the outer envelope surface are cylindrical surfaces with the predicted landing trajectory as the center and with envelope radii of an inner envelope radius and an outer envelope radius, respectively, and the outer envelope radius is greater than the inner envelope radius; A calibration quantity calculation unit configured to monitor a real-time flight trajectory of the UAV during landing, and when the real-time flight trajectory is not within the coverage of the inner envelope surface and is within the coverage of the outer envelope surface, to calculate a corresponding first parachute line retraction calibration quantity according to a first calibration model processing an inner envelope deviation amplitude between the real-time flight trajectory and the inner envelope surface; An auxiliary retraction control unit configured to generate a first parachute line retraction intervention instruction according to the first parachute line retraction calibration quantity, to activate a landing parachute auxiliary control module to assist in retraction control of a parachute line of a landing parachute of the UAV; wherein the landing parachute auxiliary control module and a flight control system module of the UAV are connected in parallel to a power module.

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