Control method, system, device and medium for anti-interference cooperative hoisting of two unmanned aerial vehicles

Abstract

The application discloses a kind of dual unmanned aerial vehicle anti-interference cooperative hoisting control method, system, equipment and medium, comprising: obtaining the actual state information of dual unmanned aerial vehicle and the desired state information of virtual leader;According to desired state information, the desired position information of dual unmanned aerial vehicle is calculated according to pre-set dual-machine cooperative decoupling control rule;With desired position information as input, based on the extended state observer and nonlinear anti-interference controller constructed in advance, the control input information of each unmanned aerial vehicle is output, so that the power system controls dual unmanned aerial vehicle anti-interference cooperative hoisting load according to control input information.The application introduces virtual leader, solves the problem of sling tension imbalance caused by independent trajectory planning;Based on dual-machine cooperative decoupling control rule, the problem of unmeasurable load pose caused by flexible sling is solved, and the extended state observer and nonlinear anti-interference controller are used to realize real-time estimation and active compensation for compound disturbance such as wind disturbance and sudden load.

Description

Technical Field

[0001] This invention relates to the field of unmanned aerial vehicle (UAV) hoisting technology, and in particular to a control method, system, equipment, and medium for dual UAV anti-interference collaborative hoisting. Background Technology

[0002] With the continuous evolution of drone swarm collaborative operation technology, dual drone collaborative hoisting is widely used in scenarios such as material delivery in complex terrain, emergency rescue, and heavy equipment handling due to its flexibility and high mobility.

[0003] In existing technologies, dual-UAV collaborative hoisting often employs independent three-dimensional trajectory tracking strategies for each drone, failing to fully consider the constraint effect of load dynamics on the motion of the two drones. Even slight temporal or spatial synchronization deviations can lead to uneven tension distribution in the slings, inducing significant load swaying or even instability and overturning. Secondly, when faced with external disturbances such as wind interference, sudden loading, or elastic deformation of the slings, traditional proportional-integral-derivative controllers can only passively compensate based on position errors. This results in sluggish response, significant overshoot, and difficulty in simultaneously ensuring trajectory tracking accuracy and overall system robustness. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to overcome the shortcomings of the prior art in which external influences are not fully considered when dual-drone collaboratively hoisting goods, and to provide a control method, system, equipment and medium for dual-drone anti-interference collaborative hoisting.

[0005] The present invention solves the above-mentioned technical problems through the following technical solution:

[0006] In a first aspect, the present invention provides a control method for dual-UAV anti-interference cooperative hoisting, the control method comprising:

[0007] The system acquires the actual status information of two drones and the expected status information of a virtual navigator. The actual status information includes the first current position information and the first speed information of the first drone, and the second current position information and the second speed information of the second drone. The expected status information includes real-time position information and expected speed information. The virtual navigator, the first drone, and the second drone form an isosceles triangle structure.

[0008] The expected position information of the two UAVs is calculated according to the actual state information and the expected state information in accordance with the pre-set dual-machine cooperative decoupling control rules; the dual-machine cooperative decoupling control rules are used to characterize the rules for calculating the expected position of the two UAVs based on the real-time position of the virtual navigator and the sling length combined with the load attitude angle constraints.

[0009] Using the desired position information as input, and based on a pre-built extended state observer and a nonlinear disturbance rejection controller, control input information for each UAV is output, enabling the power system to control the dual UAVs to collaboratively lift the load in a disturbance-resistant manner according to the control input information. The extended state observer is used to characterize a dynamic observer set based on the position error, velocity error, and total disturbance error of the first and second UAVs. The nonlinear disturbance rejection controller is used to characterize a nonlinear feedback structure that combines a saturation function with power feedback, and takes the state estimation information of each UAV output by the extended state observer as input.

[0010] Preferably, the equation of motion for the virtual navigator corresponds to the following formula:

[0011]

[0012] in, Indicates the quality of the load. This represents the acceleration vector of the virtual navigator. Represents the gravitational acceleration vector. 9.81 , Represents the desired acceleration vector. The accuracy range is ±0.5kg, either recorded before hoisting or obtained by weighing sensors before hoisting.

[0013] The geometric constraint formulas for the first UAV and the second UAV relative to the virtual navigator are as follows:

[0014]

[0015]

[0016] in, This represents the real-time position vector of the virtual navigator. This represents the current position vector of the first UAV. This represents the current position vector of the second UAV. This indicates the length of the sling connecting the virtual navigator to the first UAV and the second UAV.

[0017] Preferably, the pitch and roll angles of the load relative to the vertical direction in the dual-machine cooperative decoupling control rules are calculated using the following formulas:

[0018]

[0019]

[0020] in, Under normal hoisting conditions, 0, and 0, meaning the load remains vertically suspended;

[0021] The desired position information of the two UAVs in the dual-UAV cooperative decoupling control rule satisfies the following symmetry condition:

[0022]

[0023]

[0024] in, This represents the desired position vector of the first UAV. This represents the desired position vector of the second UAV. This represents the first fixed offset vector of the first UAV relative to the virtual navigator. This represents the second fixed offset vector of the second UAV relative to the virtual navigator, and satisfies... , , , , Indicates the horizontal distance between the two drones. This indicates the vertical component of the sling.

[0025] Preferably, the state variable corresponding to the X-axis channel of the first UAV in the extended state observer is obtained using the following formula:

[0026]

[0027] 1X 1X

[0028]

[0029] in, This indicates the position error of the first UAV. This represents the actual x-coordinate of the first UAV. This represents the desired x-coordinate of the first drone. This indicates the speed error of the first drone. 1X This indicates the actual lateral velocity of the first drone. 1X This represents the desired lateral velocity of the first drone. This represents the total disturbance error of the first UAV. This indicates that wind disturbance, sudden loading, and elastic deformation of the suspension cables constitute the total disturbance.

[0030] The dynamic equation corresponding to the first UAV in the extended state observer is adopted by the following formula:

[0031]

[0032] in, This represents the state estimation information. This indicates the control input information. , , Represents the observer bandwidth parameters, which respectively satisfy... , , , Indicates the observer bandwidth;

[0033]

[0034] in, Let saturation function be defined as:

[0035]

[0036] , Indicates control gain. Indicates the saturation boundary. The coefficient is a power factor.

[0037] Secondly, the present invention provides a control system for dual-UAV anti-interference cooperative hoisting, the control system comprising:

[0038] The acquisition module is used to acquire the actual status information of the two drones and the expected status information of the virtual navigator; the actual status information includes the first current position information and the first speed information of the first drone, and the second current position information and the second speed information of the second drone; the expected status information includes real-time position information and expected speed information; the virtual navigator, the first drone, and the second drone form an isosceles triangle structure.

[0039] The calculation module is used to calculate the expected position information of the two UAVs based on the actual state information and the expected state information according to the pre-set dual-machine cooperative decoupling control rules; the dual-machine cooperative decoupling control rules are used to characterize the rules for calculating the expected position of the two UAVs based on the real-time position of the virtual navigator and the sling length combined with the load attitude angle constraints.

[0040] The output module is used to take the desired position information as input and output control input information for each UAV based on a pre-built extended state observer and a nonlinear disturbance rejection controller, so that the power system controls the dual UAVs to cooperate in lifting the load in a disturbance-resistant manner according to the control input information; the extended state observer is used to characterize a dynamic observer set based on the position error, velocity error and total disturbance error of the first UAV and the second UAV; the nonlinear disturbance rejection controller is used to characterize a nonlinear feedback structure that combines a saturation function and power feedback, and takes the state estimation information of each UAV output by the extended state observer as input.

[0041] Preferably, the equation of motion for the virtual navigator corresponds to the following formula:

[0042]

[0043] in, Indicates the quality of the load. This represents the acceleration vector of the virtual navigator. Represents the gravitational acceleration vector. 9.81 , Represents the desired acceleration vector. The accuracy range is ±0.5kg, either recorded before hoisting or obtained by weighing sensors before hoisting.

[0044] The geometric constraint formulas for the first UAV and the second UAV relative to the virtual navigator are as follows:

[0045]

[0046]

[0047] in, This represents the real-time position vector of the virtual navigator. This represents the current position vector of the first UAV. This represents the current position vector of the second UAV. This indicates the length of the sling connecting the virtual navigator to the first UAV and the second UAV.

[0048] Preferably, the pitch and roll angles of the load relative to the vertical direction in the dual-machine cooperative decoupling control rules are calculated using the following formulas:

[0049]

[0050]

[0051] in, Under normal hoisting conditions, 0, and 0, meaning the load remains vertically suspended;

[0052] The desired position information of the two UAVs in the dual-UAV cooperative decoupling control rule satisfies the following symmetry condition:

[0053]

[0054]

[0055] in, This represents the desired position vector of the first UAV. This represents the desired position vector of the second UAV. This represents the first fixed offset vector of the first UAV relative to the virtual navigator. This represents the second fixed offset vector of the second UAV relative to the virtual navigator, and satisfies... , , , , Indicates the horizontal distance between the two drones. This indicates the vertical component of the sling.

[0056] Preferably, the state variable corresponding to the X-axis channel of the first UAV in the extended state observer is obtained using the following formula:

[0057]

[0058] 1X 1X

[0059]

[0060] in, This indicates the position error of the first UAV. This represents the actual x-coordinate of the first UAV. This represents the desired x-coordinate of the first drone. This indicates the speed error of the first drone. 1X This indicates the actual lateral velocity of the first drone. 1X This represents the desired lateral velocity of the first drone. This represents the total disturbance error of the first UAV. This indicates that wind disturbance, sudden loading, and elastic deformation of the suspension cables constitute the total disturbance.

[0061] The dynamic equation corresponding to the first UAV in the extended state observer is adopted by the following formula:

[0062]

[0063] in, This represents the state estimation information. This indicates the control input information. , , Represents the observer bandwidth parameters, which respectively satisfy... , , , Indicates the observer bandwidth;

[0064]

[0065] in, Let saturation function be defined as:

[0066]

[0067] , Indicates control gain. Indicates the saturation boundary. The coefficient is a power factor.

[0068] Thirdly, the present invention provides an electronic device, including a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the control method for dual UAV anti-interference cooperative hoisting as described above.

[0069] Fourthly, the present invention provides a computer-readable storage medium on which a computer program is stored, wherein when the computer program is executed by a processor, it implements the control method for dual UAV anti-interference cooperative hoisting as described above.

[0070] The positive and progressive effects of this invention are as follows: It acquires the actual state information of two UAVs and the expected state information of a virtual navigator; this method introduces a virtual navigator to solve the problem of sling tension imbalance caused by independent trajectory planning; it calculates the expected position information of the two UAVs according to the expected state information and pre-set dual-UAV cooperative decoupling control rules; this method, based on dual-UAV cooperative decoupling control rules, solves the problem of unmeasurable load pose caused by flexible slings; using the expected position information as input, and based on a pre-built extended state observer and nonlinear disturbance rejection controller, it outputs the control input information of each UAV; and by using the extended state observer and nonlinear disturbance rejection controller, it achieves real-time estimation and active compensation for complex disturbances such as wind disturbance and sudden loading. Attached Figure Description

[0071] Figure 1 This is a flowchart of the control method for dual-UAV anti-interference cooperative hoisting in Embodiment 1 of the present invention.

[0072] Figure 2 This is a schematic diagram of the virtual navigator architecture of the control method for dual UAV anti-interference collaborative hoisting in Embodiment 1 of the present invention.

[0073] Figure 3 This is a schematic diagram illustrating the application of the dual-UAV anti-interference collaborative hoisting control method in Embodiment 1 of the present invention.

[0074] Figure 4 This is a schematic diagram of the control system for dual UAV anti-interference collaborative hoisting in Embodiment 1 of the present invention.

[0075] Figure 5 This is a schematic diagram of the hardware structure of the electronic device according to Embodiment 3 of the present invention. Detailed Implementation

[0076] The present invention will be further illustrated by way of embodiments below, but the present invention is not limited to the scope of the embodiments described herein.

[0077] Example 1

[0078] like Figure 1 As shown, this embodiment provides a control method for dual-UAV anti-interference cooperative hoisting, the control method including:

[0079] S11. Obtain the actual status information of the two drones and the expected status information of the virtual navigator; the actual status information includes the first current position information and the first speed information of the first drone, and the second current position information and the second speed information of the second drone; the expected status information includes the real-time position information and the expected speed information; the virtual navigator, the first drone and the second drone form an isosceles triangle structure.

[0080] S12. Calculate the desired position information of the two UAVs according to the pre-set dual-machine cooperative decoupling control rules based on the actual state information and the desired state information. The dual-machine cooperative decoupling control rules are used to characterize the rules for calculating the desired position of the two UAVs based on the real-time position of the virtual navigator and the sling length combined with the load attitude angle constraints.

[0081] S13. Using the desired position information as input, and based on the pre-built extended state observer and nonlinear disturbance rejection controller, output the control input information of each UAV, so that the power system controls the dual UAVs to cooperate in lifting the load in a disturbance-resistant manner according to the control input information; the extended state observer is used to characterize the dynamic observer set based on the position error, velocity error and total disturbance error of the first UAV and the second UAV; the nonlinear disturbance rejection controller is used to characterize the nonlinear feedback structure that combines saturation function and power feedback, and takes the state estimation information of each UAV output by the extended state observer as input.

[0082] For step S11 above, the first current position of the first UAV is obtained from the airborne inertial measurement unit and the global navigation satellite fusion module. and first speed information The second current position of the second drone Second speed information The task planning module obtains the real-time location information of the virtual navigator at the current moment. and expected speed information By introducing a virtual navigator architecture, the originally coupled motion of two UAVs is transformed into an independent tracking task of the same virtual reference point, fundamentally eliminating the problem of cable tension imbalance caused by independent trajectory planning. Under the condition that the synchronization error is less than a preset time threshold, the load swing amplitude can be controlled within a preset angle range, which is significantly better than the large swing of traditional independent trajectory tracking methods.

[0083] Regarding step S12 above, based on the real-time location information of the virtual navigator... The first current position of the first drone The second current position of the second drone Calculate the desired position vector of the first UAV in a dual-UAV setup. The desired position vector of the second UAV The dual-machine collaborative decoupling control rule, constructed from load attitude angle constraints and symmetry conditions, eliminates the need for additional sensors on the load. It indirectly derives the load attitude and disturbance effects through geometric relationships, solving the problem of unmeasurable load attitude caused by flexible slings and reducing hardware complexity and cost.

[0084] For step S13 above, a combination of an extended state observer and a nonlinear disturbance rejection controller is used to estimate and actively compensate for complex disturbances such as wind disturbance and sudden loading in real time. The response delay is less than a preset time threshold, and the trajectory tracking error can still be maintained below a preset distance threshold even in strong winds. The traditional proportional-integral-derivative control method has a significantly larger error under this condition. The control input information is applied to the power systems of the two UAVs. By updating the virtual navigator state, the expected position information of the two UAVs, and the disturbance compensation amount in real time, a complete closed-loop control loop is formed to ensure that the load remains in a stable suspended state during transportation. The update cycle of the closed-loop cooperative control is no greater than a predetermined time period. All state variables are obtained by fusing data from the inertial measurement unit and the global navigation satellite system, and the data synchronization accuracy is better than the preset time threshold.

[0085] In one embodiment, the equation of motion for the virtual navigator corresponds to the following formula:

[0086]

[0087] in, Indicates the quality of the load. This represents the acceleration vector of the virtual navigator. Represents the gravitational acceleration vector. 9.81 , Represents the desired acceleration vector. The accuracy range is ±0.5kg, either recorded before hoisting or obtained by weighing sensors before hoisting.

[0088] The geometric constraint formulas for the first and second UAVs relative to the virtual navigator are as follows:

[0089]

[0090]

[0091] in, This represents the real-time position vector of the virtual navigator. This represents the current position vector of the first UAV. This represents the current position vector of the second UAV. This indicates the length of the sling connecting the virtual navigator to the first and second drones.

[0092] In this embodiment, as Figure 2 As shown, based on the center-of-mass dynamics of the load, the slender triangle structure consisting of a virtual navigator, a first UAV, and a second UAV is called the virtual navigator architecture. This virtual navigator does not correspond to any physical entity; its trajectory is determined by the desired load transport path, which is expressed as... , Representing a continuous time variable, the virtual navigator's position coordinates are directly set to... This means that the trajectory of its center of mass completely coincides with the ideal trajectory of the load's center of mass. The two drones are geometrically linked to a virtual navigator, forming a dual-drone cooperative motion framework with the virtual navigator as the reference. The motion equation of the virtual navigator is determined by the load mass, gravitational acceleration, and desired acceleration; its position coordinates directly correspond to the ideal trajectory of the load's center of mass and do not depend on the physical measurements of the actual load. Assuming the sling is an ideal rigid rod, with its upper end fixed to the mounting point below the centers of mass of both drones and the lower end connected to the load's center of mass, the two drones and the virtual navigator form an isosceles triangle structure with a base length of... .

[0093] In one embodiment, the pitch and roll angles of the load relative to the vertical direction in the dual-machine cooperative decoupling control rules are calculated using the following formulas:

[0094]

[0095]

[0096] in, Under normal hoisting conditions, 0, and 0, meaning the load remains vertically suspended;

[0097] The desired position information of the two UAVs in the dual-UAV cooperative decoupling control rule satisfies the following symmetry condition:

[0098]

[0099]

[0100] in, This represents the desired position vector of the first UAV. This represents the desired position vector of the second UAV. This represents the first fixed offset vector of the first UAV relative to the virtual navigator. Let represent the second fixed offset vector of the second UAV relative to the virtual navigator, and satisfy . , , , , Indicates the horizontal distance between the two drones. This indicates the vertical component of the sling.

[0101] In this embodiment, the load attitude angle in the dual-machine cooperative decoupling control rule includes pitch and roll angles, calculated from the relative vectors of the two machines. If the virtual navigator moves along a curved trajectory, the radius of curvature R must satisfy... , A preset distance threshold of 10 meters can be used to avoid excessive load swaying due to excessive centrifugal force. Maximum flight speed. If the speed exceeds a preset threshold, a speed of 8 m / s can be used to ensure the responsiveness of the control system. Based on the position and attitude information of the virtual navigator, combined with the sling length and direction vector between the two UAVs and the load, the desired position command of each UAV in three-dimensional space is derived, enabling the motion of the two UAVs to satisfy the load attitude constraints while achieving motion decoupling. The geometric relationship between the two UAVs and the virtual navigator is established jointly through a constant sling length constraint and a load attitude angle constraint. The sling length is set to a fixed value, and the load attitude angle is calculated from the relative position vectors of the two UAVs, thus ensuring that the motion of the two UAVs satisfies the load balance condition at any given time.

[0102] Secondly, before the lifting operation begins, an online calibration procedure for the sling length is performed. Two drones are hovered at the same height, with the load hanging naturally. The horizontal distance between the two drones is measured. Measure the vertical distance from the bottom of the load to the drone mounting point. Actual length of sling Inversely derived from trigonometric relationships:

[0103]

[0104] The calibration error must be less than the preset length threshold, which can be 0.05 meters; otherwise, recalibration will be triggered.

[0105] Using real-time acquisition , With known ,calculate And then solve and .like or ,

[0106] , If we take 5°, then... and As an auxiliary feedback signal, it is injected into the dual-machine collaborative decoupling control rules for fine-tuning. and The horizontal offset actively suppresses swaying.

[0107] In one embodiment, the state variable corresponding to the X-axis channel of the first UAV in the extended state observer is obtained using the following formula:

[0108]

[0109] 1X 1X

[0110]

[0111] in, This indicates the positional error of the first UAV. This represents the actual x-coordinate of the first UAV. This represents the expected x-coordinate of the first drone. This indicates the speed error of the first drone. 1X This indicates the actual lateral velocity of the first drone. 1X This represents the expected lateral velocity of the first drone. This represents the total disturbance error of the first UAV. This indicates that wind disturbance, sudden loading, and elastic deformation of the suspension cables constitute the total disturbance.

[0112] The dynamic equation corresponding to the first UAV in the extended state observer is adopted by the following formula:

[0113]

[0114] in, This represents state estimation information. This indicates control input information. , , Represents the observer bandwidth parameters, which respectively satisfy... , , , Indicates the observer bandwidth;

[0115]

[0116] in, Let saturation function be defined as:

[0117]

[0118] , Indicates control gain. Indicates the saturation boundary. The coefficient is a power factor.

[0119] In this embodiment, a high-order extended state observer is constructed to assess the total disturbances, including wind disturbances, sudden loading, and elastic deformation of the slings, and to estimate and compensate for the impact of these total disturbances on the UAV's position and velocity in real time. The extended state observer is third-order, and its state variables include position error, velocity error, and the estimated total disturbance. The observer's bandwidth parameter is set to be greater than or equal to a preset frequency threshold to ensure effective tracking of high-frequency disturbances. Based on the output of the extended state observer, a nonlinear feedback structure is used to replace the traditional proportional-integral-derivative controller to generate control inputs for each UAV, achieving high-precision tracking and robust response to the desired trajectory. The control gain is dynamically adjusted according to the UAV's current flight state to suppress overshoot and improve response speed.

[0120] In one embodiment, such as Figure 3 As shown, based on the desired position information, the extended state observer and nonlinear disturbance rejection controller output the control input information of each UAV. After sending the control input information to the power system, the two UAVs perform a disturbance rejection cooperative load lifting operation. The actual state information of the two UAVs and the desired state information of the virtual navigator are then updated, initiating a new round of cooperative lifting control. This method features a short closed-loop control cycle and a high update frequency. Combined with a dynamic gain adjustment mechanism, it maintains stability during high-dynamic maneuvers such as acceleration and turning, with the maximum allowable acceleration reaching a preset acceleration threshold, meeting the requirements of demanding application scenarios such as emergency rescue and rapid delivery.

[0121] In this embodiment, a control method for dual-UAV anti-disturbance collaborative hoisting is provided. A virtual navigator is introduced to solve the problem of sling tension imbalance caused by independent trajectory planning. Based on the dual-UAV collaborative decoupling control rules, the problem of unmeasurable load pose caused by flexible slings is solved. An extended state observer and a nonlinear anti-disturbance controller are used to realize real-time estimation and active compensation for complex disturbances such as wind disturbance and sudden loading.

[0122] Example 2

[0123] like Figure 4 As shown, this embodiment provides a control system for dual-UAV anti-interference collaborative hoisting, the control system including:

[0124] The acquisition module 210 is used to acquire the actual status information of the two drones and the expected status information of the virtual navigator. The actual status information includes the first current position information and the first speed information of the first drone, and the second current position information and the second speed information of the second drone. The expected status information includes the real-time position information and the expected speed information. The virtual navigator, the first drone and the second drone form an isosceles triangle structure.

[0125] The calculation module 220 is used to calculate the expected position information of the two UAVs according to the actual state information and the expected state information and the preset dual-machine cooperative decoupling control rules; the dual-machine cooperative decoupling control rules are used to characterize the rules for calculating the expected position of the two UAVs based on the real-time position of the virtual navigator and the sling length combined with the load attitude angle constraints.

[0126] Output module 230 is used to output control input information for each UAV based on a pre-built extended state observer and nonlinear disturbance rejection controller, taking the desired position information as input, so that the power system controls the dual UAVs to cooperate in lifting the load in a disturbance-resistant manner according to the control input information; the extended state observer is used to characterize the dynamic observer set based on the position error, velocity error and total disturbance error of the first UAV and the second UAV; the nonlinear disturbance rejection controller is used to characterize the nonlinear feedback structure that combines saturation function and power feedback, and takes the state estimation information of each UAV output by the extended state observer as input.

[0127] The acquisition module 210 acquires the first current position of the first UAV from the airborne inertial measurement unit and the global navigation satellite fusion module. and first speed information The second current position of the second drone Second speed information The task planning module obtains the real-time location information of the virtual navigator at the current moment. and expected speed information By introducing a virtual navigator architecture, the originally coupled motion of two UAVs is transformed into an independent tracking task of the same virtual reference point, fundamentally eliminating the problem of cable tension imbalance caused by independent trajectory planning. Under the condition that the synchronization error is less than a preset time threshold, the load swing amplitude can be controlled within a preset angle range, which is significantly better than the large swing of traditional independent trajectory tracking methods.

[0128] Based on the virtual navigator's real-time location information The first current position of the first drone The second current position of the second drone Calculate the desired position vector of the first UAV in a dual-UAV setup. The desired position vector of the second UAV The computing module 220 adopts a dual-machine collaborative decoupling control rule constructed by load attitude angle constraints and symmetry conditions. It does not require the installation of additional sensors on the load. It indirectly derives the load attitude and disturbance effects through geometric relationships, solves the problem of unmeasurable load attitude caused by flexible slings, and reduces hardware complexity and cost.

[0129] The output module 230 employs a combination of an extended state observer and a nonlinear disturbance rejection controller, enabling real-time estimation and active compensation for complex disturbances such as wind disturbances and sudden loading. The response delay is less than a preset time threshold, and even in strong winds, it maintains trajectory tracking error below a preset distance threshold. Traditional proportional-integral-derivative control methods exhibit significantly larger errors under these conditions. Control input information is applied to the power systems of both UAVs. By updating the virtual navigator state, the desired positions of the two UAVs, and disturbance compensation amounts in real time, a complete closed-loop control loop is formed, ensuring the load remains stably suspended during transport. The update cycle of the closed-loop collaborative control is no greater than a predetermined time period. All state variables are obtained through data fusion between the inertial measurement unit and the global navigation satellite system, achieving data synchronization accuracy better than a preset time threshold.

[0130] In one embodiment, the equation of motion for the virtual navigator corresponds to the following formula:

[0131]

[0132] in, Indicates the quality of the load. This represents the acceleration vector of the virtual navigator. Represents the gravitational acceleration vector. 9.81 , Represents the desired acceleration vector. The accuracy range is ±0.5kg, either recorded before hoisting or obtained by weighing sensors before hoisting.

[0133] The geometric constraint formulas for the first and second UAVs relative to the virtual navigator are as follows:

[0134]

[0135]

[0136] in, This represents the real-time position vector of the virtual navigator. This represents the current position vector of the first UAV. This represents the current position vector of the second UAV. This indicates the length of the sling connecting the virtual navigator to the first and second drones.

[0137] In this embodiment, based on the centroid dynamics of the load, the slender triangle structure consisting of a virtual navigator, a first UAV, and a second UAV is called the virtual navigator architecture. This virtual navigator does not correspond to any physical entity; its trajectory is determined by the desired load transport path, which is expressed as follows: , Representing a continuous time variable, the virtual navigator's position coordinates are directly set to... This means that the trajectory of its center of mass completely coincides with the ideal trajectory of the load's center of mass. The two drones are geometrically linked to a virtual navigator, forming a dual-drone cooperative motion framework with the virtual navigator as the reference. The motion equation of the virtual navigator is determined by the load mass, gravitational acceleration, and desired acceleration; its position coordinates directly correspond to the ideal trajectory of the load's center of mass and do not depend on the physical measurements of the actual load. Assuming the sling is an ideal rigid rod, with its upper end fixed to the mounting point below the centers of mass of both drones and the lower end connected to the load's center of mass, the two drones and the virtual navigator form an isosceles triangle structure with a base length of... .

[0138] In one embodiment, the pitch and roll angles of the load relative to the vertical direction in the dual-machine cooperative decoupling control rules are calculated using the following formulas:

[0139]

[0140]

[0141] in, Under normal hoisting conditions, 0, and 0, meaning the load remains vertically suspended;

[0142] The desired position information of the two UAVs in the dual-UAV cooperative decoupling control rule satisfies the following symmetry condition:

[0143]

[0144]

[0145] in, This represents the desired position vector of the first UAV. This represents the desired position vector of the second UAV. This represents the first fixed offset vector of the first UAV relative to the virtual navigator. Let represent the second fixed offset vector of the second UAV relative to the virtual navigator, and satisfy . , , , , Indicates the horizontal distance between the two drones. This indicates the vertical component of the sling.

[0146] In this embodiment, the load attitude angle in the dual-machine cooperative decoupling control rule includes pitch and roll angles, calculated from the relative vectors of the two machines. If the virtual navigator moves along a curved trajectory, the radius of curvature R must satisfy... , A preset distance threshold of 10 meters can be used to avoid excessive load swaying due to excessive centrifugal force. Maximum flight speed. If the speed exceeds a preset threshold, a speed of 8 m / s can be used to ensure the responsiveness of the control system. Based on the position and attitude information of the virtual navigator, combined with the sling length and direction vector between the two UAVs and the load, the desired position command of each UAV in three-dimensional space is derived, enabling the motion of the two UAVs to satisfy the load attitude constraints while achieving motion decoupling. The geometric relationship between the two UAVs and the virtual navigator is established jointly through a constant sling length constraint and a load attitude angle constraint. The sling length is set to a fixed value, and the load attitude angle is calculated from the relative position vectors of the two UAVs, thus ensuring that the motion of the two UAVs satisfies the load balance condition at any given time.

[0147] Secondly, before the lifting operation begins, an online calibration procedure for the sling length is performed. Two drones are hovered at the same height, with the load hanging naturally. The horizontal distance between the two drones is measured. Measure the vertical distance from the bottom of the load to the drone mounting point. Actual length of sling Inversely derived from trigonometric relationships:

[0148]

[0149] The calibration error must be less than the preset length threshold, which can be 0.05 meters; otherwise, recalibration will be triggered.

[0150] Using real-time acquisition , With known ,calculate And then solve and .like or ,

[0151] , If we take 5°, then... and As an auxiliary feedback signal, it is injected into the dual-machine collaborative decoupling control rules for fine-tuning. and The horizontal offset actively suppresses swaying.

[0152] In one embodiment, the state variable corresponding to the X-axis channel of the first UAV in the extended state observer is obtained using the following formula:

[0153]

[0154] 1X 1X

[0155]

[0156] in, This indicates the positional error of the first UAV. This represents the actual x-coordinate of the first UAV. This represents the expected x-coordinate of the first drone. This indicates the speed error of the first drone. 1X This indicates the actual lateral velocity of the first drone. 1X This represents the expected lateral velocity of the first drone. This represents the total disturbance error of the first UAV. This indicates that wind disturbance, sudden loading, and elastic deformation of the suspension cables constitute the total disturbance.

[0157] The dynamic equation corresponding to the first UAV in the extended state observer is adopted by the following formula:

[0158]

[0159] in, This represents state estimation information. This indicates control input information. , , Represents the observer bandwidth parameters, which respectively satisfy... , , , Indicates the observer bandwidth;

[0160]

[0161] in, Let saturation function be defined as:

[0162]

[0163] , Indicates control gain. Indicates the saturation boundary. The coefficient is a power factor.

[0164] In this embodiment, a high-order extended state observer is constructed to assess the total disturbances, including wind disturbances, sudden loading, and elastic deformation of the slings, and to estimate and compensate for the impact of these total disturbances on the UAV's position and velocity in real time. The extended state observer is third-order, and its state variables include position error, velocity error, and the estimated total disturbance. The observer's bandwidth parameter is set to be greater than or equal to a preset frequency threshold to ensure effective tracking of high-frequency disturbances. Based on the output of the extended state observer, a nonlinear feedback structure is used to replace the traditional proportional-integral-derivative controller to generate control inputs for each UAV, achieving high-precision tracking and robust response to the desired trajectory. The control gain is dynamically adjusted according to the UAV's current flight state to suppress overshoot and improve response speed.

[0165] In this embodiment, the acquisition module introduces a virtual navigator to solve the problem of cable tension imbalance caused by independent trajectory planning; the calculation module solves the problem of unmeasurable load pose caused by flexible cables based on the dual-machine collaborative decoupling control rules; and the output module adopts an extended state observer and a nonlinear disturbance rejection controller to realize real-time estimation and active compensation for complex disturbances such as wind disturbance and sudden loading.

[0166] Example 3

[0167] Figure 5 This is a schematic diagram of the structure of an electronic device provided in this embodiment. The electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the dual-UAV anti-interference cooperative hoisting control method of Embodiment 1. Figure 5 The electronic device 90 shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0168] like Figure 5 As shown, the electronic device 90 can be manifested as a general-purpose computing device, such as a server device. The components of the electronic device 90 may include, but are not limited to: at least one processor 91, at least one memory 92, and a bus 93 connecting different system components (including memory 92 and processor 91).

[0169] Bus 93 includes a data bus, an address bus, and a control bus.

[0170] The memory 92 may include volatile memory, such as random access memory (RAM) 921 and / or cache memory 922, and may further include read-only memory (ROM) 923.

[0171] The memory 92 may also include a program / utility 925 having a set (at least one) of program modules 924, including but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of these examples may include an implementation of a network environment.

[0172] The processor 91 executes various functional applications and data processing by running computer programs stored in the memory 92, such as the dual UAV anti-interference cooperative hoisting control method of Embodiment 1 of the present invention.

[0173] Electronic device 90 can also communicate with one or more external devices 94 (e.g., keyboard, pointing device, etc.). This communication can be performed via input / output (I / O) interface 95. Furthermore, the model-generating device 90 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 96. Figure 5 As shown, network adapter 96 communicates with other modules of the model-generated device 90 via bus 93. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in conjunction with the model-generated device 90, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID (disk array) systems, tape drives, and data backup storage systems.

[0174] It should be noted that although several units / modules or sub-units / modules of the electronic device have been mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, according to embodiments of the present invention, the features and functions of two or more units / modules described above can be embodied in one unit / module. Conversely, the features and functions of one unit / module described above can be further divided and embodied by multiple units / modules.

[0175] Example 4

[0176] This embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the dual-UAV anti-interference cooperative hoisting control method of Embodiment 1.

[0177] The readable storage medium may be more specifically adopted, including but not limited to: portable disk, hard disk, random access memory, read-only memory, erasable programmable read-only memory, optical storage device, magnetic storage device, or any suitable combination thereof.

[0178] In a possible implementation, the present invention can also be implemented as a program product comprising program code, which, when the program product is run on a terminal device, causes the terminal device to execute the steps of the control method for dual UAV anti-interference cooperative hoisting of Embodiment 1.

[0179] The program code for executing the present invention can be written in any combination of one or more programming languages. The program code can be executed entirely on the user device, partially on the user device, as a standalone software package, partially on the user device and partially on a remote device, or entirely on a remote device.

[0180] While specific embodiments of the present invention have been described above, those skilled in the art should understand that these are merely illustrative examples, and the scope of protection of the present invention is defined by the appended claims. Those skilled in the art can make various changes or modifications to these embodiments without departing from the principles and essence of the present invention, but all such changes and modifications fall within the scope of protection of the present invention.

Claims

1. A control method for dual-UAV anti-interference cooperative hoisting, characterized in that, The control method includes: The system acquires the actual status information of two drones and the expected status information of a virtual navigator. The actual status information includes the first current position information and the first speed information of the first drone, and the second current position information and the second speed information of the second drone. The expected status information includes real-time position information and expected speed information. The virtual navigator, the first drone, and the second drone form an isosceles triangle structure. The expected position information of the two UAVs is calculated according to the actual state information and the expected state information in accordance with the pre-set dual-machine cooperative decoupling control rules; the dual-machine cooperative decoupling control rules are used to characterize the rules for calculating the expected position of the two UAVs based on the real-time position of the virtual navigator and the sling length combined with the load attitude angle constraints. Using the desired position information as input, and based on a pre-built extended state observer and a nonlinear disturbance rejection controller, control input information for each UAV is output, enabling the power system to control the dual UAVs to collaboratively lift the load in a disturbance-resistant manner according to the control input information. The extended state observer is used to characterize a dynamic observer set based on the position error, velocity error, and total disturbance error of the first and second UAVs. The nonlinear disturbance rejection controller is used to characterize a nonlinear feedback structure that combines a saturation function with power feedback, and takes the state estimation information of each UAV output by the extended state observer as input.

2. The control method for dual-UAV anti-interference cooperative hoisting as described in claim 1, characterized in that, The equation of motion for the virtual navigator corresponds to the following formula: ； in, Indicates the quality of the load. This represents the acceleration vector of the virtual navigator. Represents the gravitational acceleration vector. 9.81 , Represents the desired acceleration vector. The accuracy range is ±0.5kg, either recorded before hoisting or obtained by weighing sensors before hoisting. The geometric constraint formulas for the first UAV and the second UAV relative to the virtual navigator are as follows: ； ； in, This represents the real-time position vector of the virtual navigator. This represents the current position vector of the first UAV. This represents the current position vector of the second UAV. This indicates the length of the sling connecting the virtual navigator to the first UAV and the second UAV.

3. The control method for dual-UAV anti-interference cooperative hoisting as described in claim 2, characterized in that, In the dual-machine cooperative decoupling control rules, the pitch and roll angles of the load relative to the vertical direction are calculated using the following formulas: ； ； in, Under normal hoisting conditions, 0, and 0, meaning the load remains vertically suspended; The desired position information of the two UAVs in the dual-UAV cooperative decoupling control rule satisfies the following symmetry condition: ； ； in, This represents the desired position vector of the first UAV. This represents the desired position vector of the second UAV. This represents the first fixed offset vector of the first UAV relative to the virtual navigator. This represents the second fixed offset vector of the second UAV relative to the virtual navigator, and satisfies... , , , , Indicates the horizontal distance between the two drones. This indicates the vertical component of the sling.

4. The control method for dual-UAV anti-interference cooperative hoisting as described in claim 1, characterized in that, The state variables corresponding to the X-axis channel of the first UAV in the extended state observer are obtained using the following formula: ； 1X 1X ； ； in, This indicates the position error of the first UAV. This represents the actual x-coordinate of the first UAV. This represents the desired x-coordinate of the first drone. This indicates the speed error of the first drone. 1X This indicates the actual lateral velocity of the first drone. 1X This represents the desired lateral velocity of the first drone. This represents the total disturbance error of the first UAV. This indicates that wind disturbance, sudden loading, and elastic deformation of the suspension cables constitute the total disturbance. The dynamic equation corresponding to the first UAV in the extended state observer is adopted by the following formula: ； in, This represents the state estimation information. This indicates the control input information. , , Represents the observer bandwidth parameters, which respectively satisfy... , , , Indicates the observer bandwidth; ； in, Let saturation function be defined as: ； , Indicates control gain. Indicates the saturation boundary. The coefficient is a power factor.

5. A control system for dual unmanned aerial vehicle (UAV) anti-interference collaborative hoisting, characterized in that, The control system includes: The acquisition module is used to acquire the actual status information of the two drones and the expected status information of the virtual navigator; the actual status information includes the first current position information and the first speed information of the first drone, and the second current position information and the second speed information of the second drone; the expected status information includes real-time position information and expected speed information; the virtual navigator, the first drone, and the second drone form an isosceles triangle structure. The calculation module is used to calculate the expected position information of the two UAVs based on the actual state information and the expected state information according to the pre-set dual-machine cooperative decoupling control rules; the dual-machine cooperative decoupling control rules are used to characterize the rules for calculating the expected position of the two UAVs based on the real-time position of the virtual navigator and the sling length combined with the load attitude angle constraints. The output module is used to take the desired position information as input and output control input information for each UAV based on a pre-built extended state observer and a nonlinear disturbance rejection controller, so that the power system controls the dual UAVs to cooperate in lifting the load in a disturbance-resistant manner according to the control input information; the extended state observer is used to characterize a dynamic observer set based on the position error, velocity error and total disturbance error of the first UAV and the second UAV; the nonlinear disturbance rejection controller is used to characterize a nonlinear feedback structure that combines a saturation function and power feedback, and takes the state estimation information of each UAV output by the extended state observer as input.

6. The control system for dual UAV anti-interference cooperative hoisting as described in claim 5, characterized in that, The equation of motion for the virtual navigator corresponds to the following formula: ； in, Indicates the quality of the load. This represents the acceleration vector of the virtual navigator. Represents the gravitational acceleration vector. 9.81 , Represents the desired acceleration vector. The accuracy range is ±0.5kg, either recorded before hoisting or obtained by weighing sensors before hoisting. The geometric constraint formulas for the first UAV and the second UAV relative to the virtual navigator are as follows: ； ； in, This represents the real-time position vector of the virtual navigator. This represents the current position vector of the first UAV. This represents the current position vector of the second UAV. This indicates the length of the sling connecting the virtual navigator to the first UAV and the second UAV.

7. The control system for dual UAV anti-interference cooperative hoisting as described in claim 6, characterized in that, In the dual-machine cooperative decoupling control rules, the pitch and roll angles of the load relative to the vertical direction are calculated using the following formulas: ； ； in, Under normal hoisting conditions, 0, and 0, meaning the load remains vertically suspended; The desired position information of the two UAVs in the dual-UAV cooperative decoupling control rule satisfies the following symmetry condition: ； ； in, This represents the desired position vector of the first UAV. This represents the desired position vector of the second UAV. This represents the first fixed offset vector of the first UAV relative to the virtual navigator. This represents the second fixed offset vector of the second UAV relative to the virtual navigator, and satisfies... , , , , Indicates the horizontal distance between the two drones. This indicates the vertical component of the sling.

8. The control system for dual UAV anti-interference cooperative hoisting as described in claim 7, characterized in that, The state variables corresponding to the X-axis channel of the first UAV in the extended state observer are obtained using the following formula: ； 1X 1X ； ； in, This indicates the position error of the first UAV. This represents the actual x-coordinate of the first UAV. This represents the desired x-coordinate of the first drone. This indicates the speed error of the first drone. 1X This indicates the actual lateral velocity of the first drone. 1X This represents the desired lateral velocity of the first drone. This represents the total disturbance error of the first UAV. This indicates that wind disturbance, sudden loading, and elastic deformation of the suspension cables constitute the total disturbance. The dynamic equation corresponding to the first UAV in the extended state observer is adopted by the following formula: ； in, This represents the state estimation information. This indicates the control input information. , , Represents the observer bandwidth parameters, which respectively satisfy... , , , Indicates the observer bandwidth; ； in, Let saturation function be defined as: ； , Indicates control gain. Indicates the saturation boundary. The coefficient is a power factor.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and for running on the processor, characterized in that, When the processor executes the computer program, it implements the control method for dual UAV anti-interference cooperative hoisting as described in any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the control method for dual UAV anti-interference cooperative hoisting as described in any one of claims 1-7.

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