A control method and device for vertical stratification multi-four-rotor unmanned aerial vehicle formation and a medium

Abstract

The application discloses a control method and device for downwash flow perception of vertical layered multi-four-rotor unmanned aerial vehicle formation and a medium, relates to the technical field of unmanned aerial vehicles, and comprises the following steps: determining a nominal formation control input set based on formation state data of each unmanned aerial vehicle, identifying that a lower unmanned aerial vehicle is affected by downwash flow of an upper unmanned aerial vehicle, and calculating downwash flow induced acceleration; constructing a robust height safety constraint and an inter-aircraft distance safety constraint; taking the nominal formation control input set as a reference, solving safe control input of each unmanned aerial vehicle by adopting quadratic programming safety filtering under the constraints of the robust height safety constraint, the inter-aircraft distance safety constraint and a preset control input boundary to obtain an optimal safe control input set; and controlling flight of the vertical layered multi-four-rotor unmanned aerial vehicle formation based on the optimal safe control input set. The application can improve flight safety and formation stability of the vertical layered multi-four-rotor unmanned aerial vehicle formation under downwash flow disturbance.

Description

Technical Field

[0001] This application relates to the field of unmanned aerial vehicle (UAV) technology, and in particular to a control method, device and medium for downwash flow sensing of vertically layered multi-quadrotor UAV formations. Background Technology

[0002] With the development of unmanned aerial vehicle (UAV) technology, multi-UAV collaborative operations have been widely applied in scenarios such as infrastructure inspection, search and rescue, collaborative transportation, environmental monitoring, and emergency response. Compared with a single UAV, multi-UAV formations can expand the mission coverage and improve operational efficiency. However, during the flight of multiple UAVs in a compact formation, each UAV not only needs to maintain a predetermined formation but also needs to avoid collisions between UAVs and meet real-time dynamic constraints and control input constraints. Especially in vertically layered quadcopter UAV formations, the downwash generated by the rotors of the upper-layer UAVs can cause aerodynamic disturbances to the lower-layer UAVs, resulting in a decrease in altitude and an increase in trajectory tracking errors. In severe cases, this may lead to insufficient altitude safety margin or even flight instability. Therefore, how to achieve safe, stable, and real-time altitude control in compact vertically layered multi-UAV formations has become an important issue in multi-UAV collaborative flight control.

[0003] Existing multi-UAV safety control methods typically formulate the safety problem as a geometric collision avoidance problem, that is, by constraining the relative distance between UAVs to ensure that any two UAVs maintain a distance no less than a preset safety distance. This type of method can avoid direct collisions between UAVs to some extent, but for vertically layered quadcopter UAV formations, relying solely on distance constraints between UAVs is insufficient to guarantee altitude safety. When a lower-level UAV is affected by the downwash flow from an upper-level UAV, even if it still meets the geometric distance safety requirements with other UAVs, it may approach or exceed the minimum safe altitude boundary due to vertical disturbances. Therefore, existing safety control methods based solely on geometric collision avoidance are insufficient to effectively address the problem of reduced altitude safety margin under the influence of downwash flows.

[0004] To address the impact of rotor downwash, existing technologies primarily focus on aerodynamic modeling, airflow measurement, and downwash sensing path planning. For example, some methods reduce the impact of downwash on lower-level UAVs by increasing the vertical spacing between upper and lower layers, establishing extended safety zones, or pre-correcting flight paths. While these methods can mitigate downwash risks to some extent, they are typically indirect avoidance or pre-planning approaches, making it difficult to perform closed-loop adjustments to control commands based on real-time flight conditions. When mission scenarios require UAVs to maintain tight formation, or when flight space is limited and increasing interlayer spacing is not a simple matter, these methods reduce formation compactness and mission efficiency, and struggle to provide a clear closed-loop altitude safety guarantee when the downwash model is uncertain.

[0005] Furthermore, methods such as control obstacle functions and quadratic programming safety filtering have been applied to UAV safety control. These methods can make minor modifications to nominal control commands while meeting safety constraints, showing potential for real-time safety control applications. However, most existing multi-UAV formation control methods based on control obstacle functions still primarily focus on the safety of inter-UAV geometric distances, insufficiently considering the reduction in altitude safety margin caused by rotor downwash. Moreover, the actual downwash intensity is affected by factors such as rotor speed, thrust variations, flight attitude, relative positions of upper and lower UAVs, airflow diffusion, and external environmental disturbances, making it difficult for the nominal downwash model to perfectly match real disturbances. If the controller does not compensate for downwash modeling errors, even if the control commands meet the safety conditions based on the estimated model, it may still fail to maintain sufficient altitude safety margin during actual flight. Summary of the Invention

[0006] The purpose of this application is to provide a control method, device and medium for downwash flow perception in vertically layered multi-quadrotor UAV formations, which can improve the flight safety and formation stability of vertically layered multi-quadrotor UAV formations under downwash flow disturbance conditions.

[0007] To achieve the above objectives, this application provides the following solution: Firstly, this application provides a control method for downwash flow sensing in vertically layered multi-quadrotor UAV formations, including: During the current control cycle, acquire the formation status data of each drone in the vertically layered multi-quadrotor drone formation; Based on the formation status data of each UAV, determine the nominal formation control input set; Based on the formation status data of each UAV, the influence of the downwash flow of the upper UAV on the lower-level UAV is identified, and the downwash flow-induced acceleration is calculated. Based on the downwash induced acceleration, the downwash modeling error boundary is determined; Based on the formation status data of each UAV, the downwash induced acceleration, and the downwash modeling error boundary, robust height safety constraints and inter-UAV distance safety constraints are constructed. With the nominal formation control input set as a reference, under the constraints of the robust height safety constraint, the inter-machine distance safety constraint, and the preset control input boundary, the safety control input of each UAV is solved by quadratic programming safety filtering to obtain the optimal safety control input set; Based on the optimal safety control input set, the flight of the vertically layered multi-quadrotor UAV formation is controlled, and when entering the next control cycle, the steps of obtaining the formation status data of each UAV are returned.

[0008] Secondly, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement a control method for downwash flow perception of vertically layered multi-quadrotor UAV formations.

[0009] Thirdly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a control method for downwash flow perception of vertically layered multi-quadrotor UAV formations.

[0010] According to the specific embodiments provided in this application, the following technical effects are disclosed: This application acquires the formation state data of each UAV in a vertically layered multi-quadrotor UAV formation in real time, identifies the influence of the downwash flow of the upper-layer UAVs on the lower-layer UAVs, calculates the downwash flow-induced acceleration, determines the downwash flow modeling error boundary, and then constructs robust height safety constraints and inter-UAV distance safety constraints. The robust height safety constraints, inter-UAV distance safety constraints, and control input boundaries are uniformly incorporated into the quadratic programming safety filtering solution process, thereby achieving unified real-time control of height safety, inter-UAV distance safety, and input boundaries under downwash flow disturbance and model uncertainty conditions while maintaining nominal formation tracking performance as much as possible. Through the above processing, this application improves the flight safety and formation stability of vertically layered multi-quadrotor UAV formations under downwash flow disturbance conditions. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 This is an application environment diagram of a control method for downwash flow sensing in a vertically layered multi-quadrotor UAV formation according to an embodiment of this application.

[0013] Figure 2 This is a flowchart illustrating a control method for downwash flow sensing in a vertically layered multi-quadrotor UAV formation according to an embodiment of this application.

[0014] Figure 3 This is a flowchart illustrating the control method for underwash flow sensing in another embodiment of this application.

[0015] Figure 4 This is a schematic diagram illustrating the interaction between the downwash flow of a vertically layered UAV formation.

[0016] Figure 5This is a schematic diagram of the internal constraint relationships of a quadratic programming security filter.

[0017] Figure 6 This is a flowchart illustrating a control system for downwash flow perception in a vertically layered multi-quadrotor UAV formation according to one embodiment of this application.

[0018] Figure 7 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0019] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0020] To address the issues of reduced height safety margin due to downwash disturbances, insufficient safety constraints under model uncertainty, and the inability to guarantee height safety solely through geometric collision avoidance, this application introduces the estimated downwash-induced acceleration and its modeling error boundary into robust height safety constraints. Furthermore, it integrates height safety constraints, inter-machine distance safety constraints, and control input boundaries into a quadratic programming safety filter for solution, thereby obtaining a safe control input that meets safety requirements and is as close as possible to the nominal formation control command.

[0021] This application is applicable to downwash flow perception-based robust altitude safety control for vertically layered multi-quadrotor UAV formations. Compared with control methods that only consider inter-aircraft geometric collision avoidance, it can simultaneously handle altitude safety, inter-aircraft distance safety, and control input boundaries when downwash flow disturbances and model uncertainties exist, thereby improving the safety and stability of vertically layered formation flight.

[0022] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0023] The control method for downwash flow sensing in vertically layered multi-quadrotor UAV formations provided in this application can be applied to, for example... Figure 1The application environment shown is illustrated. Terminal 101 communicates with server 102 via a network. A data storage system can store the data that server 102 needs to process. The data storage system can be set up independently, integrated into server 102, or placed in the cloud or on another server. Terminal 101 can send the formation status data of each UAV in the vertically layered multi-quadrotor UAV formation during the current control cycle to server 102. Upon receiving the data, server 102 determines the nominal formation control input set based on the formation status data of each UAV; it identifies the influence of the downwash flow from the upper-layer UAVs on the lower-layer UAVs based on the formation status data of each UAV, and calculates the downwash flow-induced acceleration; it determines the downwash flow modeling error boundary based on the downwash flow-induced acceleration; and it constructs robust height safety constraints and inter-UAV distance safety constraints based on the formation status data of each UAV, the downwash flow-induced acceleration, and the downwash flow modeling error boundary; using the nominal formation control input set as a reference, and under the constraints of the robust height safety constraints, the inter-UAV distance safety constraints, and the preset control input boundary, it uses quadratic programming safety filtering to solve for the safety control input of each UAV, obtaining the optimal safety control input set. Server 102 can then feed back the obtained optimal safety control input set to terminal 101. Furthermore, in some embodiments, the control method for downwash flow perception of vertically layered multi-quadrotor UAV formations can also be implemented separately by server 102 or terminal 101.

[0024] The terminal 101 can be, but is not limited to, various desktop computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, and smart in-vehicle devices. Portable wearable devices can include smartwatches, smart bracelets, and head-mounted devices. The server 102 can be implemented using a standalone server or a server cluster composed of multiple servers, or it can be a cloud server.

[0025] In one exemplary embodiment, such as Figure 2 and Figure 3 As shown, a control method for downwash flow perception in vertically layered multi-quadrotor UAV formations is provided. This method is executed by computer equipment, specifically by a terminal or server alone, or by both a terminal and a server. In this embodiment, the method is applied to... Figure 1 Taking server 102 as an example, the explanation includes the following steps 201 to 207.

[0026] Before proceeding with steps 201 through 207, a problem description is first provided.

[0027] Description of Vertically Hierarchical Multi-UAV Formation: Consider a vertically hierarchical formation consisting of N quadrotor UAVs, with the UAV index set denoted as N_set = {1, 2, ..., N}. For the i-th UAV, determine its position, velocity, attitude (also the attitude rotation matrix), and thrust in the inertial coordinate system. The multi-UAV formation safety control device collects these state variables in each control cycle and uses them as the basis for subsequent downwash flow estimation, safety constraint construction, and safety control input solution.

[0028] At the acceleration input level, the translational dynamics of the i-th UAV are expressed as: .

[0029] .

[0030] Description of the downwash effect scenario: In a vertically layered formation, when the i-th lower-layer UAV is located below the j-th upper-layer UAV, and the horizontal and vertical distances between them satisfy the downwash influence conditions, the i-th lower-layer UAV may enter the effective downwash region of the j-th upper-layer UAV. At this time, the downwash generated by the rotors of the upper-layer UAV will produce additional aerodynamic disturbances on the lower-layer UAV, leading to problems such as altitude loss, increased trajectory tracking errors, or insufficient altitude safety margin. Therefore, it is necessary to identify the downwash interaction relationship, estimate the downwash-induced acceleration, and reflect this disturbance and its modeling error in the safety control constraints within each control cycle, based on the UAV's real-time position, velocity, attitude, and thrust information.

[0031] Control objective description: The control objective is to calculate the safe control input for each UAV under the presence of downwash disturbances and uncertainties in the downwash model, so that it is as close as possible to the nominal formation control input while meeting the following requirements: .

[0032] Step 201: In the current control cycle, acquire the formation state data X(k) of each UAV in the vertically layered multi-quadrotor UAV formation; wherein, the formation state package of the UAV is read through the multi-UAV formation safety control device, including position, speed, thrust, mass, attitude and relative spatial relationship.

[0033] Step 202: Based on the formation status data of each UAV, determine the nominal formation control input set. Specifically, a multi-UAV formation safety control device is used to calculate the nominal formation control input of the UAVs based on the current position error and velocity error. The formula for calculating the nominal formation control input set is: .

[0034] in, For the nominal formation control input set, For position gain, Let i be the reference position of the i-th lower-level UAV. Let i be the position of the i-th lower-level drone. For speed gain, Let the reference velocity be that of the i-th lower-level UAV. Let be the speed of the i-th lower-level drone.

[0035] Step 203: Based on the formation status data of each UAV, identify the influence of the downwash flow of the upper UAV on the lower-level UAV, and calculate the downwash flow-induced acceleration.

[0036] In an application example, such as Figure 4 As shown, step 203 includes the following steps (31)-(36).

[0037] (31) Based on the relative spatial relationship of the UAVs, the UAVs are marked as lower-level UAVs or upper-level UAVs.

[0038] (32) For example Figure 3 As shown, based on the relative spatial relationships and positions of UAVs, a multi-UAV formation safety control device is used to calculate the vertical and horizontal distances between any lower-level UAV and its corresponding upper-level UAV. The UAV at the topmost level can also be considered a lower-level UAV, and its corresponding upper-level UAV can be considered as empty space.

[0039] The vertical distance between any i-th lower-level UAV and the j-th upper-level UAV above it and horizontal distance The calculation formula is as follows: .

[0040] .

[0041] in, Let be the position of the i-th lower-level UAV in the inertial coordinate system. Let be the position of the j-th upper-level UAV in the inertial coordinate system; I is the three-dimensional identity matrix.

[0042] (33) When the vertical spacing and the horizontal distance When the downwash flow influence condition is met, it is determined that the lower-level UAV is affected by the downwash flow of the corresponding upper-level UAV, and a corresponding downwash flow activation variable is set for the lower-level UAV, the value of which can be set to 1.

[0043] The influencing condition of the downwash flow is: horizontal distance. Radius of influence of the downwash flow less than or equal to And, vertical distance Greater than zero and less than or equal to the effective height of the downwash flow The downwash activation variable is used to indicate whether the j-th upper-layer UAV has a valid downwash effect on the i-th lower-layer UAV.

[0044] (34) When the vertical spacing and the horizontal distance do not meet the downwash flow influence conditions, it is determined that the lower-level UAV is not affected by the downwash flow of the corresponding upper-level UAV, and a corresponding downwash flow activation variable is set for the lower-level UAV, the value of which can be set to 0.

[0045] All drones with a downwash activation variable of 1 can form the set of upper-layer influencing drones corresponding to the i-th lower-layer drone. .

[0046] (35) Calculate the downwash-induced acceleration amplitude of the upper-layer UAV on the lower-layer UAV based on the UAV's thrust, mass, and vertical spacing; the formula for calculating the downwash-induced acceleration amplitude is: .

[0047] in, Let be the amplitude of the downwash-induced acceleration generated by the j-th upper-layer UAV on the i-th lower-layer UAV. The drag coefficient, For effective flow receiving area, For the thrust of the j-th upper-level UAV, For the mass of the i-th UAV, Let be the vertical distance between the j-th UAV and the i-th UAV. This is a regularization constant used to avoid... If the denominator is too small, the fraction will be too small.

[0048] (36) Calculate the downwash-induced acceleration based on the UAV's attitude, the downwash activation variable, and the amplitude of the downwash-induced acceleration. The formula for calculating the downwash-induced acceleration is: .

[0049] in, For the downwash induced acceleration of the i-th lower-layer UAV, Let be the control input to be solved for the i-th lower-level UAV. Activation variable for the downwash flow, For the attitude of the j-th upper-layer UAV, Let be the vertical unit vector in the inertial coordinate system. . This indicates the direction of the downwash flow after considering the attitude of the upper-level UAV; the negative sign indicates that the direction of the downwash flow is opposite to the direction of the thrust axis of the upper-level UAV.

[0050] Step 204: Determine the downwash flow modeling error boundary based on the downwash flow induced acceleration.

[0051] Due to the actual downwash flow acceleration With the downwash induced acceleration There are modeling errors, so the actual downwash flow acceleration is expressed as: .

[0052] The vertical modeling error boundary is determined using multi-UAV formation safety control equipment to ensure that it meets the following requirements: .

[0053] The functional formula for the error boundary of the downwash flow modeling is expressed as: .

[0054] in, To model the error boundary for the downwash flow, As a preset basic error margin, The uncertainty coefficient of the downwash flow model is given. The vertical unit vector is , For the downwash induced acceleration of the i-th lower-layer UAV, To account for the modeling error of the downwash flow, This represents the vertical component of the downwash flow modeling error. This represents the absolute value of the vertical component of the downwash flow modeling error.

[0055] also, It can also be a preset calibration value.

[0056] Step 205: Based on the formation state data of each UAV, the downwash-induced acceleration, and the downwash-modeling error boundary, construct robust height safety constraints and inter-UAV distance safety constraints. The robust height safety constraints are as follows: .

[0057] .

[0058] .

[0059] in, Let be the value of the robust height ECBF constraint for the i-th lower-level UAV. Let be a vertical unit vector, and T be the transpose of the matrix. Let be the control input to be solved for the i-th lower-level UAV. For the downwash induced acceleration of the i-th lower-layer UAV, To model the error boundary for the downwash flow, , For high ECBF gain, For the height safety margin of the i-th lower-level UAV, for The first derivative of represents the rate of change of the high safety margin; Let i be the position of the i-th lower-level drone. This is the preset minimum safe altitude for the i-th lower-level drone. Let be the speed of the i-th lower-level drone. This represents the current altitude of the i-th lower-level drone.

[0060] The above constraints can also be rearranged into linear inequalities: .

[0061] when When >=0, it indicates that the i-th lower-level UAV meets the height safety requirements; when When <0, it means that the i-th lower-level drone is below the minimum safe altitude.

[0062] The inter-machine distance safety constraint is: .

[0063] .

[0064] .

[0065] For each pair of constrained drones, the multi-drone swarm safety control system calculates the relative position and relative velocity: ; .

[0066] in, Let be the value of the ECBF constraint for the distance between the i-th lower-level UAV and the j-th upper-level UAV. Let be the control input to be solved for the i-th lower-level UAV. Let be the control input to be solved for the j-th lower-level UAV. Let be the relative velocity between the i-th lower-level UAV and the j-th upper-level UAV. Let be the relative position between the i-th lower-level UAV and the j-th upper-level UAV. For the downwash induced acceleration of the i-th lower-layer UAV, For the downwash induced acceleration of the j-th lower-level UAV, , For distance ECBF gain, The distance safety margin between the i-th lower-level UAV and the j-th upper-level UAV. for The first derivative, To preset the minimum machine-to-machine distance, Let i be the position of the i-th lower-level drone. Let j be the position of the upper-layer UAV. Let be the speed of the i-th lower-level drone. Let be the speed of the j-th upper-layer drone. This represents the relative velocity term. This represents the effect of control inputs on the relative motion between machines. This represents the effect of the difference in downwash-induced acceleration on the change in the distance between machines.

[0067] Step 206: Using the nominal formation control input set as a reference, and under the constraints of the robust height safety constraint, the inter-machine distance safety constraint, and the preset control input boundary, a quadratic programming safety filter is used to solve for the safety control input of each UAV, obtaining the optimal safety control input set. The preset control input boundary includes a lower control input bound and an upper control input bound.

[0068] In solving the safety control input of each UAV using quadratic programming safety filtering, the safety control equipment for multi-UAV formation aims to make the safety control input as close as possible to the nominal control input. A quadratic programming safety filtering problem is constructed, and the objective function and constraints for the quadratic programming safety filtering are established. The objective function for the quadratic programming safety filtering is: .

[0069] The constraints are as follows: ; ; ; , .

[0070] Among them, u For the optimal set of safety control inputs, Let be the control input to be solved for the i-th lower-level UAV. For the nominal formation control input set, Let be the value of the robust height ECBF constraint for the i-th lower-level UAV. Let be the value of the ECBF constraint for the distance between the i-th lower-level UAV and the j-th upper-level UAV. To control the lower bound of the input, To control the upper limit of the input. The set of constrained UAV pairs, representing UAV pairs that require inter-UAV distance safety constraints, can be represented as: ={(i,j)|i,j∈N,i≠j,The distance safety constraint between the i-th lower-level UAV and the j-th upper-level UAV needs to be applied}.

[0071] like Figure 5 As shown, the relationship between nominal control input, robust height safety constraint, distance safety constraint, input boundary constraint, and safety control input is illustrated.

[0072] Step 207: Based on the optimal safety control input set, control the flight of the vertically layered multi-quadrotor UAV formation, and when entering the next control cycle, return to the step of obtaining the formation status data of each UAV.

[0073] After obtaining the optimal set of safety control inputs, the multi-UAV formation safety control device sets the final safety control input for the i-th lower-level UAV as follows: .in, This represents the final safety control input executed by the i-th lower-level UAV; This represents the optimal safety control input for the i-th lower-level UAV obtained by solving a quadratic programming problem.

[0074] When height safety constraints and inter-machine distance safety constraints are not activated and Maintaining consistency or substantial consistency; when current washing flow disturbances lead to high safety risks or inter-machine distance safety risks, the secondary planning safety filter... Perform a minimum magnitude correction to obtain the result that satisfies the constraints. .

[0075] Multi-drone swarm safety control equipment will Output to the UAV flight control system. The UAV flight control system, according to... The system generates corresponding attitude, thrust, or motor control commands to enable the UAV to perform safe flight control. Subsequently, the multi-UAV formation safety control equipment enters the next control cycle and repeats the above steps to achieve closed-loop real-time control.

[0076] In summary, this application includes the following steps: system parameter and real-time status data acquisition, nominal formation control input calculation, downwash flow interaction identification, downwash flow-induced acceleration estimation, downwash flow modeling error boundary determination, robust altitude safety constraint construction, inter-drone distance safety constraint construction, quadratic programming safety filter construction and solution, and safety control command output and closed-loop update. This is executed by the UAV onboard controller, ground station control equipment, or formation centralized control computing equipment. It is used to identify the downwash flow influence on lower-layer UAVs during compact, layered flight of multiple UAVs, based on the position, velocity, attitude, thrust, and relative spatial relationships of each UAV, and to estimate the downwash flow-induced acceleration, thereby achieving robust altitude safety control based on downwash flow perception for vertically layered multi-quadrotor UAV formations.

[0077] Based on the same inventive concept, this application also provides a system for implementing the above-described problem. The solution provided by this system is similar to the solution described in the above-described method; therefore, specific limitations in one or more system embodiments provided below can be found in the limitations of the method described above, and will not be repeated here.

[0078] In one exemplary embodiment, such as Figure 6 As shown, a control system for downwash flow perception in vertically layered multi-quadrotor UAV formations is provided, including a state acquisition module, a nominal control calculation module, a downwash flow effect identification module, a downwash flow estimation module, an error boundary determination module, a robust altitude safety constraint construction module, a distance safety constraint construction module, a quadratic programming safety filtering module, and a control command output module.

[0079] The status acquisition module is used to acquire the position, velocity, attitude, and thrust information of each UAV; the nominal control calculation module is used to calculate the nominal formation control input based on the reference position, reference velocity, current position, and current velocity; the downwash effect identification module is used to determine whether the lower-level UAV is within the effective downwash influence area of ​​the upper-level UAV based on the horizontal distance, vertical spacing, and downwash influence range between the upper and lower-level UAVs; the downwash estimation module is used to calculate the downwash-induced acceleration based on the thrust, attitude, relative position, and downwash model parameters of the upper-level UAVs; the error boundary determination module is used to determine the downwash modeling error boundary; the robust altitude safety constraint construction module is used to construct robust altitude ECBF constraints based on the altitude safety function, estimated downwash-induced acceleration, and modeling error boundary; the distance safety constraint construction module is used to construct distance ECBF constraints based on the relative position, relative velocity, and estimated downwash difference of the UAVs; the quadratic programming safety filtering module is used to solve for the safety control input under the robust altitude safety constraint, distance safety constraint, and input boundary constraint; and the control command output module is used to send the solved safety control input to the UAV flight control system.

[0080] To improve the flight safety and formation stability of vertically layered multi-quadrotor UAV formations under downwash disturbance conditions, this application incorporates the estimated downwash-induced acceleration and its modeling error boundary into the altitude safety constraint. The altitude safety constraint, inter-aircraft distance safety constraint, and control input boundary are then uniformly integrated into a quadratic programming safety filter for solution, thereby generating a safe control input that meets safety requirements and approximates the nominal formation control command as closely as possible. Simulation experiments verify the effectiveness of the proposed method. Results show that: (1) This application can significantly improve the height safety margin of vertically layered UAV formations under downwash disturbance, and prevent lower-layer UAVs from exceeding the minimum safe height boundary.

[0081] (2) This application can ensure high safety while maintaining safe distance between machines, avoiding the problem of insufficient high safety caused by relying solely on geometric collision avoidance.

[0082] (3) This application can reduce formation tracking error, and the safety filter only corrects the nominal control command when the safety constraint is activated, so it will not have too much impact on normal formation tracking.

[0083] (4) The quadratic programming safety filtering process in this application has good real-time performance and can meet the online safety control requirements of multi-UAV formations. The above technical effects mainly come from the following technical points: downwash-induced acceleration estimation, modeling error boundary compensation, robust height safety constraint construction, and unified solution of height safety, distance safety and input boundary.

[0084] In one exemplary embodiment, a computer device is provided, which may be a server or a terminal, and its internal structure diagram may be as follows. Figure 7 As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and databases. The internal memory provides the environment for the operating system and computer programs stored in the non-volatile storage media. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network connection. When the computer program is executed by the processor, it implements a downflow sensing control method for vertically layered multi-quadrotor UAV formations.

[0085] Those skilled in the art will understand that Figure 7The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0086] In one exemplary embodiment, a computer device is also provided, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps in the above-described method embodiments.

[0087] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0088] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0089] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0090] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0091] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0092] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0093] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A control method for downwash flow sensing in vertically layered multi-quadrotor UAV formations, characterized in that, The method includes: During the current control cycle, acquire the formation status data of each drone in the vertically layered multi-quadrotor drone formation; Based on the formation status data of each UAV, determine the nominal formation control input set; Based on the formation status data of each UAV, the influence of the downwash flow of the upper UAV on the lower-level UAV is identified, and the downwash flow-induced acceleration is calculated. Based on the downwash induced acceleration, the downwash modeling error boundary is determined; Based on the formation status data of each UAV, the downwash induced acceleration, and the downwash modeling error boundary, robust height safety constraints and inter-UAV distance safety constraints are constructed. With the nominal formation control input set as a reference, under the constraints of the robust height safety constraint, the inter-machine distance safety constraint, and the preset control input boundary, the safety control input of each UAV is solved by quadratic programming safety filtering to obtain the optimal safety control input set; Based on the optimal safety control input set, the flight of the vertically layered multi-quadrotor UAV formation is controlled, and when entering the next control cycle, the steps of obtaining the formation status data of each UAV are returned.

2. The control method for downwash flow sensing in vertically layered multi-quadrotor UAV formations according to claim 1, characterized in that, The formation status of drones includes position, thrust, mass, attitude, and relative spatial relationships; Based on the formation state data of each UAV, the influence of the downwash flow from the upper-layer UAVs on the lower-layer UAVs is identified, and the downwash flow-induced acceleration is calculated, including: Based on the relative spatial relationship of the drones, the drones are labeled as lower-level drones or upper-level drones; Based on the relative spatial relationship and position of the UAVs, calculate the vertical distance and horizontal distance between any lower-level UAV and the corresponding upper-level UAV. When the vertical spacing and the horizontal distance meet the downwash flow influence conditions, it is determined that the lower-level UAV is affected by the downwash flow of the corresponding upper-level UAV, and a corresponding downwash flow activation variable is set for the lower-level UAV. When the vertical spacing and the horizontal distance do not meet the downwash flow influence conditions, it is determined that the lower-level UAV is not affected by the downwash flow of the corresponding upper-level UAV, and a corresponding downwash flow activation variable is set for the lower-level UAV. Based on the thrust, mass, and vertical spacing of the UAV, calculate the amplitude of the downwash-induced acceleration generated by the upper UAV on the lower UAV. The downwash-induced acceleration is calculated based on the UAV's attitude, the downwash activation variable, and the downwash-induced acceleration amplitude.

3. The control method for downwash flow sensing in vertically layered multi-quadrotor UAV formations according to claim 2, characterized in that, The formula for calculating the amplitude of the downwash-induced acceleration is as follows: ； in, Let be the amplitude of the downwash-induced acceleration generated by the j-th upper-layer UAV on the i-th lower-layer UAV. The drag coefficient, For effective flow receiving area, For the thrust of the j-th upper-level UAV, For the mass of the i-th UAV, Let be the vertical distance between the j-th UAV and the i-th UAV. Here is the regularization constant; The formula for calculating the downwash-induced acceleration is: ； in, For the downwash induced acceleration of the i-th lower-layer UAV, Let be the control input to be solved for the i-th lower-level UAV. Activation variable for the downwash flow, For the attitude of the j-th upper-layer UAV, It is a unit vector in the vertical direction.

4. The control method for downwash flow sensing in vertically layered multi-quadrotor UAV formations according to claim 1, characterized in that, The functional formula for the error boundary of the downwash flow modeling is expressed as: ； in, To model the error boundary for the downwash flow, As a preset basic error margin, The uncertainty coefficient of the downwash flow model is given. It is a unit vector in the vertical direction. Let be the downwash-induced acceleration of the i-th lower-layer UAV.

5. The control method for downwash flow sensing in vertically layered multi-quadrotor UAV formations according to claim 1, characterized in that, The formation status of drones includes their position and speed; The robust height safety constraint is: ； ； ； in, Let be the value of the robust height ECBF constraint for the i-th lower-level UAV. Let be a vertical unit vector, and T be the transpose of the matrix. Let be the control input to be solved for the i-th lower-level UAV. For the downwash induced acceleration of the i-th lower-layer UAV, To model the error boundary for the downwash flow, , For high ECBF gain, For the height safety margin of the i-th lower-level UAV, for The first derivative, Let i be the position of the i-th lower-level drone. This is the preset minimum safe altitude for the i-th lower-level drone. Let be the speed of the i-th lower-level drone.

6. The control method for downwash flow sensing in vertically layered multi-quadrotor UAV formations according to claim 1, characterized in that, The formation status of drones includes their position and speed; The inter-machine distance safety constraint is: ； ； ； ； ； in, Let be the value of the ECBF constraint for the distance between the i-th lower-level UAV and the j-th upper-level UAV. Let be the control input to be solved for the i-th lower-level UAV. Let be the control input to be solved for the j-th lower-level UAV. For relative velocity, Relative position For the downwash induced acceleration of the i-th lower-layer UAV, For the downwash induced acceleration of the j-th lower-level UAV, , For distance ECBF gain, The distance safety margin between the i-th lower-level UAV and the j-th upper-level UAV. for The first derivative, To preset the minimum machine-to-machine distance, Let i be the position of the i-th lower-level drone. Let j be the position of the upper-layer UAV. Let be the speed of the i-th lower-level drone. Let be the speed of the j-th upper-layer drone.

7. The control method for downwash flow sensing in vertically layered multi-quadrotor UAV formations according to claim 1, characterized in that, The preset control input boundary includes a lower control input boundary and an upper control input boundary; In the process of solving the safety control input of each UAV using quadratic programming safety filtering, the objective function and constraints of quadratic programming safety filtering are constructed. The objective function of the quadratic programming security filtering is: ； The constraints are as follows: ； ； ； Among them, u For the optimal set of safety control inputs, Let be the control input to be solved for the i-th lower-level UAV. For the nominal formation control input set, Let be the value of the robust height ECBF constraint for the i-th lower-level UAV. Let be the value of the ECBF constraint for the distance between the i-th lower-level UAV and the j-th upper-level UAV. To control the lower bound of the input, To control the upper limit of the input.

8. The control method for downwash flow sensing in vertically layered multi-quadrotor UAV formations according to claim 1, wherein the formula for calculating the nominal formation control input set is: ； in, For the nominal formation control input set, For position gain, Let i be the reference position of the i-th lower-level UAV. Let i be the position of the i-th lower-level drone. For speed gain, Let the reference velocity be that of the i-th lower-level UAV. Let be the speed of the i-th lower-level drone.

9. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the control method for downwash flow sensing of vertically layered multi-quadrotor UAV formations as described in any one of claims 1-8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the control method for downwash flow perception of vertically layered multi-quadrotor UAV formations as described in any one of claims 1-8.

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