A method for controlling a group of unmanned aerial vehicles (UAVs) in a wireless communication command

Abstract

The application belongs to the technical field of unmanned aerial vehicle group control, and relates to a wireless communication command unmanned aerial vehicle group control method. The communication state of each unmanned aerial vehicle is determined by sending a test signal, and abnormal unmanned aerial vehicles are excluded from the task of losing connection according to the communication state of each unmanned aerial vehicle. The unmanned aerial vehicles with normal communication state are further assigned roles. A weight parameter calculation method is formulated, the number of master control machines in the cluster and the corresponding number of member machines are determined by the number of tasks and the weight parameter sorting, the allocation principle between the remaining non-master control machines and each master control machine is formulated, the division of the non-master control machines is completed, a set of task matrixes is formed according to the role allocation, the operation mode of each unmanned aerial vehicle group is commanded by generating a task instruction according to the token level, and corresponding permissions and resources are given. The coordination degree of the role supervision mechanism and the task supervision mechanism is improved, and the control strategy can be changed in real time according to the change of the role and the acquisition parameter.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of unmanned aerial vehicle group control, and more particularly relates to a wireless communication command unmanned aerial vehicle group control method. BACKGROUND

[0002] With the rapid development of unmanned aerial vehicle technology, the control problem of unmanned aerial vehicle group has become a difficult problem in the control field of command and control system. Today, unmanned aerial vehicle performance is hot, but most of the unmanned aerial vehicle performances are based on high-precision differential positioning, relying on relatively fixed flight path planning and task planning, and do not have real-time performance and operability in more complex task environment.

[0003] The core of the unmanned aerial vehicle group control problem is how to effectively network, share information, allocate permissions, transfer permissions, make decisions and execute during the execution of the task by the unmanned aerial vehicle group, especially in the task process, such as unit failure, damage, etc. Redundant units can be supplemented in time to maintain the task completion ability of the scheme until the task is completed.

[0004] Task-Role Based Access Control (TRBAC) is an access control model that combines tasks and roles. It integrates the concepts of tasks and roles in two dimensions to better manage and control user access to resources. The multi-granularity dynamic access control model (MG-TRBAC) based on task-role further expands the traditional TRBAC model, and adds a supervision mechanism on the basis of role and task components. Through the organic combination between the two mechanisms, the constraint relevance between roles and tasks is enhanced, and the dynamic nature of role and task authorization is increased.

[0005] The role supervision mechanism and the task supervision mechanism of the MG-TRBAC model isolate the process of users obtaining role permissions from the process of assigning permissions to tasks, which makes the permissions that a certain role can obtain only related to tasks, and the flexibility of the model is insufficient. Based on this model, the present application first applies this idea to the field of unmanned aerial vehicle group control, and in practical application, the permissions obtained by executing the same task under different scenarios can be adjusted. The idea has verified the rationality and effectiveness of the method in the simulation environment. SUMMARY

[0006] OBJECTIVE

[0007] The purpose of the present application is to provide a wireless communication command unmanned aerial vehicle group control method, which obtains executable tasks through the roles assigned to it, and then controls the unmanned aerial vehicle group through the supervision mechanism based on roles and tasks.

[0008] TECHNICAL SCHEME

[0009] The application discloses a UAV group control method for wireless communication command, characterized in that: firstly, the communication states of each UAV are determined by sending test signals, and abnormal UAVs are excluded from the task of losing connection; for the UAVs with normal communication states, roles are further assigned; a weight parameter calculation method is formulated, the master control machine members in the cluster and the corresponding number of member machines are determined by the number of tasks and the weight parameter sorting; the distribution principle between the remaining non-master control machines and each master control machine is formulated, the division of the non-master control machines is completed, and all member machines are assigned corresponding token levels; finally, a set of task matrixes are formed according to the role allocation, the command system can command the operation mode of each UAV group by sending task instructions according to the token levels, and corresponding permissions and resources are assigned.

[0010] Specifically, the following steps are included:

[0011] (1) The command system formulates the task of losing connection of the UAV;

[0012] The task and task constraints of the UAV when losing connection are defined, and the task content is: waiting to be directly controlled by the authorized remaining command system, and returning if the control is unsuccessful; the task constraint is: no other task is being executed, and it is the role of the losing connection machine;

[0013] The task and task constraint are built into the UAV body before the UAV group action;

[0014] (2) Communication test and parameter collection;

[0015] (2.1) The UAV group contains N UAVs, and the numbers are 1~N;

[0016] (2.2) The command system sends test signals to each UAV, if a UAV receives the test signal, it is online, and the command system records the state parameter of the UAV as D i =1, otherwise, it is offline and the state parameter is recorded as D i =0, wherein, i=1, 2, …, N;

[0017] The UAV that successfully receives the test signal sends the test signal to the remaining UAVs again, if a UAV does not successfully receive the test signal of the command system but receives the test signal forwarded by the remaining successful UAVs, the command system also records the state parameter D i =1 of the UAV; finally, the command system counts the number of UAVs that successfully receive the test signal, and records it as b;

[0018] (2.3) Taking the position of the command system as a reference point, the horizontal coordinate p i of the ideal flight of each UAV relative to the reference point is set; i; Then each UAV collects the current horizontal coordinate through the body sensor height

[0019] (3), define the master machine;

[0020] (3.1), the command system sets the number of groups a of the UAV group, and sets the number of UAVs in each group;

[0021] (3.2), in the b UAVs that can successfully receive the test signal, the weight parameter W of each UAV is calculated respectively i :

[0022]

[0023] Where, σ h is the height weight parameter, and σ p is the horizontal position weight parameter;

[0024] (3.3), select the a UAVs with the lowest weight parameter, and sort the weight parameters from low to high, then the first a UAVs after sorting are respectively used as the master machine of each group;

[0025] (4), define the member machine;

[0026] (4.1), the remaining b-a UAVs are recorded as non-master machines, and the distance between each non-master machine and the a master machines is calculated in turn according to the number of each non-master machine from low to high in the UAV group;

[0027]

[0028] Where, d kj represents the distance between the kth non-master machine and the jth master machine, represents the horizontal coordinate and height of the jth master machine relative to the reference point, represents the horizontal coordinate and height of the kth non-master machine relative to the reference point;

[0029] (4.2), select the master machine closest to the kth non-master machine, then judge whether the member machines in the group where the master machine is located are full or not, if not, divide the kth non-master machine to the group, if full, select the second closest master machine to the kth non-master machine, then continue to judge whether the member machines in the group where the master machine is located are full or not, and so on, finally complete the grouping of all non-master machines;

[0030] (5), define the role number and set the corresponding level token;

[0031] The role number of the a master machines is Pj The role number of each member machine controlled by each master machine is P a+j , j = 1, 2, …, a; define the role number of all lost machines as P b+1 ;

[0032] The token levels of the a master machines are set as 1, 2, …, j, …, a in turn, and the token levels corresponding to the member machines controlled by each master machine are a+1, a+2, …, a+j, …, 2a in turn;

[0033] (6) Define a task instruction matrix;

[0034] (6.1) Define a single task T m , m = 1, 2, …, M, M is the number of tasks;

[0035] A single task T m includes constraints, task containing permissions and task content, and the constraints include role constraints and task constraints; wherein the role constraints are: role number; the task constraints are: token level and the relationship between task T m and other tasks;

[0036] (6.2) Construct a task instruction matrix Y according to the number of roles and the number of tasks;

[0037]

[0038] Wherein, the value of y l,m is 1 or 0, when y l,m is 1, it means that the unmanned aerial vehicle with role number P l executes task T m ; when y l,m is 0, it means that the unmanned aerial vehicle with role number P l does not execute task T m ;

[0039] (7) Execute the task;

[0040] The command system broadcasts the task instruction matrix Y, each unmanned aerial vehicle receives and analyzes the task instruction matrix, and then applies to execute the task according to the analysis result, if the unmanned aerial vehicle itself meets the task constraints and role constraints contained in the task, it obtains the task permission and executes the task.

[0041] Further, before step (1) is implemented, each unmanned aerial vehicle member in the command control system should have the ability of autonomous obstacle avoidance, autonomous return and the like to ensure its own safety.

[0042] Further, in step (1), the command system sends test signals to each unmanned aerial vehicle periodically, ensuring that the online and offline states of each member are monitored in real time within a period, avoiding the misallocation of members. The test method can be time-sharing sending or frequency sending.

[0043] Further, in step (3), the weight parameter considers not only the horizontal position advantage and height advantage, but also the communication resource advantage and task load advantage of the introduced unmanned aerial vehicle.

[0044] Further, in step (4), the number of members to be allocated by each master can be allocated evenly or unevenly according to the difficulty of each task, the minimum required number of members, etc.

[0045] Further, after step (7) is completed, when the task of the command system needs to be redistributed, steps (2)-(7) can be performed to redistribute, realize real-time allocation of the unmanned aerial vehicle cluster, and realize higher-level cluster control capability in combination with task planning, route planning, intelligent training, etc.

[0046] Further, if an online member state changes to offline during the execution of steps (3)-(7), step (2) should be performed again.

[0047] Further, after step (4) is completed, the member allocation of each master can be further implemented according to steps (1)-(7) in a single master cluster to further subdivide the task.

[0048] (1) Compared with the traditional MG-TRBAC model, the unmanned aerial vehicle group control method combines task constraint conditions with role constraint conditions, improves the coordination degree of the role supervision mechanism and the task supervision mechanism, and can change the control strategy in real time according to the changes of the role and the collected parameters.

[0049] (2) The token mechanism is introduced to divide the use control level of the unmanned aerial vehicle, so that the allocation of the control right, task authority and resource of the unmanned aerial vehicle is more rigorous, the safety of the unmanned aerial vehicle control is improved, and the unmanned aerial vehicle control can better adapt to the current complex network environment.

[0050] (3) The present application has good expansibility and adaptability, and can be applied to the control of unmanned aerial vehicle groups with small-scale to large-scale unmanned aerial vehicles. The method can continuously subdivide the task granularity, and perform secondary group control again under the condition of one-time unmanned aerial vehicle group control. When the unmanned aerial vehicle group has more computing resources, load resources and communication resources, the task instruction matrix can be more complex, and higher-level cluster control capability can be realized. DETAILED DESCRIPTION

[0051] For the purposes of making the objects, technical solutions and advantages of the present application clearer, the technical solutions in the embodiments of the present application will be described in more detail below with reference to the embodiments of the present application. In the examples, identical or similar labels are used to represent identical or similar elements or elements having identical or similar functions throughout. The described embodiments are part of, but not all of, the embodiments of the present application. The embodiments described below with reference to the drawings are exemplary and are intended to explain the present application, and cannot be understood as a limitation of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of protection of the present application. The embodiments of the present application will be described in detail below.

[0052] Embodiment

[0053] In the present embodiment, the unmanned aerial vehicle group control method of the wireless communication command of the present application comprises the following steps:

[0054] S1, the command system formulates a lost contact task of the unmanned aerial vehicle;

[0055] Define the lost contact task T0 and the task constraint that the unmanned aerial vehicle executes by itself when it is lost contact, and the content of the lost contact task is: waiting to be directly controlled by the authorized remaining command system, and if the control is unsuccessful, returning home; the task constraint is: no other task is being executed, and it is a lost contact machine role;

[0056] The lost contact task and the task constraint are built into the unmanned aerial vehicle body before the unmanned aerial vehicle group action;

[0057] Compared with ordinary tasks, the special feature of the lost contact task is that the permission is given by the unmanned aerial vehicle itself, because the task contains the control right of the action of the unmanned aerial vehicle itself, in addition to the command system, also contains in the unmanned aerial vehicle itself.

[0058] S2, collect parameters;

[0059] S2.1, assume that the unmanned aerial vehicle group contains N unmanned aerial vehicles, numbered 1-10;

[0060] In the present embodiment, it is assumed that the command system commands 10 performance unmanned aerial vehicles to complete the motion trajectory of a large circle and a small circle.

[0061] S2.2, the command system sends a test signal to each unmanned aerial vehicle, if a certain unmanned aerial vehicle receives the test signal, the command system records the state parameter of the unmanned aerial vehicle as D i = 1, otherwise, the state parameter is recorded as D i = 0, wherein i = 1, 2, …, 10;

[0062] The UAVs that successfully receive the test signal send the test signal to the rest of the UAVs again. If a UAV does not successfully receive the test signal from the command system but receives the test signal forwarded by the rest of the successfully receiving UAVs, the command system also records the state parameter D of the UAV i =1; finally, after testing, the command system counts the number of UAVs that successfully receive the test signal as 8, and the numbers of the two failed UAVs are 9 and 10;

[0063] S2.3, taking the location of the command system as a reference point, setting the ideal flight horizontal coordinates p of each UAV relative to the reference point i , the optimal height h i ; then each UAV collects the current horizontal coordinates height in meters; finally, the parameters are obtained, and the weight parameters are calculated as shown in Table 1.

[0064] Table 1. Position of each UAV and its weight parameter

[0065]

[0066] According to the collected position information, the weight parameters of each UAV can be calculated. According to Table 1, the weight of the No. 1 UAV is the smallest, followed by the No. 2 UAV; and the No. 9-10 UAVs do not participate in the selection of the master machine because their state parameters are 0, so the weight parameters are set to 0.

[0067] S3, define the master machine;

[0068] S3.1, according to the motion task of the two circles, the command system sets the number of groups of UAVs to 2, and sets the number of UAVs contained in the two groups to 7 and 3 respectively;

[0069] S3.2, among the 8 UAVs that can successfully receive the test signal, the weight parameters W i of each UAV are calculated respectively.

[0070]

[0071] wherein σ h is the height weight parameter, and σ p is the horizontal position weight parameter;

[0072] Finally, the two UAVs with the smallest weight parameters are distributed as the master machines of the two groups.

[0073] S3.3, sort the UAVs according to the weight parameters from small to large, and take the two UAVs with the lowest weight parameters as the master machines of the first group and the second group respectively according to the ranking. According to the calculation result, the No. 1 UAV is the master machine of the first group, and the No. 2 UAV is the master machine of the second group.

[0074] S4、define the member machine;

[0075] S4.1, the remaining 6 unmanned aerial vehicles are recorded as non-master machines, and the distance between each non-master machine and 2 master machines is calculated in turn according to the number of each non-master machine in the unmanned aerial vehicle group from low to high;

[0076]

[0077] Wherein, d kj represents the distance between the kth non-master machine and the jth master machine, represents the horizontal coordinate and height of the jth master machine relative to the reference point, represents the horizontal coordinate and height of the kth non-master machine relative to the reference point; The specific position data has been measured before, as shown in Table 1.

[0078] S4.2, select the master machine closest to the kth non-master machine, and then judge whether the member machine in the group where the master machine is located is full or not, if not, divide the kth non-master machine into the group, if full, select the second closest master machine to the kth non-master machine, and then continue to judge whether the member machine in the group where the master machine is located is full or not, and so on, finally complete the grouping of all non-master machines; The final calculated distance and grouping are shown in Table 2.

[0079] Table 2. Distance and grouping of member machines and master machines

[0080] UAV number With the distance d between the master and the slave in group 1 k1 ]] With the master controller distance d k2 ]] Packet 3 4.23 1.21 2 4 3.87 2.62 2 5 3.72 2.33 1 6 4.54 4.57 1 7 6.00 5.77 1 8 7.39 6.61 1

[0081] S5, define the role number and set the corresponding level token;

[0082] The role numbers of the two master machines are defined as 1 and 2, the role numbers of the 1st group of member machines, i.e. 5-8 unmanned aerial vehicles, are defined as 3, the role numbers of the 2nd group of member machines, i.e. 3-4 unmanned aerial vehicles, are defined as 4, and the role numbers of all lost machines, i.e. 9-10 unmanned aerial vehicles, are defined as 5;

[0083] The token levels of the two master machines are set as 1 and 2 in turn, the token levels corresponding to the two groups of member machines are set as 3 and 4 in turn, and the token level of the lost machine is set as 5;

[0084] S6, define the task instruction matrix;

[0085] S6.1, define a single task T m , m = 1, 2, 3, 4;

[0086] The unmanned aerial vehicle group can move along the trajectory of two circles through the following tasks:

[0087] The task content of T1 is that: the master control machine of group 1 moves according to the given track (a large circle) from the given 1st site; the role constraint condition of the task is that the role number is 1; the task constraint condition of the task is that the token level is 1; the task contains the authority and resource: the large circular motion track information and the 1st site;

[0088] The task content of T2 is that: the master control machine of group 2 moves according to the given track (a small circle) from the given 2nd site; the role constraint condition of the task is that the role number is 2; the task constraint condition of the task is that the token level is 2; the task contains the authority and resource: the small circular motion track information and the 2nd site;

[0089] The task content of T3 is that: the member machine of group 1 starts to follow the motion track of the master control machine of group 1 from the 1st site, and each unmanned aerial vehicle is spaced half a meter; the role constraint condition of the task is that the role number is 3; the task constraint condition of the task is that the token level is 3; the task contains the authority and resource: the real-time acquisition authority of the motion track of the master control machine of group 1 and other member machines;

[0090] The task content of T4 is that: the member machine of group 2 starts to follow the motion track of the master control machine of group 2 from the 2nd site, and each unmanned aerial vehicle is spaced half a meter; the role constraint condition of the task is that the role number is 4; the task constraint condition of the task is that the token level is 4; the task contains the authority and resource: the real-time acquisition authority of the motion track of the master control machine of group 2 and other member machines;

[0091] S6.2, constructing a task instruction matrix Y according to the number of roles and the number of tasks;

[0092]

[0093] The command system transmits the matrix information, so that the unmanned aerial vehicles obtain the response task instructions. The matrix indicates that the unmanned aerial vehicle with the role number 1 executes the task 1, the unmanned aerial vehicle with the role number 2 executes the task 2, the unmanned aerial vehicle with the role number 3 executes the task 3, and the unmanned aerial vehicle with the role number 4 executes the task 4. Then, each unmanned aerial vehicle only needs to meet the constraint condition of the task that the unmanned aerial vehicle needs to apply, to obtain the authority contained in the task, and to execute the task content. By issuing the instructions to execute the tasks, the unmanned aerial vehicles 1-8 move according to the preset track.

[0094] The unmanned aerial vehicles 9-10 are out of contact, and automatically execute the task T0, i.e. manual control. Since there are only 4 member machines in group 1, 2 member machines are missing, so the unmanned aerial vehicles 9-10 should be controlled to follow the master control machine of group 1 to do the following motion.

[0095] S7, executing the task;

[0096] The command system broadcasts a task instruction matrix Y, each UAV receives and analyzes the task instruction matrix, and then applies for executing the task according to the analysis result, if the UAV itself meets the task constraint condition and the role constraint condition contained in the task, the UAV obtains the task authority and executes the task, and finally obtains an effect diagram.

[0097] In addition, unless otherwise defined, technical terms or scientific terms used in the description of the present application should be understood as the general meaning understood by the general technical personnel in the field to which the present application belongs. The words indicating the direction or position relationship such as "upper", "lower", "left", "right", "center", "vertical", "horizontal", "inner", "outer" and the like used in the description of the present application are only used to indicate the relative direction or position relationship, not to imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation, and the relative position relationship may also change accordingly when the absolute position of the described object changes, therefore it cannot be understood as a limitation on the present application. The "first", "second", "third" and the like used in the description of the present application are only for the purpose of description, to distinguish different components, and cannot be understood as indicating or implying relative importance. The "one", "a" or "the" and the like used in the description of the present application should not be understood as an absolute limitation on the quantity, but should be understood as the existence of at least one. The "includes" or "contains" and the like used in the description of the present application means that the elements or objects appearing before the word are covered by the elements or objects listed after the word and their equivalents, without excluding other elements or objects.

[0098] In addition, it should be further pointed out that, unless otherwise explicitly specified and limited, the "installation", "connection", "connection" and the like used in the description of the present application should be understood in a broad sense, for example, the connection can be fixed connection, or detachable connection, or integral connection; can be mechanical connection, or electrical connection; can be directly connected, or indirectly connected through intermediate medium, or the internal communication of two elements, the skilled in the art can understand the specific meaning of the present application according to the specific situation.

[0099] The above is only a specific embodiment of the present application, and is not used to limit the present application, any skilled in the art can use the above disclosed technical content to make changes or modifications for equivalent embodiments within the spirit and principles of the present application, and apply to other fields, but any simple modification, equivalent change and improvement made on the above embodiments according to the technical essence of the present application should be included in the protection scope of the present application.

Claims

1. A method for controlling a swarm of unmanned aerial vehicles (UAVs) using wireless communication command, characterized in that, First, the communication status of each UAV is determined by sending test signals, and abnormal UAVs are excluded from the communication status and executed separately for disconnection tasks. For UAVs with normal communication status, roles are further assigned. A weight parameter calculation method is formulated, and the number of master control members and corresponding member machines in the cluster are determined by the number of tasks and the weight parameter sorting. The allocation principle between the remaining non-master control machines and each master control machine is formulated, the division of non-master control machines is completed, and all member machines are assigned the corresponding token level. The task instruction matrix is ​​defined, specifically including step (6), defining the task instruction matrix. (6.1) Define a single task T m m = 1, 2, ..., M, where M is the number of tasks; Single task T m This includes constraints, task permissions, and task content. Constraints are further divided into role constraints and task constraints. The role constraint is the role number; the task constraint is the token level and task T. m Relationship with other tasks; (6.2) Construct the task instruction matrix Y based on the number of characters and tasks; Among them, y l,m The value of y is either 1 or 0. l,m When the value is 1, it indicates that the character number is P. l Drones performing missions T m When y l,m When the value is 0, it indicates that the character number is P. l The drone does not perform the mission. m ; Controlling a drone to perform a mission includes step (7) and performing the mission. The command system broadcasts the mission instruction matrix Y. Each UAV receives and parses the mission instruction matrix, and then requests to execute the mission based on the parsing results. If it meets the mission constraints and role constraints contained in the mission, it obtains mission authorization and executes the mission.

2. The method as described in claim 1, characterized in that, It also includes the following steps: Step (1): The command system formulates a mission to address the drone's loss of contact; Define the mission and constraints that the drone will perform when it loses contact. The mission content is: wait for direct control from other authorized command systems. If control fails, return to base. The mission constraints are: no other missions are being performed and the drone is in the role of a lost drone. The mission and mission constraints are built into the drone fuselage before the drone group takes action; Step (2), communication testing and parameter acquisition; (2.1) Suppose that the drone swarm contains N drones, numbered sequentially from 1 to N; (2.2) The command system sends test signals to each UAV. If a UAV receives the test signal, it is online, and the command system records the status parameter of that UAV as D. i =1, otherwise, it is offline and the state parameter is recorded as D. i =0, where i = 1, 2, ..., N; The drone that successfully received the test signal then transmits the test signal to the other drones. If a drone fails to receive the test signal from the command system but receives a test signal forwarded by another successful drone, the command system also records the drone's state parameter D. i =1; Finally, the command system counts the number of drones that successfully received the test signal, denoted as b; (2.3) Using the location of the command system as a reference point, set the ideal horizontal coordinate p of each UAV relative to the reference point. i Optimal height h i Then, each drone uses its onboard sensors to collect its current horizontal coordinates. high Step (3): Define the main control unit; (3.1) The command system sets the number of groups a of the drone swarm and the number of drones in each group; (3.2) Among the b UAVs that can successfully receive the test signal, calculate the weight parameter W for each UAV. i : Where, σ h σ is the height weight parameter. p For horizontal position weight parameters; (3.3) Select the a-th drone with the lowest weight parameter, sort the weight parameters from low to high, and then use the sorted a-th drones as the master controllers of each group. Step (4): Define member machines; (4.1) The remaining ba drones are designated as non-master drones. According to the number of each non-master drone in the drone group from low to high, calculate the distance between each non-master drone and the a master drone. Where, d kj This represents the distance between the k-th non-master machine and the j-th master machine. This represents the horizontal coordinates and altitude of the j-th master control aircraft relative to the reference point. This represents the horizontal coordinates and altitude of the k-th non-master aircraft relative to the reference point. (4.2) Select the master machine that is closest to the kth non-master machine, and then determine whether the member machines in the group where the master machine is located are full. If they are not full, the kth non-master machine is assigned to the group. If they are full, select the master machine that is second closest to the kth non-master machine, and then continue to determine whether the member machines in the group where the master machine is located are full, and so on, until all non-master machines are grouped. Step (5): Define the role number and set the corresponding level token; Define the role number of the main control unit of frame a as P. j Each member machine controlled by the main control unit has the role number P. a+j j = 1, 2, ..., a; define the role number of all lost aircraft as P. b+1 ; The token levels of the master controller (frame A) are set as 1, 2, ..., j, ..., a, and the token levels of the member machines managed by each master controller are a+1, a+2, ..., a+j, ..., 2a.

3. The method as described in claim 2, characterized in that, In step (1), the command system sends periodic test signals to each UAV to ensure that the online and offline status of each member can be monitored in real time within a cycle; the test method is time-division sending and frequency-division sending.

4. The method as described in claim 2, characterized in that, The weighting parameters in step (3) also incorporate the UAV's communication resources and mission payload.

5. The method as described in claim 2, characterized in that, In step (4), the number of members to be allocated to each master controller is allocated either on an average or non-average basis according to the difficulty of each task and the minimum number of members required.

6. The method as described in claim 2, characterized in that, After completing step (7), when the task of the command and control system needs to be reassigned, the task is reassigned according to steps (2) to (7) to realize the real-time allocation of the UAV cluster. Combined with task planning, route planning and intelligent training capabilities, a higher level of cluster control capability is achieved.

7. The method as described in claim 2, characterized in that, If, during the execution of steps (3)-(7), an online member's status changes to offline, then step (2) is restarted.

8. The method as described in claim 2, characterized in that, After the members of each master controller are assigned in step (4), the tasks are further subdivided in steps (1)-(7) within a single master controller cluster.

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