Unmanned aerial vehicle group control method for wireless communication command

Abstract

The invention belongs to the technical field of unmanned aerial vehicle group control, and relates to an unmanned aerial vehicle group control method for wireless communication command. The communication state of each unmanned aerial vehicle is determined by sending a test signal, and abnormal unmanned aerial vehicles are excluded according to the communication state of each unmanned aerial vehicle to independently execute a communication loss task; further performing role allocation on the unmanned aerial vehicle in a normal communication state; formulating a weight parameter calculation method, and determining the number of main control computer members and the number of corresponding member computers in the cluster according to the number of tasks and the sorting of weight parameters; and formulating a distribution principle between other non-main control computers and each main control computer, completing division of the non-main control computers, forming a set of task matrix according to a role distribution condition, commanding an operation mode of each unmanned aerial vehicle group by generating a task instruction according to a token level, and endowing corresponding authority and resources. The matching degree of a role supervision mechanism and a task supervision mechanism is improved, and a control strategy can be changed in real time according to changes of roles and collection parameters.

Description

Technical Field

[0001] The present invention belongs to the technical field of drone swarm control, and more specifically, relates to a drone swarm control method commanded by wireless communication. Background Art

[0002] With the rapid development of drone technology, the control of drone swarms has become a difficult problem in the field of command and control system control. Today, drone performances are very popular, but most drone performances are based on high-precision differential positioning, relying on relatively fixed route planning and mission planning, and are not real-time and operable in more complex mission environments.

[0003] The core of the drone swarm control problem lies in how to effectively network, share information, allocate authority, transfer authority, and make decisions during the mission execution of the drone group. In particular, if unit failure or damage occurs during the mission, redundant units can be supplemented in time to continuously maintain the mission completion capability of the plan until the mission is completed.

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

[0005] The role supervision mechanism and task supervision mechanism of the MG-TRBAC model isolate the process of users obtaining role permissions from the process of granting permissions to tasks, which makes the permissions that a role can obtain only related to the task, and the model is not flexible enough. Based on this model, the present invention applies this idea to the field of drone swarm control for the first time, and in practical applications, it can make adjustments according to the permissions obtained by executing the same task in different scenarios. This idea has been verified in a simulation environment. The rationality and effectiveness of the method. Summary of the invention

[0006] Purpose of the Invention

[0007] The purpose of the present invention is to provide a method for controlling a swarm of unmanned aerial vehicles commanded by wireless communication, which obtains executable tasks by assigning them roles, and then controls the swarm of unmanned aerial vehicles through a supervision mechanism based on the roles and tasks.

[0008] Technical Solution

[0009] The present invention discloses a control method for a group of unmanned aerial vehicles commanded by wireless communication, which is characterized in that the communication status of each unmanned aerial vehicle is first determined by sending a test signal, and abnormal drones are excluded according to the communication status of each unmanned aerial vehicle to perform the lost connection task alone; roles are further assigned to the drones with normal communication status; a weight parameter calculation method is formulated, and the number of master control machine members and corresponding member machines in the cluster is determined by sorting the number of tasks and weight parameters; 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, and corresponding token levels are assigned to all member machines; finally, a set of task matrices is formed according to the role allocation situation, and according to the token level, the command system can command the operation mode of each group of unmanned aerial vehicles by issuing task instructions, and assign corresponding permissions and resources.

[0010] Specifically, the following steps are included:

[0011] (1) The command system formulates the mission of the lost drone;

[0012] Define the tasks and task constraints that the drone will perform when it loses connection. The task content is: wait for the authorized command system to directly control it. If the control fails, return home. The task constraints are: no other tasks are being performed and the drone is a lost role.

[0013] The mission and mission constraints are built into the drone body before the drone group acts;

[0014] (2) Communication test and acquisition parameters;

[0015] (2.1) Assume that the drone swarm contains N drones, numbered 1 to N;

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

[0017] The drone that successfully receives the test signal sends the test signal to the other drones again. If a drone fails to receive the test signal from the command system but receives the test signal forwarded by the other successful drones, the command system also records the state parameter D of the drone. i =1; finally, the command system counts the number of drones that successfully receive the test signal, recorded as b;

[0018] (2.3) Taking the location of the command system as the reference point, set the horizontal coordinates p of the ideal flight of each UAV relative to the reference point. i , optimal height h i; Then each drone collects the current horizontal coordinates through the fuselage sensor high

[0019] (3) Define the master control machine;

[0020] (3.1) The command system sets the number of groups a of the drone group and the number of drones in each group;

[0021] (3.2) Among the b drones that can successfully receive the test signal, calculate the weight parameter W of each drone i :

[0022]

[0023] Among them, σ h is the height weight parameter, σ p is the horizontal position weight parameter;

[0024] (3.3) Select a drone with the lowest weight parameter and sort the weight parameters from low to high, and then use the first a drones after sorting as the master control machines of each group;

[0025] (4) Define member machines;

[0026] (4.1) The remaining ba drones are recorded as non-master drones. According to the numbers of each non-master drone in the drone group from low to high, the distance between each non-master drone and the a master drone is calculated in sequence;

[0027]

[0028] Among them, d kj represents the distance between the kth non-master machine and the jth master machine, represents the horizontal coordinate and altitude of the jth master aircraft relative to the reference point. Indicates the horizontal coordinates and altitude of the kth non-master aircraft relative to the reference point;

[0029] (4.2) Select the master machine closest to the kth non-master machine, and then determine whether the member machines in the group to which the master machine belongs are full. If not, assign the kth non-master machine to the group. If it is full, select the master machine that is the second closest to the kth non-master machine, and then continue to determine whether the member machines in the group to which the master machine belongs are full, and so on, and finally complete the grouping of all non-master machines;

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

[0031] Define the role number of the host a as Pj The role number of each member machine controlled by the master machine is P a+j , j = 1, 2, ..., a; define all disconnected roles as P b+1 ;

[0032] Set the token levels of a master machine to 1, 2, ..., j, ..., a, and the token levels of the member machines controlled by each master machine to a+1, a+2, ..., a+j, ..., 2a.

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

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

[0035] Single task T m Including constraints, tasks include permissions and task content, and constraints include role constraints and task constraints; among them, role constraints are: role number; task constraints are: token level and task T m Relationship with other tasks;

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

[0037]

[0038] Among them, y l,m The value of is 1 or 0. l,m When it is 1, it means the role number is P l UAVs perform missions T m When y l,m When it is 0, it means the role number is P l The drone does not perform the mission T m ;

[0039] (7) Execute tasks;

[0040] The command system broadcasts the task instruction matrix Y, and each UAV receives and parses the task instruction matrix, and then applies to execute the task according to the parsing result. If it meets the task constraints and role constraints contained in the task, it obtains the task authority and executes the task.

[0041] Furthermore, before implementing step (1), each UAV member in the command and control system should have the capabilities of autonomous obstacle avoidance and autonomous return to home required to ensure its own safety.

[0042] Furthermore, in step (1), the command system should periodically send test signals to each drone to ensure that the online and offline status of each member can be monitored in real time within a cycle to avoid misassignment of members. The test method can be time-sharing transmission, frequency-sharing transmission, etc.

[0043] Furthermore, in addition to considering the horizontal position advantage and height advantage, the weight parameters in step (3) can also consider the communication resource advantage and mission payload advantage of the UAV.

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

[0045] Furthermore, after completing step (7), when the task of the command and control system needs to be reallocated, it can be reallocated according to (2)-(7) to achieve real-time allocation of the UAV cluster, and combine mission planning, route planning, intelligent training and other capabilities to achieve a higher level of cluster control capability.

[0046] Furthermore, if during the execution of steps (3)-(7), the status of an online member changes to offline, the process should be repeated from step (2).

[0047] Furthermore, after completing the member allocation of each master control machine in step (4), the steps (1) to (7) can be continued within a single master control machine cluster to perform a second subdivision of the task. The beneficial effects of the present application are:

[0048] (1) Compared with the traditional MG-TRBAC model, the UAV swarm control method proposed in the present invention combines the task constraint conditions with the role constraint conditions, so that the coordination between the role supervision mechanism and the task supervision mechanism is improved, and the control strategy can be changed in real time according to the changes in the role and acquisition parameters.

[0049] (2) The token mechanism is introduced to divide the control levels of drone use, making the control rights, task permissions and resource allocation of drones more rigorous, improving the security of drone control and better adapting to the current common complex network environment.

[0050] (3) The present invention has good scalability and adaptability, and can be applied to the control of drone swarms ranging from small to large numbers of drones. The method can continuously subdivide the task granularity, and perform secondary swarm control again in the case of primary swarm control of drone swarms. When the drone swarm has more computing resources, load resources, and communication resources, the task instruction matrix can become more complex, achieving a higher level of cluster control capability. DETAILED DESCRIPTION

[0051] In order to make the purpose, technical scheme and advantages of the implementation of the present invention clearer, the technical scheme in the embodiment of the present invention will be described in more detail in combination with the embodiment of the present invention. In the example, the same or similar reference numerals throughout represent the same or similar originals or elements with the same or similar functions. The described embodiments are part of the embodiments of the present invention, not all of them. The embodiments described below by reference are exemplary and intended to be used to explain the present invention, and should not be construed as limitations on the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in the field without making creative work belong to the scope of protection of the present invention. The following is a detailed description in combination with the embodiments of the present invention.

[0052] Example

[0053] In this embodiment, the present invention provides a method for controlling a drone group commanded by wireless communication, comprising the following steps:

[0054] S1. The command system formulates the mission of the lost drone;

[0055] Define the lost connection task T0 and task constraints that the drone will perform when it loses connection. The lost connection task content is: wait for the authorized command system to directly control it. If the control fails, return home. The task constraints are: no other tasks are being executed and it is a lost connection role.

[0056] The lost contact mission and mission constraints are built into the drone body before the drone group takes action;

[0057] Compared to ordinary missions, the special feature of the lost contact mission is that the authority is granted by the drone itself, because the mission includes the authority to control its own actions, which is included in the drone itself in addition to the command system.

[0058] S2, acquisition parameters;

[0059] S2.1, suppose the drone group contains N drones, numbered 1 to 10;

[0060] In this embodiment, it is assumed that the command system commands 10 performance drones to complete the motion trajectories of a large circle and a small circle.

[0061] S2.2. The command system sends a test signal to each drone. If a drone receives the test signal, the command system records the state parameter of the drone as D. i =1, otherwise, the state parameter is recorded as D i =0, where i=1,2,…,10;

[0062] The drone that successfully receives the test signal sends the test signal to the other drones again. If a drone fails to receive the test signal from the command system but receives the test signal forwarded by the other successful drones, the command system also records the state parameter D of the drone. i =1; Finally, after the test, the command system counted 8 drones that successfully received the test signal, and the 2 drones that failed were numbered 9 and 10;

[0063] S2.3. Taking the location of the command system as the reference point, set the horizontal coordinates p of the ideal flight of each UAV relative to the reference point. i , optimal height h i ; Then each drone collects the current horizontal coordinates through the fuselage sensor high The unit is m; the parameters are finally obtained and the weight parameters are calculated as shown in Table 1.

[0064] Table 1. Positions of each drone and their weight parameters

[0065]

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

[0067] S3, define the master control machine;

[0068] S3.1. According to the movement tasks of the two circles, the command system sets the number of groups of the drone group to 2, and sets the number of drones in the two groups to 7 and 3 respectively;

[0069] S3.2. Calculate the weight parameter W of each drone among the 8 drones that can successfully receive the test signal. i :

[0070]

[0071] Among them, σ h is the height weight parameter, σ p is the horizontal position weight parameter;

[0072] Finally, the two drones with the smallest weights are distributed as the master control machines of the two groups.

[0073] S3.3. Sort the drones according to the weight parameters from small to large, and select the two drones with the lowest weight parameters as the master controllers of group 1 and group 2 respectively according to the ranking. According to the calculation results, drone No. 1 is the master controller of group 1, and drone No. 2 is the master controller of group 2.

[0074] S4, define member machines;

[0075] S4.1. The remaining six drones are recorded as non-master drones. According to the numbers of the non-master drones in the drone group from low to high, the distances between each non-master drone and the two master drones are calculated in sequence.

[0076]

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

[0078] S4.2. 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 not, the kth non-master machine will be assigned to the group. If it is full, select the master machine that is next 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, and finally complete the grouping of all non-master machines; the final calculated distance and grouping situation are shown in Table 2.

[0079] Table 2. Distances between member machines and each master machine and grouping

[0080] Drone Number <![CDATA[Distance d from 1 set of master controllers k1 > <![CDATA[Distance d from two groups of master controllers k2 > Grouping 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 token of the corresponding level;

[0082] Define the role numbers of the two master machines as 1 and 2, the role number of the first group of member machines, i.e. machines 5-8, as 3; the role number of the second group of member machines, i.e. machines 3-4, as 4; define the role number of all disconnected machines, i.e. machines 9-10, as 5;

[0083] Set the token levels of the two master machines to 1 and 2, the token levels of the two member machines to 3 and 4, and the token level of the disconnected machine to 5.

[0084] S6. define the task instruction matrix;

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

[0086] The following tasks can be used to achieve the movement of the drone group along two circular trajectories:

[0087] The task content of T1 is: 1 group of master machines moves from the given position 1 according to the given trajectory (big circle); the role constraint of the task is: the role number is 1; the task constraint is: the token level is 1; the task includes permissions and resources: big circle motion trajectory information, position 1;

[0088] The task content of T2 is: 2 groups of master machines move from the given position 2 according to the given trajectory (small circle); the role constraint of the task is: the role number is 2; the task constraint of the task is: the token level is 2; the task includes permissions and resources: small circle motion trajectory information, position 2;

[0089] The task content of T3 is: 1 group of member drones follows the motion trajectory of 1 group of master drones from position 1, with each drone half a meter apart; the role constraint of the task is: the role number is 3; the task constraint is: the token level is 3; the task includes permissions and resources: the real-time acquisition permission of the motion trajectory of 1 group of master drones and other member drones;

[0090] The task content of T4 is: 2 groups of member drones follow the movement trajectory of 2 groups of master drones starting from position 2, with each drone half a meter apart; the role constraint of the task is: the role number is 4; the task constraint is: the token level is 4; the task includes permissions and resources: real-time acquisition permissions of the movement trajectory of the 2 groups of master drones and other member drones;

[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 to enable the drone to obtain the corresponding task instructions. The matrix indicates that the drone with role number 1 performs task 1, the drone with role number 2 performs task 2, the drone with role number 3 performs task 3, and the drone with role number 4 performs task 4. After that, each drone only needs to meet the constraints of the task it needs to apply for, and it can obtain the task inclusion authority and execute the task content. By issuing instructions to execute these tasks, the purpose of drones 1-8 moving according to the preset trajectory can be achieved.

[0094] As the connection is lost, the No. 9-10 UAV automatically performs the task T0, which is manual control. Since there are only 4 member aircraft in the 1st group, 2 are missing, the No. 9-10 UAV should be controlled to follow the 1st group of master aircraft to do the following movement.

[0095] S7. Execute tasks;

[0096] The command system broadcasts the task instruction matrix Y, and each drone receives and parses the task instruction matrix, and then applies to perform the task according to the parsing result. If it meets the task constraints and role constraints contained in the task, it obtains the task authority and performs the task, and finally obtains the effect diagram.

[0097] In addition, unless otherwise defined, the technical terms or scientific terms used in the description of this application shall be the common meanings understood by the general technicians in the field to which this application belongs. The words "upper", "lower", "left", "right", "center", "vertical", "horizontal", "inside", "outside" and other words indicating orientation used in the description of this application are only used to indicate the relative direction or positional relationship, and do not imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. When the absolute position of the described object changes, its relative positional relationship may also change accordingly, so it cannot be understood as a limitation on this application. The "first", "second", "third" and similar terms used in the description of this application are only used for descriptive purposes to distinguish different components, and cannot be understood as indicating or implying relative importance. The similar words "one", "one" or "the" used in the description of this application should not be understood as an absolute limitation on quantity, but should be understood as the existence of at least one. The similar words "including" or "comprising" used in the description of this application mean that the elements or objects appearing in front of the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects.

[0098] In addition, it should be noted that, unless otherwise clearly specified and limited, the words "installed", "connected", "connected" and similar terms used in the description of this application should be understood in a broad sense. For example, the connection can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, an indirect connection through an intermediate medium, or the internal connection of two components. Technical personnel in the field can understand their specific meanings in this application according to the specific circumstances.

[0099] The above description is only a specific implementation mode of the present invention and is not intended to limit the present invention. Within the spirit and principle of the present invention, any technician familiar with the profession may use the technical content disclosed above to change or modify it into an equivalent embodiment with equivalent changes and apply it to other fields. However, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention without departing from the technical solution content of the present invention, any modification, equivalent replacement, improvement, etc. made should be included in the protection scope of the present invention.

Claims

1. A method for controlling a group of unmanned aerial vehicles commanded by wireless communication, characterized in that: First, the communication status of each UAV is determined by sending a test signal, and the abnormal UAVs are excluded according to the communication status of each UAV to perform the lost connection task separately; the roles of the UAVs with normal communication status are further assigned; a weight parameter calculation method is formulated, and the number of master control machine members and the corresponding member machines in the cluster are determined by the number of tasks and 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 corresponding token levels are assigned to all member machines; finally, a task matrix is ​​formed according to the role allocation situation. According to the token level, the command system can command the operation mode of each UAV group by issuing task instructions and assign corresponding permissions and resources.

2. The method according to claim 1, characterized in that The following steps are involved: Step (1), the command system formulates the UAV loss mission; Define the tasks and task constraints that the drone will perform when it loses connection. The task content is: wait for the authorized command system to directly control it. If the control fails, return home. The task constraints are: no other tasks are being performed and the drone is a lost role. The mission and mission constraints are built into the drone body before the drone group acts; Step (2), communication test and parameter collection; (2.1) Assume that the drone swarm contains N drones, numbered 1 to N; (2.2) The command system sends a test signal to each drone. If a drone receives the test signal, it is online. The command system records the state parameter of the drone 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 receives the test signal sends the test signal to the other drones again. If a drone fails to receive the test signal from the command system but receives the test signal forwarded by the other successful drones, the command system also records the state parameter D of the drone. i =1; finally, the command system counts the number of drones that successfully receive the test signal, recorded as b; (2.3) Taking the location of the command system as the reference point, set the horizontal coordinates p of the ideal flight of each UAV relative to the reference point. i , optimal height h i ; Then each drone collects the current horizontal coordinates through the fuselage sensor high Step (3), define the master control machine; (3.1) The command system sets the number of groups a of the drone group and the number of drones in each group; (3.2) Among the b drones that can successfully receive the test signal, calculate the weight parameter W of each drone i : Among them, σ h is the height weight parameter, σ p is the horizontal position weight parameter; (3.3) Select a drone with the lowest weight parameter and sort the weight parameters from low to high, and then use the first a drones after sorting as the master control machines of each group; Step (4), define member machines; (4.1) The remaining ba drones are recorded as non-master drones. According to the numbers of each non-master drone in the drone group from low to high, the distance between each non-master drone and the a master drone is calculated in sequence; Among them, d kj represents the distance between the kth non-master machine and the jth master machine, represents the horizontal coordinate and altitude of the jth master aircraft relative to the reference point. Indicates the horizontal coordinates and altitude of the kth non-master aircraft relative to the reference point; (4.2) Select the master machine closest to the kth non-master machine, and then determine whether the member machines in the group to which the master machine belongs are full. If not, assign the kth non-master machine to the group. If it is full, select the master machine that is the second closest to the kth non-master machine, and then continue to determine whether the member machines in the group to which the master machine belongs are full, and so on, and finally complete the grouping of all non-master machines; Step (5), define the role number and set the token of the corresponding level; Define the role number of the host a as P j The role number of each member machine controlled by the master machine is P a+j , j = 1, 2, ..., a; define all disconnected roles as P b+1 ; Set the token levels of a master machine to 1, 2, ..., j, ..., a, and the token levels of the member machines controlled by each master machine to a+1, a+2, ..., a+j, ..., 2a. Step (6), defining the task instruction matrix; (6.1), define a single task T m , m=1,2,…,M, M is the number of tasks; Single task T m Including constraints, tasks include permissions and task content, and constraints include role constraints and task constraints; among them, role constraints are: role number; task constraints are: token level and task T m Relationship with other tasks; (6.2), construct the task instruction matrix Y according to the number of roles and the number of tasks; Among them, y l,m The value of is 1 or 0. l,m When it is 1, it means the role number is P l UAVs perform missions T m When y l,m When it is 0, it means the role number is P l The drone does not perform the mission T m ; Step (7), executing the task; The command system broadcasts the task instruction matrix Y, and each UAV receives and parses the task instruction matrix, and then applies to execute the task according to the parsing result. If it meets the task constraints and role constraints contained in the task, it obtains the task authority and executes the task.

3. The method according to claim 2, characterized in that Before implementing step (1), each UAV member in the command and control system should have the autonomous obstacle avoidance and autonomous return capabilities required to ensure its own safety.

4. The method according to claim 2, characterized in that In step (1), the command system should send test signals to each drone periodically 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-sharing transmission and frequency-sharing transmission.

5. The method according to claim 2, characterized in that In addition to considering the horizontal position advantage and height advantage, the weight parameters in step (3) should also take into account the communication resources and mission payload of the UAV.

6. The method according to claim 2, characterized in that In step (4), the number of members required to be allocated to each master control machine is evenly or unevenly allocated according to the difficulty of each task and the minimum number of members required.

7. The method according to claim 2, characterized in that After completing step (7), when the tasks of the command and control system need to be reallocated, they can be reallocated according to steps (2) to (7) to achieve real-time allocation of the UAV cluster. Combined with mission planning, route planning, and intelligent training capabilities, a higher level of cluster control capability can be achieved.

8. The method according to claim 2, characterized in that If during the execution of steps (3)-(7), the status of an online member changes to offline, the process should be repeated from step (2).

9. The method according to claim 2, characterized in that After completing the member allocation of each master control machine in step (4), steps (1) to (7) can be continued within a single master control machine cluster to perform a second subdivision of the task.

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