CN115993844B - Self-adaptive event-triggered time-varying grouping formation control method for group intelligent system - Google Patents

Self-adaptive event-triggered time-varying grouping formation control method for group intelligent system Download PDF

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CN115993844B
CN115993844B CN202310287895.0A CN202310287895A CN115993844B CN 115993844 B CN115993844 B CN 115993844B CN 202310287895 A CN202310287895 A CN 202310287895A CN 115993844 B CN115993844 B CN 115993844B
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CN115993844A (en
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赵宇
任雅桃
刘永芳
先程鑫
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Northwestern Polytechnical University
Shenzhen Institute of Northwestern Polytechnical University
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Shenzhen Institute of Northwestern Polytechnical University
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Abstract

The invention discloses a self-adaptive event-triggered time-varying grouping formation control method for a group intelligent system, and relates to the technical field of formation control of the group intelligent system. The method comprises the steps of establishing a dynamic model of a group intelligent system and a corresponding system communication topology; determining a Laplace matrix corresponding to the grouped systems according to the system communication topology; acquiring a time-varying formation configuration expected by a system, and constructing formation grouping conditions; constructing event triggering conditions according to the Laplace matrix corresponding to the grouped systems; determining a time-varying grouping formation control law by adopting an adaptive method; and controlling the grouping agents of the system by using a time-varying grouping formation control law to finish the designated grouping formation, and enabling the grouping agents to form a desired time-varying formation configuration. The invention realizes the formation grouping control of the group intelligent system on the basis of avoiding the use of global information and reducing the use of communication resources.

Description

Self-adaptive event-triggered time-varying grouping formation control method for group intelligent system
Technical Field
The invention relates to the technical field of formation control of intelligent group systems, in particular to a self-adaptive event-triggered time-varying grouping formation control method of an intelligent group system.
Background
The group intelligent system cooperative formation control has gained a great deal of attention in the past few years, and can be applied to many aspects such as autonomous underwater vehicles, unmanned aerial vehicles, electromagnetic satellites and the like. In practical engineering applications, agents often need to be grouped to perform tasks due to distance, different needs, or other factors. At the same time, the desired formation configuration will generally vary from one actual task to another. Therefore, the research of the time-varying grouping formation problem has great practical significance.
In practical applications, continuous communication between agents often consumes a large amount of resources, which is not beneficial to long-time task execution. The use of the event triggering technology avoids the use of continuous information in the communication process, and a user can reduce the consumption of resources as much as possible by designing proper event triggering conditions. In addition, the application of the self-adaptive technology avoids the use of global information which is not easy to obtain in the distributed formation control process, and more meets the actual requirements.
Thus, adaptive event-triggered time-varying grouping formation of a swarm intelligence system is a very realistic problem, and further research is still needed at present.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a self-adaptive event-triggered time-varying grouping formation control method for a group intelligent system.
In order to achieve the aim of the invention, the invention adopts the following technical scheme:
a self-adaptive event-triggered time-varying grouping formation control method of a population intelligent system comprises the following steps:
s1, establishing a dynamic model of a group intelligent system and a corresponding system communication topology;
s2, determining a Laplace matrix corresponding to the grouped systems according to the system communication topology;
s3, acquiring a time-varying formation configuration expected by the system, and constructing formation grouping conditions; constructing event triggering conditions according to the Laplace matrix corresponding to the grouped systems;
s4, determining a time-varying grouping formation control law according to the formation grouping conditions and the event triggering conditions by combining an adaptive method;
s5, controlling the grouping agents of the system by using a time-varying grouping formation control law, completing designated grouping formation, and enabling the groups of agents to form a desired time-varying formation configuration.
Optionally, the dynamic model of the population intelligent system established in step S1 is specifically:
Figure SMS_1
wherein ,
Figure SMS_2
representing an agentiStatus input of->
Figure SMS_3
Representing an agentiIs provided with a control input for the control of the (c),Grepresenting a matrix of the system and,Hthe input matrix is represented as such,Nindicating the number of agents.
Optionally, the method is characterized in that step S2 specifically includes the steps of:
Figure SMS_4
wherein ,
Figure SMS_6
representing the communication relationship between followers +.>
Figure SMS_9
Representing the communication relationship between the leader and follower,
Figure SMS_12
，/>
Figure SMS_5
indicate->
Figure SMS_8
Communication relationship between followers in group, +.>
Figure SMS_11
Indicate->
Figure SMS_14
Group and->
Figure SMS_7
Communication relationship between groups, and satisfies +.>
Figure SMS_10
，/>
Figure SMS_13
，zIndicating the number of system packets.
Optionally, the grouping conditions for formation constructed in step S3 are specifically:
Figure SMS_15
wherein ,
Figure SMS_24
indicate->
Figure SMS_17
Status of follower in group agent, +.>
Figure SMS_20
Indicate->
Figure SMS_27
Desired time-variant child formation configuration of followers in group agent, < >>
Figure SMS_31
Indicate->
Figure SMS_28
The number of leaders in the group agent, < +.>
Figure SMS_32
Indicate->
Figure SMS_25
The number of followers in the group agent, +.>
Figure SMS_29
，/>
Figure SMS_18
，/>
Figure SMS_23
The expression is represented by->
Figure SMS_19
1 is a column vector of elements, +.>
Figure SMS_22
Representing Cronecker product, metropolyl>
Figure SMS_26
Representing intermediate variables +.>
Figure SMS_30
Representing the status of the leader of the network,tthe time is represented by the time period of the day,qa number representing the number of the leader is provided,Urepresenting the number of followers in the system, +.>
Figure SMS_16
Indicate->
Figure SMS_21
Number of leaders in the group agent.
Optionally, the event triggering condition configured in step S3 is specifically:
Figure SMS_33
wherein ,
Figure SMS_42
representing followeriIs>
Figure SMS_36
At the time of the secondary trigger, inf represents the infinit, < +.>
Figure SMS_38
Representation or symbol->
Figure SMS_45
The representation is defined as symbol>
Figure SMS_48
，/>
Figure SMS_46
，/>
Figure SMS_49
Representing intermediate variables +.>
Figure SMS_44
A positive constant is indicated and a positive constant is indicated,Krepresenting the solution of algebraic Richman equation, < >>
Figure SMS_47
Representing followeriIn the first placekFormation tracking error at the time of the secondary trigger, +.>
Figure SMS_34
Representing formation tracking error, +.>
Figure SMS_41
and />
Figure SMS_37
Representing a non-negative function of the function,
Figure SMS_40
and />
Figure SMS_39
Representing a positive scalar function, ++>
Figure SMS_43
Representing sampling error, ++>
Figure SMS_35
Representing a 2-norm.
Optionally, the time-varying packet formation control law determined in step S4 is specifically:
Figure SMS_50
wherein ,
Figure SMS_53
representing a time-varying packet formation control law, +.>
Figure SMS_58
The adaptive parameters are represented by a set of parameters,Krepresenting the solution of algebraic Richman equation, < >>
Figure SMS_61
Representing followeriIn the first placekFormation tracking error at the time of the secondary trigger, +.>
Figure SMS_54
Represents the formation compensation signal and satisfies +.>
Figure SMS_57
，/>
Figure SMS_60
and />
Figure SMS_63
Representing a positive constant +.>
Figure SMS_51
The sign function is represented by a sign function,
Figure SMS_56
representing intermediate variables +.>
Figure SMS_59
Representing a positive constant +.>
Figure SMS_62
Representing the formation tracking error,Trepresenting the transposed symbols of the matrix,Prepresenting the positive definite matrix in the algebraic licarpa equation,Urepresenting the number of followers in the system, +.>
Figure SMS_52
Representing the elements of the non-singular matrix,Grepresenting a system matrix->
Figure SMS_55
Representing followeriA desired time-varying formation configuration.
The invention has the following beneficial effects:
(1) Compared with an algorithm using a continuous communication method, the event-triggered time-varying grouping formation algorithm reduces the communication frequency between neighbors, and is more suitable for executing real tasks;
(2) The interaction relation among the intelligent agents is directional, meets the actual requirement of more general group intelligent system communication topology, and overcomes the limitation of symmetric information interaction among the intelligent agents required by the prior art;
(3) The invention adopts the self-adaptive technology, overcomes the defect of using global information, and realizes the fully distributed time-varying grouping formation control;
(4) The invention realizes the formation grouping control of the group intelligent system on the basis of avoiding the use of global information and reducing the use of communication resources, and is beneficial to better completing the diversified formation tasks.
Drawings
FIG. 1 is a schematic flow chart of a method for controlling adaptive event-triggered time-varying grouping formation of a group intelligent system in an embodiment of the invention;
FIG. 2 is a schematic diagram of a communication topology of a group intelligent system according to an embodiment of the present invention;
fig. 3 is a schematic diagram of a state change of an unmanned aerial vehicle in a packet formation implementation process in an embodiment of the present invention;
fig. 4 is a schematic diagram of tracking error in a packet formation process implemented by an unmanned aerial vehicle according to an embodiment of the present invention;
fig. 5 is a schematic diagram of change of adaptive parameters in a packet formation process of an unmanned aerial vehicle according to an embodiment of the present invention;
fig. 6 is a schematic diagram of a trigger moment in a control process of a drone according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention is provided to facilitate understanding of the present invention by those skilled in the art, but it should be understood that the present invention is not limited to the scope of the embodiments, and all the inventions which make use of the inventive concept are protected by the spirit and scope of the present invention as defined and defined in the appended claims to those skilled in the art.
As shown in fig. 1, the embodiment of the invention provides a self-adaptive event-triggered time-varying grouping formation control method for a group intelligent system, which comprises the following steps S1 to S5:
s1, establishing a dynamic model of a group intelligent system and a corresponding system communication topology;
in an alternative embodiment of the invention, this embodiment establishes a device withNA population system of individual agents, whereinUIndividual follower
Figure SMS_64
The dynamics model of the leaders is specifically as follows:
Figure SMS_65
wherein ,
Figure SMS_67
representing an agentiStatus input of->
Figure SMS_72
Representing an agentiIs provided with a control input for the control of the (c),Grepresenting a matrix of the system and,Hthe input matrix is represented as such,Nindicating the number of agents>
Figure SMS_75
，/>
Figure SMS_69
，/>
Figure SMS_70
，
Figure SMS_73
Is stable, is->
Figure SMS_76
and />
Figure SMS_66
Respectively represent intelligent agentsiStatus and control inputs of->
Figure SMS_71
Represents a real number and is used to represent a real number,m,nrepresenting dimensions->
Figure SMS_74
，/>
Figure SMS_77
Representing the upper bound->
Figure SMS_68
Representing the upper bound of leader control input in the system,tthe time of the system is indicated as such,qa number representing the number of the leader is provided,Uindicating the number of followers.
In the group intelligent system established in the embodiment, all the agents and the corresponding neighbors can communicate, and the communication does not need to have symmetry, so that a more universal communication topology is formed.
S2, determining a Laplace matrix corresponding to the grouped systems according to the system communication topology;
in an alternative embodiment of the invention, after the swarm intelligence system is divided into z groups, laplacian matrix corresponding to each group of agents
Figure SMS_78
The method comprises the following steps:
Figure SMS_79
wherein ,
Figure SMS_80
representing the communication relationship between followers +.>
Figure SMS_84
Representing the communication relationship between the leader and follower,
Figure SMS_87
，/>
Figure SMS_82
indicate->
Figure SMS_83
Communication relationship between followers in group, +.>
Figure SMS_86
Indicate->
Figure SMS_89
Group and->
Figure SMS_81
Communication relationship between groups, and satisfies +.>
Figure SMS_85
，/>
Figure SMS_88
，zIndicating the number of system packets.
S3, acquiring a time-varying formation configuration expected by the system, and constructing formation grouping conditions; constructing event triggering conditions according to the Laplace matrix corresponding to the grouped systems;
in an alternative embodiment of the present invention, the present embodiment obtains the time-varying formation configuration desired by the system
Figure SMS_90
Selecting a suitable nonsingular matrix +.>
Figure SMS_91
So that->
Figure SMS_92
and />
Figure SMS_93
Is true, wherein->
Figure SMS_94
Is a non-singular matrix element of which,I m is thatmA unit matrix of dimensions; at the same time, the formation feasibility condition is satisfied>
Figure SMS_95
Thereby constructing system->
Figure SMS_96
The group desired time-variant sub-formation configuration forming conditions are specifically: />
Figure SMS_97
wherein ,
Figure SMS_107
indicate->
Figure SMS_100
Status of follower in group agent, +.>
Figure SMS_103
Indicate->
Figure SMS_109
Desired time-variant child formation configuration of followers in group agent, < >>
Figure SMS_113
Indicate->
Figure SMS_111
The number of leaders in the group agent, < +.>
Figure SMS_114
Indicate->
Figure SMS_108
The number of followers in the group agent, +.>
Figure SMS_112
，/>
Figure SMS_99
，/>
Figure SMS_105
The expression is represented by->
Figure SMS_101
1 is a column vector of elements, +.>
Figure SMS_102
Representing Cronecker product, metropolyl>
Figure SMS_106
Representing intermediate variables +.>
Figure SMS_110
Representing the status of the leader of the network,tthe time is represented by the time period of the day,qa number representing the number of the leader is provided,Urepresenting the number of followers in the system, +.>
Figure SMS_98
Indicate->
Figure SMS_104
Number of leaders in the group agent.
The present embodiment sets followerjDirection followeriThe directional path is weighted as
Figure SMS_116
The formation tracking error is
Figure SMS_118
Sampling error is +.>
Figure SMS_121
, wherein URepresenting the number of followers in the system, +.>
Figure SMS_117
Represent the firstiStatus of individual follower->
Figure SMS_119
Representing followeriDesired time-varying formation configuration,/->
Figure SMS_122
Represent the firstjStatus of individual follower->
Figure SMS_123
Representing followerjThe desired time-varying formation configuration is provided,qnumber representing leader->
Figure SMS_115
Representing a leaderqDirection followeriWeights of directed path, ++>
Figure SMS_120
Represent the firstqStatus of individual leaders; thus constructing event triggering conditions specifically is:
Figure SMS_124
wherein ,
Figure SMS_134
representing followeriIs>
Figure SMS_126
At the time of the secondary trigger, inf represents the infinit, < +.>
Figure SMS_130
Representing mathematical symbols or->
Figure SMS_128
The representation is defined as symbol>
Figure SMS_129
，/>
Figure SMS_133
，/>
Figure SMS_137
Representing intermediate variables +.>
Figure SMS_135
Representing a positive constant +.>
Figure SMS_139
Representing algebraic Rika's equation
Figure SMS_127
Is (are) a solution of->
Figure SMS_131
Representing followeriIn the first placekFormation tracking error at the time of the secondary trigger, +.>
Figure SMS_138
Representing formation tracking error, +.>
Figure SMS_142
and />
Figure SMS_141
Representing a non-negative function, +.>
Figure SMS_143
and />
Figure SMS_125
Represents a positive scalar function and follows +.>
Figure SMS_132
Gradually go to 0 +.>
Figure SMS_136
Representing sampling error, ++>
Figure SMS_140
Representing a 2-norm.
S4, determining a time-varying grouping formation control law according to the formation grouping conditions and the event triggering conditions by combining an adaptive method;
in an optional embodiment of the present invention, the determining, according to the formation grouping condition and the event triggering condition, by combining the adaptive method, the time-varying grouping formation control law specifically includes:
Figure SMS_144
wherein ,
Figure SMS_146
representing a time-varying packet formation control law, +.>
Figure SMS_149
The adaptive parameters are represented by a set of parameters,Krepresenting the solution of algebraic Richman equation, < >>
Figure SMS_153
Representing followeriIn the first placekFormation tracking error at the time of the secondary trigger, +.>
Figure SMS_148
Represents the formation compensation signal and satisfies +.>
Figure SMS_150
，/>
Figure SMS_154
and />
Figure SMS_157
Represent positive constant and +.>
Figure SMS_145
，/>
Figure SMS_152
Representing a sign function for eliminating the influence of the control input of the leader,/>
Figure SMS_156
Representing intermediate variables +.>
Figure SMS_158
A positive constant is indicated and a positive constant is indicated,
Figure SMS_147
representing the formation tracking error,Trepresenting the transposed symbols of the matrix,Prepresenting a positive definite matrix in the algebraic licarpa equation,Urepresenting the number of followers in the system, +.>
Figure SMS_151
Representing the elements of the non-singular matrix,Grepresenting a system matrix->
Figure SMS_155
Representing followeriA desired time-varying formation configuration.
S5, controlling the grouping agents of the system by using a time-varying grouping formation control law, completing designated grouping formation, and enabling the groups of agents to form a desired time-varying formation configuration.
The following is a specific analysis and description of a self-adaptive event-triggered time-varying grouping formation control method of a group intelligent system provided by the embodiment in combination with a specific example.
Considering a swarm intelligence system consisting of 11 unmanned aerial vehicles, the tasks to be performed are divided into the following three phases:
the first stage, 8 unmanned aerial vehicles integrally surround 3 targets in a predefined formation configuration;
in the second stage, the targets respectively go to two places according to the self requirements, 8 unmanned aerial vehicles are divided into two groups to surround the targets in two places, and 4 unmanned aerial vehicles are arranged in each group;
and thirdly, according to the requirements in actual task execution, resource scheduling is needed between two places, and finally two groups respectively comprising 3 unmanned aerial vehicles and 5 unmanned aerial vehicles are formed to surround the target.
The kinetic model of each unmanned aerial vehicle is as follows:
Figure SMS_159
wherein ,
Figure SMS_160
，/>
Figure SMS_161
。
in the first stage, the whole unmanned aerial vehicle swarm intelligent system forms a regular octagon formation within 0-15 seconds. The topology is shown in fig. 2 (a) where drones 1-8 are followers and drones 9-11 are leaders. The corresponding laplace matrix is:
Figure SMS_162
，/>
Figure SMS_163
.
the time-varying formation configuration desired at this stage is:
Figure SMS_164
in the second phase, the drones will be divided into two groups, each of which will follow its own leader, forming a predefined formation after 15 seconds. The communication topology associated with this phase is shown in fig. 2 (b). The corresponding laplace matrix is:
Figure SMS_165
，/>
Figure SMS_166
.
the desired time-varying formation is configured as
Figure SMS_167
In the third stage, 30 seconds later, the whole unmanned aerial vehicle system is divided into three groups according to instructions, and the communication topology diagram is shown in fig. 2 (c). The corresponding laplace matrix is:
Figure SMS_168
，/>
Figure SMS_169
.
as in the second phase, each group will also follow its own leader, forming a corresponding predefined time-varying formation, as shown in the following formula:
Figure SMS_170
the selection of other parameters is then performed. By solving algebraic Li-Ka equation
Figure SMS_172
. According to the procedure described above, optionally +.>
Figure SMS_176
，/>
Figure SMS_179
，/>
Figure SMS_173
，
Figure SMS_175
，/>
Figure SMS_178
，/>
Figure SMS_181
，/>
Figure SMS_171
，/>
Figure SMS_174
，/>
Figure SMS_177
，
Figure SMS_180
。
As shown in fig. 3, all drones successfully formed a predefined grouping formation configuration. Forming a predefined regular octagon formation on three targets of the 8 unmanned aerial vehicle following systems within 0-15 s, and integrally surrounding the targets; after 15s, the three targets respectively go to two places to execute tasks according to own task tracks, at the moment, the follower is divided into two groups to track the targets in two places in order to realize the surrounding of the targets, each group is respectively provided with 4 followers, when 30s, the second-stage task is finished, and the two groups of unmanned aerial vehicles accurately form a desired formation configuration; after 30s, resource scheduling is performed due to actual task demands, two groups respectively comprising 3 unmanned aerial vehicles and 5 unmanned aerial vehicles are formed, and the targets are surrounded in a desired formation configuration. By observing fig. 4, it can be obtained that the tracking error of the drone can converge to zero in all three phases. Adaptive parameters
Figure SMS_182
The course of the change in (a) is shown in FIG. 5 and can be clearly seen +.>
Figure SMS_183
Is bounded. Furthermore, as can be seen from fig. 6, there is no gano behaviour in the system. From the results, the self-adaptive event-triggered time-varying grouping formation control method of the group intelligent system can flexibly realize formation grouping control of the group intelligent system, and is beneficial to better completing diversified formation tasks.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The principles and embodiments of the present invention have been described in detail with reference to specific examples, which are provided to facilitate understanding of the method and core ideas of the present invention; meanwhile, as those skilled in the art will have variations in the specific embodiments and application scope in accordance with the ideas of the present invention, the present description should not be construed as limiting the present invention in view of the above.
Those of ordinary skill in the art will recognize that the embodiments described herein are for the purpose of aiding the reader in understanding the principles of the present invention and should be understood that the scope of the invention is not limited to such specific statements and embodiments. Those of ordinary skill in the art can make various other specific modifications and combinations from the teachings of the present disclosure without departing from the spirit thereof, and such modifications and combinations remain within the scope of the present disclosure.

Claims (5)

1. The self-adaptive event-triggered time-varying grouping formation control method for the population intelligent system is characterized by comprising the following steps of:
s1, establishing a dynamic model of a group intelligent system and a corresponding system communication topology;
s2, determining a Laplace matrix corresponding to the grouped systems according to the system communication topology;
s3, acquiring a time-varying formation configuration expected by the system, and constructing formation grouping conditions; constructing event triggering conditions according to the Laplace matrix corresponding to the grouped systems;
s4, determining a time-varying grouping formation control law according to formation grouping conditions and event triggering conditions by combining an adaptive method, wherein the time-varying grouping formation control law specifically comprises the following steps:
Figure QLYQS_1
wherein ,
Figure QLYQS_12
representing a time-varying packet formation control law, +.>
Figure QLYQS_4
The adaptive parameters are represented by a set of parameters,Krepresenting the solution of algebraic Richman equation, < >>
Figure QLYQS_8
Representing followeriIn the first placekFormation tracking error at the time of the secondary trigger, +.>
Figure QLYQS_13
Represents the formation compensation signal and satisfies +.>
Figure QLYQS_17
，/>
Figure QLYQS_16
and />
Figure QLYQS_18
Representing a positive constant +.>
Figure QLYQS_10
Representing a symbolic function +_>
Figure QLYQS_14
Representing intermediate variables +.>
Figure QLYQS_2
Representing a positive constant +.>
Figure QLYQS_6
Representing the formation tracking error,Trepresenting the transposed symbols of the matrix,Prepresenting the positive definite matrix in the algebraic licarpa equation,Urepresenting the number of followers in the system, +.>
Figure QLYQS_5
Representing the elements of the non-singular matrix,Grepresenting a system matrix->
Figure QLYQS_9
Representing followeriDesired time-varying formation configuration,/->
Figure QLYQS_11
Representing followeriIs>
Figure QLYQS_15
Time of secondary triggering>
Figure QLYQS_3
Representing followeriIs>
Figure QLYQS_7
The secondary triggering moment;
s5, controlling the grouping agents of the system by using a time-varying grouping formation control law, completing designated grouping formation, and enabling the groups of agents to form a desired time-varying formation configuration.
2. The adaptive event-triggered time-varying packet formation control method of a population intelligent system according to claim 1, wherein the dynamic model of the population intelligent system established in step S1 is specifically:
Figure QLYQS_19
wherein ,
Figure QLYQS_20
representing an agentiStatus input of->
Figure QLYQS_21
Representing an agentiIs provided with a control input for the control of the (c),Grepresenting a matrix of the system and,Hthe input matrix is represented as such,Nindicating the number of agents.
3. The adaptive event-triggered time-varying grouping formation control method of a population intelligent system according to claim 1, wherein step S2 determines a laplace matrix corresponding to the system grouping according to a system communication topology, and the laplace matrix specifically comprises:
Figure QLYQS_22
wherein ,
Figure QLYQS_25
representing the communication relationship between followers +.>
Figure QLYQS_27
Indicating the communication relationship between the leader and the follower, < +.>
Figure QLYQS_30
，/>
Figure QLYQS_24
Indicate->
Figure QLYQS_26
Communication relationship between followers in group, +.>
Figure QLYQS_29
Indicate->
Figure QLYQS_32
Group and->
Figure QLYQS_23
Communication relationship between groups, and satisfies +.>
Figure QLYQS_28
，/>
Figure QLYQS_31
，zIndicating the number of system packets.
4. The adaptive event-triggered time-varying packet formation control method of a population intelligent system according to claim 1, wherein the formation packet conditions constructed in step S3 are specifically:
Figure QLYQS_33
wherein ,
Figure QLYQS_44
indicate->
Figure QLYQS_35
Status of follower in group agent, +.>
Figure QLYQS_40
Indicate->
Figure QLYQS_37
Group intelligenceDesired time-variant sub-formation configuration of followers in the body,/->
Figure QLYQS_41
Indicate->
Figure QLYQS_45
The number of leaders in the group agent, < +.>
Figure QLYQS_49
Indicate->
Figure QLYQS_42
The number of followers in the group agent, +.>
Figure QLYQS_46
，/>
Figure QLYQS_34
，/>
Figure QLYQS_38
，/>
Figure QLYQS_47
The expression is represented by->
Figure QLYQS_50
1 is a column vector of elements, +.>
Figure QLYQS_48
Representing Cronecker product, metropolyl>
Figure QLYQS_51
Representing intermediate variables +.>
Figure QLYQS_36
Representing the status of the leader of the network,tthe time is represented by the time period of the day,qa number representing the number of the leader is provided,Urepresenting the number of followers in the system, +.>
Figure QLYQS_39
Indicate->
Figure QLYQS_43
Number of leaders in the group agent.
5. The adaptive event-triggered time-varying packet formation control method of a population intelligent system according to claim 1, wherein the event-triggered condition constructed in step S3 is specifically:
Figure QLYQS_52
wherein ,
Figure QLYQS_62
representing followeriIs>
Figure QLYQS_54
At the time of the secondary trigger, inf represents the infinit, < +.>
Figure QLYQS_58
Representation or symbol->
Figure QLYQS_57
The representation is defined as symbol>
Figure QLYQS_61
，/>
Figure QLYQS_65
，/>
Figure QLYQS_68
Representing intermediate variables +.>
Figure QLYQS_63
A positive constant is indicated and a positive constant is indicated,Krepresentation algebra Li Kadi squareSolution of course (I/O)>
Figure QLYQS_66
Representing followeriIn the first placekFormation tracking error at the time of the secondary trigger, +.>
Figure QLYQS_53
Representing formation tracking error, +.>
Figure QLYQS_59
and />
Figure QLYQS_55
Representing a non-negative function of the function,
Figure QLYQS_60
and />
Figure QLYQS_64
Representing a positive scalar function, ++>
Figure QLYQS_67
Representing sampling error, ++>
Figure QLYQS_56
Representing a 2-norm. />
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