CN116974185A - Multi-agent binary consistency control method, device, equipment and storage medium - Google Patents

Abstract

The application belongs to the technical field of multi-agent system control, and discloses a multi-agent binary consistency control method, a device, equipment and a storage medium. The application obtains a symbol diagram according to the communication relation by determining the communication relation among the intelligent agents in the multi-intelligent agent system, determines the cooperative countermeasure relation among the intelligent agents according to the symbol diagram, obtains the communication state of the intelligent agents according to the cooperative countermeasure relation, determines the bipartite consistency judging condition according to the communication state of the intelligent agents, determines the bipartite consistency of the multi-intelligent agent according to the communication state of the intelligent agents and the bipartite consistency judging condition, and eliminates the time lag and external interference influence of the intelligent agents by determining the cooperative countermeasure relation among the intelligent agents so as to achieve the bipartite consistency tracking control of the multi-intelligent agent system.

Description

Multi-agent bipartite consistency control method, device, equipment and storage medium

Technical field

The present invention relates to the technical field of multi-agent system control, and in particular to a multi-agent bipartite consistency control method, device, equipment and storage medium.

Background technique

As an important branch of distributed artificial intelligence, multi-agent systems have received extensive research and attention in fields such as mobile robot formation control, satellite formation systems, biological systems, and social systems. Consistency, as the basis of collaborative control, is one of the core issues in current research on multi-agent systems. Most studies on consistency issues only focus on collaborative interaction, that is, using positive weights to represent the communication relationship of the system. There is often a competitive relationship between multiple agents. By grouping the agents, the agents in each group can complete different tasks by cooperating or competing according to the same group or different groups. However, in the actual operation of the system, During the process, each agent will inevitably be disturbed by time delays and some unknown uncertainties, thereby reducing the efficiency and stability of the system operation.

The above content is only used to assist in understanding the technical solution of the present invention, and does not represent an admission that the above content is prior art.

Contents of the invention

The main purpose of the present invention is to provide a multi-agent bipartite consistency control method, device, equipment and storage medium, aiming to solve the technical problems of disturbance, parameter uncertainty and internal time lag in the existing technology.

In order to achieve the above objectives, the present invention provides a multi-agent binary consistency control method, which method includes the following steps:

Determine the communication relationship between the various agents in the multi-agent system, and obtain the symbol graph based on the communication relationship;

Determine the cooperative and confrontational relationship between each agent according to the symbolic diagram;

Obtain the communication status of each agent according to the cooperative confrontation relationship;

Determine the binary consistency judgment condition according to the communication status of each agent;

The binary consistency of the multi-agent is determined according to the communication status of each agent and the binary consistency judgment condition.

Optionally, the cooperative confrontation relationship includes a cooperative relationship and a confrontation relationship. Determining the cooperative confrontation relationship between each agent according to the symbolic diagram includes:

Determine the position of each agent according to the symbol graph, and obtain a node set according to the position;

According to the communication relationship between the various agents, an adjacency matrix is obtained;

The cooperative and antagonistic relationship between each agent is obtained according to the adjacency matrix and the node set. When the corresponding weight value between the agents is a positive number, it is determined that the cooperative relationship between the agents is;

When the corresponding weight value between the agents is a negative number, there is an adversarial relationship between the agents.

Optionally, the multi-agent includes a leader and several followers, and obtaining the communication status of each agent according to the cooperative confrontation relationship includes:

Determine the control input of the leader and the control input of the follower according to the cooperative confrontation relationship;

Obtain the communication status of the leader according to the leader's control input, system time delay, leader's current state and leader's nonlinear time delay function;

The communication status of the follower is obtained according to the follower's control input, system time delay, the follower's current state, the instability factors of the follower agent and the follower's nonlinear time delay function.

Optionally, before determining the binary consistency of the multi-agent according to the communication status of each agent and the binary consistency judgment condition, the method further includes:

Construct a controller through scalar control gain, feedback control gain matrix, symbolic function, and nonlinear function;

The controller can perform communication control on each intelligent agent and update the status of each intelligent agent;

The consistency error is obtained based on the updated status of the leader and follower and the sign function;

The binary consistency judgment condition is updated according to the consistency error.

Optionally, determining the bipartite consistency of the multi-agent based on the status of each agent and the corresponding judgment condition includes:

Construct a Lyapunov function based on the state error between the follower and the leader in a multi-agent system;

The corresponding relationship between consistency errors is obtained according to the Lyapunov function;

The first change amount and the second change amount are obtained according to the corresponding relationship between the state error between the follower and the leader and the consistency error, the scalar control gain and the feedback control gain;

When neither the first change amount nor the second change amount is greater than zero, the multi-agent system achieves bipartite consistency.

Optionally, after obtaining the corresponding relationship between the state error between the follower and the leader and the consistency error according to the Lyapunov function, the method further includes:

The Lyapunov function is differentiated according to the closed-loop error system to obtain the bipartite consistency condition of the closed-loop error system, which includes a leader and a follower.

In addition, in order to achieve the above object, the present invention also proposes a control device for multi-agent bipartite consistency. The control device for multi-agent bipartite consistency includes:

The communication traversal module is used to determine the communication relationship between various agents in the multi-agent system, and obtain the symbol graph based on the communication relationship;

A communication classification module, used to determine the cooperative and confrontational relationship between various agents based on the symbol graph;

A communication confirmation module, used to obtain the communication status of each agent according to the cooperative confrontation relationship;

A communication judgment module, used to determine the binary consistency judgment condition according to the communication status of each agent;

A result output module is configured to determine the binary consistency of the multi-agent according to the communication status of each agent and the binary consistency judgment condition.

In addition, to achieve the above object, the present invention also proposes a multi-agent bipartite consistency control device. The multi-agent bipartite consistency control device includes: a memory, a processor and a device that is stored in the memory and can be used in The multi-agent binary consistency control program running on the processor is configured to implement the steps of the multi-agent binary consistency control method as described above.

In addition, in order to achieve the above object, the present invention also proposes a storage medium. A control program for bipartite consistency of multi-agent is stored on the storage medium. The control program of bipartite consistency of multi-agent is implemented when executed by a processor. The steps of the multi-agent bipartite consistency control method as described above.

The present invention determines the communication relationship between each agent in the multi-agent system, obtains a symbol diagram based on the communication relationship, determines the cooperative confrontation relationship between the various agents based on the symbol diagram, and obtains the cooperative confrontation relationship based on the cooperative confrontation relationship. The communication status of each intelligent agent is determined according to the communication status of each intelligent agent. The binary consistency judgment condition is determined according to the communication status of each intelligent agent and the binary consistency judgment condition. The binary consistency judgment condition of the multi-agent is determined. , by determining the cooperation and confrontation relationships between agents through the communication relationship between agents, eliminating the time lag and external interference effects of agents, and achieving bipartite consistent tracking control of multi-agent systems.

Description of the drawings

Figure 1 is a schematic structural diagram of a multi-agent binary consistency control device of a hardware operating environment involved in an embodiment of the present invention;

Figure 2 is a schematic flow chart of the first embodiment of the multi-agent binary consistency control method of the present invention;

Figure 3 is a schematic flow chart of the second embodiment of the multi-agent binary consistency control method of the present invention;

Figure 4 is a structural block diagram of a first embodiment of a multi-agent bipartite consistency control device of the present invention.

The realization of the purpose, functional features and advantages of the present invention will be further described with reference to the embodiments and the accompanying drawings.

Detailed ways

It should be understood that the specific embodiments described here are only used to explain the present invention and are not intended to limit the present invention.

Referring to Figure 1, Figure 1 is a schematic structural diagram of a multi-agent binary consistency control device of a hardware operating environment involved in an embodiment of the present invention.

As shown in Figure 1, the multi-agent binary consistency control device may include: a processor 1001, such as a central processing unit (Central Processing Unit, CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Among them, the communication bus 1002 is used to realize connection communication between these components. The user interface 1003 may include a display screen (Display) and an input unit such as a keyboard (Keyboard). The optional user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wireless-Fidelity (Wi-Fi) interface). The memory 1005 may be a high-speed random access memory (Random Access Memory, RAM) memory or a stable non-volatile memory (Non-Volatile Memory, NVM), such as a disk memory. The memory 1005 may optionally be a storage device independent of the aforementioned processor 1001.

Those skilled in the art can understand that the structure shown in Figure 1 does not constitute a limitation on the multi-agent bipartite consistency control device, and may include more or less components than shown in the figure, or combine certain components, or Different component arrangements.

As shown in Figure 1, the memory 1005 as a storage medium may include an operating system, a network communication module, a user interface module, and a multi-agent binary consistency control program.

In the multi-agent binary consistency control device shown in Figure 1, the network interface 1004 is mainly used for data communication with the network server; the user interface 1003 is mainly used for data interaction with the user; the multi-agent binary consistency of the present invention The processor 1001 and the memory 1005 in the control device can be set in the multi-agent binary consistency control device. The multi-agent binary consistency control device calls the multi-agent binary stored in the memory 1005 through the processor 1001. Consistency control program, and execute the multi-agent binary consistency control method provided by the embodiment of the present invention.

Embodiments of the present invention provide a control method for binary consistency of multiple agents. Refer to Figure 2 , which is a schematic flow chart of a method for controlling binary consistency of multiple agents according to the first embodiment of the present invention.

In this embodiment, the multi-agent binary consistency control method includes the following steps:

Step S10: Determine the communication relationship between the various agents in the multi-agent system, and obtain the symbol graph based on the communication relationship.

It should be noted that the execution subject of this embodiment is a multi-agent bipartite consistent control device, wherein the multi-agent bipartite consistent control device has functions such as data processing, data communication and program running. The multi-agent bipartite consistency control device The control device for body bipartite consistency can be an integrated controller, a control computer and other devices, and of course it can also be other devices with similar functions, which is not limited in this embodiment.

It should be understood that a multi-agent system can include several agents, in which the multiple agents can establish communication with each other, and the agents can cooperate with each other or compete with each other to complete specific tasks. There are unreasonable communication relationships between multiple agents, and there are logical oppositions between these two communication relationships. Therefore, in order to better describe the communication relationship between multiple agents, we can use the The communication relationship obtains the symbolic graph G = (V, E, A), where V represents the node set, A is the adjacency matrix, and E represents the edge set between two agents that can communicate with each other.

Step S20: Determine the cooperation and confrontation relationship between the various agents according to the symbol graph.

It should be noted that there is a communication relationship between various agents, and the communication relationship is based on the existence of cooperation between the agents on specific tasks, or the competition between multiple agents to complete specific tasks.

In the specific implementation, the Laplacian matrix L of the symbol graph G is defined as [l _ij ] _N×N , where,

In a multi-agent system containing N agents, it is represented by a symbolic graph G = (V, E, A), where V = {v ₁ ,..., v _N } is the node set, and A = [a _ij ] ∈R ^n×n is the adjacency matrix, node v _i represents the i-th agent, and the edge set (v _i , v _j )∈E indicates that agent i and agent j can communicate with each other. For the adjacency matrix A of the symbolic graph G , when there is (v _i , v _j )∈E, agent i and agent j are in a cooperative relationship, a _ij >0; agent i and agent j are in an antagonistic relationship, a _ij <0.

Step S30: Obtain the communication status of each intelligent agent according to the cooperation and confrontation relationship.

In the specific implementation, in the symbolic graph G, there are two non-empty node sets V ₁ and V ₂ , and the interactive behavior of the agents inside each node set is cooperative. If the agents in V ₁ and the agents in V ₂ If there is interactive behavior among the agents, then this behavior is confrontational. And V ₁ and V ₂ satisfy V ₁ ∪V ₂ =V, When v _i , v _j ∈V _s (s∈1,2), a _ij ≥ 0; when v _i ∈V _s , v _j ∈V _t , s≠t(s,t∈{1,2}) When a _ij ≤ 0, the symbolic graph G is said to be structurally balanced, otherwise it is said to be structurally unbalanced. For the structurally balanced symbolic graph, there is a symbolic matrix S = diag (s ₁ , s ₂ ,..., s _N ) such that all entries of the matrix SAS are non-negative. When i∈V _s , s _i = 1; when When i∈V _t , s _i =-1. According to the node set corresponding to each agent belonging to V ₁ and V ₂ , the current communication status of the agent can be obtained.

Step S40: Determine the binary consistency judgment condition according to the communication status of each agent.

It should be noted that the binary consistency judgment condition is used to determine whether the current agent has solved the problem of disturbance, parameter uncertainty and internal time based on the communication status between each agent during the communication process of multiple agents. Judgment conditions for stagnation problems.

Further, the multi-agent includes a leader and several followers, and obtaining the communication status of each agent according to the cooperative confrontation relationship includes:

Determine the control input of the leader and the control input of the follower according to the cooperative confrontation relationship;

Obtain the communication status of the leader according to the leader's control input, system time delay, leader's current state and leader's nonlinear time delay function;

The communication status of the follower is obtained according to the follower's control input, system time delay, the follower's current state, the instability factors of the follower agent and the follower's nonlinear time delay function.

In specific implementation, the multi-agent system includes a leader and several followers, where the leader and followers constitute the entire multi-agent system, and the multi-agent system can be:

Among them, the number of leaders is 1, the number of followers is N, x _i (t)∈R ⁿ , u _i (t)∈R ^p , respectively representing the state and control input of the i-th agent. f(x _i (t-τ(t))) represents the nonlinear time delay function, τ(t) represents the time delay of the system and satisfies 0<τ(t)<τ, where τ and μ are known constants. /> Represented as a matching uncertainty term including the external interference of the i-th agent and parameter uncertainty. A, B and F are constant matrices. x ₀ (t)∈R ⁿ represents the state of the leader agent, u ₀ (t)∈R ^p represents the control input of the leader agent, f(x ₀ (t-τ(t))) represents the leader’s Nonlinear time delay function. For the leader-follower multi-agent system (2) under the designed distributed controller, it satisfies:

Step S50: Determine the binary consistency of the multi-agent according to the communication status of each agent and the binary consistency judgment condition.

In specific implementation, if the conditions described in equation (3) can be satisfied in multi-agent systems, it means that the current multi-agent system achieves bipartite consistency. For the agents in node sets V ₁ and V ₂ , the interactive behavior of the agents within each node set is cooperative. If the agents in V ₁ and the agents in V ₂ have interactive behaviors, then this Behavior is confrontational. When making a binary consistency determination, first determine which node set the current agent belongs to. If the current agent belongs to the node set corresponding to V ₁ , the difference between the current node's state and the leader's current state needs to be limited. Determine whether the limit of the absolute value of the difference tends to 0, and repeat the same processing method for each node in the V ₁ node. Similarly, if the current node is the V ₂ node set, the current node needs to be The sum of the state and the current state of the leader is used as the limit, and it is judged whether the limit of the absolute value of the difference tends to 0, and the same processing method is repeated for each node in the V ₂ node. If the results are all tending to is 0, it means that the current multi-agent system has achieved bipartite consistency.

Further, the cooperative confrontation relationship includes a cooperative relationship and a confrontation relationship. Determining the cooperative confrontation relationship between each agent according to the symbolic diagram includes:

Determine the position of each agent according to the symbol graph, and obtain a node set according to the position;

According to the communication relationship between the various agents, an adjacency matrix is obtained;

The cooperative and antagonistic relationship between each agent is obtained according to the adjacency matrix and the node set. When the corresponding weight value between the agents is a positive number, it is determined that the cooperative relationship between the agents is;

When the corresponding weight value between the agents is a negative number, there is an adversarial relationship between the agents.

In the specific implementation, when the symbolic graph is obtained, the symbolic graph can reflect the communication relationship between the agents, and can indirectly reflect the location of the agents. According to the location of the agents, the location of the agents can be determined. The node set includes two non-empty node subsets V ₁ and V ₂ in the multi-agent system. According to the node sets V ₁ and V ₂ , it can be judged whether the current symbolic graph is in a balanced state. If two nodes with interactive behaviors are in the same node set, it means that there is a cooperative relationship between the two nodes. If there are When the interactive nodes are in different node sets, there is an antagonistic relationship between the two nodes. If the nodes in the node set can all satisfy the above relationship, it means that the current symbol graph is structurally balanced. For structurally balanced symbols The graph has a signed matrix that makes all entries of the matrix SAS non-negative.

This embodiment determines the communication relationship between each agent in the multi-agent system, obtains a symbol diagram based on the communication relationship, determines the cooperative confrontation relationship between the various agents based on the symbol diagram, and determines the cooperative confrontation relationship between the various agents based on the symbolic diagram. Obtain the communication status of each intelligent agent, determine the binary consistency judgment condition according to the communication status of each intelligent agent, and determine the binary consistency of the multi-agent according to the communication status of each intelligent agent and the binary consistency judgment condition. property, by determining the cooperation and confrontation relationships between agents through the communication relationship between agents, eliminating the time lag and external interference effects of agents, and achieving bipartite consistent tracking control of multi-agent systems.

Referring to Figure 3, Figure 3 is a schematic flow chart of a second embodiment of a multi-agent binary consistency control method of the present invention.

Based on the above-mentioned first embodiment, the multi-agent binary consistency control method in this embodiment also includes before step S50:

Step S501: Construct a controller through scalar control gain, feedback control gain matrix, symbolic function, and nonlinear function;

Step S502: The controller can perform communication control on each intelligent agent and update the status of each intelligent agent;

Step S503: Obtain the consistency error according to the updated status of the leader and follower and the sign function;

Step S504: Update the binary consistency judgment condition according to the consistency error.

In the specific implementation, based on the information interaction between the agent and its neighbor nodes, in order to solve the problems of first-order agents with disturbances and time delays, a distributed controller of the i-th follower is proposed.

In formula (4), c ₁ >0, c ₂ >0 represents the scalar control gain, K represents the feedback control gain matrix, sgn(·) represents the sign function, and g(·) is a nonlinear function, defined as follows:

Let the state error between the i-th agent and the leader be defined as: e _i (t) = x _i (t) - s _i x ₀ (t), error signal Then the leader-follower closed-loop error system can be described as:

Bringing the controller (4) into the power system (6), we can get:

in

make The available consistency tracking error is:

where G(e(t)) is expressed as

The binary consistency judgment condition is updated according to the obtained consistency tracking error pair.

Further, determining the bipartite consistency of the multi-agent according to the status of each agent and the corresponding judgment condition includes:

Construct a Lyapunov function based on the state error between the follower and the leader in a multi-agent system;

The corresponding relationship between consistency errors is obtained according to the Lyapunov function;

The first change amount and the second change amount are obtained according to the corresponding relationship between the state error between the follower and the leader and the consistency error, the scalar control gain and the feedback control gain;

When neither the first change amount nor the second change amount is greater than zero, the multi-agent system achieves bipartite consistency.

In the specific implementation, for multi-agent systems, the Lyapunov function is constructed:

V(t)＝V ₁ (t)+V ₂ (t) (9)

in

Noting that K=-F ^T R, taking the derivative with respect to V ₁ (t) gives:

For the multi-agent system described, the following assumptions exist:

Assumption 1: If the undirected symbolic graph G is connected and structurally balanced, it contains a directed spanning tree with the leader as the root node, and its subgraph G _s contains N followers.

The communication relationship between the leader and the follower is described by a diagonal matrix A ₀ , A ₀ =diag(a ₁₀ ,...,a _N0 ). If the follower i can communicate with the leader, then a _i0 > 0, otherwise a _i0 =0.

Using L represents the Laplacian matrix about the graph G, since the leader has no neighbors, L can be expressed as:

Among them, L ₂ ∈ ^{R N×1} and L ₁ ∈ ^{R N×N} .

Assumption 2: There is a constant β>0 such that ||u ₀ (t)||≤β.

Assumption 3: is continuous and bounded, that is, there is a constant γ>0, such that

Assumption 4: The nonlinear function f satisfies the following conditions:

||f(x _i (t-τ(t)),t)-s _i f(x ₀ (t-τ(t)),t)||≤κ||x _i (t-τ(t) )-s _i x ₀ (t-τ(t))||, where the constant κ>0.

It also includes two lemmas:

Lemma 1: For an undirected connected graph G, if it contains a directed spanning tree with the leader as the root node, then its Laplacian matrix L about the graph G is positive definite.

Lemma 2: For any given vector X, Y∈R ⁿ and positive definite matrix P∈R ^n×n , we have

2X ^T Y≤X ^T PX+Y ^T P ^-1 Y.

If assumptions 1-4 are true. When there are conditions c ₂ ≥ρ,K＝-F ^T R, where/> λ ₂ is the smallest nonzero eigenvalue of L ₁ such that the inequality

Established, then the leader-follower multi-agent system can achieve bipartite consistency through the above distributed controller.

Further, after obtaining the corresponding relationship between the state error between the follower and the leader and the consistency error according to the Lyapunov function, the method further includes:

The Lyapunov function is differentiated according to the closed-loop error system to obtain the bipartite consistency condition of the closed-loop error system, which includes a leader and a follower.

In the specific implementation, first, the first term in the Lyapunov function is derived according to the leader-follower closed-loop error system to obtain According to the above assumptions 2 and 3, we get/> Γ=γ+β, then in the above formula (11)/> It can be further expressed as:

And in equation (11) Then it is further expressed as:

And it is known that c ₂ ≥ρ, substituting the above equations (13) and (14) into equation (11), we get

According to Lemma 1, it can be seen that the Laplacian matrix L ₁ is positive definite, and the subgraph G _s about G is undirected and connected, and at least one agent can communicate with the leader, then there is a unitary matrix as follows ,

in Y ₁ ∈R ^N×N-1 is obtained through state transition/> in At the same time, (λ ₁ ≤λ ₂ …≤λ _N ) is the eigenvalue of L ₁ . Order/> (15) in Eq. It can be simplified to:

According to Lemma 2 and Assumption 4, equation (15) can be The formula is further expressed as:

Putting equations (17) and (18) into equation (15), we get

right Find the derivative and note/> Available

Derive the second term of the Lyapunov function according to the system time delay. At this time, equations (19) and (20) can be substituted into equation (9), and we can get:

According to Theorem 1, Δ ₁ ≤ 0, Δ ₂ ≤ 0, then When t→∞, the system error approaches 0. Therefore, the leader-follower system (2) can asymptotically achieve bipartite consistency under the controller (4).

Under the condition that the symbolic graph structure is balanced, this embodiment not only handles the internal time delay of the agent, but also designs a corresponding distributed controller for each follower, solving certain uncertainties associated with the agent. Includes parameter uncertainties and the effects of external disturbances. In the end, a group of agents tracked the leader to achieve consistent state values, and the other group of agents converged to a state value with the same modulo equal sign and opposite sign as the leader, achieving the bipartite consistent tracking goal.

In addition, the embodiment of the present invention also proposes a storage medium. The storage medium stores a multi-agent binary consistency control program. When the multi-agent binary consistency control program is executed by a processor, the control program is implemented as described above. The steps of the multi-agent bipartite consistency control method described above.

Referring to Figure 4, Figure 4 is a structural block diagram of a first embodiment of a multi-agent binary consistency control device of the present invention.

As shown in Figure 4, the multi-agent binary consistency control device proposed by the embodiment of the present invention includes:

The communication traversal module 10 is used to determine the communication relationship between various agents in the multi-agent system, and obtain the symbol graph based on the communication relationship;

The communication classification module 20 is used to determine the cooperative and confrontational relationship between each agent according to the symbol graph;

The communication confirmation module 30 is used to obtain the communication status of each intelligent agent according to the cooperative confrontation relationship;

The communication judgment module 40 is used to determine the binary consistency judgment condition according to the communication status of each agent;

The result output module 50 is configured to determine the binary consistency of the multi-agent according to the communication status of each agent and the binary consistency judgment condition.

This embodiment determines the communication relationship between each agent in the multi-agent system, obtains a symbol diagram based on the communication relationship, determines the cooperative confrontation relationship between the various agents based on the symbol diagram, and determines the cooperative confrontation relationship between the various agents based on the symbolic diagram. Obtain the communication status of each intelligent agent, determine the binary consistency judgment condition according to the communication status of each intelligent agent, and determine the binary consistency of the multi-agent according to the communication status of each intelligent agent and the binary consistency judgment condition. property, by determining the cooperation and confrontation relationships between agents through the communication relationship between agents, eliminating the time lag and external interference effects of agents, and achieving bipartite consistent tracking control of multi-agent systems.

In one embodiment, the communication classification module 20 is also used to determine the position of each agent according to the symbol graph, and obtain a node set according to the position; and obtain the adjacency according to the communication relationship between the agents. Matrix; obtain the cooperative and antagonistic relationship between each agent according to the adjacency matrix and the node set, and when the corresponding weight value between the agents is a positive number, it is determined that the cooperative relationship between the agents; When the corresponding weight value between the agents is a negative number, there is an adversarial relationship between the agents.

In one embodiment, the communication confirmation module 30 is further configured to determine the control input of the leader and the control input of the follower according to the cooperative confrontation relationship; according to the control input of the leader, the system time The leader's communication state is obtained by using the delay, the leader's current state and the leader's nonlinear time delay function; according to the follower's control input, system time delay, the follower's current state, the instability factors of the follower agent and The follower's nonlinear delay function obtains the follower's communication status.

In one embodiment, the result output module 50 is also used to construct a controller through scalar control gain, feedback control gain matrix, symbolic function, and nonlinear function; the controller can perform communication control on each intelligent agent. , update the status of each agent; obtain the consistency error based on the updated status of the leader and follower, and the sign function; update the binary consistency judgment condition based on the consistency error.

In one embodiment, the result output module 50 is also used to construct a Lyapunov function based on the state error between the follower and the leader in the multi-agent system; obtain the consistency error based on the Lyapunov function The corresponding relationship between the follower and the leader; the first change amount and the second change amount are obtained according to the corresponding relationship between the state error between the follower and the leader and the consistency error, the scalar control gain and the feedback control gain; in When neither the first change amount nor the second change amount is greater than zero, the multi-agent system achieves bipartite consistency.

In one embodiment, the result output module 50 is also used to derive the Lyapunov function according to a closed-loop error system to obtain the bipartite consistency condition of the closed-loop error system. The closed-loop error system includes a leader followers and followers.

It should be understood that the above are only examples and do not constitute any limitation on the technical solution of the present invention. In specific applications, those skilled in the art can make settings as needed, and the present invention does not impose any limitations on this.

It should be noted that the workflow described above is only illustrative and does not limit the scope of the present invention. In practical applications, those skilled in the art can select some or all of them for implementation according to actual needs. The purpose of this embodiment is not limited here.

It should be understood that although each step in the flow chart in the embodiment of the present application is displayed in sequence as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated in this article, the execution of these steps is not strictly limited in order, and they can be executed in other orders. Moreover, at least some of the steps in the figure may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but may be executed at different times, and their execution order is not necessarily sequential. may be performed in turn or alternately with other steps or sub-steps of other steps or at least part of stages.

Furthermore, it should be noted that, as used herein, the terms "include", "comprises" or any other variation thereof are intended to cover a non-exclusive inclusion, such that a process, method, article or system that includes a list of elements includes not only those elements, but also other elements not expressly listed or elements inherent to the process, method, article or system. Without further limitation, an element defined by the statement "comprises a..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

The above serial numbers of the embodiments of the present invention are only for description and do not represent the advantages and disadvantages of the embodiments.

Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus the necessary general hardware platform. Of course, it can also be implemented by hardware, but in many cases the former is better. implementation. Based on this understanding, the technical solution of the present invention can be embodied in the form of a software product that is essentially or contributes to the existing technology. The computer software product is stored in a storage medium (such as a read-only memory). , ROM)/RAM, magnetic disk, optical disk), including several instructions to cause a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the method described in various embodiments of the present invention.

The above are only preferred embodiments of the present invention, and do not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the description and drawings of the present invention may be directly or indirectly used in other related technical fields. , are all similarly included in the scope of patent protection of the present invention.

Claims (9)

1. A control method for binary consistency of multi-agent, characterized in that the control method for binary consistency of multi-agent includes: Determine the communication relationship between the various agents in the multi-agent system, and obtain the symbol graph based on the communication relationship; Determine the cooperative and confrontational relationship between each agent according to the symbolic graph; Obtain the communication status of each agent according to the cooperative confrontation relationship; Determine the binary consistency judgment condition according to the communication status of each agent; The binary consistency of the multi-agent is determined according to the communication status of each agent and the binary consistency judgment condition. 2. The method according to claim 1, wherein the cooperative confrontation relationship includes a cooperative relationship and a confrontation relationship, and determining the cooperative confrontation relationship between each agent according to the symbol diagram includes: Determine the position of each agent according to the symbol graph, and obtain a node set according to the position; According to the communication relationship between the various agents, an adjacency matrix is obtained; The cooperative and antagonistic relationship between each agent is obtained according to the adjacency matrix and the node set. When the corresponding weight value between the agents is a positive number, it is determined that the cooperative relationship between the agents is; When the corresponding weight value between the agents is a negative number, there is an adversarial relationship between the agents. 3. The method of claim 1, wherein the multi-agent includes a leader and several followers, and obtaining the communication status of each agent according to the cooperative confrontation relationship includes: Determine the control input of the leader and the control input of the follower according to the cooperative confrontation relationship; Obtain the communication status of the leader according to the leader's control input, system time delay, leader's current state and leader's nonlinear time delay function; The communication status of the follower is obtained according to the follower's control input, system time delay, the follower's current state, the instability factors of the follower agent and the follower's nonlinear time delay function. 4. The method of claim 1, wherein before determining the binary consistency of the multi-agent according to the communication status of each agent and the binary consistency judgment condition, it further includes: Construct a controller through scalar control gain, feedback control gain matrix, symbolic function, and nonlinear function; The controller can perform communication control on each intelligent agent and update the status of each intelligent agent; The consistency error is obtained based on the updated status of the leader and follower and the sign function; The binary consistency judgment condition is updated according to the consistency error. 5. The method of claim 4, wherein determining the bipartite consistency of the multi-agent according to the status of each agent and corresponding judgment conditions includes: Construct a Lyapunov function based on the state error between the follower and the leader in a multi-agent system; The corresponding relationship between consistency errors is obtained according to the Lyapunov function; The first change amount and the second change amount are obtained according to the corresponding relationship between the state error between the follower and the leader and the consistency error, the scalar control gain and the feedback control gain; When neither the first change amount nor the second change amount is greater than zero, the multi-agent system achieves bipartite consistency. 6. The method of claim 5, wherein after obtaining the corresponding relationship between the state error between the follower and the leader and the consistency error according to the Lyapunov function, Also includes: The Lyapunov function is differentiated according to the closed-loop error system to obtain the bipartite consistency condition of the closed-loop error system, which includes a leader and a follower. 7. A control device for multi-agent binary consistency, characterized in that the control device for multi-agent binary consistency includes: The communication traversal module is used to determine the communication relationship between various agents in the multi-agent system, and obtain the symbol graph based on the communication relationship; A communication classification module, used to determine the cooperative and confrontational relationship between various agents based on the symbol graph; A communication confirmation module, used to obtain the communication status of each agent according to the cooperative confrontation relationship; A communication judgment module, used to determine the binary consistency judgment condition according to the communication status of each agent; A result output module is configured to determine the binary consistency of the multi-agent according to the communication status of each agent and the binary consistency judgment condition. 8. A multi-agent binary consistency control device, characterized in that the device includes: a memory, a processor, and a multi-agent binary consistency stored in the memory and capable of running on the processor. The control program of the multi-agent binary consistency is configured to implement the steps of the control method of the multi-agent binary consistency according to any one of claims 1 to 6. 9. A storage medium, characterized in that a multi-agent binary consistency control program is stored on the storage medium, and when the multi-agent binary consistency control program is executed by a processor, the implementation of claims 1 to 1 Steps of the multi-agent bipartite consistency control method described in any one of 6.