Second-order multi-agent system predefined time event trigger control method and system

Abstract

The invention relates to the technical field of multi-agent system event triggering, and provides a second-order multi-agent system predefined time event triggering control method and system.The method comprises the steps that firstly, the communication topology of a multi-agent system is defined based on the graph theory, and the communication relation between agents is described through an adjacent matrix and a Laplacian matrix; thirdly, a dynamic model of the multi-agent system is established, the dynamic model comprises the positions and the speed states of the agents, and a control target is designed to achieve the consistency of the multi-agent system; then, a control protocol based on event triggering is provided, unnecessary communication is reduced through event triggering conditions, control signal updating is optimized, and the resource utilization efficiency is improved.

Description

Technical Field

[0001] The present disclosure relates to the technical field related to event triggering of multi-agent systems, and more specifically, to a method and system for controlling triggering of predefined time events of a second-order multi-agent system. Background Art

[0002] The statements in this section merely provide background information related to the present disclosure and do not necessarily constitute prior art.

[0003] With the widespread application of multi-agent systems in the fields of drone swarms, autonomous driving fleets, industrial robot collaboration, etc., event-triggered control has received increasing attention as a strategy to save resources and improve control efficiency. Compared with traditional periodic control methods, event-triggered control significantly reduces system resource consumption by reducing unnecessary communication and control updates. However, multi-agent systems still face many challenges in practical applications, especially in dynamic and complex environments and with limited resources. It is particularly important to design efficient control strategies.

[0004] Second-order multi-agent systems are widely used in many engineering systems, such as aircraft formation control and robotic arm collaboration tasks, because they contain dynamic characteristics such as acceleration and velocity. The control objectives of these systems usually include state consistency, efficient task allocation, and optimization of resource utilization. However, in actual scenarios, the communication topology of the multi-agent system may change randomly due to the influence of the external environment, resulting in unstable communication links, which further increases the difficulty of collaborative control. In addition, certain tasks such as emergency response and dynamic tracking require the system to achieve state consistency within a limited time, which places higher requirements on traditional asymptotic convergence control methods.

[0005] At present, studies have proposed a variety of event-triggered control methods to reduce the communication burden and computing cost. These methods have solved the problem of resource waste to a certain extent, but most methods use the asymptotic stability of the system, which cannot meet the requirements of achieving the goal within a predefined time. At the same time, the robustness and adaptability of existing methods are still insufficient in random communication topologies and dynamic environments, which may lead to a decrease in the system's collaborative performance. Summary of the invention

[0006] In order to solve the above problems, the present invention proposes a predefined time event trigger control method and system for a second-order multi-agent system, which is used for the efficient collaborative control of the second-order multi-agent system. By designing a flexible event trigger mechanism and a predefined time control strategy, the rapid consistency goal of the second-order multi-agent system in a dynamic and complex environment is achieved, while the consumption of communication and computing resources is significantly reduced, ensuring that the system completes the target task within a limited time. It has important theoretical significance and practical value.

[0007] In order to achieve the above objectives, the present disclosure adopts the following technical solutions:

[0008] One or more embodiments provide a second-order multi-agent system predefined time event triggering control method, comprising the following steps:

[0009] Construct the communication topology diagram of the second-order multi-agent system;

[0010] Based on the communication topology, combined with the speed and position state of each agent, a second-order model of the second-order multi-agent system is constructed; with the goal of making the state of the agent converge to a consistent state within a predefined time, a consistent objective function is constructed;

[0011] According to the consistency objective function, based on the difference calculated between the error function term corresponding to the current measurement error and the speed error, an event trigger function is constructed, and the trigger time is determined according to the event trigger function value;

[0012] Based on the measurement error term at the triggering moment, a distributed event-triggered controller is constructed to calculate the control input value of each agent at the triggering moment, and to control the second-order multi-agent system to achieve consistent control within a finite time.

[0013] One or more embodiments provide a second-order multi-agent system predefined time event trigger control system, including:

[0014] A communication topology graph building module, configured to build a communication topology graph of a second-order multi-agent system;

[0015] The model building module is configured to build a second-order model of the second-order multi-agent system based on the communication topology and in combination with the speed and position state of each agent; and to build a consistent objective function with the goal of making the states of the agents converge to a consistent state within a predefined time;

[0016] The triggering moment judgment module is configured to construct an event triggering function according to the consistency objective function and the difference calculated based on the error function term corresponding to the current measurement error and the speed error, and determine the triggering moment according to the event triggering function value;

[0017] The control module is configured to construct a distributed event-triggered controller based on the measurement error term at the triggering moment, calculate the control input value of each agent at the triggering moment, and control the second-order multi-agent system to achieve consistent control within a finite time.

[0018] An electronic device includes a memory and a processor, as well as computer instructions stored in the memory and running on the processor. When the computer instructions are executed by the processor, the steps in the above-mentioned predefined time event triggering control method for the second-order multi-agent system are completed.

[0019] A computer-readable storage medium is used to store computer instructions. When the computer instructions are executed by a processor, the steps in the above-mentioned predefined time event triggering control method for a second-order multi-agent system are completed.

[0020] Compared with the prior art, the present invention has the following beneficial effects:

[0021] In this disclosure, a control strategy that does not rely on the global initial state or communication topology information is proposed for the second-order multi-agent system by combining the predefined time stability theory and event-triggered control. The event trigger mechanism and the predefined time convergence theory are combined to ensure that the multi-agent system can achieve rapid collaborative control in complex dynamic environments and randomly switched communication topologies, and ensure that the system can achieve consistency within a specified time. In addition, a new event-triggered controller and trigger conditions are designed to further improve the adaptability and efficiency of the system in a dynamic environment. Through the flexibly designed trigger conditions, each agent can dynamically adjust the control strategy using only the local information between neighbors, thereby significantly reducing the communication burden and computational cost of the system.

[0022] The method disclosed in the present invention is applicable to dynamic environments and scenarios with limited resources, and can ensure the performance and stability of multi-agent systems under uncertainty and external interference, and has the remarkable characteristics of being distributed and adaptive.

[0023] The advantages of the present disclosure and the advantages of additional aspects will be described in detail in the following specific embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The accompanying drawings constituting a part of the present disclosure are used to provide a further understanding of the present disclosure. The exemplary embodiments of the present disclosure and the description thereof are used to explain the present disclosure but do not constitute a limitation of the present disclosure.

[0025] Figure 1 is a flow chart of the control method of Embodiment 1 of the present disclosure;

[0026] Figure 2 In the simulation example of Embodiment 1 of the present disclosure, each agent is in T c = Position change trajectory diagram under 10;

[0027] Figure 3 In the simulation example of Embodiment 1 of the present disclosure, each agent is in T c = Speed ​​error trajectory diagram under 10;

[0028] Figure 4 In the simulation example of Embodiment 1 of the present disclosure, each agent is in T c = Position change trajectory diagram under 15;

[0029] Figure 5In the simulation example of Embodiment 1 of the present disclosure, each agent is in T c = Speed ​​error trajectory diagram under 15;

[0030] Figure 6 In the simulation example of Embodiment 1 of the present disclosure, each agent is in T c =Event triggering time diagram under 10;

[0031] Figure 7 In the simulation example of Embodiment 1 of the present disclosure, each agent is in T c =Event triggering time diagram under 15;

[0032] Figure 8 This is a communication topology diagram of the intelligent agents in the simulation example of Embodiment 1 of the present disclosure. DETAILED DESCRIPTION

[0033] The present disclosure is further described below in conjunction with the accompanying drawings and embodiments.

[0034] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present disclosure. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present disclosure belongs.

[0035] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit exemplary embodiments according to the present disclosure. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof. It should be noted that, in the absence of conflict, the various embodiments in the present disclosure and the features in the embodiments can be combined with each other. The embodiments will be described in detail below in conjunction with the accompanying drawings.

[0036] Example 1

[0037] In the technical solutions disclosed in one or more embodiments, Figures 1 to 8 As shown, a predefined time event triggering control method for a second-order multi-agent system includes the following steps:

[0038] Step 1: Construct a communication topology diagram of a second-order multi-agent system;

[0039] Step 2: Based on the communication topology, a second-order model of the second-order multi-agent system is constructed through the speed and position state of each agent, with the goal of making the state of the agent converge to a consistent state within a predefined time, and a consistency objective function is constructed;

[0040] Step 3: According to the consistency objective function, based on the difference calculated between the error function term corresponding to the current measurement error and the speed error, an event trigger function is constructed, and the trigger time is determined according to the event trigger function value;

[0041] Step 4: Based on the measurement error term at the triggering time, a distributed event-triggered controller is constructed to calculate the control input value of each agent at the triggering time, and control the second-order multi-agent system to achieve consistent control within a limited time.

[0042] In the above scheme, the communication topology of the multi-agent system is first defined based on graph theory, and the communication relationship between agents is described by the adjacency matrix and the Laplace matrix. Then, the dynamic model of the multi-agent system is established, including the position and velocity states of the agents, and the control objectives are designed to achieve the consistency of the multi-agent system. Then, an event-triggered control protocol is proposed, which reduces unnecessary communication through event triggering conditions, optimizes control signal updates, and improves resource utilization efficiency. Finally, theoretical analysis and simulation verify that the proposed method can achieve the consistency of the multi-agent system within a predefined time under random switching of communication topology, and demonstrates its effectiveness and robustness.

[0043] In this embodiment, a control strategy that does not rely on the global initial state or communication topology information is proposed for the second-order multi-agent system by combining the predefined time stability theory and event-triggered control. The event trigger mechanism and the predefined time convergence theory are combined to ensure that the multi-agent system can achieve rapid collaborative control in complex dynamic environments and randomly switched communication topologies, and ensure that the system can achieve consistency within a specified time. In addition, a new event-triggered controller and trigger conditions are designed to further improve the adaptability and efficiency of the system in a dynamic environment. Through the flexibly designed trigger conditions, each agent can dynamically adjust the control strategy using only the local information between neighbors, thereby significantly reducing the communication burden and computing cost of the system.

[0044] In step 1, the communication topology of the second-order multi-agent system is defined based on graph theory, and the communication relationship between agents is described by the adjacency matrix and the Laplace matrix, that is, the construction of the communication topology and mathematical model is realized;

[0045] To define the communication topology of a second-order multi-agent system, the steps are as follows:

[0046] Step 1.1, assume that the multi-agent system consists of N agents, numbered 1,…,N; define the agent set Where N represents the total number of agents;

[0047] Step 1.2, define the edge set Used to describe the communication relationship between agents; if (i,j)∈ε, it means that the agent can pass information to agent j;

[0048] Step 1.3, based on graph theory, define the communication topology graph as in Is a directed or undirected graph that describes the communication structure of all agents;

[0049] Step 1.4, give the adjacency matrix of the communication topology graph and the Laplacian matrix The communication relationship between agents is described by adjacency matrix and Laplacian matrix.

[0050] Adjacency Matrix The definition is as follows:

[0051]

[0052] The Laplace matrix is The relationship between the Laplacian matrix and the adjacency matrix is: in is the degree matrix.

[0053] In step 2, a dynamic model of the second-order multi-agent system is constructed and designed.

[0054] Step 21, combining the speed and position state of each agent to establish a second-order dynamics model;

[0055] The nonlinear multi-agent system has M agents, and the communication topology is a connected undirected graph. For agent i (i.e. agent i), its state dynamics is expressed as:

[0056]

[0057] Among them, x i (t) is the state of the agent, v i (t) is the speed of the agent, u i (t) is the control input.

[0058] Step 22, constructing a consistency objective function based on the Lyapunov function so that the states of all agents converge to a consistent state within a predefined time;

[0059] In this embodiment, a new more general predefined time stability theorem is designed as the consistency objective function, as follows:

[0060]

[0061] Among them, V(e(t))>0, indicating the Lyapunov function; a≥1, c≥0, q∈(0,2), all are set values; T crepresents the predefined time, and e(t) represents the state error or deviation;

[0062] In this embodiment, by introducing the predefined time convergence theory, the system can achieve the consistency target within the specified time and meet the task requirements of high responsiveness and time constraints.

[0063] The following proves that the constructed predefined time stability theorem can make the states of all intelligences converge to a consistent state within a predefined time, that is, satisfy certain convergence or stability conditions in time:

[0064]

[0065] Right now:

[0066] The goal of step 3 is to design event-triggered control strategies to reduce the communication and computation costs in multi-agent systems while ensuring the stability and performance of the system.

[0067] Step 31, constructing an event trigger function based on the difference between the current measurement error and the error function term corresponding to the speed error, and determining whether a trigger is required based on the event trigger function value;

[0068] According to the predefined time stability theory, a controller that meets the trigger condition is constructed. The trigger condition is determined based on the state error and the trigger threshold.

[0069] First, define the speed error of agent i as the error system, which is:

[0070] e i (t) = v i (t)-v0,

[0071] The event trigger function is:

[0072] g i (t)=|E i (t)|-εc1sign(e i (t))|e i (t)| 1-q -εc2sign(e i (t))|e i (t)| 1+q -εc3sign(e i (t))

[0073] Among them, g i (t) represents the event trigger function value, c1, c2, c3 represent the set control parameters, ε∈(0,1), q is the set value;

[0074] Among them, the error function term corresponding to the velocity error is:

[0075] εc1sign(e i (t))|e i (t)| 1-q +εc2sign(e i (t))|e i (t)| 1+q +εc3sign(e i (t));

[0076] E i (t) is the measurement error of agent i at the current time t, and is the error term recorded at the current trigger time:

[0077]

[0078] in, is the latest triggering time of agent i, i.e. the last triggering time; t is the current time;

[0079] The event trigger function is a judgment condition used to dynamically determine whether the system needs to trigger certain operations, such as updating control signals or communication signals, specifically;

[0080] g i (t)<0: This indicates that the current error has not reached the trigger condition and the system does not need to update the control signal or communication.

[0081] g i (t) ≥ 0: indicates that the trigger condition is met and the system needs to trigger an event immediately (such as updating a control signal or communication);

[0082] In this embodiment, by measuring the error and the error term calculated based on the speed error, the trigger function is reasonably designed to reduce unnecessary trigger frequency, thereby reducing communication and computing costs while maintaining the stability and performance of the system. The trigger mechanism design ensures that the trigger frequency is dynamically adjusted to adapt to different environmental changes while avoiding Zeno behavior. The event trigger mechanism avoids the waste of resources caused by traditional periodic updates. The intelligent agent triggers the control signal only when necessary, effectively reducing the communication frequency and energy consumption.

[0083] Step 4: Based on the measurement error term at the triggering time, a distributed event-triggered controller is constructed to calculate the control input value u calculated by the controller i , where the distributed event triggering controller constructed is:

[0084]

[0085] Among them, c1, c2, c3 represent control parameters respectively, and q is the set value; Indicates that agent i is Speed ​​error at the moment; is the latest triggering moment of agent i.

[0086] In this embodiment, according to the consistency objective function, the trigger conditions are set with the state error and the trigger threshold, a control strategy based on event-triggered control is designed, and an event trigger function of a second-order multi-agent is established to ensure that the control signal is updated only when the trigger conditions are met, thereby effectively reducing the communication frequency and resource consumption; the designed controller directly uses the error term multiplied by the coefficient as the control input value of each agent, which can achieve fast and effective control.

[0087] Further technical solution, step 5, stability verification of distributed event-triggered controller; using Lyapunov stability theory to verify the stability of distributed event-triggered controller;

[0088] Design a Lyapunov function and verify the effectiveness of the control method based on the Lyapunov stability theory. The stability verification method includes the following steps:

[0089] Construct the Lyapunov function as:

[0090] Taking the derivative of V(t) we get:

[0091]

[0092] When a≤2c1,a≤2c2,0≤c≤c3|e i |When

[0093]

[0094] It can be seen that the goal is to satisfy the determined consistency objective function, that is, to make the state of the agent converge to a consistent state within a predefined time;

[0095] In order to further illustrate the effect of the method of this embodiment, a simulation experiment is conducted to verify whether the event-triggered control strategy based on the event-triggered function and the distributed event-triggered controller meet the requirements.

[0096] In this embodiment, for example, a simulation experiment is performed by Matlab:

[0097] The dynamic model of the second-order multi-agent is:

[0098]

[0099] Among them, x i (t) is the state of the agent, v i (t) is the speed of the agent, u i(t) is the control input.

[0100] Take the example of setting 5 agents as the topology diagram Figure 8 As shown, the initial position and velocity are x(0) = [1; 2; 1; 2; -1] T , v(0)=[1;3;2;-1;-2] T The parameter values ​​are v0=0, q=0.5, c1=1, c2=0.5, c3=0.1.

[0101] The Laplace matrix is:

[0102]

[0103] Get T c The simulation results are equal to 10, such as Figure 2 , Figure 3 and Figure 6 As shown, Figure 2 The state evolution trajectories of all agents (Agent1-Agent5) are shown. It can be seen that the multi-agent system achieves state consistency under the control strategy described in this embodiment. Figure 3 The velocity error trajectories of each agent under the event-triggered strategy are given. Figure 6 The trigger times (Event Trigger Times) under the event trigger strategy are given. It can be seen that the event trigger mechanism proposed in this embodiment significantly reduces the number of communications.

[0104] In order to verify the trajectory change and T c Related, change T c The value is 15, such as Figure 4 , Figure 5 and Figure 7 As shown, Figure 4 The state evolution trajectories of all agents are shown. It can be seen that under the control strategy described in this embodiment, the multi-agent system achieves state consistency. Figure 5 The velocity error trajectory of each agent under the event-triggered strategy is given. Figure 7 The trigger times (Event Trigger Times) under the event trigger strategy are given. It can be seen that after the change, the state of the agent can still be in T c The velocity error trajectory converges to zero.

[0105] Experiments show that the predefined time event-triggered control method for the second-order multi-agent system designed in this embodiment can achieve accurate trajectory tracking under a fixed communication topology and event-triggered control mechanism, while significantly reducing the consumption of communication resources. This fully verifies the effectiveness and practicality of the method in this embodiment. Two predefined times were used in the simulation experiment in this embodiment. The results confirm the effectiveness of the stability theorem and the feasibility of the proposed controller.

[0106] This embodiment provides a new solution to the problem of efficient collaborative control in multi-agent systems, and has broad application prospects in the fields of drone formations, intelligent transportation, distributed energy networks, etc.; by combining predefined time control theory with event triggering strategy, the present invention significantly improves the robustness and collaborative efficiency of the system, and provides reliable technical support for the control of multi-agent systems in complex environments.

[0107] The method of this embodiment can be applied to the following fields, including but not limited to: In the field of cooperative control of unmanned aerial vehicles, this method can be applied to trajectory tracking and cooperative flight of unmanned aerial vehicle groups to ensure efficient completion of tasks and reliability of communication. In this application, the intelligent agent is a unmanned aerial vehicle;

[0108] In intelligent transportation systems, this method can be applied to vehicle networking communications to optimize information sharing between vehicles, thereby improving traffic safety and efficiency. In the field of industrial automation, this method can be used for coordinated control of industrial equipment to ensure efficient operation of production systems and reduce communication delays. The intelligent agent in this application is the vehicle controller;

[0109] In smart grids, this method can be used for coordinated scheduling and load management of distributed energy sources to improve the stability of the grid and the reliability of power supply.

[0110] In telemedicine and emergency response systems, this method can be used for collaborative control and real-time communication between key devices to ensure the reliability and stability of the system at critical moments.

[0111] In addition, in a distributed robot system, this method can be used to achieve efficient communication and collaboration between robots and improve the efficiency of task completion. In this application, the agent is a robot.

[0112] Through these applications, the method of this embodiment can improve the coordination and robustness of the system in multiple scenarios, especially showing its superiority in environments with limited resources and communication constraints.

[0113] Example 2

[0114] Based on Example 1, this embodiment provides a second-order multi-agent system predefined time event trigger control system, including:

[0115] A communication topology graph building module, configured to build a communication topology graph of a second-order multi-agent system;

[0116] The model building module is configured to build a second-order model of the second-order multi-agent system based on the communication topology and in combination with the speed and position state of each agent; and to build a consistent objective function with the goal of making the states of the agents converge to a consistent state within a predefined time;

[0117] The triggering moment judgment module is configured to construct an event triggering function according to the consistency objective function and the difference calculated based on the error function term corresponding to the current measurement error and the speed error, and determine the triggering moment according to the event triggering function value;

[0118] The control module is configured to construct a distributed event-triggered controller based on the measurement error term at the triggering moment, calculate the control input value of each agent at the triggering moment, and control the second-order multi-agent system to achieve consistent control within a finite time.

[0119] The distributed event triggering controller constructed is:

[0120]

[0121] Among them, c1, c2, c3 represent control parameters respectively, and q is the set value; Indicates that agent i is Speed ​​error at the moment; is the latest triggering moment of agent i.

[0122] It should be noted here that the various modules in this embodiment correspond one-to-one to the various steps in Example 1, and the specific implementation process is the same, which will not be repeated here.

[0123] Example 3

[0124] This embodiment provides an electronic device, including a memory and a processor, and computer instructions stored in the memory and running on the processor. When the computer instructions are executed by the processor, the steps in the predefined time event triggering control method of the second-order multi-agent system of Example 1 are completed.

[0125] Example 4

[0126] This embodiment provides a computer-readable storage medium for storing computer instructions. When the computer instructions are executed by a processor, the steps in the predefined time event triggering control method for a second-order multi-agent system of Embodiment 1 are completed.

[0127] The above description is only a preferred embodiment of the present disclosure and is not intended to limit the present disclosure. For those skilled in the art, the present disclosure may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

[0128] Although the above describes the specific implementation methods of the present disclosure in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present disclosure. Technical personnel in the relevant field should understand that on the basis of the technical solution of the present disclosure, various modifications or variations that can be made by those skilled in the art without creative work are still within the scope of protection of the present disclosure.

Claims

1. A predefined time event triggering control method for a second-order multi-agent system, characterized in that: The steps include: Construct the communication topology of a second-order multi-agent system; Based on the communication topology, combined with the speed and position state of each agent, a second-order model of the second-order multi-agent system is constructed; with the goal of making the state of the agent converge to a consistent state within a predefined time, a consistent objective function is constructed; According to the consistency objective function, based on the difference calculated between the error function term corresponding to the current measurement error and the speed error, an event trigger function is constructed, and the trigger time is determined according to the event trigger function value; Based on the measurement error term at the triggering moment, a distributed event-triggered controller is constructed to calculate the control input value of each agent at the triggering moment, and to control the second-order multi-agent system to achieve consistent control within a finite time.

2. The method for triggering control of a predefined time event in a second-order multi-agent system according to claim 1, characterized in that: The communication topology of the second-order multi-agent system is defined based on graph theory, and the communication relationship between agents is described by adjacency matrix and Laplace matrix.

3. The method for triggering control of a predefined time event in a second-order multi-agent system according to claim 1, characterized in that: A consistency objective function is constructed based on the Lyapunov function so that the states of all agents converge to a consistent state within a predefined time; the consistency objective function is as follows: Where V(e(t))>0, indicating Lyapunov function; a≥1, c≥0, q∈(0,2), a, c and q are set values; T c represents the predefined time, and e(t) represents the state error.

4. The method for triggering control of a predefined time event in a second-order multi-agent system according to claim 1, characterized in that: The event trigger function is: g i (t)=|E i (t)|-εc1sign(e i (t))|e i (t)| 1-q -εc2sign(e i (t))|e i (t)| 1+q -εc3sign(e i (t)) Where gi(t) represents the event trigger function value, c1, c2, c3 represent the set control parameters, ε∈(0, 1), q is the set value; E i (t) is the measurement error of agent i at the current time t, e i (t) represents the velocity error of agent i.

5. The method for triggering control of a predefined time event in a second-order multi-agent system according to claim 1, characterized in that: The distributed event triggering controller constructed is: Among them, c1, c2, c3 represent the set control parameters respectively, and q is the set value; Indicates that agent i is Speed ​​error at the moment; is the last triggering time of agent i.

6. The method for triggering control of a predefined time event in a second-order multi-agent system according to claim 1, characterized in that: The stability of the distributed event-triggered controller is verified using Lyapunov stability theory.

7. A second-order multi-agent system with predefined time event triggering control system, characterized in that: include: A communication topology graph building module, configured to build a communication topology graph of a second-order multi-agent system; The model building module is configured to build a second-order model of the second-order multi-agent system based on the communication topology and in combination with the speed and position state of each agent; and to build a consistent objective function with the goal of making the states of the agents converge to a consistent state within a predefined time; The triggering moment judgment module is configured to construct an event triggering function according to the consistency objective function and the difference calculated based on the error function term corresponding to the current measurement error and the speed error, and determine the triggering moment according to the event triggering function value; The control module is configured to construct a distributed event-triggered controller based on the measurement error term at the triggering moment, calculate the control input value of each agent at the triggering moment, and control the second-order multi-agent system to achieve consistent control within a finite time.

8. The second-order multi-agent system predefined time event triggered control system as claimed in claim 7, characterized in that: The distributed event triggering controller constructed is: Among them, c1, c2, c3 represent control parameters respectively, and q is the set value; Indicates that agent i is Speed ​​error at the moment; is the last triggering time of agent i.

9. An electronic device, characterized in that: It includes a memory and a processor, and computer instructions stored in the memory and running on the processor. When the computer instructions are executed by the processor, the steps in the predefined time event triggering control method for a second-order multi-agent system as described in any one of claims 1-6 are completed.

10. A computer-readable storage medium, characterized in that: Used to store computer instructions, which, when executed by a processor, complete the steps of the predefined time event triggering control method for a second-order multi-agent system as described in any one of claims 1-6.

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