Safe self-adaptive dynamic event trigger control method of multi-agent network system

Abstract

The invention provides a security self-adaptive dynamic event trigger control method for a multi-agent network system, and belongs to the technical field of automatic control, the method comprises the following steps: acquiring relative state information among a plurality of agents in the multi-agent network system, and then acquiring a security self-adaptive dynamic event trigger control result of the multi-agent network system based on the relative state information; and controlling a first intelligent agent in the plurality of intelligent agents by adopting a first control law, and controlling a second intelligent agent in the plurality of intelligent agents by adopting a second control law so as to cope with denial of service attack. By adopting the technical scheme provided by the invention, a completely distributed solution can be realized based on a safe self-adaptive dynamic event trigger control strategy, and relative information among the intelligent agents is used without global network topology information and a global coordinate framework, so that the dependence on the global coordinate framework is eliminated, and the safety of the intelligent agents is improved. The self-healing capability of the multi-agent network can be improved to cope with network attacks.

Description

Technical Field

[0001] The present application relates to the field of automatic control technology, and in particular, to a secure adaptive dynamic event-triggered control method for a multi-agent network system. Background Art

[0002] The cooperative control of multi-agent network systems (MAS) has been widely studied and applied in many fields such as swarms of robots, wireless networks, and intelligent transportation systems. However, the agents in MAS systems usually rely on wireless communication networks, which are very vulnerable to network attacks in practical applications, such as Denial of Service (DoS) attacks. Moreover, different from the security issues of computing systems, industrial MAS systems are usually closely connected to physical entities. Therefore, once a MAS system is attacked, it may not only affect the system itself, but also cause serious consequences to these physical entities, and even lead to major real-world damage. Therefore, how to improve the self-healing ability of MAS systems to cope with network attacks has become an urgent technical problem in the field. Summary of the Invention

[0003] The main objective of the embodiments of the present application is to propose a secure adaptive dynamic event-triggered control method for a multi-agent network system, aiming to improve the self-healing ability of MAS systems when encountering network attacks.

[0004] To achieve the above objective, a first aspect of the embodiments of the present application proposes a secure adaptive dynamic event-triggered control method for a multi-agent network system, the method including:

[0005] Obtain the relative state information among multiple agents in the multi-agent network system;

[0006] Based on the relative state information, use a first control law to control a first agent among the multiple agents, and use a second control law to control a second agent among the multiple agents to cope with a Denial of Service attack.

[0007] In some embodiments, the method further includes:

[0008] Detect whether a Denial of Service attack meets the requirements of a preset trigger function to obtain a detection result; the trigger function is a trigger function designed for an adaptive dynamic event-triggered control strategy;

[0009] The using a first control law to control a first agent among the multiple agents, and using a second control law to control a second agent among the multiple agents based on the relative state information includes:

[0010] When the detection result indicates that the denial-of-service attack meets the requirements of the triggering function, based on the relative state information, a first control law is used to control the first agent among the multiple agents, and a second control law is used to control the second agent among the multiple agents.

[0011] In some embodiments, the method further includes:

[0012] Updating the triggering condition of the dynamic event-triggered control strategy to increase the average non-triggering range of the denial-of-service attack.

[0013] In some embodiments, the updating of the triggering condition of the dynamic event-triggered control strategy includes:

[0014] Adding a preset dynamic variable to the triggering condition of the dynamic event-triggered control strategy to update the triggering condition;

[0015] wherein the dynamic variable is used to extend the average event interval time to increase the average non-triggering range of the denial-of-service attack.

[0016] In some embodiments, the method further includes:

[0017] Updating the adaptation law based on the external interference factors of the multi-agent network system to obtain an updated adaptation law;

[0018] Based on the updated adaptation law, perform the steps of using the first control law to control the first agent among the multiple agents and using the second control law to control the second agent among the multiple agents.

[0019] In some embodiments, the using the first control law to control the first agent among the multiple agents and using the second control law to control the second agent among the multiple agents includes:

[0020] During the sleep period of the denial-of-service attack, use the first control law to control the first agent among the multiple agents and use the second control law to control the second agent among the multiple agents.

[0021] In some embodiments, the multiple agents include a leader agent and multiple follower agents;

[0022] The obtaining of the relative state information between multiple agents in the multi-agent network system includes:

[0023] Defining a first state of the leader agent and defining a second state of the multiple follower agents;

[0024] Determine the relative state information between the leader agent and the multiple follower agents based on the first state and the multiple second states;

[0025] Determine the relative state information between the multiple follower agents based on the multiple second states.

[0026] To achieve the above object, a second aspect of the embodiments of the present application provides a security adaptive dynamic event-triggered control device for a multi-agent network system, the device comprising:

[0027] A state acquisition module, configured to acquire the relative state information between multiple agents in the multi-agent network system;

[0028] An agent control module, configured to control a first agent among the multiple agents by using a first control law and control a second agent among the multiple agents by using a second control law based on the relative state information to cope with a denial-of-service attack.

[0029] To achieve the above object, a third aspect of the embodiments of the present application provides a security adaptive dynamic event-triggered control device for a multi-agent network system, the security adaptive dynamic event-triggered control device for the multi-agent network system comprising a memory and a processor, the memory storing a computer program, and the processor implementing the method described in the first aspect when executing the computer program.

[0030] To achieve the above object, a fourth aspect of the embodiments of the present application provides a computer-readable storage medium, the computer-readable storage medium storing a computer program, and the computer program implementing the method described in the first aspect when executed by a processor.

[0031] To achieve the above object, a fifth aspect of the embodiments of the present application provides a computer program product, the computer program product storing a computer program, and the computer program implementing the method described in the first aspect when executed by a processor.

[0032] The security adaptive dynamic event-triggered control method, device, device, computer-readable storage medium, and computer program product proposed by the embodiments of the present application obtain the relative state information between multiple agents in the multi-agent network system, and then control a first agent among the multiple agents by using a first control law and control a second agent among the multiple agents by using a second control law based on the relative state information to cope with a denial-of-service attack.

[0033] Thus, the embodiments of the present application use the relative state information between agents and adopt different control laws to control multiple agents respectively to cope with the Denial of Service (DoS) attack. That is, the embodiments of the present application are based on an adaptive technology that allows the control protocol to operate without any global network topology information. Since the advantage of the proposed protocol is that it relies on relative information rather than absolute information, the embodiments of the present application neither require global network topology information nor a global coordinate frame, eliminating the dependence on the global coordinate frame and achieving a fully distributed implementation. In this way, compared with the event-triggered control strategy of the traditional Multi-Agent System (MAS) network system, the embodiments of the present application can effectively improve the self-healing ability of the multi-agent network to cope with DoS network attacks. Description of the Drawings

[0034] Figure 1 Schematic diagram of the step flow of the secure adaptive dynamic event-triggered control method for the multi-agent network system provided by the embodiments of the present application in some embodiments;

[0035] Figure 2 Schematic diagram of achieving leader-follower consensus of the MAS system in a state involved in the secure adaptive dynamic event-triggered control method for the multi-agent network system provided by the embodiments of the present application in some embodiments;

[0036] Figure 3 Schematic diagram of achieving leader-follower consensus of the MAS system in another state involved in the secure adaptive dynamic event-triggered control method for the multi-agent network system provided by the embodiments of the present application in some embodiments;

[0037] Figure 4 Schematic diagram of the statistics of the triggering times of the existing strategy after adding additional variables to the triggering conditions involved in the secure adaptive dynamic event-triggered control method for the multi-agent network system provided by the embodiments of the present application in some embodiments;

[0038] Figure 5 Schematic diagram of the step flow of the secure adaptive dynamic event-triggered control method for the multi-agent network system provided by the embodiments of the present application in some other embodiments;

[0039] Figure 6 Schematic diagram of the flow of the overall control strategy involved in the secure adaptive dynamic event-triggered control method for the multi-agent network system provided by the embodiments of the present application in one complete embodiment;

[0040] Figure 7 Schematic diagram of the multi-agent network architecture involved in the secure adaptive dynamic event-triggered control method for the multi-agent network system provided by the embodiments of the present application in one complete embodiment;

[0041] Figure 8 Schematic diagram for achieving leader-following consensus on the network architecture shown in Figure 7 ;

[0042] Figure 9 Schematic diagram of the structure of the monitoring system provided by the embodiment of the present application;

[0043] Figure 10 Schematic diagram of the hardware structure of the security adaptive dynamic event-triggered control device for the multi-agent network system provided by the embodiment of the present application. Detailed implementation manners

[0044] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0045] It should be noted that although the functional modules are divided in the device schematic diagram and the logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order from the module division in the device or the order in the flowchart. Terms such as "first" and "second" in the specification, claims and the above-mentioned drawings are used to distinguish similar objects and do not necessarily need to describe a specific order or sequence.

[0046] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present application belongs. The terms used herein are only for the purpose of describing the embodiments of the present application and are not intended to limit the present application.

[0047] First, a brief description will be given to the professional technical terms involved in the embodiments of the present application.

[0048] A multi-agent network system MAS (which can also be called a cyber-physical multi-agent system) is composed of multiple agents with autonomous decision-making, perception and communication capabilities, and is a complex network system. In a cyber-physical system, these agents in the MAS system interact closely with the physical environment and undertake various control tasks. However, the MAS system is vulnerable to network threats such as denial-of-service attacks DoS, which poses severe challenges to its security and stability.

[0049] In engineering applications, such as robot swarms, wireless sensor networks and intelligent transportation systems, etc., they can usually be modeled as MAS systems with limited onboard resources. These MAS systems often face the following challenges in practical applications: 1) The communication network shared by agents is vulnerable to network attacks, 2) In some cases, the absolute information of agents is difficult to accurately measure, 3) Agents may also be affected by external interference.

[0050] Next, the overall concept of the embodiments of the present application will be described.

[0051] Nowadays, the cooperative control of MAS systems has been widely studied and applied in many fields such as robot swarms, wireless networks, and intelligent transportation systems. A core issue in the field of MAS systems is the consensus problem, which can generally be divided into leaderless consensus and leader-following consensus. For task-driven applications such as trajectory tracking, leader-following consensus is more suitable, and its goal is to develop distributed protocols to ensure that the states of the followers can converge to the state of the leader. However, in related technologies, MAS usually relies on wireless communication networks, and these networks are vulnerable to cyberattacks in practical applications. Different from the security issues of computing systems, industrial MAS systems are usually closely connected to physical entities. Therefore, an attack on MAS may not only affect the system itself, but may also cause serious consequences to these entities, and even lead to major real-world damage, such as an attack on a nuclear facility. Therefore, it is particularly important to endow MAS with self-healing capabilities when encountering cyberattacks (for example, being able to quickly restore leader-following consensus).

[0052] Based on this, the embodiments of the present application propose a security adaptive dynamic event-triggered control method, device, equipment, computer-readable storage medium, and computer program product for a multi-agent network system. By obtaining the relative state information between multiple agents in the multi-agent network system, and then based on the relative state information, a first control law is used to control a first agent among the multiple agents, and a second control law is used to control a second agent among the multiple agents to cope with denial-of-service attacks.

[0053] In this way, the embodiments of the present application use the relative state information between agents and adopt different control laws to control multiple agents respectively to cope with denial-of-service attacks DoS. That is, the embodiments of the present application are based on an adaptive technology that allows the control protocol to operate without any global network topology information. Since the advantage of the proposed protocol is that it relies on relative information rather than absolute information, the embodiments of the present application neither require global network topology information nor a global coordinate frame, eliminating the dependence on the global coordinate frame and achieving a fully distributed implementation. In this way, compared with the event-triggered control strategy of traditional multi-agent network systems MAS, the embodiments of the present application can effectively improve the self-healing ability of multi-agent networks to cope with DoS cyberattacks.

[0054] In addition, the embodiments of the present application also introduce a dynamically evolving internal variable into the triggering condition of the dynamic event triggering control strategy, thereby reducing the event triggering time. This not only further reduces the risk of being attacked by DoS but also can reduce energy consumption. Moreover, the embodiments of the present application also add new conditions to the adaptive law, enabling the dynamic event triggering control strategy to enhance the robustness of the multi-agent network on the premise of ensuring the boundedness of the adaptive parameters and the candidate Lyapunov function, and can resist DoS attacks with external interference.

[0055] That is to say, compared with the event triggering control of traditional MAS systems, the embodiments of the present application provide a method for solving a fully distributed event triggering control strategy that utilizes the relative information of agents in the MAS system, and provide an effective control strategy for the MAS system to resist DoS attacks with external interference.

[0056] Next, based on the overall concept of the above embodiments of the present application, specific embodiments of the security adaptive dynamic event triggering control method, device, equipment, computer-readable storage medium, and computer program product of the multi-agent network system provided by the embodiments of the present application are proposed. First, each specific embodiment of the security adaptive dynamic event triggering control method of the multi-agent network system in the embodiments of the present application is described in detail.

[0057] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Among them, artificial intelligence (AI) is a theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use knowledge to obtain the best results.

[0058] Artificial intelligence basic technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technology, operation / interaction systems, and mechatronics. Artificial intelligence software technologies mainly include several major directions such as computer vision technology, robotics, biometric technology, speech processing technology, natural language processing technology, and machine learning / deep learning.

[0059] It should be noted that in each specific embodiment of the present application, when it comes to relevant processing based on data related to the user's identity or characteristics, such as user information, user behavior data, user historical data, and user location information, the user's permission or consent will be obtained first. Moreover, the collection, use, and processing of these data will comply with relevant laws, regulations, and standards. In addition, when the embodiments of the present application need to obtain the user's sensitive personal information, the user's separate permission or separate consent will be obtained through methods such as pop-up windows or redirecting to a confirmation page. After clearly obtaining the user's separate permission or separate consent, the necessary user-related data for the normal operation of the embodiments of the present application will be obtained.

[0060] In addition, the security adaptive dynamic event-triggered control method for the multi-agent network system provided by the embodiments of the present application relates to the field of automatic control technology. The security adaptive dynamic event-triggered control method for the multi-agent network system provided by the embodiments of the present application can be applied to terminals, can also be applied to the server side, or can also be software running on the terminal or the server side. In some embodiments, the terminal can be a terminal device capable of controlling the operation of the MAS system, such as a smart phone, a tablet computer, a laptop computer, a desktop computer, etc.; the server side can be configured as an independent physical server, can also be configured as a server cluster or a distributed system composed of multiple physical servers, or can also be configured as a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms; the software can be an application that implements the security adaptive dynamic event-triggered control method for the multi-agent network system, etc., but is not limited to the above forms.

[0061] Alternatively, the embodiments of the present application can also be used in many general-purpose or special-purpose computer system environments or configurations. For example: MAS systems, personal computers, server computers, handheld or portable devices, tablet-type devices, multi-processor systems, microprocessor-based systems, set-top boxes, programmable consumer computer devices, network PCs, small computers, large computers, distributed computing environments including any of the above systems or devices, and so on. The present application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application can also be practiced in a distributed computing environment, where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0062] For the convenience of understanding and description, in the following text, the security adaptive dynamic event-triggering control method of the multi-agent network system provided by the embodiments of the present application will be taken as an example for MAS system to be described in detail. The implementation of the security adaptive dynamic event-triggering control method of the multi-agent network system provided by the embodiments of the present application for any of the above forms of the theme can refer to the process of the security adaptive dynamic event-triggering control method of the multi-agent network system applied by the MAS system described later.

[0063] Please refer to Figure 1 , Figure 1 which is the schematic flow chart of the steps of the security adaptive dynamic event-triggering control method of the multi-agent network system provided by the embodiments of the present application in some embodiments. It should be understood that although Figure 1 the execution order of some method steps is shown in Figure 1 due to different design requirements in actual applications, the security adaptive dynamic event-triggering control method of the multi-agent network system provided by the embodiments of the present application can of course adopt an execution order different from that shown in the figure. That is, Figure 1 the order of the method steps shown does not constitute a limitation on the execution logic order of the security adaptive dynamic event-triggering control method of the multi-agent network system provided by the embodiments of the present application, and any reasonable changes based on

[0064] such as Figure 1 shown, in some embodiments, the security adaptive dynamic event-triggering control method of the multi-agent network system provided by the embodiments of the present application may include, but is not limited to, step S101 and step S102.

[0065] Step S101: Obtain the relative state information between multiple agents in the multi-agent network system.

[0066] During the operation of the MAS system, the relative state information between multiple agents in the system is continuously obtained.

[0067] In some embodiments, the multiple agents in the MAS system may include a leader agent and multiple follower agents. In this case, step S101 may include, but is not limited to, the following steps:

[0068] Define the first state of the leader agent and the second states of the multiple follower agents;

[0069] Determine the relative state information between the leader agent and the multiple follower agents based on the first state and the multiple second states;

[0070] Determine the relative state information among the multiple follower agents based on the multiple second states.

[0071] It should be noted that in a linear MAS system, there is usually a leader agent and multiple follower agents. Based on this, the dynamic equation of the MAS system can be expressed as:

[0072]

[0073] Among them, is the state of the leader agent, is the state of the follower agent, is the control input. Matrices A and B are system matrices and input matrices with appropriate dimensions.

[0074] When the MAS system obtains the relative state information among multiple agents, it first defines the first state of the leader agent and, defines the second state of the follower agent After that, based on the first state and the second state the relative state information between the leader agent and each of the multiple follower agents can be obtained, and, based on the second state of each follower agent the relative state information among the multiple follower agents can be obtained.

[0075] For example, the relative state information among agents can be defined as follows:

[0076]

[0077] Among them, for any agent i in the MAS system, only the state information of the other two agents connected to it in the MAS system is required.

[0078] Step S102: Based on the relative state information, control the first agent among the multiple agents using a first control law, and control the second agent among the multiple agents using a second control law to cope with a denial-of-service attack.

[0079] It should be noted that the MAS system can apply different control inputs using adaptive techniques according to different state information among agents.

[0080] After the MAS system obtains the relative state information among multiple agents, it can adopt an adaptive technique. According to the relative state information among the agents, it uses the first control law to control the first agent among the multiple agents, and uses a second control law different from the first control law to control other second agents among the multiple agents except the first agent, so as to cope with the suffered denial-of-service attack (DoS).

[0081] In some embodiments, in the above step S102, the step of "using the first control law to control the first agent among the multiple agents and using the second control law to control the second agent among the multiple agents" may include but is not limited to the following steps:

[0082] During the sleep period of the denial-of-service attack, use the first control law to control the first agent among the multiple agents and use the second control law to control the second agent among the multiple agents.

[0083] It should be noted that according to the DoS attack model, the time of the DoS attack can be divided into a sleep period and an attack period.

[0084] When the MAS system controls different agents using different control laws based on the relative state information among the multiple agents, it does not control the agents during the attack period of the DoS attack, but during the sleep period of the DoS attack, it uses the first control law to control the first agent and the second control law to control the second agent.

[0085] In some embodiments, both the above first control law and the second control law can be feedback control laws with adaptive techniques:

[0086]

[0087] Among them, u i (t) represents the control input to agent i, t ∈ Ξ s (t0, t) represents being in the sleep period of the DoS attack, t ∈ Ξ a (t0, t) represents being in the attack period represents the k-th triggering instant of agent i is the relative state information sampled by the MAS system at time t k

[0088] Facing different state information of the agents, the MAS system uses different control laws for each agent using the adaptive principle. Therefore, the adaptive law of c i can be determined by the following formula:

[0089] ​

[0090] Among them, the weight μ>0, ρ1 is a positive constant, and F is the gain matrix.

[0091] In some embodiments, the MAS system can use an event-triggered control method. When the requirements of the trigger function are met and the trigger condition is determined to be met, different control laws are used to control the state of the agent according to different state information of the agent, so as to achieve the consistency of navigation and following, for example, Figure 2 The MAS system shown in FIG. 1 achieves leader-follower consistency in one state, or achieves the following: Figure 3 The MAS system shown achieves leader-follower consistency in another state.

[0092] In this case, the secure adaptive dynamic event triggering control method for a multi-agent network system provided in the embodiment of the present application may also include but is not limited to the following steps:

[0093] Detect whether the denial of service attack meets the requirements of the preset trigger function and obtain the detection result.

[0094] It should be noted that the trigger function is a trigger function designed in advance for the MAS system to adapt to the dynamic event trigger control strategy.

[0095] During the operation of the MAS system, it can also continuously monitor whether it is attacked by a denial of service DoS, and if it is detected that it is under a DoS attack, it can further detect whether the DoS attack meets the requirements of the trigger function to obtain the detection result.

[0096] Based on this, the above step S102: based on the relative state information, using the first control law to control the first intelligent agent among the multiple intelligent agents, and using the second control law to control the second intelligent agent among the multiple intelligent agents, may include but is not limited to the following steps:

[0097] When the detection result indicates that the denial of service attack meets the requirements of the trigger function, based on the relative state information, a first control law is used to control a first intelligent agent among the multiple intelligent agents, and a second control law is used to control a second intelligent agent among the multiple intelligent agents.

[0098] After the MAS system detects whether a DoS attack meets the requirements of the trigger function and obtains the detection result, if the detection result indicates that the DoS attack does not meet the requirements of the trigger function, the MAS system does not perform state control on the agent. However, if the detection result indicates that the DoS attack meets the requirements of the trigger function, in this case, the MAS system determines that the DoS attack meets the trigger condition, and thus begins to control the first agent using the above-mentioned first control law, and also controls the second agent using the second control law.

[0099] In the embodiments of the present application, during the operation of the MAS system, the relative state information between multiple agents in the system is continuously obtained. After that, the MAS system can adopt an adaptive technique to control the first agent among the multiple agents using the first control law based on the relative state information between the agents, and also use a second control law different from the first control law to control the other second agents except the first agent among the multiple agents to cope with the Denial of Service (DoS) attack suffered.

[0100] In this way, the embodiments of the present application use the relative state information between agents and adopt different control laws to control multiple agents respectively to cope with the DoS attack. That is, the embodiments of the present application are based on an adaptive technique that allows the control protocol to operate without any global network topology information. Since the advantage of the proposed protocol is that it relies on relative information rather than absolute information, the embodiments of the present application neither require global network topology information nor a global coordinate frame, eliminating the dependence on the global coordinate frame and achieving a fully distributed implementation. In this way, compared with the event-triggered control strategy of traditional MAS systems, the embodiments of the present application can effectively improve the self-healing ability of the multi-agent network to cope with DoS network attacks.

[0101] In some embodiments, when the MAS system controls the agent based on the dynamic event-triggered control strategy, an additional non-negative dynamic variable can also be added to the trigger condition of the dynamic event-triggered control strategy to increase the average non-trigger range and thus shorten the trigger time. In this way, since less trigger time means less communication, the risk of the MAS system being attacked can be reduced while reducing the overall energy consumption of the MAS system.

[0102] In this case, the secure adaptive dynamic event-triggered control method for the multi-agent network system provided by the embodiments of the present application may further include, but is not limited to, the following steps:

[0103] Update the trigger condition of the dynamic event-triggered control strategy to increase the average non-trigger range of the Denial of Service attack.

[0104] When the MAS system controls the agent based on the dynamic event-triggered control strategy, during the operation, it can also update the triggering conditions of the dynamic event-triggered control strategy, thereby increasing the average non-triggering range of the DoS attack, and further shortening the triggering time for the DoS attack to trigger the state control of the agent.

[0105] In some embodiments, the step of "updating the triggering conditions of the dynamic event-triggered control strategy" may include the following steps:

[0106] Add a preset dynamic variable to the triggering conditions of the dynamic event-triggered control strategy to update the triggering conditions.

[0107] It should be noted that the preset dynamic variable can be the above-mentioned non-negative dynamic variable, which is used to extend the average event interval time, thereby increasing the average non-triggering range of the denial-of-service attack.

[0108] In order to increase the average non-triggering range of the DoS attack, the MAS system can add a dynamic variable for extending the average event interval time to the triggering conditions of the dynamic event-triggered control strategy, so as to update the triggering conditions, thereby increasing the average non-triggering range of the DoS attack, and further shortening the triggering time for the DoS attack to trigger the state control of the agent.

[0109] Exemplarily, the MAS system can add a dynamic variable to the triggering function of the dynamic event-triggered control strategy to update the triggering conditions of the dynamic event-triggered control strategy. For example, the MAS system can define the triggering function h i (t) as:

[0110]

[0111] where 0 < β < 1, γ i (t) is the added dynamic variable, and the definition of γ i (t) is:

[0112]

[0113] where η > 0, 0 < ξ < 1. Combining with γ i (t0) > 0, the dynamic interval variable can be deduced

[0114]

[0115] The embodiments of the present application can also update the triggering conditions of the control strategy through the MAS system for dynamic events, so as to increase the average non-triggering range of DoS attacks, and further shorten the triggering time for the agent to perform state control when a DoS attack is triggered. As Figure 4 shown, after adding an additional variable to the triggering condition, the number of times of triggering a DoS attack by the secure adaptive dynamic event-triggering control method (Theorem1) of the multi-agent network system provided by the embodiments of the present application is significantly reduced compared with the number of times of triggering a DoS attack by other existing strategies (Sampled-Data, Xu

[44] , Zhang

[40] , etc.). That is to say, by introducing a dynamically evolving internal variable into the triggering condition of the dynamic event-triggering control strategy, the event triggering time is reduced, which can further reduce the risk of the MAS system being attacked by DoS. Moreover, fewer triggering times mean less communication, so the overall energy consumption of the MAS system can be reduced while reducing the risk of being attacked.

[0116] In some embodiments, the MAS system can also add new conditions to the adaptive law, so as to ensure the boundedness of the adaptive parameters and the candidate Lyapunov function. Therefore, bounded consensus can be achieved even when the MAS system is under external interference.

[0117] Please refer to Figure 5 , Figure 5 which is a schematic diagram of the step flow of the secure adaptive dynamic event-triggering control method of the multi-agent network system provided by the embodiments of the present application in some other embodiments.

[0118] As Figure 5 shown, in some embodiments, the secure adaptive dynamic event-triggering control method of the multi-agent network system provided by the embodiments of the present application may further include, but is not limited to, step S501 and step S502 shown below.

[0119] Step S501: Update the adaptive law based on the external interference factors of the multi-agent network system to obtain an updated adaptive law.

[0120] During the operation of the MAS system, when different control laws are adopted based on the adaptive law to perform state control for different agents, the MAS system may also be suffering from or about to suffer from external interference factors. Add a term containing past information to the adaptive law to update the adaptive law, so as to obtain an updated adaptive law.

[0121] It should be noted that the term containing past information added by the MAS system to the adaptive law can ensure the boundedness of the adaptive parameters and the candidate Lyapunov function.

[0122] Exemplarily, the MAS system can add a term containing past information to the adaptive law, so as to update and adjust the above-mentioned adaptive law to:

[0123]

[0124] wherein, the weight μ>0, ρ is a positive constant, F is a gain matrix, and ρc i (t) is a term containing past information that can ensure the boundedness of the adaptive parameters and the candidate Lyapunov function.

[0125] Step S502: Based on the updated adaptive law, perform the steps of controlling the first agent among the multiple agents by using the first control law and controlling the second agent among the multiple agents by using the second control law.

[0126] After the MAS system updates the adaptive law to obtain the updated adaptive law, in the subsequent running process, it can adopt the updated adaptive law to run the process shown in the above-mentioned step S102 and its refinement steps, so that when the DoS attack meets the requirements of the triggering function of the dynamic event-triggered control strategy, different control laws are used to control the states of different agents.

[0127] The embodiment of the present application also slightly adjusts the adaptive law by adding an additional term containing past information to the adaptive law of the MAS system, so that the dynamic event-triggered control strategy enhances the robustness of the multi-agent network on the premise of ensuring the boundedness of the adaptive parameters and the Lyapunov function, and thus can resist the DoS attack with external interference.

[0128] Next, a complete embodiment of the secure adaptive dynamic event-triggered control method for the multi-agent network system proposed in the embodiment of the present application is presented.

[0129] In this embodiment, for the secure adaptive dynamic event-triggered control method for the multi-agent network system proposed in the embodiment of the present application, first, based on the relative state information among multiple agents, a secure adaptive event-triggered protocol is proposed; then, by adding a dynamic variable to the triggering condition, the average non-triggering range is increased, thereby shortening the triggering time; finally, a term containing past information is added to the adaptive law to ensure the boundedness of the adaptive parameters and the candidate Lyapunov function, so that bounded consensus of the leader-follower can be achieved even under external interference.

[0130] This embodiment can be implemented according to the following specific steps:

[0131] Based on the relative state information, a fully distributed adaptive event-triggered control protocol is proposed.

[0132] In this embodiment, as Figure 6 shown, the overall control strategy is divided into four parts: sensing, control, event triggering, and attack detection. First, the multi-agent network measures the relative state information between interconnected agents through sensing devices, and then transmits the information to the controller for calculation. The calculation result is then sent to the event-triggering mechanism (ETM) to decide whether to update the control law. At this time, if no attack is detected, the latest control law is sent to the actuator; otherwise, the control input is 0.

[0133] Among them, a linear multi-agent network usually has a leader and multiple followers. For example, Figure 7 the multi-agent network shown is composed of one leader and four followers, and the leader-follower consensus implemented on this network architecture is as Figure 8 shown. Among them, the dynamic equation of the multi-agent network can be expressed as:

[0134]

[0135] where, is the state of the leader, is the state of the follower, is the control input. Matrices A and B are system matrices and input matrices with appropriate dimensions.

[0136] The relative state information between agents can be defined as follows:

[0137]

[0138] where agent i only needs the state information of the two agents connected to it.

[0139] Since a DoS attack needs to accumulate energy to launch subsequent attacks, this results in time being divided into a sleep period and an attack period. In its attack period, the feedback control law is not adopted, while in the sleep period, the feedback control law with adaptive technology is adopted:

[0140]

[0141] where, u i (t) represents the control input to agent i, t ∈ Ξ s (t0, t) represents the sleep period of the DoS attack, t ∈ Ξ a (t0, t) represents the attack period, represents the kth triggering instant of agent i, is the relative state information sampled at time t k .

[0142] Obviously, different control laws need to be adopted for different state information, so the i adaptive law of can be determined by the following formula:

[0143]

[0144] where the weight μ > 0, ρ1 is a positive constant, and F is the gain matrix.

[0145] The difference between the theoretical state information of the agent and the state information obtained through the sensor is the state error, which can be expressed by the following formula:

[0146]

[0147] Adjust the control law of the agent according to the relative state information between agents, so that the error gradually shrinks and reaches stability, thereby realizing a fully distributed adaptive event-triggered control strategy.

[0148] Step 2: Add a dynamic variable to the triggering condition.

[0149] After using the event-triggered control strategy to reach stability, this embodiment proposes to add an additional non-negative dynamic variable to the triggering condition to increase the average non-triggering range.

[0150] The triggering function h i (t) is defined as follows:

[0151]

[0152] where 0 < β < 1, γ i (t) is the added dynamic variable, and its definition is:

[0153]

[0154] where η > 0, 0 < ξ < 1. Combining with γ i (t0) > 0, the dynamic interval variable can be deduced

[0155]

[0156] Since the core idea of event-triggered control is to reduce energy consumption as much as possible, adding the new variable γ i (t) reduces the triggering time, and less triggering time means less communication, so the risk of being attacked can also be reduced.

[0157] Step 3: Update the adaptive law.

[0158] In this embodiment, a term containing past information is added to the adaptive law to enhance the robustness of the system. Due to the existence of bounded external disturbances, the adaptive law can be modified into the following form:

[0159]

[0160] where the weight μ > 0, ρ is a positive constant, and F is a gain matrix. By using this method, the boundedness of the adaptive parameters and the candidate Lyapunov function can be guaranteed, and bounded consensus can be achieved even under external disturbances. Through minor adjustments, the robustness of this method against bounded external disturbances is realized.

[0161] Through the above steps 1 to 4 in this embodiment, a secure adaptive event-triggered control strategy for a linear multi-agent network system under DoS attacks can be finally realized and applied to the multi-agent network to mitigate the impact of DoS network attacks. Moreover, by introducing a dynamically evolving internal variable into the triggering condition to extend the time between events, the triggering time can be further reduced and the energy consumption can be lowered. In addition, research has shown that under DoS attacks, the method proposed in this embodiment can not only achieve exponential leader-following consensus without interference, but also resist external disturbances with only minor adjustments to the adaptive law.

[0162] Next, please refer to Figure 9 , this embodiment of the present application also provides a secure adaptive dynamic event-triggered control device for a multi-agent network system. The secure adaptive dynamic event-triggered control device for a multi-agent network system can be the control device in the above MAS system, or it can also be a device that can communicate with the above MAS system and control the MAS system. The secure adaptive dynamic event-triggered control device for a multi-agent network system can implement the secure adaptive dynamic event-triggered control method for the above multi-agent network system.

[0163] As Figure 9 shown, in some embodiments, the secure adaptive dynamic event-triggered control device for a multi-agent network system provided in this embodiment of the present application may include:

[0164] A state acquisition module, configured to acquire the relative state information among multiple agents in the multi-agent network system;

[0165] An agent control module, configured to control a first agent among the multiple agents by using a first control law and control a second agent among the multiple agents by using a second control law based on the relative state information to cope with denial-of-service attacks.

[0166] In some embodiments, the security adaptive dynamic event-triggering control device of the multi-agent network system provided by the embodiments of the present application may further include:

[0167] A detection module, configured to detect whether a denial-of-service attack meets the requirements of a preset trigger function, and obtain a detection result; the trigger function is a trigger function designed to adapt to the dynamic event-triggering control strategy;

[0168] The agent control module is further configured to, when the detection result indicates that the denial-of-service attack meets the requirements of the trigger function, based on the relative state information, control a first agent among the multiple agents by using a first control law, and control a second agent among the multiple agents by using a second control law.

[0169] In some embodiments, the security adaptive dynamic event-triggering control device of the multi-agent network system provided by the embodiments of the present application may further include:

[0170] A trigger condition update module, configured to update the trigger condition of the dynamic event-triggering control strategy to increase the average non-trigger range of the denial-of-service attack.

[0171] In some embodiments, the trigger condition update module is further configured to add a preset dynamic variable to the trigger condition of the dynamic event-triggering control strategy to update the trigger condition;

[0172] Wherein, the dynamic variable is used to extend the average event interval time to increase the average non-trigger range of the denial-of-service attack.

[0173] In some embodiments, the security adaptive dynamic event-triggering control device of the multi-agent network system provided by the embodiments of the present application may further include:

[0174] An adaptive law module, configured to update the adaptive law based on external interference factors of the multi-agent network system to obtain an updated adaptive law;

[0175] The agent control module is further configured to perform the steps of controlling a first agent among the multiple agents by using a first control law and controlling a second agent among the multiple agents by using a second control law based on the updated adaptive law.

[0176] In some embodiments, the agent control module is further configured to, during the sleep period of the denial-of-service attack, control a first agent among the multiple agents by using a first control law, and control a second agent among the multiple agents by using a second control law.

[0177] In some embodiments, the multiple agents include a leader agent and multiple follower agents;

[0178] The state acquisition module is further configured to define a first state of the leader agent and a second state of the multiple follower agents; determine relative state information between the leader agent and the multiple follower agents based on the first state and the multiple second states; and determine relative state information between the multiple follower agents based on the multiple second states.

[0179] It should be noted that the specific implementation manner of the monitoring system provided in the embodiments of the present application is basically the same as the specific embodiments of the above-mentioned security adaptive dynamic event-triggered control method for the multi-agent network system, and will not be elaborated here.

[0180] The embodiments of the present application further provide a security adaptive dynamic event-triggered control device for a multi-agent network system. The security adaptive dynamic event-triggered control device for a multi-agent network system includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the above-mentioned security adaptive dynamic event-triggered control method for the multi-agent network system is implemented. The security adaptive dynamic event-triggered control device for the multi-agent network system can be any intelligent terminal device including a tablet computer, an in-vehicle computer, etc.

[0181] Please refer to Figure 10 , Figure 10 which schematically shows the hardware structure of the security adaptive dynamic event-triggered control device for the multi-agent network system in some embodiments. The security adaptive dynamic event-triggered control device for the multi-agent network system may include:

[0182] A processor 1101, which can be implemented in a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, etc., and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present application;

[0183] The memory 1102 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM), etc. The memory 1102 can store an operating system and other application programs. When implementing the technical solutions provided in the embodiments of this specification through software or firmware, the relevant program codes are stored in the memory 1102 and are called by the processor 1101 to execute the security adaptive dynamic event-triggered control method of the multi-agent network system in the embodiments of this application;

[0184] The input / output interface 1103 is used to implement information input and output;

[0185] The communication interface 1104 is used to implement communication interaction between this device and other devices. Communication can be achieved through wired means (such as USB, network cable, etc.) or through wireless means (such as mobile network, WIFI, Bluetooth, etc.);

[0186] The bus 1105 transmits information between various components of the device (such as the processor 1101, the memory 1102, the input / output interface 1103, and the communication interface 1104);

[0187] Among them, the processor 1101, the memory 1102, the input / output interface 1103, and the communication interface 1104 are communicatively connected to each other inside the device through the bus 1105.

[0188] The embodiments of this application also provide a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it implements the above-mentioned security adaptive dynamic event-triggered control method of the multi-agent network system.

[0189] As a non-transitory computer-readable storage medium, the memory can be used to store non-transitory software programs and non-transitory computer-executable programs. In addition, the memory can include high-speed random access memory, and can also include non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state storage devices. In some embodiments, the memory can optionally include a memory remotely set relative to the processor, and these remote memories can be connected to the processor through a network. Examples of the above networks include but are not limited to the Internet, an enterprise intranet, a local area network, a mobile communication network, and combinations thereof.

[0190] The embodiments of this application also provide a computer program product. The computer program product stores a computer program, and when the computer program is executed by a processor, it implements the above-mentioned security adaptive dynamic event-triggered control method of the multi-agent network system.

[0191] The security adaptive dynamic event-triggered control device for a multi-agent network system, the security adaptive dynamic event-triggered control device for a multi-agent network system, the computer-readable storage medium, and the computer program product provided by the embodiments of the present application each obtain the relative state information between multiple agents in the multi-agent network system, and then, based on the relative state information, use a first control law to control a first agent among the multiple agents, and use a second control law to control a second agent among the multiple agents to cope with a denial-of-service attack.

[0192] In this way, by using the relative state information between agents and adopting different control laws to control multiple agents respectively to cope with the denial-of-service attack (DoS), that is, based on an adaptive technology that allows the control protocol to operate without any global network topology information. Since the advantage of the proposed protocol is that it relies on relative information rather than absolute information, it neither requires global network topology information nor a global coordinate frame, eliminating the dependence on the global coordinate frame and realizing a fully distributed implementation, which can effectively improve the self-healing ability of the multi-agent network to cope with DoS network attacks.

[0193] In addition, by introducing a dynamically evolving internal variable into the triggering condition of the dynamic event-triggered control strategy, the event triggering time is reduced, which can not only further reduce the risk of suffering from a DoS attack but also reduce energy consumption. And by adding new conditions to the adaptive law, the dynamic event-triggered control strategy enhances the robustness of the multi-agent network on the premise of ensuring the boundedness of the adaptive parameters and the candidate Lyapunov function, and can resist DoS attacks with external interference.

[0194] The embodiments described in the embodiments of the present application are for more clearly explaining the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided by the embodiments of the present application. Those skilled in the art can know that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of the present application are equally applicable to similar technical problems.

[0195] Those skilled in the art can understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and may include more or fewer steps than those shown in the figures, or combine some steps, or different steps.

[0196] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0197] Those of ordinary skill in the art can understand that all or some of the steps in the methods disclosed above, and the functional modules / units in systems and devices can be implemented as software, firmware, hardware, and their appropriate combinations.

[0198] In the specification of this application and the above-mentioned drawings, the terms "first", "second", "third", "fourth", etc. (if any) are used to distinguish similar objects and do not necessarily have to be used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances so that the embodiments of this application described here can be implemented in an order different from those illustrated or described here. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products, or devices.

[0199] It should be understood that in this application, "at least one (item)" means one or more, and "a plurality" means two or more. "And / or" is used to describe the association relationship of associated objects and indicates that there can be three relationships. For example, "A and / or B" can mean: only A exists, only B exists, and both A and B exist at the same time. Among them, A and B can be singular or plural. The character " / " generally means that the associated objects before and after are in an "or" relationship. "At least one (one) of the following" or its similar expression refers to any combination of these items, including any combination of single item (one) or plural items (ones). For example, at least one (one) of a, b, or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a, b, and c", where a, b, and c can be single or multiple.

[0200] In several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the above-mentioned unit division is only a logical function division, and there can be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection to each other can be through some interfaces, and the indirect coupling or communication connection of devices or units can be in electrical, mechanical, or other forms.

[0201] The units described above as separate components may or may not be physically separated. The components shown as units may or may not be physical units, that is, they may be located in one place or distributed over multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0202] In addition, each functional unit in various embodiments of the present application may be integrated into one processing unit, may exist separately as individual physical units, or two or more units may be integrated into one unit. The above integrated units can be implemented in the form of hardware or in the form of software functional units.

[0203] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods in various embodiments of the present application. The aforementioned storage medium includes: USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks, or optical discs and other various media that can store programs.

[0204] The preferred embodiments of the embodiments of the present application have been described above with reference to the accompanying drawings. However, this does not limit the scope of the rights of the embodiments of the present application. Any modifications, equivalent replacements, and improvements made by those skilled in the art without departing from the scope and essence of the embodiments of the present application shall fall within the scope of the rights of the embodiments of the present application.

Claims

1. A secure adaptive dynamic event-triggered control method for a multi-agent network system, characterized in that, The method includes: Obtaining the relative state information among multiple agents in a multi-agent network system; Based on the relative state information, using a first control law to control a first agent among the multiple agents, and using a second control law to control a second agent among the multiple agents to cope with a denial-of-service attack.

2. The method according to claim 1, wherein The method further includes: Detecting whether the denial-of-service attack meets the requirements of a preset trigger function to obtain a detection result; the trigger function is a trigger function designed for an adaptive event-triggered control strategy; The using a first control law to control a first agent among the multiple agents and using a second control law to control a second agent among the multiple agents based on the relative state information includes: In the case where the detection result indicates that the denial-of-service attack meets the requirements of the trigger function, based on the relative state information, using a first control law to control a first agent among the multiple agents, and using a second control law to control a second agent among the multiple agents.

3. The method according to claim 2, wherein The method further includes: Updating the trigger condition of the adaptive event-triggered control strategy to increase the average non-trigger range of the denial-of-service attack.

4. The method according to claim 3, wherein The updating the trigger condition of the adaptive event-triggered control strategy includes: Adding a preset dynamic variable to the trigger condition of the adaptive event-triggered control strategy to update the trigger condition; wherein the dynamic variable is used to extend the average event interval time to increase the average non-trigger range of the denial-of-service attack.

5. The method according to claim 1, characterized in that, The method further includes: Updating an adaptive law based on the external interference factors of the multi-agent network system to obtain an updated adaptive law; Based on the updated adaptive law, performing the steps of using a first control law to control a first agent among the multiple agents and using a second control law to control a second agent among the multiple agents.

6. The method according to any one of claims 1 to 5, characterized in that, The using a first control law to control a first agent among the multiple agents and using a second control law to control a second agent among the multiple agents includes: During the sleep period of the denial-of-service attack, using a first control law to control a first agent among the multiple agents, and using a second control law to control a second agent among the multiple agents.

7. The method according to claim 1, wherein The multiple agents include a leader agent and multiple follower agents; The obtaining the relative state information among multiple agents in a multi-agent network system includes: Defining a first state of the leader agent and defining second states of the multiple follower agents; Determining the relative state information between the leader agent and the multiple follower agents based on the first state and the multiple second states; Determining the relative state information among the multiple follower agents based on the multiple second states.

8. A security adaptive dynamic event-triggered control device for a multi-agent network system, characterized in that, The device includes: A state acquisition module, configured to obtain the relative state information among multiple agents in a multi-agent network system; The agent control module is used to control a first agent among the multiple agents based on the relative state information by using a first control law, and to control a second agent among the multiple agents by using a second control law to cope with a denial-of-service attack.

9. A security adaptive dynamic event-triggered control device for a multi-agent network system, characterized in that, The security adaptive dynamic event-triggered control device of the multi-agent network system includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the security adaptive dynamic event-triggered control method of the multi-agent network system according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the security adaptive dynamic event-triggered control method of the multi-agent network system according to any one of claims 1 to 7.

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