Control method of networked unmanned system based on event-triggered strategy with memory function

Abstract

The present invention discloses a control method for a networked unmanned system under an event-triggered strategy with a memory function, comprising the following steps: S100, establishing a state space model of the networked unmanned system; S200, establishing a deception attack model with limited energy to describe the intermittent time characteristics of the attack; S300, first, designing an event trigger mechanism with a memory function; secondly, designing an anti-deception attack controller; then, based on Lyapunov stability theory, deriving controller parameter conditions to ensure system stability, and converting nonlinear matrix constraints into linear matrix inequalities; S400, obtaining the weight matrix and controller gain parameters of the event trigger mechanism by solving the linear matrix inequality, thereby achieving safe and stable control of the unmanned system under deception attacks. While improving communication efficiency with the help of an event trigger mechanism with a memory function, the present invention can also ensure the safe and stable operation of the system when deception attacks tamper with some key data.

Description

Technical Field

[0001] The present invention relates to the technical field of networked unmanned vehicle control, and in particular to a control method for a networked unmanned system under an event triggering strategy with a memory function. Background Art

[0002] With the development of network communication technologies, networked unmanned vehicle systems (such as self-driving cars and drones) are increasingly being used in transportation, logistics, military, and other fields. However, these systems typically rely on wireless communication networks (such as 5G and Wi-Fi) for data transmission, but communication bandwidth and energy resources are limited, which can lead to data transmission delays or loss.

[0003] Furthermore, vehicle systems have high real-time requirements. Unmanned vehicles must respond in real time in complex environments. Traditional periodic control strategies can waste communication resources or inadequate control precision. Furthermore, networked vehicle systems, due to their network communication, are vulnerable to cyber spoofing attacks. Hackers can tamper with critical system data, disrupting normal operation. Such attacks can potentially lead to system loss of control or accidents. Summary of the Invention

[0004] This invention proposes a communication solution based on event triggering with memory. This event triggering mechanism with memory improves communication efficiency for unmanned systems while ensuring secure and stable operation in the event of spoofing attacks that tamper with critical data. This event triggering mechanism with memory can mitigate the impact of spoofing attacks, reduce the burden on network communications, improve efficiency, and ensure the safe operation of networked unmanned systems.

[0005] To achieve the above object, the present invention provides the following technical solution: a control method for a network unmanned system under an event triggering strategy with a memory function, comprising the following steps:

[0006] S100. Establish a state space model for the networked unmanned system, defining the system state, control input, external disturbance, and output variables;

[0007] S200, establishing a deception attack model with limited energy, describing the intermittent time characteristics of the attack: including the start time, duration interval, closing time interval and closing time of each round of attack;

[0008] S300. First, design an event trigger mechanism with memory function:

[0009] Store historical trigger data packets and record the most recently released M data packets. At the sampling time, extract the calculation errors corresponding to the most recently triggered M data packets, calculate the weighted combination of the above M error values, compare the weighted combination result with the function value of the current system state, and decide whether to trigger new data transmission based on the comparison result;

[0010] Second, design a controller that is resistant to spoofing attacks:

[0011] Define attack flag parameters to distinguish the system attack status;

[0012] When the attack flag indicates that there is no attack, a control input is generated using the latest trigger data packet;

[0013] When the attack flag indicates an attack, the tampered system state data is used to generate a control input;

[0014] Then, based on Lyapunov stability theory, the controller parameter conditions that ensure system stability are derived, and the nonlinear matrix constraints are transformed into linear matrix inequalities.

[0015] S400. By solving linear matrix inequalities, the weight matrix and controller gain parameters of the event trigger mechanism are obtained, and the controller input and trigger strategy parameters are collaboratively designed to achieve safe and stable control of the unmanned system under deception attacks.

[0016] The state-space model:

[0017]

[0018] in is the system state vector, is the system input, is the measurable system output, is the external disturbance of the system, is the external output of the system, the matrix , , , , , is a constant matrix of appropriate dimensions.

[0019] The energy-limited deception attack in step S200 can be modeled by the following time interval:

[0020]

[0021] Among them, the symbol For the The start time of the round attack, symbol For the The duration interval of the round spoofing attack, symbol For the The duration of the round of spoofing attack, The closing time interval of the round spoofing attack is symbol , No. The closing time of the round spoofing attack is symbol .

[0022] In step S300, an event triggering mechanism with a memory function is designed:

[0023]

[0024] Among them, the symbol It is the trigger moment of the future, is the latest triggering moment of the system, is the sampling time of the system, Indicates recent The number of packets released, error Based on the recently released The error calculated for each data packet is , the symbol is is the error weight, is the event trigger threshold parameter, the latest trigger mean, yes Event trigger mechanism weight moment.

[0025] In step S300, an anti-spoofing attack controller is designed based on an event triggering mechanism with a memory function:

[0026]

[0027] Among them, the symbol Used to describe whether the system is under attack. When it is detected, it indicates that the system is under a deception attack;

[0028] when When , it means that the system is not attacked by deception, and its mathematical expectation is:

[0029] is the controller gain to be designed, For data packets transmitted and stored in the controller, the interval is: , It is a system state that is replaced due to a spoofing attack on data during transmission.

[0030] The step S300 further includes:

[0031] Based on the design of an event trigger mechanism with memory function and the design of an anti-spoofing attack controller, the condition matrix that can meet the system stability is given as follows:

[0032] When there is a positive constant ,matrix , so that the positive definite matrix and matrix To make the system stable, the following relationship is satisfied:

[0033]

[0034] in:

[0035]

[0036]

[0037]

[0038]

[0039]

[0040]

[0041]

[0042] .

[0043] The step S300 further includes:

[0044] Linearize the nonlinear condition matrix given by the condition matrix that satisfies the system stability. ,matrix , so that the positive definite matrix and matrix The system is stable if the following relationship is satisfied:

[0045]

[0046] in:

[0047]

[0048]

[0049]

[0050]

[0051]

[0052]

[0053] .

[0054] The design of the controller input in step S400 specifically includes the following steps:

[0055] S401, based on steps S100-S300, the given parameters Substituting the given conditional linear matrix inequality, the controller gain of the unmanned system can be obtained , the weight matrix of the event trigger mechanism ;

[0056] Combined with the actual physical meaning, the following state space matrix parameters of the unmanned vehicle system are given:

[0057]

[0058] By passing the given parameters

[0059] , substituting into the given conditional linear matrix inequality, we can obtain the controller gain of the unmanned system and the weight matrix of the event trigger mechanism as follows:

[0060] .

[0061] A control system under a memory event trigger control strategy includes the following modules:

[0062] An event trigger unit based on memory function has the function of caching data packets and combining these data packet information to determine whether these data packets are transmitted to the network controller;

[0063] The system calculation unit is used to calculate the controller gains and event trigger parameters that can ensure stable operation of the system based on the event trigger mechanism with memory function when the system is attacked by deception, using the conditions of S300;

[0064] Networked unmanned system control unit for final design controller input.

[0065] Compared with the prior art, the present invention has the following beneficial effects:

[0066] While improving communication efficiency with the help of an event trigger mechanism with a memory function, the present invention can also ensure the safe and stable operation of the system in the event of deception attacks and tampering of some key data. The event trigger mechanism with a memory function can reduce the impact of deception attacks, alleviate the burden of network communication, improve efficiency, and ensure the safe operation of networked unmanned systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] Figure 1 Schematic diagram of the method flow of the present invention;

[0068] Figure 2 This is a diagram of the simulation results of the event trigger interval of the present invention;

[0069] Figure 3 This is a simulation result diagram of the state response of the unmanned vehicle system of the present invention. DETAILED DESCRIPTION

[0070] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0071] See also Figure 1-3 The present invention provides a technical solution: a control method for a network unmanned system under an event triggering strategy with a memory function, comprising the following steps:

[0072] S100. Establish a state space model for the networked unmanned system, defining the system state, control input, external disturbance, and output variables;

[0073] S200, establishing a deception attack model with limited energy, describing the intermittent time characteristics of the attack: including the start time, duration interval, closing time interval and closing time of each round of attack;

[0074] S300. First, design an event trigger mechanism with memory function:

[0075] Store historical trigger data packets and record the most recently released M data packets. At the sampling time, extract the calculation errors corresponding to the most recently triggered M data packets, calculate the weighted combination of the above M error values, compare the weighted combination result with the function value of the current system state, and decide whether to trigger new data transmission based on the comparison result;

[0076] Second, design a controller that is resistant to spoofing attacks:

[0077] Define attack flag parameters to distinguish the system attack status;

[0078] When the attack flag indicates that there is no attack, a control input is generated using the latest trigger data packet;

[0079] When the attack flag indicates an attack, the tampered system state data is used to generate a control input;

[0080] Then, based on Lyapunov stability theory, the controller parameter conditions that ensure system stability are derived, and the nonlinear matrix constraints are transformed into linear matrix inequalities.

[0081] S400. By solving linear matrix inequalities, the weight matrix and controller gain parameters of the event trigger mechanism are obtained, and the controller input and trigger strategy parameters are collaboratively designed to achieve safe and stable control of the unmanned system under deception attacks.

[0082] The state-space model:

[0083]

[0084] in is the system state vector, is the system input, is the measurable system output, is the external disturbance of the system, is the external output of the system, the matrix , , , , , is a constant matrix of appropriate dimensions.

[0085] When a system is attacked by spoofing, the attacker usually tampered with the data sent by the sampler to the event trigger in an extremely covert way.

[0086] The system cannot detect this covert attack behavior, resulting in the controller receiving the system status being tampered with and erroneous data, which will cause the controller to make incorrect judgments about the system status and give incorrect control behaviors.

[0087] Due to the limitations of network communication security protocols, attackers cannot always tamper with data, and deception attacks are subject to certain time limits. The attack starts at a certain point in time and lasts for a certain duration.

[0088] The energy-limited spoofing attack can be modeled by the following time interval:

[0089]

[0090] Among them, the symbol For the The start time of the round attack, symbol For the The duration interval of the round spoofing attack, symbol For the The duration of the round of spoofing attack, The closing time interval of the round spoofing attack is symbol , No. The closing time of the round spoofing attack is symbol .

[0091] The step S300 designs an event triggering mechanism with a memory function:

[0092] To reduce the harm caused by spoofing attacks to the system, this invention designs a trigger mechanism with a memory function to reduce this impact. This mechanism can store previous trigger data and comprehensively consider this data to determine whether the sampled data is transmitted to the network controller. This mechanism can be described as follows:

[0093]

[0094] Among them, the symbol It is the trigger moment of the future, is the latest triggering moment of the system, is the sampling time of the system, Indicates recent The number of packets released, error Based on the recently released The error calculated for each data packet is , the symbol is is the error weight, is the event trigger threshold parameter, the latest trigger mean, yes Event trigger mechanism weight moment.

[0095] The step S300 is based on the design of a controller with an event trigger mechanism having a memory function:

[0096]

[0097] Among them, the symbol Used to describe whether the system is under attack. When it is detected, it indicates that the system is under a deception attack;

[0098] when When , it means that the system is not attacked by deception, and its mathematical expectation is:

[0099] is the controller gain to be designed, For data packets transmitted and stored in the controller, the interval is: , It is a system state that is replaced due to a spoofing attack on data during transmission.

[0100] The step S300 further includes: providing a condition matrix that can satisfy system stability based on the design of an event trigger mechanism with a memory function and the design of an anti-spoofing attack controller as follows:

[0101] When there is a positive constant ,matrix , so that the positive definite matrix and matrix To make the system stable, the following relationship is satisfied:

[0102]

[0103] in:

[0104]

[0105]

[0106]

[0107]

[0108]

[0109]

[0110]

[0111] .

[0112] The step S300 further includes: performing linearization processing on the nonlinear condition matrix given by the condition matrix that satisfies the system stability, and when there is a positive constant ,matrix , so that the positive definite matrix and matrix The system is stable if the following relationship is satisfied:

[0113]

[0114] in:

[0115]

[0116]

[0117]

[0118]

[0119]

[0120]

[0121] .

[0122] The design of the controller input in step S400 specifically includes the following steps:

[0123] S401, based on steps S100-S300, the given parameters Substituting the given conditional linear matrix inequality, the controller gain of the unmanned system can be obtained , the weight matrix of the event trigger mechanism ;

[0124] Combined with the actual physical meaning, the following state space matrix parameters of the unmanned vehicle system are given:

[0125]

[0126] Its networked control system architecture is as follows Figure 1 shown.

[0127] By passing the given parameters

[0128] , substituting into the given conditional linear matrix inequality, we can get the controller gain of the unmanned system;

[0129] The weight matrix of the event trigger mechanism is as follows:

[0130] .

[0131] The above solution parameters are simulated, and the simulation results are shown in the figure below. Figure 2 and Figure 3 As shown, it can be seen that the event triggering interval is relatively sparse. When the system is attacked by deception, the system can still operate stably. This shows that the application of the memory event triggering mechanism in unmanned systems can effectively reduce the communication pressure and reduce the impact of deception attacks on the system.

[0132] A control system under a memory event trigger control strategy includes the following modules:

[0133] An event trigger unit based on memory function has the function of caching data packets and combining these data packet information to determine whether these data packets are transmitted to the network controller;

[0134] The system calculation unit is used to calculate the controller gains and event trigger parameters that can ensure stable operation of the system based on the event trigger mechanism with memory function when the system is attacked by deception, using the conditions of S300;

[0135] Networked unmanned system control unit for final design controller input.

[0136] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

Claims

1. A control method for a networked unmanned system under an event-triggered strategy with a memory function, characterized in that: The following steps are involved: S100. Establish a state space model for the networked unmanned system, defining the system state, control input, external disturbance, and output variables; S200, establish a deception attack model with limited energy and describe the intermittent time characteristics of the attack; S300. First, design an event trigger mechanism with memory function: Store historical triggered data packets, record the data packets, extract the calculation errors corresponding to the most recent M triggered data packets at the sampling time, calculate the weighted combination result of the above M error values, compare the weighted combination result with the function value of the current system state, and decide whether to trigger new data transmission based on the comparison result; Second, design a controller that is resistant to spoofing attacks: Define attack flag parameters to distinguish the system attack status; When the attack flag indicates that there is no attack, a control input is generated using the latest trigger data packet; When the attack flag indicates an attack, the tampered system state data is used to generate a control input; Then, based on Lyapunov stability theory, the controller parameter conditions to ensure system stability are derived, and the nonlinear matrix constraints are transformed into linear matrix inequalities. S400. By solving linear matrix inequalities, the weight matrix and controller gain parameters of the event trigger mechanism are obtained, and the controller input and trigger strategy parameters are collaboratively designed to achieve safe and stable control of the unmanned system under deception attacks.

2. The control method of a network unmanned system under an event-triggered strategy with a memory function according to claim 1, characterized in that: The state-space model: in is the system state vector, is the system input, is the measurable system output, is the external disturbance of the system, is the external output of the system, the matrix , , , , , is a constant matrix of appropriate dimensions.

3. The control method of a network unmanned system under an event-triggered strategy with a memory function according to claim 1, characterized in that: The energy-limited deception attack in step S200 can be modeled by the following time interval: Among them, the symbol For the The start time of the round attack, symbol For the The duration interval of the round spoofing attack, symbol For the The duration of the round of spoofing attack, The closing time interval of the round spoofing attack is symbol , No. The closing time of the round spoofing attack is symbol .

4. The control method of a network unmanned system under an event-triggered strategy with a memory function according to claim 1, characterized in that: In step S300, an event triggering mechanism with a memory function is designed: Among them, the symbol It is the trigger moment of the future, is the latest triggering moment of the system, is the sampling time of the system, , Indicates recent The number of packets released, error Based on the recently released The error calculated for each data packet is , the symbol is is the error weight, is the event trigger threshold parameter, the latest trigger mean, yes Event trigger mechanism weight moment.

5. The control method of a network unmanned system under an event-triggered strategy with a memory function according to claim 1, characterized in that: In step S300, an anti-spoofing attack controller is designed based on an event triggering mechanism with a memory function: Among them, the symbol Used to describe whether the system is under attack. When it is detected, it indicates that the system is under a deception attack; when When , it means that the system is not attacked by deception, and its mathematical expectation is: is the controller gain to be designed, For data packets transmitted and stored in the controller, the interval is: , It is a system state that is replaced due to a spoofing attack on data during transmission.

6. The control method of a network unmanned system under an event-triggered strategy with a memory function according to claim 1, characterized in that: The step S300 further includes: providing a condition matrix that can satisfy system stability based on the design of an event trigger mechanism with a memory function and the design of an anti-spoofing attack controller as follows: When there is a positive constant ,in ,matrix , so that the positive definite matrix and matrix To make the system stable, the following relationship is satisfied: in: 。 7. The control method of a network unmanned system under an event-triggered strategy with a memory function according to claim 1, characterized in that: The step S300 further includes: performing linearization processing on the nonlinear condition matrix given by the condition matrix that satisfies the system stability, and when there is a positive constant ,in ,matrix , so that the positive definite matrix and matrix The system is stable if the following relationship is satisfied: in: 。 8. The control method of a network unmanned system under an event-triggered strategy with a memory function according to claim 1, characterized in that: The design of the controller input in step S400 specifically includes the following steps: S401, based on steps S100-S300, the given parameters ,in , substituting the given conditional linear matrix inequality, we can get the controller gain of the unmanned system , the weight matrix of the event trigger mechanism ; Combined with the actual physical meaning, the following state space matrix parameters of the unmanned vehicle system are given: By passing the given parameters , substituting into the given conditional linear matrix inequality, we can obtain the controller gain of the unmanned system and the weight matrix of the event trigger mechanism as follows: 。 9. A control system under a memory event triggering control strategy, used to implement the control method of a network unmanned system under an event triggering strategy with a memory function as described in any one of claims 1 to 8, characterized in that: Includes the following modules: An event trigger unit based on memory function has the function of caching data packets and combining these data packet information to determine whether these data packets are transmitted to the network controller; The system calculation unit is used to calculate the controller gains and event trigger parameters that can ensure stable operation of the system based on the event trigger mechanism with memory function when the system is attacked by deception, using the conditions of S300; Networked unmanned system control unit for final design controller input.

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