CN114070582B - Event trigger control method and system - Google Patents

Event trigger control method and system Download PDF

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CN114070582B
CN114070582B CN202111189483.0A CN202111189483A CN114070582B CN 114070582 B CN114070582 B CN 114070582B CN 202111189483 A CN202111189483 A CN 202111189483A CN 114070582 B CN114070582 B CN 114070582B
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network attack
information physical
time
random network
state
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CN114070582A (en
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侯林林
罗文德
孙海滨
杨东
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Qufu Normal University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00—Network architectures or network communication protocols for network security
    • H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
    • H04L63/1408—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic by monitoring network traffic
    • H04L63/1416—Event detection, e.g. attack signature detection
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/14—Network analysis or design
    • H04L41/145—Network analysis or design involving simulating, designing, planning or modelling of a network
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00—Network architectures or network communication protocols for network security
    • H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
    • H04L63/1441—Countermeasures against malicious traffic

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  • Engineering & Computer Science (AREA)
  • Computer Security & Cryptography (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
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Abstract

The invention discloses an event triggering control method and system, wherein the method comprises the following steps: based on the switching information physical system receiving random network attacks in various different forms, establishing a switching information physical system model; transmitting data by using an event trigger control method; and designing a switching signal and a state feedback controller by adopting a mode dependent average residence time method. The invention provides an event trigger control method for switching information physical systems under random network attack, which ensures that the performance of the information physical systems is improved under the influence of the random network attack.

Description

Event trigger control method and system
Technical Field
The invention relates to the technical field of information physical systems, in particular to an event trigger control method and an event trigger control system for switching the information physical system under random network attack.
Background
In recent years, with the rapid development of computing, communication and intelligent control technologies, the information physical system realizes on-demand response and dynamic optimization of resource allocation and operation due to interaction and coordination of various elements in a physical space and a network space, and research on the information physical system becomes a hot spot problem. In addition, the stability analysis and control of the switching system are widely focused by people, and great achievements are achieved due to practical value. Because the switching system is a hybrid system and has features that can approximate complex nonlinear processes, it can be used to describe and model the behavior of complex systems. It is due to this superior property that many complex systems are modeled as switching systems. Thus, the information physical system acts as a multidimensional complex system and can also be modeled as a switching system.
In the information physical system, the controller and the sensor communicate through a network, however, due to the more open and shared network and communication, the information physical system becomes more sensitive to external environmental influences, and in particular, they are vulnerable to malicious network attacks, so that the system performance is reduced and the stability is destroyed. Moreover, information physical systems are commonly used for a number of critical large infrastructures, and the occurrence of malicious network attacks may threaten national security and social stability, causing huge economic losses.
The security problem of information physical systems is to be solved and becomes a very challenging problem. In addition, in order to solve the shortages that the periodical control scheme sometimes occupies network bandwidth and wastes computing resources, event-triggered control is proposed to reduce the unnecessary wastes, save system resources and reduce network load. In practical systems, there is typically a threat of random network attacks, so it is necessary to study the problem of alleviating network load and controller design for attacks in case of attacks.
The invention comprises the following steps:
the invention aims to provide an event trigger control method and an event trigger control system for a switching information physical system under random network attack.
In order to achieve the above object, in one aspect, the present invention provides an event trigger control method, including:
s100, based on the switching information physical system receiving random network attacks in various different forms, establishing a switching information physical system model;
s200, transmitting data by using an event trigger control method;
s300, designing a switching signal and a state feedback controller by adopting a mode dependent average residence time method.
In a preferred embodiment, in S100, the handover information physical system Σ is:
wherein x (t) ∈R n ,u(t)∈R m Respectively representing the state and control input of the system, R represents a real number set, R n And R is R m Respectively representing n-dimensional real vector space and m-dimensional real vector space, n and m can be arbitrarily selected to be positive integers greater than or equal to 1, sigma (t) is a switching signal which is a piecewise constant function in a finite setWherein M is a subsystemThe number of systems defines the switching sequence as +.>Where N is a natural number set, when σ (t i )＝h i At the time of the h i The individual subsystem is activated and additionally +.>A i ∈R n×n And B i ∈R n×m Is a known constant matrix with corresponding dimensions.
In a preferred embodiment, in S100, the system receives two random network attacks with different characteristics, where the two random network attacks are represented by two nonlinear functions:
β(t)f 1 (x(t-d(t)))+(1-β(t))f 2 (x(t-η(t))),
wherein f 1 (x (t)) and f 2 (x (t)) represents two different characteristics of random network attack, d (t) E [0, d M ]Sum eta (t) epsilon [0, eta M ]Respectively corresponding network attack time delay, d M > 0 and eta M > 0 represents the maximum delay of two network attacks, and the random variables alpha (t) and beta (t) obey probabilities, respectivelyAnd probability->And whether the random network attack occurs is controlled by a bernoulli distribution variable α (t); said f 1 (x (t)) and f 2 (x (t)) satisfies the following condition:
f 1 T (x(t))f 1 (x(t))≤x T (t)G T Gx(t),
where G and H are known constant matrices that represent the upper bound of a network attack.
In a preferred embodiment, the bernoulli distribution variable α (t) =1 indicates that the system is under random network attack, and the bernoulli distribution variable α (t) =0 indicates that the system is not under network attack, and the data is normally transmitted; bernoulli distribution variable β (t) =1 represents the network attack f 1 (x (t-d (t))), bernoulli distribution variable β (t) =0 represents network attack f 2 (x (t-eta (t))).
In a preferred embodiment, in S200, a state x (t) k h) The event trigger conditions for whether released are:
wherein t is k h and t k+1 h represents the latest trigger time and the next trigger time respectively, h is the sampling period, N is a natural number set, t k h+l k h represents the current sampling instant, x (t k h) Is the system state at the latest trigger time, x (t k h+l k h) System state at current sampling instant e k (t)＝x(t k h)-x(t k h+l k h) Is the corresponding state difference between the two states, scalar delta i E (0, 1) is the event trigger parameter, Ω 1i > 0 andis a positive symmetric weight matrix, +.>Is a finite set of subsystem numbers and σ (t) is the switching signal.
In a preferred embodiment, in S300, the state feedback controller is designed to:
wherein K is σ(t) Gain for controllerSigma (t) is a switching signal, u (t) is a system input, f 1 (x (t-d (t))) and f 2 (x (t-eta (t))) represents random network attacks of two different characteristics, d (t) and eta (t) are respectively corresponding network attack time delays, x (t-tau (t)) is a system state, tau (t) is a system time delay, alpha (t) and beta (t) are Bernoulli distribution variables respectively representing whether attacks occur and which characteristics of attacks occur,representing the state difference between the sampling instant and the triggering instant, < + >>ι＝0,1，...，ι k -1，/>0≤τ(t)≤τ M ，/>Is the sampling time, h is the sampling period, τ M Is the maximum system time lag.
In a preferred embodiment, the switching signal meets the following requirements:
wherein τ ai For the mode dependent average residence time,the minimum modal dependence mean residence time obtained for the solution +.>Is a finite set of subsystem numbers, θ i > 0 and mu i > 1 is a given constant for adjusting the modality dependent average residence time.
In another aspect, the present invention provides an event-triggered control system, including:
the model building unit is used for building a switching information physical system model based on the fact that the switching information physical system receives random network attacks in various different forms;
the event trigger control unit is used for transmitting data by using an event trigger control method;
and the state feedback controller design unit is used for designing the switching signal and the state feedback controller by adopting a mode dependent average residence time method.
Compared with the prior art, the invention has the following beneficial effects: the invention designs an event trigger control method for an information physical system under random network attack, considers that the system is under random network attack in various forms for one type of switching information physical system, adopts event trigger strategy to design a state feedback controller for saving system resources and relieving network load by analyzing and modeling the attacked system, eliminates the influence of the random network attack on the system, designs a switching signal by using a mode dependent average residence time method, and ensures the mean square index stability of the system. Therefore, the event trigger control method for switching the information physical system under the random network attack, which is designed by the invention, ensures that the performance of the information physical system is improved under the influence of the random network attack.
Description of the drawings:
FIG. 1 is a schematic flow chart of the method of the present invention;
fig. 2 is a block diagram of the system of the present invention.
The specific embodiment is as follows:
the following detailed description of specific embodiments of the invention is, but it should be understood that the invention is not limited to specific embodiments.
Throughout the specification and claims, unless explicitly stated otherwise, the term "comprise" or variations thereof such as "comprises" or "comprising", etc. will be understood to include the stated element or component without excluding other elements or components.
As shown in fig. 1, the event trigger control method disclosed by the invention comprises the following steps:
s100, based on the switching information physical system receiving random network attacks in various different forms, a switching information physical system model is built.
Specifically, in this step, the handover information physical system Σ is specifically:
wherein x (t) ∈R n ,u(t)∈R m Respectively representing the state and control input of the system, R represents a real number set, R n And R is R m Respectively representing n-dimensional real vector space and m-dimensional real vector space, n and m can be arbitrarily selected to be positive integers greater than or equal to 1, sigma (t) is a switching signal which is a piecewise constant function in a finite setWherein M is the number of subsystems, defining a switching sequence as +.>Where N is a natural number set, when σ (t i )＝h i At the time of the h i The individual subsystem is activated and additionally +.>A i ∈R n×n And B i ∈R n×m Is a known constant matrix= with corresponding dimensions. The switching signal refers to a subsystem that is switched to the subsystem corresponding to the time at the time t, for example: at t 1 At the moment, according to the switching sequence, the h 1 The subsystem is activated, switching to h 1 And a subsystem.
If the number of subsystems in the system is 3, i.e. m=3, then the system matrix a σ(t) Respectively A 1 、A 2 、A 3 ，B σ(t) Respectively B 1 、B 2 And B 3 ：
Considering that the switching information physical system receives two different types of random network attacks, the random network attacks with two different characteristics can be described by the following two nonlinear functions:
β(t)f 1 (x(t-d(t)))+(1-β(t))f 2 (x(t-η(t))),
wherein f 1 (x (t)) and f 2 (x (t)) represents two different characteristics of random network attack, d (t) E [0, d M ]Sum eta (t) epsilon [0, eta M ]Respectively corresponding network attack time delay, d M > 0 and eta M > 0 represents the maximum delay of two network attacks, and the random variables alpha (t) and beta (t) obey probabilities, respectivelyAnd probability->And whether the random network attack occurs is controlled by a bernoulli distribution variable α (t). Specifically, the bernoulli distribution variable α (t) =1 indicates that the system is under random network attack, and the bernoulli distribution variable α (t) =0 indicates that the system is not under network attack, and data is normally transmitted; bernoulli distribution variable β (t) =1 represents the network attack f 1 (x (t-d (t))), bernoulli distribution variable β (t) =0 represents network attack f 2 (x (t-eta (t))).
Said f 1 (x (t)) and f 2 (x (t)) satisfiesThe following conditions were:
f 1 T (x(t))f 1 (x(t))≤x T (t)G T Gx(t),
where G and H are known constant matrices that represent the upper bound of a network attack.
Random network attacks as two different features can be described by the following two nonlinear functions:
the known constant matrices G and H are diag {0.03,0.5} and diag {0.5,0.2} respectively.
It should be noted that only two different kinds of network attacks are used, such as other attack f i (x (t)) the following inequality needs to be satisfied:
f i T (x(t))f i (x(t))≤x T (t)L i T L i x(t),
wherein L is i Is a known constant matrix representing the upper bound of network attacks.
S200, transmitting data by using an event trigger control method.
Specifically, in this step, in order to reduce the communication load of the network, an event-triggered scheme is employed, and the system state x (t k h) Whether released is determined by the following event trigger conditions:
wherein t is k h and t k+1 h represents the latest trigger time and the next trigger time respectively, h is the sampling period, N is a natural number set, t k h+l k h represents the current sampling instant, x (t k h) Is the latest touchSystem state at time of issue, x (t k h+l k h) System state at current sampling instant e k (t)＝x(t k h)-x(t k h+l k h) Is the corresponding state difference between the two states, scalar delta i E (0, 1) is the event trigger parameter, Ω 1i > 0 andis a positive symmetric weight matrix, +.>Is a finite set of subsystem numbers and σ (t) is the switching signal. By using two different weight matrices Ω 1i And omega 2i Can increase its flexibility, and in addition, the threshold value parameter delta i Affecting the release frequency of the data.
Such as event trigger parameter delta 1 ＝0.1、δ 2 =0.2 and δ 3 =0.3, matrix can be obtained:
s300, designing a switching signal and a state feedback controller by adopting a mode dependent average residence time method.
Specifically, in this step, the state feedback controller is designed to:
wherein K is σ(t) For the controller gain, σ (t) is the switching signalThe number u (t) is the system input, f 1 (x (t-d (t))) and f 2 (x (t-eta (t))) represents random network attacks of two different characteristics, d (t) and eta (t) are respectively corresponding network attack time delays, x (t-tau (t)) is a system state, tau (t) is a system time delay, alpha (t) and beta (t) are Bernoulli distribution variables respectively representing whether attacks occur and which characteristics of attacks occur,representing the state difference between the sampling instant and the triggering instant, < + >>ι＝0,1，...，ι k -1，/>0≤τ(t)≤τ M ，/>Is the sampling time, h is the sampling period, τ M Is the maximum system time lag. Interval t k h,t k+1 h) Can be divided into [ t ] k h+ιh,t k h+(ι+1)h,ι＝0,1,...，ι k -2]And [ t ] k h+(ι k -1)h,t k+ 1 h]。
The switching signal meets the following requirements:
wherein τ ai For the mode dependent average residence time,the minimum modal dependence mean residence time obtained for the solution +.>Is a finite set of subsystem numbers, θ i > 0 and mu i The number > 1 is a given constant and,for adjusting the modality dependent average residence time.
In correspondence to the above-mentioned event trigger control method, as shown in fig. 2, the disclosed event trigger control system includes:
the model building unit is used for building a switching information physical system model based on the fact that the switching information physical system receives random network attacks in various different forms;
the event trigger control unit is used for transmitting data by using an event trigger control method;
and the state feedback controller design unit is used for designing the switching signal and the state feedback controller by adopting a mode dependent average residence time method.
The principle of each module may refer to the descriptions in the steps S100 to S200, and the description is omitted herein.
The invention has the advantages that the invention designs an event trigger control method for the information physical system under random network attack, considers that the system is under random network attack in different forms for one type of switching information physical system, analyzes and models the attacked system, adopts an event trigger strategy to save system resources and lighten network load, designs a state feedback controller, eliminates the influence of the random network attack on the system, designs a switching signal by adopting a mode dependent average residence time method, and ensures the mean square index stability of the system. Therefore, the event trigger control method for switching the information physical system under the random network attack, which is designed by the invention, ensures that the performance of the information physical system is improved under the influence of the random network attack.
It should be noted that what is not described in detail in the present specification belongs to the prior art known to those skilled in the art.
The foregoing descriptions of specific exemplary embodiments of the present invention are presented for purposes of illustration and description. It is not intended to limit the invention to the precise form disclosed, and obviously many modifications and variations are possible in light of the above teaching. The exemplary embodiments were chosen and described in order to explain the specific principles of the invention and its practical application to thereby enable one skilled in the art to make and utilize the invention in various exemplary embodiments and with various modifications as are suited to the particular use contemplated. It is intended that the scope of the invention be defined by the claims and their equivalents.

Claims (3)

1. An event-triggered control method, comprising:
s100, based on the switching information physical system receiving random network attacks in various different forms, establishing a switching information physical system model;
s200, transmitting data by using an event trigger control method;
s300, designing a switching signal and a state feedback controller by adopting a mode dependent average residence time method;
in the step S100, the handover information physical system model Σ is:
Σ:
wherein x (t) ∈R n ,u(t)∈R m Respectively representing the state and control input of the system, R represents a real number set, R n And R is R m Respectively representing n-dimensional real vector space and m-dimensional real vector space, n and m can be arbitrarily selected to be positive integers greater than or equal to 1, sigma (t) is a switching signal which is a piecewise constant function in a finite setWherein M is the number of subsystems, defining a switching sequence as +.>Where N is a natural number set, when σ (t i )＝h i At the time of the h i The individual subsystem is activated and additionally +.>A i ∈R n×n And B i ∈R n×m Is a known constant matrix with corresponding dimensions;
in S200, a state x (t k h) The event trigger conditions for whether released are:
wherein t is k h and t k+1 h represents the latest trigger time and the next trigger time respectively, h is the sampling period, N is a natural number set, t k h+l k h represents the current sampling instant, x (t k h) Is the system state at the latest trigger time, x (t k h+l k h) System state at current sampling instant e k (t)＝x(t k h)-x(t k h+l k h) Is the corresponding state difference between the two states, scalar delta i E (0, 1) is the event trigger parameter, Ω 1i > 0 and Ω 2i > 0 is a positive symmetric weight matrix, i ε M, M is a finite set of subsystem numbers, σ (t) is the switching signal;
in the step S300, the state feedback controller is designed to:
wherein K is σ(t) For the controller gain, σ (t) is the switching signal, u (t) is the system input, f 1 (x (t-d (t))) and f 2 (x (t-eta (t))) represents random network attacks of two different characteristics, d (t) and eta (t) are respectively corresponding network attack time delays, x (t-tau (t)) is a system state, tau (t) is a system time delay, alpha (t) and beta (t) are Bernoulli distribution variables respectively representing whether attacks occur and which characteristics of attacks occur,representing the state difference between the sampling instant and the triggering instant, < + >>l k -1，0≤τ(t)≤τ M ，/>Is the sampling time, h is the sampling period, τ M Is the maximum system time lag;
in S300, the switching signal satisfies the following requirements:
wherein τ ai For the mode dependent average residence time,the minimum modality-dependent average residence time obtained for the solution,is a finite set of subsystem numbers, θ i > 0 and mu i > 1 is a given constant for adjusting the modality dependent average residence time;
in the step S100, the system receives two random network attacks with different characteristics, where the two random network attacks are represented by two nonlinear functions:
β(t)f 1 (x(t-d(t)))+(1-β(t))f 2 (x(t-η(t))),
wherein f 1 (x (t)) and f 2 (x (t)) represents two different characteristics of random network attack, d (t) E [0, d M ]Sum eta (t) epsilon [0, eta M ]Respectively corresponding network attack time delay, d M > 0 and eta M > 0 represents the maximum delay of two network attacks, and the random variables alpha (t) and beta (t) obey probabilities, respectivelyAnd probability->And whether the random network attack occurs is controlled by a bernoulli distribution variable α (t); said f 1 (x (t)) and f 2 (x (t)) satisfies the following condition:
f 1 T (x(t))f 1 (x(t))≤x T (t)G T Gx(t),
where G and H are known constant matrices that represent the upper bound of a network attack.
2. The method for controlling event triggering according to claim 1, wherein the bernoulli distribution variable α (t) =1 indicates that the system is under random network attack, and the bernoulli distribution variable α (t) =0 indicates that the system is not under network attack, and data is normally transmitted; bernoulli distribution variable β (t) =1 represents the network attack f 1 (x (t-d (t))) occurs and bernoulli distribution variable β (t) =0 represents network attack f 2 (x (t-eta (t))).
3. An event triggered control system employing the event triggered control method of claim 1, said system comprising:
the model building unit is used for building a switching information physical system model based on the fact that the switching information physical system receives random network attacks in various different forms;
the event trigger control unit is used for transmitting data by using an event trigger control method;
and the state feedback controller design unit is used for designing the switching signal and the state feedback controller by adopting a mode dependent average residence time method.
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