CN115589319B - Synchronization and attack processing method of time-lag switching system based on observer - Google Patents
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Abstract
The application relates to the technical field of time-lag switching systems, in particular to a synchronization and attack processing method of a time-lag switching system based on an observer, which introduces an original system and sends an original signal through a sending end of the original system; decomposing the original signal to obtain an attack elimination signal and an attack correlation signal in the original signal; designing an observer based on the attack elimination signal, solving the observation gain of the observer, estimating the attack signal, and sending the state of the observer to the controller; the feedback controller is designed based on the state of the observer, the gain of the feedback controller is solved, the synchronous control of the subsystem is realized, the attack signal is divided into an attack elimination signal and an attack related signal, the attack elimination signal is utilized to accurately observe the state of the original system, then the synchronous control of the subsystem is realized through the controller with the designed base feedback, the performance index is introduced when the controller is designed, the anti-interference performance is ensured, and the control effect of the controller is ensured.
Description
Technical Field
The application relates to the technical field of time-lag switching systems, in particular to a synchronization and attack processing method of a time-lag switching system based on an observer.
Background
A switching system is a special class of hybrid systems comprising a plurality of subsystems described by differential or differential equations and a switching signal responsible for coordinating the switching sequence between the subsystems. The Lyapunov direct method is generally adopted to study the dynamic behavior of a switching system, but the method cannot be applied to a time-lapse system. It is well known that time lags are unavoidable in practical engineering.
With the development of information and communication technology, remote communication is becoming an indispensable part of life, and plays a role in promoting production and life. However, malicious network attacks are often experienced during the signaling process. A communication system mainly comprises a transmitting end, a receiving end and a channel. Considering that network attacks may be suffered in a channel, so that an original signal and an attack signal are mixed together, and meanwhile, the attack signal is generally unknown to a receiving end, the receiving end cannot distinguish the original signal from the attacked signal, and neither the exact expression of the attack nor the upper bound of the attack is known, which poses a serious challenge to actual communication security.
In the conventional network attack processing method, almost all controller designs can only be performed on the attacked signal, and the control effect of the controller is also affected and reduced due to the influence of the attacked signal.
Disclosure of Invention
The application aims to provide a synchronization and attack processing method of a time-lag switching system based on an observer, and aims to solve the problem that a controller is influenced by an attack signal and the control effect is reduced in the traditional network attack processing method.
In order to achieve the above object, the present application provides a synchronization and attack processing method of an observer-based time lag switching system, comprising the steps of:
introducing an original system and sending an original signal through a sending end of the original system;
decomposing the original signal to obtain an attack elimination signal and an attack signal in the original signal;
designing an observer based on the attack elimination signal, solving the observation gain of the observer, estimating the attack signal, and sending the state of the observer to a controller;
and designing a feedback controller based on the state of the observer, solving the gain of the feedback controller, and realizing synchronous control of the subsystem.
The specific mode of decomposing the original signal and obtaining an attack elimination signal and an attack related signal in the original signal is as follows:
the receiving end of the original system receives the original signal and establishes a network attack decomposition method;
and decomposing the network attack in the original signal by using the network attack decomposition method to obtain an attack elimination signal and an attack correlation signal in the original signal.
Wherein the original system is a nonlinear system.
Wherein the network attack includes intermittent network attack or continuous network attack.
The method for solving the gain of the feedback controller is characterized in that the method for solving the gain of the feedback controller is a Lyapunov method and a linear matrix inequality.
According to the synchronization and attack processing method of the time lag switching system based on the observer, an original system is introduced, and an original signal is sent through a sending end of the original system; decomposing the original signal to obtain an attack elimination signal and an attack correlation signal in the original signal; designing an observer based on the attack elimination signal, solving the observation gain of the observer, estimating the attack signal, and sending the state of the observer to a controller; the method comprises the steps of dividing an attack signal into two parts of an attack elimination signal and an attack related signal, simultaneously realizing accurate observation of the state of the original system by the observer by utilizing the attack elimination signal, and then realizing synchronous control of the subsystem by designing the feedback controller based on the state of the observer. Since the original system is chaotic, the state change of the original system appears to be uncertain, unrepeatable and unpredictable, so that secret communication can be realized. At the same time, H is introduced in designing the controller in consideration of possible interference ∞ Performance index, guaranteed interference immunity. After accurate observation is achieved, the attack signal is identified from the attack-related signal using the available observer state. The application not only successfully solves the problem of network attack, but also can estimate the specific form of the attack, and solves the problem that the controller is influenced by the attack signal and the control effect is reduced in the traditional network attack processing method.
Drawings
In order to more clearly illustrate the embodiments of the application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a nonlinear system diagram of a synchronization and attack processing method of an observer-based time lag switching system.
Fig. 2 is a diagram of two types of network attack signals.
Fig. 3 is a graph of the time response of the observed error.
Fig. 4 is a graph comparing network attacks with estimated signals.
Fig. 5 is a graph of a synchronization error time response.
FIG. 6 is a zero initial conditionIntegral plot of gain.
Fig. 7 is a flowchart of a synchronization and attack processing method of the observer-based time lag switching system provided by the application.
Detailed Description
Embodiments of the present application are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the drawings are illustrative and intended to explain the present application and should not be construed as limiting the application.
Referring to fig. 1 to 7, the present application provides a synchronization and attack processing method of an observer-based time lag switching system, comprising the following steps:
s1, introducing an original system, and transmitting an original signal through a transmitting end of the original system;
specifically, the original system is a nonlinear system, and the original system with wonton characteristics is introduced into the original system by a dynamic equation:
wherein x (t) ∈R n Representing an initial value asSystem state vector,/-for (2)>Representing the measured output. A, I/O>B，/> Is a matrix with known parameters. />Is a nonlinear term in the dynamic equation, τ (t) represents a bounded time-varying delay.
In actual communication, the system state x (t) of the original system is often unknown and is generally difficult to obtain, and y can be obtained only through measurement x (t). Thus, the original signal y sent by the sending end in the anti-interference secret communication can be obtained x (t)。
Wherein x (t) = (x) 1 (t)，x 2 (t)，x 3 (t)) T Nonlinear term
f(x(t))＝(|x 1 (t)+1|-|x 1 (t)-1|，0，0) T
The specific parameters are as follows: τ (t) =0.01, δ 1 ＝10，δ 2 ＝15，ξ 1 ＝19.53，ξ 2 ＝14.53，ω c ＝0.16，v c ＝0.5，∈ c ＝0.2，a＝-1.43，b＝0.87，
Initial state of host systemv∈[-0.01，0]The switching signal σ (t) ∈ {1,2}, the initial state σ (0) =2, the residence time of each subsystem is [0.1,0.15 ]]The upper satisfaction was expected to be 0.125 with a variance of 2.08X10 -4 Is a uniform distribution of (c). y is x (t)＝(y 1 (t)，y 3 (t)，y 3 (t)) T Is the output of the system and is also the original signal to be transmitted in the communication. A nonlinear system at this particular parameter is shown in fig. 1.
S2, decomposing the original signal to obtain an attack elimination signal and an attack signal in the original signal;
the specific mode is as follows:
s21, a receiving end of the original system receives the original signal and establishes a network attack decomposition method;
s22, decomposing the network attack in the original signal by utilizing the network attack decomposition method to obtain an attack elimination signal and an attack correlation signal in the original signal.
In particular, due to the original signal y x (t) often encounters unknown network attacks when transmitting in a communication network. Thus, the signal actually received at the receiving endIs that
y(t)＝y x (t)+Dd(t) (2)
Wherein the method comprises the steps ofp > q is a line-full order matrix obtained based on known channel transmission characteristics, +.>Representing an unknown network attack in the channel. The form of d (t) is not strictly limited without losing generality, and can be a form of denial of service attack, injection attack and the like, so that the method has a wide application range.
For a full rank matrix D σ(t) Presence matrixMake->Is a non-singular matrix. Decomposing matrix for network attack
Representing attack cancellation signal,/->Representing attack-related signals, in the form of
Wherein the method comprises the steps ofRepresents an attack cancellation matrix, satisfies F 1 D＝0，/>Represents an attack correlation matrix, satisfies F 2 D＝I q×q ，I q×q Is an identity matrix of q rows and q columns. Since F is a non-singular matrix, F 1 Is a full-line matrix, which also means that the attack cancellation signal +.>The original signal y is preserved x All information of (t).
The network attacks include intermittent network attacks or continuous network attacks, intermittent attack signals d (t) =round (cos (5 t)) and continuous attack signals d (t) =cos (20 t). Fig. 2 shows four cases of a network attack signal diagram.
After the attack signal is given, the network attack decomposition method is utilized to carry out the analysis on the actual received signal y (t) =y at the receiving end x (t) +Dd (t) as decomposition,
due to
Give the matrix
So thatAs a non-singular matrix, a matrix is obtained from equation (3)
F 2，1 ＝(-4.1070，1.4285，2.3214)，F 2，2 ＝(-3.1111，0.8889，2)。
S3, designing an observer based on the attack elimination signal, solving the observation gain of the observer, estimating the attack signal and sending the state of the observer to a controller;
in particular, by means of which the attack signal has been cancelledThe following observer is designed
Wherein s (t) ∈R n Representing a state vector of the observer,in order for the initial state of the observer,is the controller gain obtained by design.
In addition to attack cancellation signalsBesides, the observer can also receive the attack-related signal +.>From the formulas (1), (3) it can be known +.>If the observer can accurately observe the original system, the network attack can be accurately estimated by the following formula
Wherein d is e And (t) represents an attack signal estimated by the observer. Since the state of the original system is difficult to obtain, the design of the observer equation (4) is necessary as shown in the equation (5), and the method is characterized in thatThis may utilize the observed state s (t) to estimate the original system state x (t).
Since A has been given in the first step i ，B i ，/>And the specific parameters and form of the nonlinear term f (·), the observation gain is designed>As will be shown in the following,
given an observer initial state ofv∈[-0.01，0]The dynamic equation of the observer can be accurately represented based on the above conditions. Fig. 3 shows a graph of the time response of the observed error δ (t) between the original system equation (1) and the observer equation (4) according to an embodiment of the present application, where δ (t) gradually goes to zero as time progresses, i.e. the observer can accurately observe the original system. Based on equation (5), when s (t) =x (t), the unknown cyber attack signal d (t) can be d e (t) accurate estimation. Fig. 4 shows a comparison of unknown network attacks and estimated signals in accordance with an embodiment of the present application.
S4, designing a feedback controller based on the state of the observer, solving the gain of the feedback controller, and realizing synchronous control of the subsystem.
Specifically, the method for solving the gain of the feedback controller is a Lyapunov method and a linear matrix inequality, and considers a dynamic equation of a slave system
Wherein z (t) ∈R n Representing an initial value asU (t) ∈R n Is a controller needing to be designed, w (t) epsilon R n Is satisfied->External disturbances of (a) are provided.
Let e (t) =z (t) -x (t) be the synchronization error between the slave system and the original system, δ (t) =s (t) -x (t) be the observation error between the observer and the original system, the controller can be designed to
Based on formulas (1), (4), (6) and (7), an augmented error dynamic equation can be obtained
Wherein:
g(e(t))＝f(z(t))-f(x(t))，
g(e(t-τ(t)))＝f(z(t-τ(t)))-f(x(t-τ(t)))，
g(δ(t))＝f(s(t))-f(x(t))，
g(δ(t-τ(t)))＝f(s(t-τ(t)))-f(x(t-τ(t)))，
augmentation matrix
I 2 ＝(0 n×n ，I n ) T 。
When switching signal sigma (t) =r, using dwell time division technique of time-lapse system, gain is observed by designing proper lyapunov functional V (t) and establishing sufficient linear matrix inequality conditionController gain K σ(t) Can be accurately solved to realize synchronous control of the subsystem.
Designing a controller gain based on observer state feedback from the system formula (6), and estimating ω (t) =exp (-2.5 t) × (0.5,0.2,0.7) for external disturbance T By solving the linear inequality, an anti-interference controller is obtained, wherein the gain K is controlled 1 ，K 2 As will be shown in the following,
given the initial state of the slave systemv∈[-0.01，0]Fig. 5 shows a graph of the synchronization error e (t) time response between an original system and a slave system according to an embodiment of the present application. FIG. 6 showsZero initial condition according to an embodiment of the present application +.>Gain γ= 0.0252->And (3) withIntegrating the graph.
The above disclosure is only a preferred embodiment of the present application, and it should be understood that the scope of the application is not limited thereto, and those skilled in the art will understand that all or part of the above-described embodiments may be implemented and equivalents thereof may be modified according to the scope of the appended claims.
Claims (3)
1. The synchronization and attack processing method of the time lag switching system based on the observer is characterized by comprising the following steps:
introducing an original system, transmitting an original signal through a transmitting end of the original system, specifically, introducing an original system dynamic equation into the original system with wonton characteristics, wherein the original system is a Lorentz system:
wherein x (t) ∈R n Representing an initial value asSystem state vector,/-for (2)>Representing the measured output; a, I/O>B，/>Is a matrix with known parameters; f (.): />Is a nonlinear term in the dynamic equation, τ (t) represents a bounded time-varying delay;
wherein x (t) = (x) 1 (t)，x 2 (t)，x 3 (t)) T Nonlinear term f (x (t))= (|x) 1 (t)+1|-|x 1 (t)-1|，0，0) T The method comprises the steps of carrying out a first treatment on the surface of the The specific parameters are as follows: τ (t) =0.01, δ 1 ＝10，δ 2 ＝15’ξ 1 ＝19.53’ξ 2 ＝14.53’w c ＝0.16’v c ＝0.5’∈ c ＝0.2’a＝-1.43’b＝0.87’i＝1，2’
Initial state of host systemv∈[-0.01，0]The switching signal σ (t) ∈ {1,2}, the initial state σ (0) =2, the residence time of each subsystem is [0.1,0.15 ]]The upper satisfaction was expected to be 0.125 with a variance of 2.08X10 -4 Is uniformly distributed; y is x (t)＝(y 1 (t)，y 3 (t)，y 3 (t)) T Is the output of the system and is also the original signal to be sent in communication;
decomposing the original signal to obtain an attack elimination signal and an attack signal in the original signal, wherein the specific mode is as follows:
the receiving end of the original system receives the original signal and establishes a network attack decomposition method;
decomposing network attacks in the original signals by using the network attack decomposition method to obtain attack elimination signals and attack related signals in the original signals, wherein the signals actually received at the receiving end are specifically;
y(t)＝y x (t)+Dd(t) (2)
wherein the method comprises the steps ofp > q is a line-full order matrix obtained based on known channel transmission characteristics, +.>Representing an unknown network attack in the channel;
for a full rank matrix D σ(t) Presence matrixMake->Is a non-singular matrix; enabling the network attack to decompose the matrix;
representing attack cancellation signal,/->Representing attack-related signals, in the form of
Wherein the method comprises the steps ofRepresents an attack cancellation matrix, satisfies F 1 D＝0，/>Represents an attack correlation matrix, satisfies F 2 D＝I q×q ，I q×q A unit matrix of q rows and q columns;
the network attack comprises intermittent network attack or continuous network attack, wherein intermittent attack signal d (t) =round (cos (5 t)) and continuous attack signal d (t) =cos (20 t);
after the attack signal is given, the network attack decomposition method is utilized to carry out the analysis on the actual received signal y (t) =y at the receiving end x (t) +Dd (t) as decomposition,
give the matrix
So thati=1, 2 is a nonsingular matrix, composed of a common matrixThe matrix obtainable by (3)
F 2，1 ＝(-4.1070，1.4285，2.3214)，F 2，2 ＝(-3.1111，0.8889，2)；
Designing an observer based on the attack cancellation signal and solving an observation gain of the observer, estimating the attack signal, and transmitting an observer state to a controller, in particular, using the attack signal that has been cancelledThe following observer is designed
Wherein s (t) ∈R n Representing a state vector of the observer,for the initial state of the observer, +.>The gain of the controller is obtained through design;
in addition to attack cancellation signalsBesides, the observer can also receive the attack-related signal +.>From the formula (1),(3) It can be seen that->If the observer can accurately observe the original system, the network attack can be accurately estimated by the following formula
Wherein d is e (t) represents an attack signal estimated by an observer; estimating an original system state x (t) by using the observed state s (t);
wherein A is given above i ，B i ，/>Specific parameters and form of i=1, 2 and nonlinear term f (·), designed observation gain +.>As will be shown in the following,
given an observer initial state ofv∈[-0.01，0]Based on the above conditions, the dynamic equation of the observer can be accurately represented; and designing a feedback controller based on the state of the observer, solving the gain of the feedback controller, and realizing synchronous control of the subsystem.
2. The method for synchronization and attack handling of an observer-based time lapse switching system according to claim 1,
the network attack includes intermittent network attack or continuous network attack.
3. The method for synchronization and attack handling of an observer-based time lapse switching system according to claim 1,
the method for solving the gain of the feedback controller is a Lyapunov method and a linear matrix inequality.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108733030A (en) * | 2018-06-05 | 2018-11-02 | 长春工业大学 | A kind of network-based switching time lag system centre estimator design method |
| CN110531616A (en) * | 2019-07-29 | 2019-12-03 | 浙江工业大学 | A kind of network motion control systems under coloured noise attack discrimination method |
| CN113110055A (en) * | 2021-04-20 | 2021-07-13 | 山东师范大学 | Self-adaptive event trigger output feedback control method and system of time-lag switching system |
| CN113741309A (en) * | 2021-09-16 | 2021-12-03 | 云境商务智能研究院南京有限公司 | Dual-dynamic event trigger controller model design method based on observer |
| CN114421499A (en) * | 2022-01-28 | 2022-04-29 | 南京财经大学 | Attack reconstruction and elastic control method of multi-region load frequency system |
-
2022
- 2022-10-09 CN CN202211225764.1A patent/CN115589319B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108733030A (en) * | 2018-06-05 | 2018-11-02 | 长春工业大学 | A kind of network-based switching time lag system centre estimator design method |
| CN110531616A (en) * | 2019-07-29 | 2019-12-03 | 浙江工业大学 | A kind of network motion control systems under coloured noise attack discrimination method |
| CN113110055A (en) * | 2021-04-20 | 2021-07-13 | 山东师范大学 | Self-adaptive event trigger output feedback control method and system of time-lag switching system |
| CN113741309A (en) * | 2021-09-16 | 2021-12-03 | 云境商务智能研究院南京有限公司 | Dual-dynamic event trigger controller model design method based on observer |
| CN114421499A (en) * | 2022-01-28 | 2022-04-29 | 南京财经大学 | Attack reconstruction and elastic control method of multi-region load frequency system |
Non-Patent Citations (2)
| Title |
|---|
| 基于改进观测器的信息物理系统安全状态估计和攻击重建;郑孝怡;方晓敏;;科技创新导报(第07期);全文 * |
| 隐蔽式攻击下的离散系统区间观测器设计;刘坤;张淇瑞;郭航;刘涛;夏元清;;控制理论与应用(第08期);全文 * |
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