Train operation safety control method and system based on memory dynamic event triggering

Abstract

The invention discloses a train operation safety control method and system based on memory dynamic event triggering, and relates to the technical field of train operation control. Comprises: acquiring a train network control system; determining internal influence factors and external influence factors of the train network control system; a dynamic event triggering mechanism based on memory is designed on the premise of saving network resources and ensuring safe operation of a train network control system; a memory state feedback controller enabling the train network control system to operate safely is obtained by combining a stability theory; and obtaining the gain of a memory state feedback controller and a weight matrix of a dynamic event triggering mechanism, and obtaining the minimum safe transmission time requirement for ensuring the stability of a train network control system according to the longest attack time of the DoS attack, thereby realizing H-infinity guaranteed cost control. According to the invention, through collaborative design of the event triggering weight matrix and the controller gain, balance between network information transmission saving and system performance is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of train operation safety control, and in particular to a guaranteed cost control method and system based on a memory dynamic event trigger mechanism. Background Art

[0002] Due to the limitations of geographical distribution and network resources, train operation control systems often face problems such as data conflicts, connection interruptions, and network congestion. When data is transmitted over long distances in the network, transmission delay is particularly significant, and this phenomenon has been widely discussed by many scholars. In order to effectively save network resources, event triggering mechanisms have emerged. This mechanism only transmits relevant data when the trigger conditions are met. Compared with periodic triggering mechanisms, it can more efficiently utilize the limited communication and computing resources in train operation control systems.

[0003] Based on the memory dynamic event trigger mechanism, the internal dynamic factors are further integrated as thresholds on the basis of the event trigger mechanism, and historical data are considered in the trigger conditions. This trigger strategy dynamically adjusts the threshold parameters to adapt to the changes in system signals, while utilizing the key information that may be contained in historical data, thus achieving a good balance between ensuring the required system performance and improving communication efficiency.

[0004] In recent years, train operation control systems are also facing the risk of cyber attacks. Among them, denial of service (DoS) attacks, as an easy-to-implement and ubiquitous type of attack, pose a serious threat to system security. DoS attacks can generally be divided into three types: periodic DoS attacks, random DoS attacks, and non-periodic DoS attacks. Periodic DoS attacks can be modeled as a switching control signal that switches between an attack dormant interval and an attack active interval; random DoS attacks assume that they follow a specific statistical model, such as the Bernoulli distribution model; and non-periodic DoS attacks are based on different assumptions, but the existing assumptions are limited in system performance analysis. Therefore, proposing a model that can combine different assumptions has become one of the key motivations for solving this problem.

[0005] In addition, actuator saturation is also a common problem in train operation control systems. When the actual measurement value exceeds the operating limit of the actuator, it will cause the control signal to be non-smooth, which will have an adverse effect on the control performance and may even cause fluctuations or instability within the system. Therefore, the impact of input saturation on the system must be discussed in depth to ensure the stability and performance of the train operation control system. Specifically, the guaranteed cost control technology can ensure the stability of the system when the actuator is saturated and the networked control system faces DoS attacks. However, there are relatively few studies on the stability analysis and guaranteed cost control of networked control systems under actuator saturation, especially in the application of train operation control systems. Summary of the invention

[0006] The purpose of the present invention is to propose a train operation safety control method based on memory dynamic event triggering to solve the stability problems faced by the train operation control system under various adverse conditions such as DoS attacks, actuator saturation and external disturbances.

[0007] According to a first aspect of an embodiment of the present disclosure, a train operation safety control method based on memory dynamic event triggering is provided, comprising the following steps:

[0008] Access to train network control systems;

[0009] Determine the internal and external influencing factors of the train network control system;

[0010] Based on the saving of network resources and the premise of ensuring the safe operation of the train network control system, a dynamic event trigger mechanism based on memory is designed; combined with the stability theory, a memory state feedback controller that enables the safe operation of the train network control system is obtained;

[0011] The memory state feedback controller gain and the weight matrix of the dynamic event trigger mechanism are obtained, and the minimum safe transmission time requirement to ensure the stability of the train network control system is obtained according to the longest attack time of the DoS attack, thereby realizing H ∞ Ensure cost control.

[0012] In one embodiment, the train network control system state equation of car b is described as:

[0013]

[0014] in: are the system state and control input respectively; is the system output, A, B and C are constant matrices; is an external disturbance, and assuming in:

[0015]

[0016] sat(u(t)) represents the saturation input, w(t) represents the external disturbance, and x(t) represents the spring deformation between trains and the error between the deformation and speed of each train and the set equilibrium position, which can be expressed as The first (b-1) term of the error state They are the error between the spring deformation between the jth and j+1th carriages and the spring deformation at the equilibrium point. The latter b term of the error state is the error between the speed of the jth vehicle and the speed of the equilibrium point; yj (t), v j (t),u j (t) represent the spring displacement of the adjacent j-th and j+1-th cars, the speed of the j-th car, and the control input of the j-th car at time t, respectively. They represent the spring deformation displacement, design speed and control input when the train is cruising:

[0017]

[0018]

[0019]

[0020] where y r and v r is the set balance point displacement value and cruising speed, is the mass of each carriage;

[0021] Control Input Control input j is the error between the input of the jth car and the required input of the equilibrium point position. The control input sat(u(t)) of the actuator saturation is described as:

[0022] sat(u(t))=[sat(u1(t)), sat(u2(t)),…, sat(u b (t))],

[0023] where sat(u i (t)) = sgn(u i (t))mmin{u i (t), 1}.

[0024] The system matrices in the error dynamics equation are expressed as:

[0025]

[0026]

[0027]

[0028]

[0029] Where K>0 represents the stiffness coefficient, c0, c1 and c2 are parameters related to gust force and aerodynamic pull when the train is running at high speed.

[0030] In one embodiment, the internal influencing factors of the train network control system include actuator saturation; the external influencing factors of the train network control system include the maximum energy of the DoS attack and the external disturbance d w The size of the denial of service network attack is assumed to be:

[0031] For the time interval H without denial of service network attack n , there exists a positive scalar minimum safe communication time d min satisfy:

[0032]

[0033] For the time interval D with denial of service network attack n , there is a positive scalar maximum attack duration gma x satisfy:

[0034]

[0035] Let n(t) denote the number of DoS attack close / open transitions occurring in the interval [0, t], that is Where card represents the number of elements in the set. D =d min and For all have:

[0036]

[0037] In one embodiment, the memory state feedback controller is obtained by defining H in the following manner: n State error in interval:

[0038] e k，n (t) = x(t k，n h)-x(t k，n h+lh).

[0039] Where x(t k，n h+lh) represents the last sampling moment, x(t k，n h) indicates the last release moment; The latest triggering moment t k，n The number of samples not transmitted after h; the historical state error is:

[0040] e k-i，n (t) = x(t k-i，n h)-x(t k，n h+lh).

[0041] In order to determine whether the current sampled state measurement value should be transmitted to the controller via the network, the next transmission time t k+1，n h satisfies the following judgment conditions:

[0042]

[0043] where m is the number of memory samples considered in the event-triggered strategy, and ε i ∈[0, 1] is a given weight constant, satisfying ε1≥ε2≥...≥ε m ,and is the time-varying event trigger threshold with decreasing rate λ, Ω>0 is the event trigger weight matrix to be designed;

[0044] In interval I z =[t k +τ k , t k+1 +τ k+1 ) uses a zero-order holder to keep the control signal constant, and this interval is divided into several sub-intervals, so that

[0045]

[0046] in satisfy: Let η(t) = tt k h-lh, then η(t) is a piecewise function that satisfies and

[0047] According to the considered memory dynamic event triggering strategy, the following memory state feedback controller is proposed:

[0048]

[0049] Where F and K i is the controller gain matrix to be designed.

[0050] In one embodiment, the closed-loop system based on the memory dynamic event trigger mechanism is obtained by: setting a given constant b≥1 and a vector So that ||θ|| ∞ ≤1; where ||θ|| ∞ is the infinite norm of the vector θ; the set is a set of b×b-dimensional diagonal matrices whose diagonal elements can only be 1 or 0, respectively. The elements in D i,i∈I[1,2 b ]; define function f b (i):I[1,2 b ]→I[1,2 b-1 ], let f b (0) = 0, defined as follows:

[0051]

[0052] Then for any vector have:

[0053]

[0054] in is defined as:

[0055]

[0056] represents the Kochikov product;

[0057] Corresponding to the above controller, for any If there exists ||θ|| ∞ ≤1, the following auxiliary feedback controller is introduced:

[0058]

[0059] Where L and U i is the auxiliary controller gain matrix to be designed.

[0060] Based on the above analysis, the closed-loop system based on the memory dynamic event trigger mechanism is as follows:

[0061]

[0062] in:

[0063] In one embodiment, based on a closed-loop system, the guaranteed cost function is given by considering the actuator saturation phenomenon as follows:

[0064]

[0065] Where M and W are given positive definite weight matrices;

[0066] If the closed-loop system is asymptotically stable under zero initial conditions, and for any nonzero w(t), and given The output z(t) satisfies The closed-loop system is said to achieve weighted H ∞ Dynamic attenuation level

[0067] In one embodiment, H is implemented ∞ The cost control method is:

[0068] Given a constant ε1,…,ε m ∈(0,1),h∈(0,d min ), d max ∈[d min , +∞), And given positive definite matrices M and W, if there exists a positive scalar β1,…,β4, symmetric positive definite matrix and matrix And the following linear matrix inequality holds,

[0069]

[0070] in:

[0071]

[0072] Δ c =ln(μ1μ2)+2(α1+α2).

[0073] Given an initial value that satisfies And satisfy in:

[0074] After that, the closed-loop system is asymptotically stable under non-periodic DoS attacks with weighted H ∞ Disturbance attenuation level and guarantee the upper bound of cost, the upper bound of cost is expressed as

[0075] Then, the symmetric positive definite matrix Ω, the feedback gain F, K1, ..., K m and auxiliary feedback gains L, U1, ..., U m Given by:

[0076]

[0077] According to a second aspect of an embodiment of the present disclosure, a train operation safety control system based on memory dynamic event triggering is provided, comprising:

[0078] Train network control module, obtaining train network control system;

[0079] The influencing factor module determines the internal and external influencing factors of the train network control system;

[0080] The controller building module is designed based on the memory-based dynamic event trigger mechanism, with the starting point of saving network resources and the premise of ensuring the safe operation of the train network control system. The memory state feedback controller that enables the safe operation of the train network control system is obtained by combining the stability theory.

[0081] The guaranteed cost control module obtains the memory state feedback controller gain and the weight matrix of the dynamic event trigger mechanism, and obtains the minimum safe transmission time requirement to ensure the stability of the train network control system according to the longest attack time of the DoS attack, thereby realizing H ∞ Ensure cost control.

[0082] According to the third aspect of an embodiment of the present disclosure, there is provided an electronic device comprising a memory, a processor and a computer program stored and running on the memory, wherein when the processor executes the program, the train operation safety control method based on memory dynamic event triggering is implemented.

[0083] According to a fourth aspect of an embodiment of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored. When the program is executed by a processor, the train operation safety control method based on memory dynamic event triggering is implemented.

[0084] Compared with the prior art, the above technical solution adopted by the present invention has the following advantages: in practical applications, the present invention realizes the coordinated design of event trigger weight matrix and controller gain, effectively balances the economy of network information transmission and the requirements of system performance, and ensures the safety and stability of the train operation control system. BRIEF DESCRIPTION OF THE DRAWINGS

[0085] The drawings in the specification, which constitute a part of the present application, are used to provide further understanding of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute improper limitations on the present application.

[0086] Figure 1 This is the framework diagram of the train network control system under non-periodic DoS attack;

[0087] Figure 2 This is a schematic diagram of a non-periodic DoS attack signal;

[0088] Figure 3 is a state response diagram with auxiliary feedback;

[0089] Figure 4 is the control input diagram with auxiliary feedback;

[0090] Figure 5 It is a triggering serial diagram of the event generator in which a DoS attack exists;

[0091] Figure 6It is a schematic diagram of dynamic event trigger parameters;

[0092] Figure 7 It is the state response diagram without auxiliary feedback under DoS attack;

[0093] Figure 8 It is the control input diagram without auxiliary feedback under DoS attack. DETAILED DESCRIPTION

[0094] The present disclosure is further described below in conjunction with the accompanying drawings and embodiments.

[0095] It should be noted that the following detailed descriptions are illustrative and are intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used in the present invention have the same meanings as those commonly understood by those skilled in the art to which the present application belongs.

[0096] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0097] It should be noted that the flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the methods and systems according to various embodiments of the present disclosure. It should be noted that each box in the flowchart or block diagram can represent a module, a program segment, or a part of a code, and the module, program segment, or a part of a code may include one or more executable instructions for implementing the logical functions specified in each embodiment. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, or they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the flowchart and / or block diagram, and the combination of boxes in the flowchart and / or block diagram can be implemented using a dedicated hardware-based system that performs a specified function or operation, or can be implemented using a combination of dedicated hardware and computer instructions.

[0098] With the continuous expansion of train control network applications and the increase in data, passengers and technicians have put forward new requirements for train network control systems, including higher real-time performance, information transmission effectiveness, safety and higher reliability. Traditional train network control technology can no longer meet these requirements, and new technologies are urgently needed.

[0099] Embodiment 1:

[0100] This embodiment provides a train operation safety control method based on memory dynamic event triggering, comprising the following steps:

[0101] S1. Obtain the train network control system;

[0102] Specifically, Figure 1 As shown, the event generator compares the current state with the historical trigger state in the memory buffer and sends the signal that meets the trigger condition to the controller through the network. It is assumed that the sampler is clock-driven with a fixed sampling period h. The controller and actuator are driven by a memory-based dynamic event trigger mechanism. In the present invention, it is assumed that all state variables are available for measurement and their respective values ​​are transmitted together as a single data packet in each sampling period.

[0103] S2. Determine the internal and external influencing factors of the train network control system;

[0104] Specifically, DoS attacks may affect the sensor-to-controller channel and the controller-to-actuator channel. Figure 2 As shown, in order to quantitatively describe the impact of such DoS attacks on system performance, It represents the n+1th denial of service sleep interval, allowing the sensor to controller and controller to actuator channels to communicate normally at the same time. Indicates the (n+1)th active denial-of-service interval in which the interference signal is active and the sensor-to-controller and controller-to-actuator channels cannot transmit control signals at the same time;

[0105] For the time interval H without DoS attack n , there exists a positive scalar minimum safe communication time d min satisfy:

[0106]

[0107] For the time interval D with DoS attack n , there is a positive scalar maximum attack duration gma x satisfy:

[0108]

[0109] Let n(t) denote the number of DoS off / on transitions occurring in the interval [0, t], i.e. Where card represents the number of elements in the set. D =d min and For all have:

[0110]

[0111] S3. Based on the saving of network resources and the premise of ensuring the safe operation of the train network control system, a dynamic event trigger mechanism based on memory is designed; combined with the stability theory, a memory state feedback controller that enables the safe operation of the train network control system is obtained;

[0112] Specifically, due to the limited communication bandwidth in the network system, a trigger strategy based on memory dynamic events is proposed to reduce redundant transmission data. In this invention, H is defined in the following way n State error in interval:

[0113] e k，n (t) = x(t k，n h)-x(t k，n h+lh)

[0114] Where x(t k，n h+lh) represents the last sampling moment, x(t k，n h) indicates the last release moment; The latest triggering moment t k，n The number of samples not transmitted after h; the following historical state error is also defined:

[0115] e k-i，n (t) = x(t k-i，n h)-x(t k，n h+lh)

[0116] In order to determine whether the current sampled state measurement value should be transmitted to the controller via the network, the next transmission time t k+1，n h satisfies the following judgment conditions:

[0117]

[0118] where m is the number of memory samples considered in the event-triggered strategy, and ε i ∈[0,1] is a given weight constant, satisfying ε1≥ε2≥...≥ε m ,and is the time-varying event trigger threshold with decreasing rate λ, and Ω>0 is the event trigger weight matrix to be designed.

[0119] In the networked control scheme considered, in interval I z =[t k +τ k , t k+1 +τ k+1) uses a zero-order holder to keep the control signal constant. This interval can be divided into several sub-intervals, so that

[0120]

[0121] in satisfy: Let η(t) = tt k h-lh, then η(t) is a piecewise function that satisfies and

[0122] According to the dynamic memory event triggering strategy considered, the following memory state feedback controller is proposed:

[0123]

[0124] Among them, and K i is the controller gain matrix to be designed.

[0125] S4. Obtain the memory state feedback controller gain and the weight matrix of the dynamic event trigger mechanism, and derive the minimum safe transmission time requirement to ensure the stability of the train network control system according to the longest attack time of the DoS attack, thereby achieving H ∞ Ensure cost control.

[0126] Specifically, let a given constant b ≥ 1 and a vector So that ||θ|| ∞ ≤1. Among them, ||θ|| ∞ is the infinite norm of the vector θ. The set is a set of b×b-dimensional diagonal matrices whose diagonal elements can only be 1 or 0, respectively. The elements in D i , i∈I[1,2 b ] Define function f b (i):I[1,2 b ]→I[1,2 b-1 ], let f b (0) = 0, defined as follows:

[0127]

[0128] Then for any vector have:

[0129]

[0130] in is defined as:

[0131]

[0132] represents the Korotkoff product.

[0133] Corresponding to the above controller, for any If there exists ||θ|| ∞ ≤1, the following auxiliary feedback controller is introduced:

[0134]

[0135] Where L and U i is the auxiliary controller gain matrix to be designed.

[0136] Substituting the feedback controller and the state error into the system equation, the closed-loop state equation of the system is:

[0137]

[0138] in:

[0139] Assume that the initial function is continuously differentiable, its magnitude and differential are bounded, so the initial function belongs to the following set φ δ :

[0140]

[0141] Among them: δ1 and δ2 specify the range of the initial state.

[0142] Based on the closed-loop system, the guaranteed cost function is designed as follows:

[0143]

[0144] where M and W are given positive definite weight matrices.

[0145] If the following two conditions are met, the closed-loop system (1) is said to be in the weighted H ∞ The disturbance attenuation level is Asymptotically stable when:

[0146] (1) When w(t) = 0, if: The closed-loop system (1) is said to be asymptotically stable.

[0147] (2) If the closed-loop system (1) is asymptotically stable under zero initial conditions, and for any nonzero w(t), and given The output z(t) satisfies The closed-loop system (1) is said to achieve weighted H∞ Disturbance attenuation level

[0148] If there exists a positive scalar J * , the closed-loop system (1) is asymptotically stable and satisfies the weighted H ∞ Disturbance attenuation level And the cost function (2) satisfies J≤J * , then J * It is to ensure the cost ceiling.

[0149] Take Japan's Shinkansen high-speed train as an example. It consists of four carriages. c0=1.176×10 -2 N / kg, c1=7.7616×10 -4 Ns / m kg, c2=1.6×10 -5 N 2 / m 2 kg, K = 80 × 10 3 N / m. Required velocity v at equilibrium position r =220km / h. The initial condition of the error state is: x0 = [11, -3, 5, 0, -9, 2, -6] T , the interference function is: w(t) = -0.001(1 + Cos(t)). Other parameters are as follows: γ = 0.5, λ = 200, m = 3, ε1 = 0.7, ε2 = 0.17, ε3 = 0.13, ρ1 = 0.1, ρ2 = 0.3, b=4, β1=β2=0.3, β3=β4=48, α1=0.18, α2=0.216, μ1=μ2=1.01, d w =0.016, M=W=I, assuming that the sampling period of the clock drive is h=0.1s. Through the LMI toolbox of Matlab, the following positive definite weight matrix can be obtained:

[0150]

[0151] The memory-based feedback gain matrix can be obtained:

[0152]

[0153] After obtaining the controller gains, we can now analyze the simulation results by examining the system response to initial conditions and disturbances to evaluate the performance of the control system. The attack parameter is set to d min =4.26s, g max =3s. Figure 3The error trajectory of the train operation control system with auxiliary feedback controller under DoS attack is shown, indicating that the error state ranges from -8 to 12, and the system reaches stability at about 17s. Figure 4 The control input of the train operation control system with auxiliary feedback is shown. It can be seen that the control input ranges from -20 to 25 and decays to 0 in the 4th DoS attack sleep interval.

[0154] Figure 5 The figure shows the trigger times and corresponding trigger intervals of the memory-based dynamic event trigger when the DoS attack simulation time is 50 seconds. During the simulation, a total of 178 triggers were activated, which effectively reduced the burden on network transmission. Figure 6 It shows that in the unstable stage of the system, ρ(t) is between ρ1 and The maximum values ​​of the parameters δ1 and δ2 of the attraction domain are 16.60 and 7.97 respectively. The guaranteed cost upper limit J * =17586, indicating that the proposed control strategy is effective and economically feasible under the given constraints.

[0155] Likewise, simulations were performed without considering the actuator saturation phenomenon to allow for comparative analysis. Figure 7 The error trajectory of the train operation control system without auxiliary feedback controller under DoS attack is shown, showing that the error state ranges from -20 to 10, and the system stabilizes around the 10th second. Figure 8 Figure 2 shows the control inputs in the presence of DoS attacks in the event generator to controller and controller to actuator paths. Figure 8 It can be seen from FIG. 1 that the maximum control input reaches 40 or higher and decays to 0 in the second DoS attack sleep interval. Therefore, it is obvious that the method proposed in the present invention is also applicable to the train control system without actuator saturation.

[0156] Figure 3 , 4 and Figure 7 , 8 In contrast, the introduction of the auxiliary feedback controller plays an important role in solving the actuator saturation problem because it effectively reduces the control input and state error, thereby improving the comfort of train operation. In addition, it is worth noting that this introduction prolongs the time required to achieve system stability to some extent. This trade-off between improving ride comfort and the time to reach stability is an important factor to be considered when designing and improving advanced train control systems.

[0157] In the following discussion, we will explore g max and d min Specifically, the equation From the perspective of When it remains unchanged, for each g max There is a fixed value for d min From these curves, select the one-dimensional quadratic curve that satisfies the above inequality equation with the smallest d min Usually d max ≥d min , assuming constant γ = 0.5, Table 1 shows the corresponding max D min and It can be clearly seen from Table 1 that as g max The increase of weighted H ∞ Interference attenuation level Will also increase.

[0158] Table 1 Different g max The corresponding d min and value

[0159]

[0160] This embodiment introduces a memory-based dynamic event trigger controller and an auxiliary controller to fully utilize the data information in the network control system during the absence of DoS attacks. A set of sufficient conditions is derived to ensure that the weighted H ∞ The local asymptotic stability of the closed-loop system with disturbance attenuation performance is determined. In addition, the upper limit of the cost function is determined and an estimation of the attractive force domain is provided. Finally, the effectiveness and superiority of the control method proposed in this invention are demonstrated through the simulation of the high-speed train operation control system.

[0161] Embodiment 2:

[0162] This embodiment provides a train operation safety control system based on memory dynamic event triggering, including:

[0163] Train network control module, obtaining train network control system;

[0164] The influencing factor module determines the internal and external influencing factors of the train network control system;

[0165] The controller building module is designed based on the memory-based dynamic event trigger mechanism, with the starting point of saving network resources and the premise of ensuring the safe operation of the train network control system. The memory state feedback controller that enables the safe operation of the train network control system is obtained by combining the stability theory.

[0166] The guaranteed cost control module obtains the memory state feedback controller gain and the weight matrix of the dynamic event trigger mechanism, and obtains the minimum safe transmission time requirement to ensure the stability of the train network control system according to the longest attack time of the DoS attack, thereby realizing H ∞ Ensure cost control.

[0167] Embodiment three:

[0168] An electronic device includes a memory, a processor, and a computer program stored and running on the memory, wherein the processor implements the above-mentioned train operation safety control method based on memory dynamic event triggering when executing the program, including:

[0169] Access to train network control systems;

[0170] Determine the internal and external influencing factors of the train network control system;

[0171] Based on the saving of network resources and the premise of ensuring the safe operation of the train network control system, a dynamic event trigger mechanism based on memory is designed; combined with the stability theory, a memory state feedback controller that enables the safe operation of the train network control system is obtained;

[0172] The memory state feedback controller gain and the weight matrix of the dynamic event trigger mechanism are obtained, and the minimum safe transmission time requirement to ensure the stability of the train network control system is obtained according to the longest attack time of the DoS attack, thereby realizing H ∞ Ensure cost control.

[0173] Embodiment 4:

[0174] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the above-mentioned train operation safety control method based on memory dynamic event triggering, including:

[0175] Access to train network control systems;

[0176] Determine the internal and external influencing factors of the train network control system;

[0177] Based on the saving of network resources and the premise of ensuring the safe operation of the train network control system, a dynamic event trigger mechanism based on memory is designed; combined with the stability theory, a memory state feedback controller that enables the safe operation of the train network control system is obtained;

[0178] The memory state feedback controller gain and the weight matrix of the dynamic event trigger mechanism are obtained, and the minimum safe transmission time requirement to ensure the stability of the train network control system is obtained according to the longest attack time of the DoS attack, thereby realizing H ∞ Ensure cost control.

[0179] Those skilled in the art should understand that the modules or steps of the present disclosure can be implemented by a general-purpose computer device, or alternatively, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. The present disclosure is not limited to any specific combination of hardware and software.

[0180] The above description is only the preferred embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

[0181] Although the above describes the specific implementation methods of the present disclosure in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present disclosure. Technical personnel in the relevant field should understand that on the basis of the technical solution of the present disclosure, various modifications or variations that can be made by those skilled in the art without creative work are still within the scope of protection of the present disclosure.

Claims

1. A train operation safety control method based on memory dynamic event triggering, characterized in that: The following steps are involved: Access to train network control systems; Determine the internal and external influencing factors of the train network control system; Based on the saving of network resources and the premise of ensuring the safe operation of the train network control system, a dynamic event trigger mechanism based on memory is designed; combined with the stability theory, a memory state feedback controller that enables the safe operation of the train network control system is obtained; The memory state feedback controller gain and the weight matrix of the dynamic event trigger mechanism are obtained, and the minimum safe transmission time requirement to ensure the stability of the train network control system is obtained according to the longest attack time of the DoS attack, thereby realizing H ∞ Ensure cost control.

2. According to claim 1, the train operation safety control method based on memory dynamic event triggering is characterized in that: The error dynamics equation of a train running system with b carriages is as follows: in: are the system state and control input respectively; is the system output, A, B and C are constant matrices; is an external disturbance, and assuming in: sat(u(t)) represents the saturation input, w(t) represents the external disturbance, and x(t) is the error between the spring deformation between trains and the running speed of each train and the deformation and speed at the set equilibrium position; The system matrices in the error dynamics equation are expressed as: C=[0 I b ], Where k>0 represents the stiffness coefficient, c0, c1 and c2 are parameters related to gust force and aerodynamic pull when the train is running at high speed.

3. The train operation safety control method based on memory dynamic event triggering according to claim 1 is characterized in that: The internal influencing factors of the train network control system include actuator saturation; the external influencing factors of the train network control system include the maximum energy of the DoS attack and the external disturbance d w The size of the DoS attack is: For the time interval H without DoS attack n , there exists a positive scalar minimum safe communication time d min satisfy: For the time interval D with DoS attack n , there is a positive scalar maximum attack duration g max satisfy: Let n(t) denote the number of DoS off / on transitions occurring in the interval [0, t], i.e. Where card represents the number of elements in the set. D =d min and For all have:

4. The train operation safety control method based on memory dynamic event triggering according to claim 1 is characterized in that: The memory state feedback controller is obtained by defining H in the following way: n State error in interval: e k,n (t)=x(t k,n h)-x(t k,n h+lh)。 Where x(t k,n h+lh) represents the last sampling moment, x(t k,n h) indicates the last release moment; The latest triggering moment t k,n The number of samples not transmitted after h; the historical state error is: e k-i,n (t)=x(t k-i,n h)-x(t k,n h+lh) In order to determine whether the current sampled state measurement value should be transmitted to the controller via the network, the next transmission time t k+1,n h satisfies the following judgment conditions: where m is the number of memory samples considered in the event-triggered strategy, and ε i ∈[0,1] is a given weight constant, satisfying ε1≥ε2≥...≥ε m ,and is the time-varying event trigger threshold with decreasing rate λ, Ω>0 is the event trigger weight matrix to be designed; In interval I z =[t k +τ k ,t k+1 +τ k+1 ) uses a zero-order holder to keep the control signal constant, and this interval is divided into several sub-intervals, so that According to the dynamic memory event triggering strategy considered, the following memory state feedback controller is proposed: Where F and K i is the controller gain matrix to be designed. Corresponding to the above controller, for any If there exists ||θ|| ∞ ≤1, the following auxiliary feedback controller is introduced: Where L and U i is the auxiliary controller gain matrix to be designed.

5. The train operation safety control method based on memory dynamic event triggering according to claim 1 is characterized in that: The closed-loop system equation is: in:

6. The train operation safety control method based on memory dynamic event triggering according to claim 5 is characterized in that: Based on the closed-loop system, considering the actuator saturation phenomenon, the guaranteed cost function is given as follows: Where M and W are given positive definite weight matrices; If the closed-loop system is asymptotically stable under zero initial conditions, and for any nonzero w(t), and given The output z(t) satisfies The closed-loop system is said to achieve weighted H ∞ Disturbance attenuation level 7. The train operation safety control method based on memory dynamic event triggering according to claim 1 is characterized in that: Implementation of H ∞ The cost control method is: Given a constant ε1,…,ε m ∈(0,1), h∈(0,d min ), d max ∈[d min ,+∞), And given positive definite matrices M and W, if there exists a positive scalar β1, ..., β4, symmetric positive definite matrix X1, X2, and matrix And the linear matrix inequality holds; Given an initial value that satisfies And satisfy in: After that, the closed-loop system is asymptotically stable under non-periodic DoS attacks with weighted H ∞ Disturbance attenuation level and guarantee the upper bound of cost, the upper bound of cost is expressed as Then, the symmetric positive definite matrix Ω, the feedback gain F, K1, ..., K m and auxiliary feedback gains L, U1, ..., U m Given by:

8. Train operation safety control system based on memory dynamic event triggering, characterized in that: include: Train network control module, obtaining train network control system; The influencing factor module determines the internal and external influencing factors of the train network control system; The controller building module is designed based on the memory-based dynamic event trigger mechanism, with the starting point of saving network resources and the premise of ensuring the safe operation of the train network control system. The memory state feedback controller that enables the safe operation of the train network control system is obtained by combining the stability theory. The guaranteed cost control module obtains the memory state feedback controller gain and the weight matrix of the dynamic event trigger mechanism, and obtains the minimum safe transmission time requirement to ensure the stability of the train network control system according to the longest attack time of the DoS attack, thereby realizing H ∞ Ensure cost control.

9. An electronic device comprising a memory, a processor and a computer program stored and running on the memory, characterized in that: When the processor executes the program, the train operation safety control method based on memory dynamic event triggering is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the train operation safety control method based on memory dynamic event triggering is implemented.

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