Event-triggered multi-aircraft fault-tolerant cooperative guidance method, device and medium

Abstract

The application discloses a kind of multi-aircraft fault-tolerant cooperative guidance method, device and medium based on event triggering, it is related to cooperative guidance field;The method comprises: obtaining the running data of agent;According to running data, construct multi-aircraft system state model;According to multi-aircraft system state model, based on communication resource limited scene, determine guidance mathematical model;According to state variable trigger function and line-of-sight angle state, judge whether line-of-sight angle state deviation meets trigger condition, if yes, then according to line-of-sight angle state deviation, the update of line-of-sight angle state is carried out, and updated line-of-sight angle state is obtained;According to adaptive parameter and adaptive parameter trigger function, judge whether adaptive gain meets trigger condition, if yes, then according to adaptive gain, the update of adaptive parameter is carried out, and updated adaptive parameter is obtained, and then determine cooperative guidance law to control N aircraft, and single maneuvering target is cooperatively intercepted;The application can improve communication stability and control precision.

Description

Technical Field

[0001] This invention relates to the field of cooperative guidance, and in particular to a fault-tolerant cooperative guidance method, apparatus and medium for multiple aircraft based on event triggering. Background Technology

[0002] Multi-vehicle cooperative guidance (MVC) is an advanced military technology with extremely important strategic significance. With continuous technological advancements, the battlefield environment is becoming increasingly complex, and the demand for precision strikes and tactical flexibility is growing. The introduction of MVC offers an efficient and innovative method to address these challenges. As incoming targets become more maneuverable and intelligent, single aircraft often struggle to adapt to changing battlefield conditions, leading to significant interception errors. MVC enhances operational precision; through cooperative guidance, multiple aircraft can coordinate and share information to achieve more accurate target interception. This significantly improves interception effectiveness and effectively protects the safety of high-value buildings and civilians.

[0003] Currently, most research on the cooperative guidance of aircraft swarms relies on continuous communication and precise control accuracy between swarms. However, in actual battlefield operations, the stability of communication between swarms and the control accuracy of individual aircraft are difficult to guarantee. On the one hand, in complex battlefield environments, data links and communication networks between swarms are susceptible to enemy electromagnetic interference, physical obstruction, and extreme weather interference, leading to interference or interruptions in data transmission. On the other hand, due to manufacturing defects, material fatigue, external environmental factors, and electronic component failures, actuators, including various critical components such as control surfaces, fuzes, and propulsion systems, are prone to failure. High-speed, highly maneuverable aircraft may experience loss of heading, attitude, or propulsion control, thus affecting their flight path and accuracy. Communication blockage and actuator failures between swarms can prevent the swarm from accurately executing its intended mission or cause abnormal situations during flight, significantly impacting aircraft performance and mission execution.

[0004] In recent years, fault-tolerant cooperative guidance technology for multiple aircraft has become a research focus, attracting the attention of many experts and scholars. However, to date, related research results are relatively limited, especially event-triggered fault-tolerant cooperative guidance methods, which have received almost no extensive and in-depth research. Li and Dong proposed actuator fault-constrained fault-tolerant guidance laws for attacking stationary targets and intercepting maneuvering targets, respectively. However, Li only considered stationary targets and cannot be directly applied to maneuvering target interception scenarios. Dong's guidance law uses partial actuator fault information and cannot cope with safe cooperative guidance under completely unknown fault conditions. In order to achieve cooperative guidance and interception missions among aircraft swarms under limited communication resources, event-triggered cooperative guidance methods with intermittent communication mechanisms can be adopted. Sinha et al. introduced an event-triggered mechanism to reduce the use of communication resources, while Liu et al.'s event-triggered cooperative guidance law is based on optimal control theory and designs guidance laws with angle constraints and time consistency. These two cooperative guidance methods can be used for cooperative guidance problems under resource constraints, but are limited to attacking stationary targets. Overall, current research on fault-tolerant cooperative guidance under limited communication resources only touches upon actuator failure-tolerant guidance and event-triggered cooperative guidance. To date, a systematic approach has not yet been developed to address the challenge of cooperatively intercepting maneuvering targets under conditions of limited communication resources and actuator failure.

[0005] In multi-vehicle systems that collaboratively intercept maneuvering targets, achieving optimal interception results requires a formation with a specific line-of-sight angle for encirclement. However, during interception, harsh battlefield environments and external interference can lead to actuator malfunctions and limited communication resources, making it difficult for multi-vehicle systems to achieve precise interception of maneuvering targets. Therefore, it is essential to investigate methods for achieving collaborative guidance under conditions of limited communication resources and actuator malfunctions. By employing event-triggered mechanisms and adaptive fault-tolerant methods, a collaborative guidance method is designed to achieve collaborative interception of maneuvering targets. Summary of the Invention

[0006] The purpose of this invention is to provide a fault-tolerant cooperative guidance method, device and medium for multiple aircraft based on event triggering, which can improve communication stability and control accuracy.

[0007] To achieve the above objectives, the present invention provides the following solution:

[0008] A fault-tolerant cooperative guidance method for multiple aircraft based on event triggering, the method comprising:

[0009] Acquire operational data of the intelligent agent; the intelligent agent includes: N aircraft and a single maneuvering target; the operational data includes: flight data and relative distance; the flight data includes: trajectory inclination angle, constant velocity, and velocity lead angle;

[0010] A multi-vehicle system state model is constructed based on the operational data. The multi-vehicle system state model is based on the relative kinematic equations in polar coordinates of a multi-vehicle system consisting of N aircraft, which cooperate to intercept a single maneuvering target.

[0011] Based on the state model of the multi-vehicle system, a guidance mathematical model is determined under the scenario of limited communication resources. The guidance mathematical model is constructed based on sliding mode variables and cooperative guidance laws. The scenario of limited communication resources refers to the multi-vehicle system in a distributed communication topology where only two adjacent vehicles receive communication information based on an adjacency matrix.

[0012] For any aircraft, perform the following:

[0013] Based on the state variable trigger function and the line-of-sight angle state, determine whether the line-of-sight angle state deviation meets the trigger condition, and obtain the first judgment result;

[0014] If the first judgment result is yes, then the line of sight angle state is updated according to the line of sight angle state deviation to obtain the updated line of sight angle state;

[0015] Based on the adaptive parameters and the adaptive parameter triggering function, determine whether the adaptive gain meets the triggering condition, and obtain the second judgment result;

[0016] If the second judgment result is yes, then the adaptive parameters are updated according to the adaptive gain to obtain the updated adaptive parameters;

[0017] Based on all updated line-of-sight states, all updated adaptive parameters, and the guidance mathematical model, a cooperative guidance law is determined; the cooperative guidance law is used to control N aircraft to cooperate in intercepting a single maneuvering target.

[0018] Optionally, the multi-vehicle system state model specifically includes:

[0019]

[0020] Where, r i (t) represents the relative distance between the aircraft and the target; V T θ represents the constant velocity of the maneuvering target. T,i (t) represents the velocity lead angle of the maneuvering target; V M,i Let θ be the constant velocity of the i-th aircraft; M,i (t) represents the velocity lead angle of the i-th aircraft; λi (t) represents the line-of-sight angle; γ M,i (t) represents the trajectory inclination angle of the i-th aircraft; γ T (t) represents the trajectory inclination angle of the maneuvering target; The overload command is perpendicular to the velocity of the i-th aircraft; a T (t) represents the overload command of the maneuvering target perpendicular to its own velocity; For r i (t) is the first derivative of (t) with respect to time t; For λ i (t) is the first derivative of (t) with respect to time t; For γ M,i (t) is the first derivative of (t) with respect to time t; For γ T (t) is the first derivative of (t) with respect to time t.

[0021] Optionally, the guidance mathematical model specifically includes:

[0022]

[0023]

[0024]

[0025] in, K is the sliding mode variable; k1 is the positive constant gain; N is the number of aircraft; Let a be the triggering time of the i-th aircraft determined by the triggering function; M,i (t) represents the cooperative guidance law; For piecewise constant adaptive gain; r i (t) represents the relative distance between the aircraft and the target; θ M,i (t) represents the velocity lead angle of the i-th aircraft; l i (t) is a time-varying function; h i Let i be the line-of-sight formation vector for the i-th aircraft; For the i-th aircraft in The state of the line of sight at any given moment; For the j-th aircraft in The state of the line of sight at any given moment; h j Let J be the line-of-sight formation vector for the j-th aircraft; For λ i (t) is the first derivative of u with respect to time t; i (t) is an intermediate parameter; a ij a represents the communication relationship between aircraft if and only if there is a communication link between aircraft i and aircraft j. ij =1, otherwise, a ij =0.

[0026] Optionally, the expression for the state variable trigger function is:

[0027]

[0028] Among them, f i (t) is the state variable trigger function; The maximum adaptive gain is defined for aircraft i and the aircraft with which it has a communication link. The maximum adaptive gain among aircraft that have a communication link with aircraft i; ψ i ={j|a ij =1} represents the set of aircraft that have a communication link with aircraft i; For line-of-sight angle triggering error; ∈ i The positive real numbers driving the convergence of the sliding mode variables; φ and ν are both positive real numbers, φe -νt Together they are used to exclude the Zeno phenomenon.

[0029] Optionally, the expression for the adaptive parameter triggering function is:

[0030]

[0031] Among them, f α，i (t) is the adaptive parameter trigger function; α i (t) is the adaptive parameter; The adaptive gain is a piecewise constant; μ i It is a positive real number.

[0032] A computer device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the event-triggered multi-aircraft fault-tolerant cooperative guidance method described above.

[0033] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the event-triggered multi-aircraft fault-tolerant cooperative guidance method described above.

[0034] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0035] This invention discloses a fault-tolerant cooperative guidance method, device, and medium for multiple aircraft based on event triggering. The method includes: acquiring operational data of an intelligent agent; constructing a multi-aircraft system state model based on the operational data; determining a guidance mathematical model based on the multi-aircraft system state model and a scenario with limited communication resources; determining whether the line-of-sight angle state deviation meets the triggering condition based on the state variable triggering function and the line-of-sight angle state; if so, updating the line-of-sight angle state based on the line-of-sight angle state deviation to obtain an updated line-of-sight angle state; determining whether the adaptive gain meets the triggering condition based on the adaptive parameters and the adaptive parameter triggering function; if so, updating the adaptive parameters based on the adaptive gain to obtain updated adaptive parameters, thereby determining a cooperative guidance law to control N aircraft for cooperative interception of a single maneuvering target. This invention can improve communication stability and control accuracy. Attached Figure Description

[0036] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0037] Figure 1 A flowchart of an event-triggered multi-vehicle fault-tolerant cooperative guidance method provided in an embodiment of the present invention;

[0038] Figure 2 This is a schematic diagram of the motion trajectories of multiple aircraft and targets provided in an embodiment of the present invention;

[0039] Figure 3 This is a schematic diagram of the line-of-sight cross-section of multiple aircraft provided in an embodiment of the present invention;

[0040] Figure 4 This is a schematic diagram of the line-of-sight conversion rate curves for multiple aircraft provided in an embodiment of the present invention;

[0041] Figure 5 This is a schematic diagram of the local error curves of each aircraft provided in the embodiments of the present invention;

[0042] Figure 6 This is a schematic diagram of the overload curves of multiple aircraft provided in an embodiment of the present invention;

[0043] Figure 7 This is a schematic diagram of the curve of the trigger sliding mode variable provided in an embodiment of the present invention;

[0044] Figure 8 Sliding mode variable provided in the embodiments of the present invention Line graph;

[0045] Figure 9 This is a schematic diagram of the state triggering interval of the aircraft 1 provided in an embodiment of the present invention;

[0046] Figure 10 This is a schematic diagram of the state triggering interval of the aircraft 2 provided in an embodiment of the present invention;

[0047] Figure 11 This is a schematic diagram of the state triggering interval of the aircraft 3 provided in an embodiment of the present invention;

[0048] Figure 12 This is a schematic diagram of the state triggering interval of the aircraft 4 provided in an embodiment of the present invention;

[0049] Figure 13 The adaptive gain α of each aircraft provided in the embodiments of the present invention i (t) curve diagram;

[0050] Figure 14 This is a schematic diagram illustrating the gain triggering status of various aircraft provided in the embodiments of the present invention;

[0051] Figure 15 This is a schematic diagram illustrating the steps of an event-triggered distributed fault-tolerant collaborative guidance method in a practical application provided by an embodiment of the present invention. Detailed Implementation

[0052] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0053] The purpose of this invention is to provide a fault-tolerant cooperative guidance method, device, and medium for multiple aircraft based on event triggering, which aims to improve communication stability and control accuracy.

[0054] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0055] Example 1

[0056] like Figure 1 As shown in this embodiment, a fault-tolerant cooperative guidance method for multiple aircraft based on event triggering is provided. The method includes:

[0057] Step 100: Obtain the operational data of the intelligent agent. The intelligent agent includes: N aircraft and a single maneuvering target; the operational data includes: flight data and relative distance; the flight data includes: trajectory inclination angle, constant velocity, and velocity lead angle.

[0058] Step 200: Construct a multi-vehicle system state model based on operational data. The multi-vehicle system state model is constructed based on the relative kinematic equations in polar coordinates of a multi-vehicle system consisting of N aircraft, cooperating to intercept a single maneuvering target.

[0059] Step 300: Based on the multi-vehicle system state model and the scenario with limited communication resources, determine the guidance mathematical model. The guidance mathematical model is constructed based on sliding mode variables and cooperative guidance laws; the scenario with limited communication resources is a multi-vehicle system in a distributed communication topology, where only two adjacent aircraft receive communication information based on an adjacency matrix.

[0060] For any aircraft, perform the following:

[0061] Step 400: Based on the state variable trigger function and the line-of-sight angle state, determine whether the line-of-sight angle state deviation meets the trigger condition, and obtain the first judgment result.

[0062] Step 500: If the first judgment result is yes, then update the sight angle state according to the sight angle state deviation to obtain the updated sight angle state.

[0063] Step 600: Based on the adaptive parameters and the adaptive parameter trigger function, determine whether the adaptive gain meets the trigger condition, and obtain the second judgment result.

[0064] Step 700: If the second judgment result is yes, then update the adaptive parameters according to the adaptive gain to obtain the updated adaptive parameters.

[0065] Step 800: Based on all updated line-of-sight angle states, all updated adaptive parameters, and the guidance mathematical model, determine the cooperative guidance law. The cooperative guidance law is used to control N aircraft to cooperate in intercepting a single maneuvering target.

[0066] The multi-vehicle system state model specifically includes:

[0067]

[0068] Where, r i (t) represents the relative distance between the aircraft and the target; V T θ represents the constant velocity of the maneuvering target. T,i (t) represents the velocity lead angle of the maneuvering target; V M,i Let θ be the constant velocity of the i-th aircraft; M,i (t) represents the velocity lead angle of the i-th aircraft; λ i (t) represents the line-of-sight angle; γ M,i (t) represents the trajectory inclination angle of the i-th aircraft; γ T(t) represents the trajectory inclination angle of the maneuvering target; The overload command is perpendicular to the velocity of the i-th aircraft; a T (t) represents the overload command of the maneuvering target perpendicular to its own velocity; For r i (t) is the first derivative of (t) with respect to time t; For λ i (t) is the first derivative of (t) with respect to time t; For γ M,i (t) is the first derivative of (t) with respect to time t; For γ T (t) is the first derivative of (t) with respect to time t.

[0069] Guidance mathematical models, specifically including:

[0070]

[0071]

[0072]

[0073] in, K is the sliding mode variable; k1 is the positive constant gain; N is the number of aircraft; Let a be the triggering time of the i-th aircraft determined by the triggering function. M,i (t) represents the cooperative guidance law; For piecewise constant adaptive gain; r i (t) represents the relative distance between the aircraft and the target; θ M,i (t) represents the velocity lead angle of the i-th aircraft; l i (t) is a time-varying function; h i Let i be the line-of-sight formation vector for the i-th aircraft; For the i-th aircraft in The state of the line of sight at any given moment; For the j-th aircraft in The state of the line of sight at any given moment; h j Let J be the line-of-sight formation vector for the j-th aircraft; For λ i (t) is the first derivative of u with respect to time t; i (t) is an intermediate parameter; a ij a represents the communication relationship between aircraft if and only if there is a communication link between aircraft i and aircraft j. ij =1, otherwise, a ij =0.

[0074] The expression for the state variable trigger function is:

[0075]

[0076] Among them, f i (t) is the state variable trigger function; The maximum adaptive gain is defined for aircraft i and the aircraft with which it has a communication link. The maximum adaptive gain among aircraft that have a communication link with aircraft i; ψ i ={j|a ij =1} represents the set of aircraft that have a communication link with aircraft i; For line-of-sight angle triggering error; ∈ i The positive real numbers driving the convergence of the sliding mode variables; φ and ν are both positive real numbers, φe -νt Together they are used to exclude the Zeno phenomenon.

[0077] The expression for the adaptive parameter trigger function is:

[0078]

[0079] Among them, f α，i (t) is the adaptive parameter trigger function; α i (t) is the adaptive parameter; The adaptive gain is a piecewise constant; μ i It is a positive real number used to exclude the Zeno phenomenon in the adaptive parameter triggering mechanism.

[0080] In practical applications, the specific operation process of this method is as follows:

[0081] First, all aircraft and maneuvering targets are considered as intelligent agents. Multiple aircraft systems can communicate with each other. However, in actual applications, aircraft may experience actuator failures and communication limitations due to malfunctions, interference, or other reasons.

[0082] Then, considering the impact of actuator failures on cooperative guidance, a distributed fault-tolerant guidance method is designed. Based on this, to address the communication limitation problem, an event-triggered mechanism is designed to enable information exchange between multiple aircraft systems. Finally, the event-triggered cooperative fault-tolerant guidance method is used to achieve cooperative interception of maneuvering targets.

[0083] like Figure 15 As shown, the steps of the proposed event-triggered distributed fault-tolerant cooperative guidance method are summarized as follows:

[0084] Step 1: Construct a state model of the multi-vehicle system.

[0085] Consider a multi-aircraft system consisting of N aircraft collaboratively intercepting a single maneuvering target. The target's index is denoted by T, and the aircraft's indices are 1, 2, ..., N. The relative kinematic equations in polar coordinates are shown below.

[0086]

[0087] Where i∈{1,2,…,N}, r i (t) represents the relative distance between the aircraft and the target, λ i (t) is the line-of-sight angle, γ M,i (t) and γ T (t) represents the trajectory inclination angle between aircraft i and the target, V M,i With V T For the corresponding constant velocity, With a T (t) represents the corresponding overload command perpendicular to its own velocity, θ M,i (t)=λ i (t)-γ M,i (t) and θ T,i (t)=λ i (t)-γ T (t) represents the velocity lead angle of each individual.

[0088] Overload command This does not refer to the guidance law that needs to be designed, but rather the output command of the actuator (such as a servo motor) that takes into account potential malfunctions. This output command is as follows.

[0089]

[0090] Among them, a M,i (t) represents the cooperative guidance law, ρ i (t) is the time-varying actuator efficiency loss function, b i (t) represents the output bias of the time-varying actuator.

[0091] The desired line-of-sight formation for multiple aircraft is determined by the formation vector h = [h 1,λ ,h 2,λ ,…,h N,λ ] T What is depicted.

[0092] The communication structure of a multi-aircraft system consisting of N aircraft is described by graph G, and its adjacency matrix is ​​defined as follows: a ij =1, otherwise, a ij =0.

[0093] Step 2: Sliding mode variable calculation and guidance law design.

[0094] To adapt to scenarios with limited communication resources, consider the following piecewise continuous sliding mode variables. With the cooperative guidance law a M,i (t).

[0095]

[0096]

[0097] in,

[0098]

[0099] For aircraft i, Let i be the triggering time determined by the triggering function. For piecewise constant adaptive gain, l i (t) > 0 is a time-varying function used to mitigate chattering. k1 represents the positive constant gain.

[0100] Step 3: Triggering mechanism for line-of-sight angle state.

[0101] Choose φ>0, ν>0, ∈ i >0, the trigger time for the design view angle state is The trigger function f of the state variable i (t) is designed as follows:

[0102]

[0103] in, The maximum adaptive gain is defined for aircraft i and the aircraft with which it has a communication link. The maximum adaptive gain among aircraft that have a communication link with aircraft i; ψ i ={j|a ij =1} represents the set of aircraft that have a communication link with aircraft i. This refers to the line-of-sight angle triggering error.

[0104] If the line-of-sight angle deviation of aircraft i meets the trigger condition f i (t), the line-of-sight angle state λ i (t) is transmitted to neighboring aircraft, and both the aircraft itself and its neighboring aircraft use the updated line-of-sight (LAS) state to calculate the guidance law; if the LAS state deviation of aircraft i does not meet the trigger condition f i (t), then the line-of-sight angle state λ is not transmitted. i (t).

[0105] Step 4: Triggering mechanism and update of adaptive gain.

[0106] Adaptive parameter initialization is set to

[0107] Select μ i >0, Design The trigger time is For the last time The initial value is set to the trigger time. The trigger function f α,i (t) is designed as follows:

[0108]

[0109] Adaptive parameter α i The update law for (t) is designed as follows:

[0110]

[0111] Where, τ i >0 represents the update gain coefficient of the adaptive parameters, D + α i (t) represents the expression for α i (t) Find the upper Dini derivative.

[0112] When the adaptive parameter α of aircraft i i (t) and The trigger condition f is met α,i At time (t), aircraft i will Updated to α i The current value of (t) is obtained and transmitted to neighboring aircraft to update their respective guidance laws; if the adaptive parameter α of aircraft i is... i (t) and The trigger condition f is not met. α,i (t), then keep It remains unchanged, and the adaptive parameter α is not transmitted. i (t).

[0113] The effectiveness of the proposed method is verified through a specific example of a multi-vehicle system collaboratively intercepting a single maneuvering target. The specific implementation steps of this example are as follows:

[0114] (1) Target setting.

[0115] Consider a maneuvering target. In an inertial Cartesian coordinate system, the target's initial coordinates are [x...]. T (0),y T [0] = [30, 15] km, flight speed is V T =300m / s², the overload adopts a sinusoidal overload maneuver, and its acceleration command is a. T (t)=30sin0.5t m / s2 The initial trajectory angle of the target is 180°.

[0116] (2) Multi-aircraft system setup.

[0117] Consider N=4 aircraft coordinating to intercept a maneuvering target. In the inertial rectangular coordinate system, the initial distances between the aircraft and the target are r1(0)=9.5km, r2(0)=10km, r3(0)=9km, r4(0)=10km; the flight speeds of the aircraft are V1=500m / s, V2=500m / s, V3=500m / s, V4=500m / s; the initial line-of-sight angles of the aircraft are λ1(0)=35°, λ2(0)=25°, λ3(0)=45°, λ4(0)=15°; the initial ballistic tilt angles of the aircraft are γ1(0)=20°, γ2(0)=20°, γ3(0)=10°, γ4(0)=20°.

[0118] (3) Desired line-of-sight formation settings.

[0119] To depict the desired encirclement configuration, the following line-of-sight formation design reference is provided:

[0120] h1=45°, h2=30°, h3=55°, h4=15°.

[0121] (4) Design of parameters for distributed fault-tolerant collaborative guidance law based on event triggering.

[0122] To implement the proposed event-triggered distributed fault-tolerant cooperative guidance law, for aircraft i, i∈{1,2,…,N}, its main parameter is set as α. i (0) = 5, μ i =0.001, ∈ i =0.2, φ=2, ν=1.5, τ i =2.

[0123] (5) Results analysis.

[0124] Figure 2 The data shows the trajectories of multiple aircraft and the target, demonstrating that multiple aircraft engaged and attacked the target from different directions. Secondly, Figure 3 A line-of-sight profile of multiple aircraft is presented, and the line-of-sight angles of multiple aircraft eventually converge to the terminal value constrained by the flight angle formation vector. Figure 4 The line-of-sight rate curves for multiple aircraft are presented, showing that the line-of-sight rate eventually approaches 0, thus enabling the multi-aircraft guidance process. Figure 5 The local error curves of each aircraft are shown. As the guidance process progresses, the local error of each aircraft tends to 0, which also verifies the effectiveness of the proposed guidance law. Figure 6The data presents the overload curves of multiple aircraft. It can be seen that the overload of multiple aircraft basically reaches saturation within the first 2 seconds, and the overload gradually decreases thereafter. This is because, under the action of the guidance law, each aircraft uses its current overload capacity to reduce the line-of-sight angle deviation and line-of-sight rate deviation in the initial moment in order to complete the coordinated strike target. Figure 7 The curves for triggering the sliding mode variables are shown. Both variables eventually converge to 0, thus verifying the effectiveness of the guidance law in stabilizing sliding mode dynamics. Secondly, Figures 8 to 11 The trigger times and intervals for the line-of-sight angle states of each aircraft are given. Considering that the step size in the simulation process in this chapter is 0.002s, the shortest interval of all four aircraft is greater than the compensation value, which fully demonstrates that the Zeno phenomenon does not exist in the cooperative guidance process. Figure 12 , Figure 13 and Figure 14 The adaptive gain of the aircraft and its triggering behavior are presented separately. The various gains of the aircraft eventually tend to certain specific constants, and the number of triggers is less than that of state-triggered events. In summary, the effectiveness of the proposed method is verified.

[0125] In practical applications of cooperative guidance methods for intercepting maneuvering targets using multiple aircraft, data links and communication networks between aircraft swarms are easily affected by enemy electromagnetic interference, physical obstructions, and extreme weather conditions in complex battlefield environments, leading to interference or interruptions in data link transmission. Furthermore, due to manufacturing defects, material fatigue, external environmental factors, and electronic component failures, actuators, including various critical components such as control surfaces, fuses, and propulsion systems, are susceptible to actuator failures. High-speed, highly maneuvering aircraft may experience loss of heading, attitude, or propulsion control, thus affecting their flight path and accuracy. This invention proposes an event-triggered cooperative fault-tolerant guidance method for multiple aircraft. Utilizing intermittent communication status information through an event-triggered mechanism, and employing an adaptive method to estimate and compensate for actuator failures, this method enables the multi-aircraft system to be robust to actuator failures and limited communication resources, allowing for cooperative interception of maneuvering targets even under these conditions.

[0126] Example 2

[0127] A computer device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the event-triggered multi-aircraft fault-tolerant cooperative guidance method of Embodiment 1.

[0128] Example 3

[0129] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the event-triggered multi-vehicle fault-tolerant cooperative guidance method of Embodiment 1.

[0130] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0131] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A multi-vehicle fault-tolerant cooperative guidance method based on event triggering, characterized in that, The method includes: Acquire operational data of the intelligent agent; the intelligent agent includes: N aircraft and a single maneuvering target; the operational data includes: flight data and relative distance; the flight data includes: trajectory inclination angle, constant velocity, and velocity lead angle; A multi-vehicle system state model is constructed based on the operational data. The multi-vehicle system state model is based on the relative kinematic equations in polar coordinates of a multi-vehicle system consisting of N aircraft, which cooperate to intercept a single maneuvering target. Based on the state model of the multi-vehicle system, a guidance mathematical model is determined under the scenario of limited communication resources. The guidance mathematical model is constructed based on sliding mode variables and cooperative guidance laws. The scenario of limited communication resources refers to the multi-vehicle system in a distributed communication topology where only two adjacent vehicles receive communication information based on an adjacency matrix. For any aircraft, perform the following: Based on the state variable trigger function and the line-of-sight angle state, determine whether the line-of-sight angle state deviation meets the trigger condition, and obtain the first judgment result; If the first judgment result is yes, then the line of sight angle state is updated according to the line of sight angle state deviation to obtain the updated line of sight angle state; Based on the adaptive parameters and the adaptive parameter triggering function, determine whether the adaptive gain meets the triggering condition, and obtain the second judgment result; If the second judgment result is yes, then the adaptive parameters are updated according to the adaptive gain to obtain the updated adaptive parameters; Based on all updated line-of-sight states, all updated adaptive parameters, and the guidance mathematical model, a cooperative guidance law is determined; the cooperative guidance law is used to control N aircraft to cooperate in intercepting a single maneuvering target. The expression for the state variable trigger function is: ； in, The function is triggered by the state variable; For aircraft And the largest adaptive gain among the aircraft with which it has a communication link; To be with the aircraft The largest adaptive gain among aircraft with communication links; Indicates with aircraft A collection of aircraft with communication links; This refers to the line-of-sight angle triggering error. A positive real number that drives the convergence of the sliding mode variable; and All are positive real numbers. Together they are used to eliminate the Zeno phenomenon; For sliding mode variables; For aircraft Piecewise constant adaptive gain; This indicates the communication relationship between aircraft; The viewing angle; For the first The triggering time for each aircraft is determined by a triggering function; For aircraft The stopping time determined by the trigger function; For the first A flying vehicle The state of the line of sight at any given moment; The expression for the adaptive parameter triggering function is: ； in, This is a function triggered by adaptive parameters. For adaptive parameters; An adaptive gain with piecewise constant values; It is a positive real number.

2. The event-triggered multi-vehicle fault-tolerant cooperative guidance method according to claim 1, characterized in that, The multi-vehicle system state model specifically includes: ； in, The relative distance between the aircraft and the target; The constant velocity of the maneuvering target; The speed lead angle of the maneuvering target; For the first The constant speed of an aircraft; For the first The speed of the aircraft is ahead of the leading angle; The viewing angle; For the first The trajectory tilt angle of the aircraft; The trajectory inclination angle of the maneuvering target; For the first An overload command perpendicular to the speed of an aircraft; An overload command that is perpendicular to the speed of the maneuvering target; for Regarding time The first derivative; for Regarding time The first derivative; for Regarding time The first derivative; for Regarding time The first derivative.

3. The event-triggered multi-vehicle fault-tolerant cooperative guidance method according to claim 1, characterized in that, The guidance mathematical model specifically includes: ； ； ； in, For sliding mode variables; Gain is a positive constant. The number of aircraft; For the first The triggering time for each aircraft is determined by a triggering function; For coordinated guidance laws; An adaptive gain with piecewise constant values; The relative distance between the aircraft and the target; For the first The speed of the aircraft is ahead of the leading angle; It is a time-varying function; For the first Line-of-sight formation vector for each aircraft; For the first A flying vehicle The state of the line of sight at any given moment; For the first A flying vehicle The state of the line of sight at any given moment; For the first Line-of-sight formation vector for each aircraft; for Regarding time The first derivative; For intermediate parameters; To indicate the communication relationship between aircraft, if and only if the aircraft With aircraft When there is a communication link between them, ,otherwise, .

4. A computer device, comprising: The memory and processor contain a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the event-triggered multi-vehicle fault-tolerant cooperative guidance method according to any one of claims 1-3.

5. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the event-triggered multi-vehicle fault-tolerant cooperative guidance method as described in any one of claims 1-3.

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