Modeling simulation method for digital twin model of fixed-wing unmanned aerial vehicle

Abstract

The invention provides a modeling simulation method for a digital twin model of a fixed-wing unmanned aerial vehicle, and relates to the technical field of digital twin. The method comprises the following steps: establishing a fixed-wing unmanned aerial vehicle three-dimensional model Establishing dynamics and kinematics equations of the fixed-wing unmanned aerial vehicle; deducing a linear model of the fixed-wing unmanned aerial vehicle and an actuator fault model; establishing a digital twinborn model of the fixed-wing unmanned aerial vehicle; establishing a real-time communication relation between the fixed-wing unmanned aerial vehicle digital twin model and the entity fixed-wing unmanned aerial vehicle model; and operating the digital twin model of the fixed-wing unmanned aerial vehicle for simulation, and outputting flight state data in a visual interface. The method has the characteristics of high synchronism and coordination of the equipment entity and the equipment model, and the purposes of comprehensively controlling the actual operation state of the equipment and establishing the digital twin model of the fixed-wing unmanned aerial vehicle can be achieved.

Description

Technical Field

[0001] The present invention belongs to the technical field of digital twins, and in particular relates to a method for modeling and simulating a digital twin model of a fixed-wing unmanned aerial vehicle. Background Art

[0002] Digital twin technology can abstract the properties, phenomena, formation process and performance of physical entities, and comprehensively describe and simulate the equipment in virtual space. Through digital twin technology, a virtual space mapping of the correspondence between physical space entities can be established, thereby simulating the full life cycle of physical space entities in virtual space. Digital twin technology can establish a high-fidelity digital twin model of equipment, which can comprehensively describe the behavior and performance of the equipment entity. However, due to the large number of structural parts of drones and the complex and changeable operation conditions, if the drone is calculated and analyzed based on the traditional three-dimensional model, the physical information data of the equipment cannot be dynamically updated, resulting in problems such as untimely detection and inconsistent information.

[0003] There are three main types of modeling methods currently being studied, namely, modeling methods based on 3D modeling software, modeling methods based on mathematical models, and modeling methods based on big data. However, the above three methods have problems such as the simulation model being out of touch with the actual environment, being unable to fully control the actual operating status of the equipment, and poor synchronization and coordination between the equipment entity and the equipment model in practice. Summary of the invention

[0004] In order to overcome the problems existing in the above-mentioned prior art, the present invention provides a modeling and simulation method of a digital twin model of a fixed-wing UAV, which has the characteristics of strong synchronization and coordination between the equipment entity and the equipment model, and can achieve the purpose of fully controlling the actual operating status of the equipment and establishing a digital twin model of a fixed-wing UAV.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is:

[0006] A fixed-wing UAV digital twin model modeling and simulation method comprises the following steps:

[0007] Step 1, build a three-dimensional model of the fixed-wing UAV;

[0008] Step 2, establish the dynamics and kinematics equations of the fixed-wing UAV;

[0009] Step 3, through the fixed-wing UAV dynamics and kinematics equations and the fault state analysis of the fixed-wing UAV, derive the fixed-wing UAV linearization model and actuator fault model;

[0010] Step 4: Use the fixed-wing UAV linearization model and actuator fault model to guide the simulated flight state of the fixed-wing UAV three-dimensional model and establish a fixed-wing UAV digital twin model;

[0011] Step 5, establishing real-time communication between the fixed-wing UAV digital twin model and the physical fixed-wing UAV model;

[0012] Step 6: Run the fixed-wing UAV digital twin model for simulation and output the flight status data in the visualization interface.

[0013] Furthermore, the specific method of step 1 is:

[0014] In Unity 3D software, a 3D model of the fixed-wing UAV is established according to its 3D size and internal structure.

[0015] Furthermore, the specific method of step 2 is:

[0016] Step 201, analyze the forces and moments on the drone, and the gravity F G , air resistance F 阻 , lateral force F 侧 , and the torque of the engine thrust are combined to calculate the linear acceleration and angular acceleration of the UAV fuselage axis in the body coordinate system, and combined with the wind velocity, the relevant parameters of the UAV flight process are calculated;

[0017] Step 202, with the ground coordinate system as a reference, decompose the angular velocity of the fuselage axis to obtain the change rate of the drone's angle of attack α, sideslip angle β and angular velocity H; decompose the angular velocity to obtain the drone's pitch angle θ, yaw angle y and roll angle Obtain the flight attitude parameters of the UAV;

[0018] Step 203, establish the dynamic equation of the UAV linear motion based on the ground coordinate system as follows:

[0019]

[0020] In the formula, ω x ,ω y ,ω z is the angular velocity component of the UAV's flight angular velocity along the x-axis, y-axis, and z-axis in the body coordinate system; v x 、v y 、v z It represents the flight speed of the drone along the x-axis, y-axis, and z-axis; X, Y, and Z represent the projection of air resistance on the x-axis, y-axis, and z-axis of the velocity coordinate system, which are the resistance, side force, and lift of the drone respectively; g is the acceleration due to gravity; Represents the transfer matrix of the velocity coordinate system relative to the body coordinate system, Represents the transfer matrix of the ground coordinate system relative to the body coordinate system;

[0021] Step 204, establish the kinematic equation of the drone rotating around the center of mass based on the ground coordinate system as follows:

[0022]

[0023] In the formula, ω xb ,ω yb ,ω zb It is the angular velocity component of the UAV's flight angular velocity along the x-axis, y-axis, and z-axis in the body coordinate system; θ and ψ are flight attitude angle variables; the angular velocity of the UAV depends on the rate of change of the flight attitude angle and in is the rate of change along the x-axis, is the rate of change along the y-axis, is the rate of change along the z-axis.

[0024] Furthermore, in step 3, the linearization model of the fixed-wing UAV is derived as follows:

[0025] According to the UAV dynamics and kinematics equations, a six-degree-of-freedom fixed-wing UAV linear model is established, and the flight speed v and angle of attack α of the UAV are constrained within the interval to ensure the authenticity and reliability of the model;

[0026] According to the state space expression of the nonlinear system, through the dynamics and kinematics equations of the UAV, combined with the principle of small disturbance linearization, the linearized model of the UAV is expressed as:

[0027]

[0028] y(t)=Cx(t)

[0029] In the formula, represents the derivative of the state vector, x(t) is the state vector of the system, which contains the internal state information of the drone; A is the state matrix, B is the input matrix, u(t) represents the control input vector, y(t) represents the output vector, which contains the state and measurement value of the drone; C is the output matrix.

[0030] Furthermore, in step 3, the actuator fault model is derived as follows:

[0031] Analyze common fixed-wing UAV actuator failures, including left and right aileron stuck at zero position, elevator stuck at zero position, rudder stuck at zero position, and engine full power loss;

[0032] make is the actual output of the actuator, This is the signal that the actuator should output when it is normal, and the actuator failure is represented as:

[0033]

[0034] In the formula, Indicates the output value when the actuator is stuck at zero position, ranging from and between; It indicates the degree of actuator damage and is a variable that changes with time; Indicates the signal that the actuator should output when it is normal.

[0035] For the above four common fixed-wing UAV actuator faults, combined with the UAV linearization model, the fault behavior of the fixed-wing UAV actuator is expressed as follows:

[0036]

[0037] y(t)=Cx(t)

[0038] In the formula, f a ∈R m Represents the fault vector of the actuator, n out (t) is a function of actuator failure. represents the state vector, represents the input vector, represents the output vector, and A, B, and C represent the system matrices.

[0039] Furthermore, in step 5, the MAVLink2.0 communication protocol is used to establish a real-time communication connection between the fixed-wing UAV digital twin model and the physical fixed-wing UAV model. The specific steps are as follows:

[0040] Step 501, using the UAV flight ground station to obtain flight control data information, and using the MaVlink2.0 protocol to analyze the information content of the control system status, aircraft attitude, and orientation;

[0041] Step 502, forming a TCP / IP connection with the gateway, and performing terminal user login, authentication, terminal heartbeat packet transmission and response analysis according to the JT / T-808 protocol; then, assembling the JT / T-808 position report data frame according to the information parsed in step 501, and uploading it to the gateway;

[0042] Step 503, realize the connection of the terminal user, and judge the network connection status according to the general response; if the communication is interrupted, store the data frames of this situation for subsequent use; if the network restores the communication, upload the data frames in batches to supplement the stored data frame information.

[0043] The beneficial effects of the present invention are:

[0044] 1. The present invention uses the concept of digital twins to establish a digital twin model of a drone. Through Unity 3D software, the appearance and internal structure of the fixed-wing drone can be accurately described, and a three-dimensional model of the drone can be established; through the drone dynamics and kinematics equations, the drone linearization model and actuator fault model can be derived; through mathematical models, the three-dimensional model is guided to establish a digital twin model of the drone, providing a real, real-time, and objective model foundation for drone fault diagnosis and management, and ensuring the high fidelity of the digital twin model.

[0045] 2. The existing simulation model is divorced from the actual environment and overly relies on prior knowledge to evaluate the equipment. It lacks the support of big data and cannot fully control the actual operating status of the equipment. In addition, the existing simulation model has the problem of poor synchronization and coordination between the equipment entity and the equipment model in practice. The present invention solves the above problems. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 is a flow chart of a method for modeling and simulating a digital twin model of a fixed-wing UAV in an embodiment of the present invention;

[0047] Figure 2 It is a schematic diagram of a three-dimensional simulation model of a fixed-wing UAV;

[0048] Figure 3 This is a schematic diagram of the force analysis of a fixed-wing UAV;

[0049] Figure 4 It is a schematic diagram of the digital twin model of a fixed-wing UAV;

[0050] Figure 5 It is the communication flow chart between the digital twin model of the fixed-wing UAV and the physical fixed-wing UAV model. DETAILED DESCRIPTION

[0051] The specific implementation of the present invention is further described below in conjunction with the accompanying drawings and technical solutions.

[0052] A modeling and simulation method for a digital twin model of a fixed-wing UAV is provided. This method organically combines the modeling method based on three-dimensional modeling software, the modeling method based on mathematical models, and the modeling method based on big data, opening up a new technical route. Specifically, this method uses the concept of digital twins to establish a digital twin model of a UAV; through Unity3D software, an accurate description of the appearance and internal structure of the fixed-wing UAV is achieved, and a three-dimensional model of the UAV is established; through the UAV dynamics and kinematics equations, the linearization model of the UAV and the actuator fault model are derived; through the mathematical model, the three-dimensional model is guided to establish a digital twin model of the UAV, providing a real, real-time, and objective model basis for the fault diagnosis and management of the UAV, and ensuring the high fidelity of the digital twin model.

[0053] like Figure 1 As shown, the method comprises the following steps:

[0054] (1) Establish a three-dimensional model of a fixed-wing UAV;

[0055] (2) Establish the dynamics and kinematics equations of fixed-wing UAVs;

[0056] (3) Through the fixed-wing UAV dynamics and kinematics equations and the fault state analysis of the fixed-wing UAV, the fixed-wing UAV linearization model and actuator fault model are derived;

[0057] (4) Through the linearization model and actuator fault model of the fixed-wing UAV, the simulated flight state of the fixed-wing UAV three-dimensional model is guided to establish a digital twin model of the fixed-wing UAV;

[0058] (5) Use the MAVLink2.0 communication protocol to establish real-time communication between the fixed-wing UAV digital twin model and the physical fixed-wing UAV model;

[0059] (6) Run the digital twin model simulation and output relevant flight status data in the visualization interface.

[0060] In step 1, a 3D model of the fixed-wing drone is created in Unity 3D software according to the 3D size and internal structure of the fixed-wing drone. Figure 2 As shown in the figure. In the process of designing the digital twin model on the Unity 3D platform, the model needs to be processed in many ways, including drawing the fixed-wing drone 3D model, improving the model's appearance design, and writing C# language programs to control the model's motion behavior. By inputting the relevant flight parameters of the drone, the flight status of the drone can be controlled and real-time communication with the physical drone can be established.

[0061] In step 2, first, consider the forces and moments acting on the drone, such as Figure 3 As shown, the gravity FG , air resistance F 阻 , lateral force F 侧 , engine thrust and other torques are combined to calculate the linear acceleration and angular acceleration of the drone fuselage axis in the body coordinate system, and combined with the wind velocity, the relevant parameters of the drone flight process are inferred. With the ground coordinate system as a reference, the angular velocity of the fuselage axis is decomposed to obtain the drone's angle of attack α, sideslip angle β and the rate of change of angular velocity H. The angular velocity is decomposed to obtain the drone's pitch angle θ, yaw angle y and roll angle The flight attitude parameters of the UAV can be obtained.

[0062] The dynamic equation of the UAV linear motion based on the ground coordinate system is established as follows:

[0063]

[0064] In the above formula, X, Y, and Z represent the projection of air resistance on the x-axis, y-axis, and z-axis of the velocity coordinate system, which are the drag, side force, and lift of the drone, respectively. g is the acceleration due to gravity. Represents the transfer matrix of the velocity coordinate system relative to the body coordinate system, Represents the transfer matrix of the ground coordinate system relative to the body coordinate system.

[0065] The kinematic equation for the rotation of the drone around the center of mass based on the ground coordinate system is as follows:

[0066]

[0067] In the above formula, ω xb ,ω yb ,ω zb It is the angular velocity component of the UAV's flight angular velocity along the x-axis, y-axis, and z-axis in the body coordinate system. The angular velocity of the UAV depends on the rate of change of the flight attitude angle. and in is the rate of change along the z-axis, is the rate of change along the y-axis, is the rate of change along the x-axis.

[0068] In step 3, based on the UAV dynamics and kinematics equations, a six-degree-of-freedom fixed-wing UAV linearization model can be established, and the flight speed v and angle of attack α of the UAV are constrained within the interval to ensure the authenticity and reliability of the model. According to the state space expression of the nonlinear system, through the above-derived UAV dynamics and kinematics equations, combined with the principle of small perturbation linearization, the UAV linearization model is expressed as:

[0069]

[0070] y(t)=Cx(t)

[0071] In the formula, represents the derivative of the state vector, x(t) is the state vector of the system, which contains the internal state information of the drone, such as position, velocity, attitude angle, etc.; A is the state matrix, B is the input matrix, u(t) represents the control input vector, y(t) represents the output vector, which contains the state and measurement value of the drone; C is the output matrix, which determines how to extract and combine the output vector y(t) from the system state vector x(t).

[0072] Actuator failure is typical in UAV failures. The working condition of the actuator is closely related to the flight attitude of the fixed-wing UAV. If a failure occurs, the lift of the fixed-wing UAV will decrease rapidly, causing the three-axis motion posture, mode and flight characteristics to change, thus seriously affecting the stability of the fixed-wing UAV's navigation. Research is conducted on the diagnosis of common fixed-wing UAV actuator faults, which mainly include the left and right ailerons stuck at zero position, the elevator stuck at zero position, the rudder stuck at zero position, and the full power loss of the engine. Let n out is the actual output of the actuator, n in This is the signal that the actuator should output when it is normal. The actuator failure can be expressed as follows:

[0073]

[0074] For the above four common fixed-wing UAV faults, combined with the above UAV linearization model, the fault behavior of the fixed-wing UAV actuator can be expressed as follows:

[0075]

[0076] y(t)=Cx(t)

[0077] In the above formula, f a ∈R m Represents the fault vector of the actuator, n out (t) is the function of the actuator failure.

[0078] In step 4, the digital twin model is mainly three-dimensionally modeled through Unity 3D software. This process requires the extraction of relevant features of the complete fixed-wing UAV physical entity, including geometric parameters, mechanical properties, fuselage materials and other information, as well as corresponding signal characteristics, status data and other information of the fixed-wing UAV physical entity during normal operation and failure. Finally, the fixed-wing UAV digital twin model is initialized by combining the above data with the linearized model to obtain the fixed-wing UAV digital twin model, which consists of physical space, digital space (virtual space), twin database, UAV fault diagnosis system and the connection between the various parts, such as Figure 4 shown.

[0079] The digital twin model includes a three-dimensional model of the fixed-wing UAV and a packaged linearized model of the fixed-wing UAV. The real-time feature data transmitted by the physical fixed-wing UAV is used to drive the digital twin model in real time, thereby accurately simulating the actual working state of the fixed-wing UAV. A real-time communication connection between the physical entities of the fixed-wing UAV is established to achieve dynamic transmission and update of real-time data. Finally, the linearized model of the fixed-wing UAV is combined with the three-dimensional model of the fixed-wing UAV to realize the creation of the fixed-wing UAV twin model.

[0080] In step 5, the communication protocol used for data exchange between the flight control system of the physical UAV and the flight control system of the twin UAV is MAVLink2.0. Figure 5 As shown, the specific steps are as follows:

[0081] (1) Use the UAV flight ground station to obtain flight control data information, and use the MaVlink2.0 protocol to analyze the control system status, aircraft attitude, orientation and other information;

[0082] (2) Establish a TCP / IP connection with the gateway and perform terminal user login, authentication, terminal heartbeat packet transmission and response analysis according to the JT / T-808 protocol; then, combine the JT / T-808 location report data frame based on the parsed data and upload it to the gateway;

[0083] (3) To achieve the connection of the terminal user, the network connection status is determined based on the general response. If the communication is interrupted, the data frames of this situation are stored for subsequent use. If the network restores the communication, the stored data information can be supplemented by using batch upload data frames.

[0084] The principle of the present invention is as follows:

[0085] Digital twin technology is characterized by virtual-real mapping and real-time synchronization. It is an important tool that enables the interaction and integration of physical space and information space, and helps promote the process of intelligent manufacturing. Digital twin technology can abstract the properties, phenomena, formation process and performance of physical entities, and comprehensively describe and simulate the equipment in the virtual space. Through digital twin technology, a virtual space mapping of the correspondence between physical space entities can be established, thereby simulating the full life cycle of physical space entities in the virtual space. However, existing algorithms have problems such as the simulation model being out of touch with the actual environment, being unable to fully control the actual operating status of the equipment, and poor synchronization and coordination between the equipment entity and the equipment model during practice. In order to solve the above problems, the present invention proposes a modeling and simulation method for a digital twin model of a fixed-wing unmanned aerial vehicle.

[0086] (1) Derive the linearization model and fault model expressions of fixed-wing UAV.

[0087] Taking into account the forces and moments of the drone, that is, combining multiple moments such as gravity FG, air resistance F, side force F, and engine thrust, the linear acceleration and angular acceleration of the drone fuselage axis in the body coordinate system are calculated, and combined with the wind velocity, the relevant parameters of the drone flight process are inferred and inverted. With the ground coordinate system as a reference, the angular velocity of the fuselage axis is decomposed to establish the dynamics and kinematics equations of the fixed-wing drone. According to the dynamics and kinematics equations of the drone, a linearized model of a six-degree-of-freedom fixed-wing drone and an expression for the actuator fault model can be established.

[0088] (2) Combine the three-dimensional model and mathematical model to establish a digital twin model of fixed-wing UAV.

[0089] The digital twin model is mainly based on three-dimensional virtual modeling using Unity 3D software. This process requires the extraction of relevant features of the complete fixed-wing UAV physical entity, including geometric parameters, mechanical properties, fuselage material and other information, as well as the corresponding signal characteristics, status data and other information of the fixed-wing UAV physical entity during normal operation and failure. The initialization of the fixed-wing UAV digital twin model is completed by combining the above data with the linearized model.

[0090] (3) Establish a real-time communication interface between the digital twin model of the fixed-wing UAV and the physical entity.

[0091] The MAVLink2.0 communication protocol is used to establish real-time communication between the digital twin model of the fixed-wing UAV and the physical fixed-wing UAV model. By utilizing digital information, big data, computer communication, the Internet, database and other technologies, the real-time acquisition and transmission of the UAV's physical space information is realized, making the UAV's physical entity and virtual twin interconnected and interactively mapped. While realizing real-time online monitoring of the UAV's internal working status, it can arrange staff to carry out targeted maintenance in a timely manner.

[0092] In summary, the present invention mainly solves two technical problems. One is that the simulation model is divorced from the actual environment and overly relies on prior knowledge to evaluate the equipment, lacks the support of big data, and is unable to fully control the actual operating status of the equipment. The other is the poor synchronization and coordination between the equipment entity and the equipment model in practice.

[0093] The above disclosure is only an example of the present invention, and certainly cannot be used to limit the scope of the present invention. Ordinary technicians in this field can understand the process of implementing the above example and make equivalent changes according to the claims of the present invention.

Claims

1. A fixed-wing UAV digital twin model modeling and simulation method, characterized in that: The steps include: Step 1, build a three-dimensional model of the fixed-wing UAV; Step 2, establish the dynamics and kinematics equations of the fixed-wing UAV; Step 3, through the fixed-wing UAV dynamics and kinematics equations and the fault state analysis of the fixed-wing UAV, derive the fixed-wing UAV linearization model and actuator fault model; Step 4: Use the fixed-wing UAV linearization model and actuator fault model to guide the simulated flight state of the fixed-wing UAV three-dimensional model and establish a fixed-wing UAV digital twin model; Step 5, establishing real-time communication between the fixed-wing UAV digital twin model and the physical fixed-wing UAV model; Step 6: Run the fixed-wing UAV digital twin model for simulation and output the flight status data in the visualization interface.

2. A fixed-wing UAV digital twin model modeling and simulation method as claimed in claim 1, characterized in that: The specific method of step 1 is: In Unity 3D software, a 3D model of the fixed-wing UAV is established according to its 3D size and internal structure.

3. A fixed-wing UAV digital twin model modeling and simulation method as claimed in claim 1, characterized in that: The specific method of step 2 is: Step 201, analyze the forces and moments on the drone, and the gravity F G , air resistance F 阻 , lateral force F 侧 , and the torque of the engine thrust are combined to calculate the linear acceleration and angular acceleration of the UAV fuselage axis in the body coordinate system, and combined with the wind velocity, the relevant parameters of the UAV flight process are calculated; Step 202, with the ground coordinate system as a reference, decompose the angular velocity of the fuselage axis to obtain the change rate of the drone's angle of attack α, sideslip angle β and angular velocity H; decompose the angular velocity to obtain the drone's pitch angle θ, yaw angle ψ and roll angle Obtain the flight attitude parameters of the UAV; Step 203, establish the dynamic equation of the UAV linear motion based on the ground coordinate system as follows: In the formula, ω x ,ω y ,ω z is the angular velocity component of the UAV's flight angular velocity along the x-axis, y-axis, and z-axis in the body coordinate system; v x 、v y 、v z It represents the flight speed of the drone along the x-axis, y-axis, and z-axis; X, Y, and Z represent the projection of air resistance on the x-axis, y-axis, and z-axis of the velocity coordinate system, which are the resistance, side force, and lift of the drone respectively; g is the acceleration due to gravity; Represents the transfer matrix of the velocity coordinate system relative to the body coordinate system, Represents the transfer matrix of the ground coordinate system relative to the body coordinate system; Step 204, establish the kinematic equation of the drone rotating around the center of mass based on the ground coordinate system as follows: In the formula, ω xb ,ω yb ,ω zb It is the angular velocity component of the UAV's flight angular velocity along the x-axis, y-axis, and z-axis in the body coordinate system; θ and ψ are flight attitude angle variables; the angular velocity of the UAV depends on the rate of change of the flight attitude angle and in is the rate of change along the x-axis, is the rate of change along the y-axis, is the rate of change along the z-axis.

4. A fixed-wing UAV digital twin model modeling and simulation method as claimed in claim 3, characterized in that: In step 3, the linearization model of the fixed-wing UAV is derived as follows: According to the UAV dynamics and kinematics equations, a six-degree-of-freedom fixed-wing UAV linear model is established, and the flight speed v and angle of attack α of the UAV are constrained within the interval to ensure the authenticity and reliability of the model; According to the state space expression of the nonlinear system, through the dynamics and kinematics equations of the UAV, combined with the principle of small disturbance linearization, the linearized model of the UAV is expressed as: y(t)=Cx(t) In the formula, represents the derivative of the state vector, x(t) is the state vector of the system, which contains the internal state information of the drone; A is the state matrix, B is the input matrix, u(t) represents the control input vector, y(t) represents the output vector, which contains the state and measurement values ​​of the drone; C is the output matrix.

5. A fixed-wing UAV digital twin model modeling and simulation method as claimed in claim 4, characterized in that: In step 3, the actuator fault model is derived as follows: Analyze common fixed-wing UAV actuator failures, including left and right aileron stuck at zero position, elevator stuck at zero position, rudder stuck at zero position, and engine full power loss; Let n out is the actual output of the actuator, n in This is the signal that the actuator should output when it is normal, and the actuator failure is represented as: In the formula, a n Indicates the output value when the actuator is stuck in zero position, ranging from n min and n max Between; n (t) represents the degree of actuator damage and is a variable that changes with time; n in (t) indicates the signal that the actuator should output when it is normal. For the above four common fixed-wing UAV actuator faults, combined with the UAV linearization model, the fault behavior of the fixed-wing UAV actuator is expressed as follows: y(t)=Cx(t) In the formula, f a ∈R m Represents the fault vector of the actuator, n out (t) is the function of actuator failure. x(t) represents the state vector, u(t) represents the input vector, y(t) represents the output vector, and A, B, and C represent the system matrices.

6. A fixed-wing UAV digital twin model modeling and simulation method as claimed in claim 1, characterized in that: In step 5, the MAVLink2.0 communication protocol is used to establish real-time communication between the fixed-wing UAV digital twin model and the physical fixed-wing UAV model. The specific steps are as follows: Step 501, using the UAV flight ground station to obtain flight control data information, and using the MaVlink2.0 protocol to analyze the information content of the control system status, aircraft attitude, and orientation; Step 502, forming a TCP / IP connection with the gateway, and performing terminal user login, authentication, terminal heartbeat packet transmission and response analysis according to the JT / T-808 protocol; then, assembling the JT / T-808 position report data frame according to the information parsed in step 501, and uploading it to the gateway; Step 503, realizing the connection of the terminal user, and determining the network connection status according to the general response; If the communication is interrupted, the data frames of this situation are stored for subsequent use; If the network resumes communication, data frames are uploaded in batches to supplement the stored data frame information.

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