Flight simulator motion control system based on digital twin model

Abstract

The invention relates to the technical field of digital twinning, in particular to a flight simulator motion control system based on a digital twinning model. The system comprises a physical platform module, a digital twin system, a parameter identification system and a parameter optimization system, wherein the physical platform module at least comprises an upper computer, a motion control module and a flight simulator motion execution module; the digital twin system is used for real-time visualization of mechanical motion of the flight simulator, verification and optimization of controller parameters and real-time feedback of a control effect; the parameter identification system carries out kinetic parameter identification, adjustment and correction on the digital twin model of the flight simulator; and the parameter optimization system optimizes controller parameters of the motion control module based on the identified simulation result of the digital twin system. According to the invention, by building and optimizing the electromechanical integrated digital twin model, the control performance can be optimized, and the equipment safety and motion performance of the flight simulator can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of digital twin, and more specifically, to a motion control system of a flight simulator based on a digital twin model. Background Art

[0002] As the core equipment for flight training, flight simulators play an irreplaceable role in reducing training costs, improving safety and training efficiency. The accuracy, stability and reliability of their motion control systems directly affect the simulation training effect and the level of aviation safety.

[0003] However, the existing motion control systems of flight simulators still face significant challenges in practical applications. Although the widely used servo-driven PID control method has the advantages of simple structure and convenient debugging, it has obvious limitations when dealing with the complex electromechanical system of a flight simulator: on the one hand, the dynamic characteristics of this system show strong coupling and high nonlinearity. The traditional PID control based on empirical parameter tuning is difficult to achieve accurate decoupling control, and problems such as response lag and overshoot are likely to occur; on the other hand, factors such as wear of mechanical components during long-term use and changes in environmental temperature and humidity will cause drift of system dynamic parameters. Due to the lack of online adaptive adjustment ability, the traditional PID algorithm cannot effectively compensate for such changes, resulting in a decrease in control accuracy over the running time and threatening the system stability.

[0004] In recent years, digital twin technology has provided new ideas for the optimization of flight simulator control systems, but there are still deficiencies in the modeling dimension and control integration depth of the existing technical solutions.

[0005] At the modeling level, existing research mostly establishes theoretical simulation models based on the mechanical dynamic characteristics of the Stewart platform (such as mass, inertia and friction parameters). Although it can assist in the motion trajectory planning of the platform, it ignores the modeling of the dynamic characteristics of motors and drive systems. For example, the electromagnetic equation of a permanent magnet synchronous motor and the dynamic response characteristics of the current loop and speed loop of the driver are not included in the model framework. This "mechanical-electrical split" modeling method results in the digital twin system being unable to reproduce the coupling characteristics of the real electromechanical system and is difficult to accurately predict the impact of complex working conditions such as harmonic vibration and load mutation on control performance.

[0006] In addition, existing digital twin models mostly rely on sensor data (such as displacement, acceleration) to realize the virtual-real mapping of the mechanical system, but their application scope is often limited to state monitoring and visual display, and has not penetrated into the core link of control system design, and has not built a closed-loop twin framework covering controller parameter optimization and electromechanical interaction testing.

[0007] Meanwhile, the existing flight simulator control design still mainly relies on the joint space PID algorithm with fixed parameters. In the context where the digital twin model is not deeply integrated with the control system, it is difficult to dynamically adjust the controller parameters using real-time simulation data, and it cannot adapt to the dynamic changes caused by parameter drift or external interference during the long-term operation of the system.

[0008] The limitations of the existing technologies and the urgency of the actual requirements indicate that there is an urgent need for a more perfect flight simulator motion control system. Summary of the Invention

[0009] The object of the present invention is to provide a flight simulator motion control system based on a digital twin model to solve the problem of the decline in motion accuracy of existing flight simulators due to the separation of the electromechanical model and the dependence on hardware.

[0010] Another object of the present invention is to provide a flight simulator motion control system based on a digital twin model to solve the problem that it is difficult to optimize the controller parameters of existing flight simulators.

[0011] To achieve the above objects, the present invention provides a flight simulator motion control system based on a digital twin model, including a physical platform module, a digital twin system, a parameter identification system, and a parameter optimization system:

[0012] The physical platform module includes at least a host computer, a motion control module, and a flight simulator motion execution module;

[0013] The host computer is used to run the digital twin system, the parameter identification system, and the parameter optimization system;

[0014] The motion control module is used to execute the instructions of the host computer, perform motion control on the flight simulator motion execution module, and achieve safe motion;

[0015] The flight simulator motion execution module performs relevant motion actions on the flight simulator and feeds back status parameters;

[0016] The digital twin system is a flight simulator digital twin model set in the host computer, including at least a mechanical system digital twin model and a drive system digital twin model. The mechanical system digital twin model is used for the real-time visualization of the mechanical motion of the flight simulator, and the drive system digital twin model is used to verify and optimize the controller parameters and feedback the control effect in real time;

[0017] The parameter identification system is set in the host computer and, based on the status parameters fed back by the flight simulator motion execution module, performs dynamic parameter identification, adjustment, and correction on the flight simulator digital twin model;

[0018] The parameter optimization system is set in the host computer and optimizes the controller parameters of the motion control module based on the simulation results of the identified digital twin system.

[0019] In one embodiment, the host computer further includes:

[0020] A visual host computer interface, located in the middle layer between the digital twin system and the motion control module, is used to display the operating status and motion trajectory information of the flight simulator.

[0021] In one embodiment, the motion execution module of the flight simulator at least includes a servo motor, a mechanical structure of the flight simulator, and several sensors. The motion control module includes a controller and a driver:

[0022] The controller performs real-time motion control on the motion execution module of the flight simulator based on the instructions of the host computer;

[0023] The driver is used to drive the current magnitude of the servo motor to achieve servo tracking control of the motor.

[0024] In one embodiment, the digital twin model of the mechanical system of the flight simulator is built and implemented through the following steps:

[0025] Construct a mechanical system model according to the mechanical system structure of the flight simulator, and import the mechanical system model into the visual simulation tool environment to build the digital twin model of the mechanical system of the flight simulator.

[0026] In one embodiment, the digital twin model of the mechanical system is built and implemented through the following steps:

[0027] Step S11: According to the mechanical system structure of the flight simulator, construct a corresponding 3D model, and define the attributes of each component model in the 3D model. The attribute definition includes material attributes and geometric shapes;

[0028] Step S12: Assemble each component model in the 3D model into a mechanical system model, and ensure that the mechanical structure and motion characteristics of the mechanical system model are consistent with the actual mechanical system structure of the aircraft simulator by adding corresponding assembly constraints;

[0029] Step S13: Convert the mechanical system model into a specified format file, and the specified format file contains mechanical structure, assembly constraint, and motion characteristic information;

[0030] Step S14: Import the specified format file into the visual simulation tool to generate a corresponding multi-body dynamics model, and the multi-body dynamics model is used as the digital twin model of the mechanical system of the flight simulator.

[0031] In one embodiment, the digital twin model of the drive system includes a mechatronics digital twin model and a drive control system digital twin model, which is built and implemented through the following steps:

[0032] Step S21: Establish a digital twin model of the motor body according to the physical characteristics of the servo motor, and couple the digital twin model of the motor body with the digital twin model of the mechanical system based on the transmission relationship of the drive system to establish a mechatronics digital twin model;

[0033] Step S22: Establish a digital twin model of the drive control system according to the drive control architecture of the flight simulator;

[0034] Among them, the mechatronics digital twin model and the drive control system digital twin model constitute the digital twin model of the drive system of the flight simulator through signal interaction.

[0035] In one embodiment, the digital twin model of the motor body is constructed by electrical equations, electromagnetic torque equations and mechanical transmission equations.

[0036] In one embodiment, in step S21, the digital twin model of the motor body is coupled with the digital twin model of the mechanical system based on the transmission relationship of the drive system:

[0037] Based on the transmission relationship of the drive system, the screw telescopic amount L is used as the input of the digital twin model of the mechanical system, and the digital twin model of the mechanical system outputs the driving force As the load torque of the digital twin model of the motor body, the physical coupling of the mechanical system and the drive system of the flight simulator is realized.

[0038] In one embodiment, the digital twin model of the drive control system includes a current loop control model and a speed loop control model;

[0039] The current loop control model is a digital twin model of the current loop controller established according to the current loop PI control structure of the driver, adopting the discrete form of the PI controller and setting a voltage limiter;

[0040] The speed loop control model is a digital twin model of the speed loop controller established according to the speed loop PI control structure of the driver, adopting the discrete form of the PI controller and setting a current limiter.

[0041] In one embodiment, the digital twin system sets the sampling time and the simulation step length to be the same to achieve synchronization and real-time data interaction between the digital twin system and the flight simulator.

[0042] In one embodiment, the digital twin model of the flight simulator includes a flight simulator dynamics model;

[0043] The parameter identification system constructs a dynamic model of the flight simulator through the principle of virtual work, updates, identifies, and adjusts the parameters of the flight simulator dynamic model through a non-linear optimization algorithm, and conducts a fidelity test on the digital twin model of the flight simulator.

[0044] In one embodiment, the parameter identification system updates, identifies, and adjusts the parameters of the flight simulator dynamic model through a particle swarm non-linear optimization algorithm.

[0045] In one embodiment, the parameter optimization system builds a digital twin model controller based on the identified and adjusted digital twin model;

[0046] Optimizes the controller parameters through a non-linear optimization algorithm;

[0047] Establishes the constraint conditions for optimizing the controller parameters;

[0048] Transfers the optimized controller parameters to the controller.

[0049] In one embodiment, the dynamic model of the flight simulator constructed by the parameter identification system through the principle of virtual work has the corresponding expression: ; Wherein, is the velocity Jacobian matrix of the upper platform, is the driving force of the outrigger, is the external and inertial torque of the simulator cockpit and the upper platform, , are respectively the transposes of the velocity Jacobian matrices of the th lower limb and upper limb, , are respectively the external and inertial torques of the th lower limb and upper limb.

[0050] In one embodiment, the parameter identification system uses the inertial sensor data and the outrigger displacement sensor data as the inputs of the flight simulator dynamic model, and uses the driving forces of each outrigger as the outputs of the flight simulator dynamic model. Taking the error between the output value and the actual outrigger pressure sensor data as the optimization objective function, the expression of the optimization objective function is:

[0051] Wherein, is the deviation value between the driving force of the th outrigger of the flight simulator dynamic model identified for the th time and the force measured by the pressure sensor, and the defined constraint condition is: .

[0052] In one embodiment, the parameter identification system optimizes the parameter identification of the flight simulator dynamics model by the following steps:

[0053] Obtain the sensor data set saved in the visualization interface;

[0054] Determine the target flight simulator dynamics model and the parameters of the flight simulator dynamics model that need to be optimized and identified;

[0055] Determine the particle swarm dimension, particle swarm size, inertia factor, acceleration constant, and initialize the position and velocity of the particles;

[0056] According to the optimized objective function, calculate the fitness value of each example, and update the positions of the individual optimal and global optimal;

[0057] Iterate the above steps until the termination condition is met;

[0058] Output the global optimal position as the optimal solution of the parameters.

[0059] In one embodiment, the parameter identification system transmits the model parameters obtained by optimization and identification to the digital twin system, modifies the upper platform structure inertia parameters and limb inertia parameters of the digital twin model, and simultaneously monitors the torque information output by the digital twin system during operation and the pressure information collected by the actual operation pressure sensor. Calculate the digital twin model fidelity R through the following expression:

[0060]

[0061] Where is the measurement force of the th leg pressure sensor collected for the th time.

[0062] In one embodiment, the parameter optimization system optimizes the parameters of the current loop controller and the speed loop controller through a nonlinear optimization algorithm, defines the amplitude and frequency tracking performance of sinusoidal motion for different degrees of freedom through weighted summation, and constructs a total objective function to measure the motion control performance of the flight simulator.

[0063] In one embodiment, the mechanical structure of the flight simulator includes: an upper platform, a simulator cockpit, a Hooke hinge, an inner cylinder, an outer cylinder, a motor, a base, and a lead screw.

[0064] In one embodiment, the several sensors include pressure sensors and inertial sensors:

[0065] The pressure sensor is used to monitor and feedback the force condition of the mechanical structure of the flight simulator;

[0066] An inertial sensor for monitoring and feeding back the attitude and motion state of the mechanical structure of a flight simulator.

[0067] The motion control system of a flight simulator based on a digital twin model provided by the present invention can comprehensively test and optimize the control system in a virtual environment by building and optimizing the mechatronic digital twin model, reducing the need for physical testing, accelerating the hardware development process, and lowering the development and testing costs. Brief Description of the Drawings

[0068] The above and other features, properties, and advantages of the present invention will become more apparent from the following description in conjunction with the drawings and embodiments, where like reference numerals always denote like features, wherein:

[0069] Figure 1 Discloses a block diagram of a motion control system of a flight simulator based on a digital twin model according to an embodiment of the present invention;

[0070] Figure 2 Discloses a block diagram of a physical platform module according to an embodiment of the present invention;

[0071] Figure 3 Discloses a schematic diagram of information interaction between a digital twin model and an actual model according to an embodiment of the present invention;

[0072] Figure 4 Discloses a step diagram for building a motion control system of a flight simulator based on a digital twin model according to an embodiment of the present invention;

[0073] Figure 5 Discloses a flowchart of the operation process of parameter identification of a motion platform of a flight simulator according to an embodiment of the present invention.

[0074] For clarity, the following gives a brief description of the reference numerals, and the meanings of the respective reference numerals are as follows:

[0075] 100 Physical platform module;

[0076] 110 Digital twin system;

[0077] 101 Digital twin model of the mechanical system;

[0078] 102 Digital twin model of the drive system;

[0079] 120 Parameter identification system;

[0080] 130 Parameter optimization system;

[0081] 20 Simulator cockpit;

[0082] 21 Hook hinge;

[0083] 22 Inner cylinder;

[0084] 23 Outer cylinder;

[0085] 24 Motor;

[0086] 25 Base;

[0087] 310 Host computer;

[0088] 311 Host computer visualization interface;

[0089] 320 Flight simulator motion execution module;

[0090] 321 Controller;

[0091] 322 Motion control unit;

[0092] 323 Driver;

[0093] 330 Flight simulator motion execution module;

[0094] 331 Flight simulator mechanical structure;

[0095] 332 Pressure sensor;

[0096] 333 Inertial sensor;

[0097] 334 Motor. Detailed implementation manners

[0098] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the invention and are not used to limit the invention.

[0099] In the prior art, the modeling and simulation of the mechanical system of a flight simulator are generally based on the simulation model of a Stewart motion platform, which is also called a six-degree-of-freedom platform (6-DOF platform). It is a motion platform based on a parallel structure and is often used in fields such as simulation, virtual reality, and flight simulators. The base of the platform and the platform base are connected by six adjustable support rods. By precisely controlling the length of each support rod, the platform can move in three translational degrees of freedom (in the X, Y, and Z axis directions) and three rotational degrees of freedom (pitch, roll, and yaw).

[0100] The simulation model of the Stewart motion platform in the prior art is used for control system design and motion trajectory planning. In the modeling process, it mainly relies on theoretical CAD parameters, such as dynamic parameters like mass, inertia, and friction characteristics. The focus of dynamic modeling mainly concentrates on the mechanical structure and dynamic characteristics, neglecting the dynamic characteristics of the motor and drive system, resulting in the lack of a complete mechatronics consideration in the overall modeling.

[0101] Figure 1 Reveals the block diagram of the motion control system of a flight simulator based on the digital twin model according to an embodiment of the present invention, as Figure 1 shown, the motion control system of the flight simulator may include: a physical platform module 100, a digital twin system 110, a visualization host computer interface, a parameter identification system 120, a motion control module, and a parameter optimization system 130.

[0102] The physical platform module 100 may include a host computer, a motion control module, and a motion execution module of the flight simulator, and is used for motion control, data transmission, and status monitoring of the flight simulator.

[0103] The host computer is used to run the digital twin system 110, the parameter identification system 120, and the parameter optimization system 130.

[0104] The motion control module is used to execute the instructions of the host computer, perform motion control on the motion execution module of the flight simulator, and achieve safe motion.

[0105] In this application, the motion control module is mainly used to execute the motion instructions sent by the visualization host computer, and control the operation signal of the servo motor through a finite state machine to support the multi-functional operation of the motor.

[0106] Among them, the multi-functional operation may include enabling, motion control, emergency stop protection, etc., and is used to flexibly achieve safe and reliable motion control.

[0107] The motion execution module of the flight simulator performs relevant motion actions on the flight simulator and feeds back status parameters.

[0108] In this embodiment, the motion execution module of the flight simulator at least includes a motor, a mechanical structure of the flight simulator, and several sensors.

[0109] The digital twin system 110 is a digital twin model of the flight simulator set in the host computer, and at least includes a digital twin model 101 of the mechanical system and a digital twin model 102 of the drive system. The digital twin model of the mechanical system is used for real-time visualization of the mechanical motion of the flight simulator, and the digital twin model of the drive system is used to verify and optimize the controller parameters and real-time feedback of the control effect.

[0110] The visualization host computer interface is located in the middle layer between the digital twin system and the motion control module, and is used to display the operating status and trajectory of the flight simulator. It can receive and transmit the kinetic feedforward compensation signal verified by the digital twin system 110 and the optimized and adjusted controller parameters, and send the operating status and motion trajectory information of the flight simulator. The visualization host computer interface provides real-time visualization display.

[0111] The parameter identification system 120 is set in the host computer. Based on the status parameters fed back by the motion execution module of the flight simulator, it performs kinetic parameter identification, adjustment, and correction on the digital twin model of the flight simulator.

[0112] The parameter identification system 120 may include: a data acquisition system 121, a kinetic parameter identification module 122, and a digital twin model verification module 123:

[0113] The data acquisition system 121 collects the real-time data of the digital twin system 110, processes and calculates the kinetic parameters through the kinetic parameter identification module 122, and transmits the results to the digital twin model verification module 123 for verification and adjustment to ensure the accuracy and effectiveness of the digital twin model.

[0114] The present invention obtains sensor data in real time through the parameter identification system 120, and online identifies and updates the inertial parameters in the digital twin model, solving the problem of performance degradation caused by personnel or equipment changes during the continuous operation of the controller, thereby improving the accuracy of the model and the kinetic feedforward control performance.

[0115] In an embodiment, the digital twin model of the flight simulator includes a flight simulator kinetic model. The parameter identification system 120 constructs a flight simulator kinetic model through the principle of virtual work, updates, identifies, and adjusts the parameters of the flight simulator kinetic model through a nonlinear optimization algorithm, and performs a fidelity test on the digital twin model of the flight simulator.

[0116] The parameter identification system 120 can update, identify, and adjust the parameters of the flight simulator kinetic model through a particle swarm nonlinear optimization algorithm.

[0117] The parameter optimization system 130 is set in the host computer and optimizes the controller parameters of the motion control module based on the simulation results of the identified digital twin system.

[0118] In an embodiment, the parameter optimization system 130 constructs a digital twin model controller based on the identified and adjusted digital twin model;

[0119] Optimizes the controller parameters through a nonlinear optimization algorithm;

[0120] Establishes the constraint conditions for optimizing the controller parameters;

[0121] Transfer the optimized controller parameters to the controller.

[0122] Figure 2 Disclosed is a block diagram of the physical platform module structure according to an embodiment of the present invention. In combination with Figure 1 and Figure 2 , the physical platform module 100 may include 1 host computer, 1 controller, 6 drivers, 6 motors, a flight simulator mechanical structure, 6 pressure sensors and 1 inertial sensor.

[0123] The physical platform module 100 provides the basic hardware part for the flight simulator motion control system, including a host computer, a controller, drivers, motors, a flight simulator mechanical structure, an inertial sensor and a pressure sensor, etc., for flight simulator motion control, data transmission and status monitoring.

[0124] Among them, the host computer is a Windows PC host computer, which is used to run the digital twin system 110 and the visualization host computer interface system.

[0125] 1 controller and 6 drivers constitute the motion control module;

[0126] 6 motors, the flight simulator mechanical structure, 6 pressure sensors and 1 inertial sensor constitute the flight simulator motion execution module.

[0127] More specifically, the controller can communicate with the host computer visualization interface to run the motion control system. Specifically, the controller is responsible for executing the speed control instructions of the drivers in the motion control system, and communicating with the host computer visualization interface through the ADS (Automation Device Specification) protocol, and is responsible for real-time processing of motion control instructions.

[0128] The driver is used to drive the current magnitude of the servo motor to achieve servo tracking control of the motor.

[0129] The 6 motors are servo motors, which are connected to the driver by the CAN bus and communicate through the EtherCAT network, and are responsible for executing precise motion control to provide power for the flight simulator.

[0130] The flight simulator mechanical structure is a Stewart platform, which is driven by the motor 24 to simulate the actual flight motion, and may include: an upper platform, a simulator cockpit 20, a Hooke hinge 21, an inner cylinder 22, an outer cylinder 23, a lead screw and a base 25:

[0131] Among them, the upper platform is connected to the base 25 by six support rods, and the upper platform is used to carry the device to be simulated;

[0132] The simulator cockpit 20 is a part of the flight simulator and provides a place for simulating flight operations.

[0133] The Hooke hinge 21, as a component of the mechanical structure of the flight simulator, participates in realizing functions such as the motion connection of the mechanical structure;

[0134] The inner cylinder 22, in the mechanical structure of the flight simulator, cooperates with the outer cylinder 23, etc., to provide certain support or motion conditions for realizing the simulated flight motion;

[0135] The outer cylinder 23, in the mechanical structure of the flight simulator, collaborates with the inner cylinder 22, etc., participates in realizing the motion of the mechanical structure, and helps to simulate the actual flight motion;

[0136] The base 25 plays a role in supporting the entire mechanical structure of the flight simulator;

[0137] The lead screw, in cooperation with the motor, etc., participates in the motion of the mechanical structure of the flight simulator.

[0138] Six pressure sensors are distributed at the connection between the motor and the lead screw of the Stewart platform, and are used to monitor and feedback the force condition of the mechanical structure.

[0139] One inertial sensor is installed at the center point of the upper platform of the Stewart platform, and is used to monitor and feedback the attitude and motion state of the mechanical structure in real time.

[0140] A motion control system for a flight simulator based on a digital twin model provided by the present invention adds the modeling of the motor and the drive system on the basis of the traditional mechanical system digital twin model, designs and verifies the controller in the virtual twin body in advance, can optimize the control performance, avoid the potential impact on the hardware of direct deployment, thereby improving the equipment safety and motion performance of the flight simulator, realizing the mechatronic digital twin model, and thus better reflecting the internal coupling relationship between the motor drive and the mechanical system.

[0141] Figure 3 Reveals the information interaction schematic diagram between the digital twin model and the actual model, such as Figure 3 The motion control system for a flight simulator based on digital twin technology shown, in which the physical platform module may include: a host computer 310, a motion control module 320, and a flight simulator motion execution module 330.

[0142] Next, it will be combined with Figures 1 to 3 Further describe how the information between the digital twin model and the actual model is interacted.

[0143] In practical applications, the host computer 310 can run on the PC-WINDOWS system, and the host computer 310 runs the host computer visualization interface 311, the digital twin system 110, the parameter identification system 120, and the parameter optimization system 130;

[0144] The digital twin system 110 communicates with the upper computer visualization interface 311, the parameter identification system 120, and the parameter optimization system 130 through the UDP protocol.

[0145] Among them, UDP (User Datagram Protocol) is a datagram mode that provides packet-switching computer communication in a group of interconnected computer network environments. Simply put, UDP is a network communication protocol suitable for scenarios that require fast transmission but have low requirements for reliability.

[0146] The motion control module 320, which is set in the control cabinet, includes a controller 321 and a driver 323. The controller 321 performs real-time motion control on the flight simulator motion execution module based on the instructions of the upper computer, and the driver 323 is used to drive the current magnitude of the servo motor to achieve servo tracking control of the motor.

[0147] The controller 321 communicates with the driver 323 and the motor 334 through the Ethercat protocol to control the operation of the flight simulator.

[0148] In this embodiment, the controller 321 includes at least a motion control unit 322.

[0149] The motion control unit 322 is an embedded controller PLC, which is responsible for precisely controlling the speed command of the servo motor.

[0150] The embedded controller PLC is a controller specifically used to control mechanical motion systems. It is based on a programmable logic controller and realizes precise control of mechanical motion systems by writing control programs, and has the advantages of high reliability, high precision, and high flexibility.

[0151] The flight simulator motion execution module 330, which is a part of the flight simulator, may include: the flight simulator mechanical structure 331, a pressure sensor 332, and an inertial sensor 333:

[0152] The pressure sensor 332, the inertial sensor 333, and the motor 334 are connected to the motion control unit 322 (PLC) in the motion control module 320 through the Ethercat protocol to obtain real-time data and perform precise motion control.

[0153] In addition, the flight simulator mechanical structure 331, the pressure sensor 332, the inertial sensor 333, and the motor 334 perform motion through mechanical connection.

[0154] The flight simulator motion control system based on the digital twin model provided by the present invention adopts a mechatronic modeling and digital twin solution, combines the motor characteristics with the mechanical dynamic characteristics, realizes higher-precision simulation and control, and combines the real-time correction and optimization algorithm of the dynamic model to enhance the adaptive ability of the controller to dynamic changes, and realizes higher robustness and stability.

[0155] Figure 4 Reveals a setup step diagram of the flight simulator motion control system based on the digital twin model according to an embodiment of the present invention, as Figure 4 shown, the method for setting up the flight simulator motion control system includes the following steps:

[0156] Step S1: Construct a mechanical system model according to the mechanical system structure of the flight simulator, and import the mechanical system model into the Simulink environment to set up a digital twin model of the flight simulator mechanical system;

[0157] Step S2: Set up a digital twin model of the flight simulator drive system. Specifically, the digital twin model of the drive system includes a mechatronic digital twin model and a digital twin model of the drive control system;

[0158] Step S3: Set the sampling time to be the same as the simulation step size to achieve synchronization and real-time data interaction between the digital twin system and the flight simulator;

[0159] Step S4: Construct a dynamic model of the flight simulator through the principle of virtual work, update, identify and adjust the parameters of the flight simulator dynamic model through a nonlinear optimization algorithm, and conduct a fidelity test on the digital twin model of the flight simulator;

[0160] Step S5: Set up a digital twin model controller and optimize the controller parameters.

[0161] Among them, the step S1 is used to set up a digital twin model of the mechanical system.

[0162] More specifically, the digital twin model of the mechanical system is set up through the following steps:

[0163] Construct a mechanical system model according to the mechanical system structure of the flight simulator, and import the mechanical system model into the visual simulation tool environment to set up a digital twin model of the flight simulator mechanical system.

[0164] In this embodiment, the digital twin model of the mechanical system is set up through the following steps:

[0165] Step S11: Construct a corresponding 3D model based on the mechanical system structure of the flight simulator, and define the attributes of each component model in the 3D model. The attribute definition includes material attributes and geometric shapes.

[0166] Specifically, based on the mechanical structure of the flight simulator defined and constructed from the component models of the motion platform of the flight simulator, construct the corresponding component models;

[0167] Among them, each component includes but is not limited to the upper platform, base, motor, lead screw, driver, Hooke's joint, outer cylinder and inner cylinder, and the simulator cockpit, etc.;

[0168] The material attributes include: density, elastic modulus, and Poisson's ratio;

[0169] The geometric shapes include dimensions, shapes, and volume characteristics.

[0170] Step S12: Assemble each component model in the 3D model into a mechanical system model, and ensure that the mechanical structure and motion characteristics of the mechanical system model are consistent with the actual mechanical system structure of the aircraft simulator by adding corresponding assembly constraints.

[0171] In one embodiment, SolidWorks software can be used to assemble each component model in the 3D model into a mechanical system model, and ensure that the mechanical structure and motion characteristics of the mechanical system model are consistent with the mechanical system structure of the aircraft simulator by adding corresponding assembly constraints. Among them, the assembly constraints include mating relationships such as concentricity and / or coincidence between each component.

[0172] Step S13: Convert the mechanical system model into a specified format file, and the specified format file contains mechanical structure, assembly constraints, and motion characteristic information.

[0173] Among them, the specified format file can be an XML format file.

[0174] In one embodiment, the Simscape Multibody Link plugin in MATLAB software can be used to convert the SolidWorks mechanical system model into an XML format file, and the XML format file contains mechanical structure, assembly constraints, and motion characteristic information.

[0175] Step S14: Import the specified format file into a visualization simulation tool to generate a corresponding multi-body dynamics model, and the multi-body dynamics model serves as the digital twin model of the flight simulator mechanical system.

[0176] Among them, the visualization simulation tool can be Simulink software.

[0177] In one embodiment, in the MATLAB environment, the XML format file is imported into Simulink through the Simscape Multibody module to generate a corresponding Simscape multibody dynamics model, and the multibody dynamics model serves as a digital twin model of the mechanical system of the flight simulator.

[0178] Step S2: Build a digital twin model of the drive system of the flight simulator. Specifically, the digital twin model of the drive system includes a mechatronics digital twin model and a drive control system digital twin model.

[0179] The digital twin model of the drive system includes a mechatronics digital twin model and a drive control system digital twin model, which is built through the following steps:

[0180] Step S21: Establish a mechatronics digital twin model: Based on the physical characteristics of the servo motor, establish a digital twin model of the motor body, and physically couple the motor model with the digital twin model of the mechanical system based on the transmission relationship of the drive system to establish a mechatronics digital twin model.

[0181] The digital twin model of the motor body constructed in Step S21 includes: electrical equations, electromagnetic torque equations, and mechanical transmission equations;

[0182] The expression of the electrical equation is: ,

[0183] ,

[0184] The expression of the electromagnetic torque equation is:

[0185] The expression of the mechanical transmission equation is:

[0186]

[0187]

[0188] Among them, are respectively the axis components of the stator voltage, , are respectively the axis components of the stator current, are respectively the axis components of the stator flux linkage, is the stator winding, , is the stator Axis inductance, Electrical angular velocity, is the permanent magnet flux linkage; is the output torque of the motor, Number of pole pairs is the mechanical angular speed of the motor, is the load torque of the motor, is the total viscous friction coefficient of the lead screw and the motor; is the moment of inertia of the motor, is the lead of the lead screw, is the driving force of the motor, is the motor rotation angle, is the telescopic amount of the lead screw.

[0189] Specifically, the parameters of the digital twin model of the motor body , , , , , are obtained by looking up according to the model of the motor and the corresponding manual.

[0190] In step S21, physically coupling the motor model and the digital twin model of the mechanical system based on the transmission relationship of the drive system further includes:

[0191] In the Simulink software, take the telescopic amount L of the lead screw as the input of the digital twin model of the mechanical system, and the output driving force as the load torque of the motor to achieve physical coupling between the mechanical system and the drive system of the flight simulator.

[0192] More specifically, according to the transmission relationship of the drive system, use the Prismatic Joint and the Simulink-PSConverter module to take the telescopic amount of the lead screw as the input of the multi-body dynamics model, and the output force of the multi-body dynamics model as the load torque of the motor, so as to realize the physical connection between the two, reflecting the internal coupling relationship between the motor drive and the mechanical system.

[0193] Among them, the Prismatic Joint and the Simulink-PS Converter module are built-in modules in the simulink software. The Simulink-PS Converter module is used to convert the digital input into the physical input of the mechanical system, and the Prismatic Joint is a linear motion joint.

[0194] Step S22. Establish a digital twin model of the drive control system: According to the drive control architecture of the flight simulator, establish a digital twin model of the drive control system, where the digital twin model of the drive control system includes a current loop control model and a speed loop control model;

[0195] Among them, the mechatronics digital twin model and the digital twin model of the drive control system form the digital twin model of the drive system of the flight simulator through signal interaction.

[0196] The step S22 further includes:

[0197] S221. Establish a current loop control model: The current loop control model is a digital twin model of the current loop controller established according to the current loop PI control structure of the driver, adopting the discrete form of the PI controller and setting a voltage limiter;

[0198] S222. Establish a speed loop control model: The speed loop control model is a digital twin model of the speed loop controller established according to the speed loop PI control structure of the driver, adopting the discrete form of the PI controller and setting a current limiter.

[0199] The digital twin model of the current loop controller has the corresponding expression:

[0200]

[0201]

[0202] Among them, is the output of the current loop PI controller at the current moment, is the output of the current loop PI controller at the previous moment, is the proportional gain, is the integral gain, is the current error at the current moment, the current error at the previous moment is the q-axis reference voltage output by the controller, sat is the saturation function, , are the maximum and minimum values of the q-axis reference voltage.

[0203] The digital twin model of the speed loop controller has the corresponding expression:

[0204]

[0205]

[0206]

[0207] Among them, is the output of the speed loop PI controller at the current moment, is the output of the speed loop PI controller at the previous moment, is the proportional gain of the speed loop, is the integral gain, is the speed error at the current moment, is the speed error at the previous moment, ) is the rotational speed tracking signal sent by the motion control plc, is the actual rotational speed of the motor, is the current feedforward signal calculated according to the dynamic model, is the tracking signal of the drive current loop, , are the minimum and maximum values of the reference current of the q-axis of the motor.

[0208] The prior art uses sensors (such as displacement sensors, speed sensors, and acceleration sensors) to capture system state data (including position, speed, and acceleration) in real time to drive the synchronous operation of the virtual model and the physical model, thereby realizing digital twin. The digital twin model of the prior art is mainly applied to the real-time state monitoring and motion visualization of the system, which helps to evaluate the operating state of the platform. However, it fails to fully demonstrate the inherent dynamic connection between the motor and the mechanical system, making it difficult to optimize the overall performance of the electromechanical system.

[0209] The present invention establishes a complete digital twin model of the flight simulator through step S2. The digital twin model includes a mechanical system and a motor drive system. By using the model to verify and optimize the controller parameters, it can simulate the dynamic behavior of the flight simulator in real time, significantly improve the accuracy of the control system, ensure the precise and reliable motion control of the flight simulator, and achieve high-precision motion control.

[0210] Step S3: Set the sampling time to be the same as the simulation step size to achieve synchronization and real-time data interaction between the digital twin system and the flight simulator.

[0211] The present invention can ensure a high degree of consistency between the digital twin system of the flight simulator and the actual physical platform module through real-time data synchronization (such as data exchange with the actual system through interfaces such as UDP, RS485, and RS422). This real-time synchronization enhances the stability and reliability of the system, and ensures the rapid response and precise execution of control commands.

[0212] Step S3 further includes:

[0213] Step S31: Synchronize the simulation step size in the visualization simulation tool. Specifically, in Simulink, synchronize the simulation step size through the Real-Time Synchronization module and set its parameters to be consistent with the simulation step size, thereby achieving precise synchronization between the digital twin model and the actual system.

[0214] Step S32: Receive the actual system data of the flight simulator, including the rotational speed command, sensor data, and motor encoder data, through the data interaction interface, and send the identified dynamic parameters of the digital twin model and the optimized controller parameters back to the actual system.

[0215] Receive the actual system data of the flight simulator through the UDP Receive module. The actual system data includes: rotational speed command, sensor data, and motor encoder data;

[0216] Send the identified dynamic parameters of the digital twin model and the optimized controller parameters back to the actual system through the UDP Send module.

[0217] In this embodiment, by introducing the UDP Receive module and setting its sampling time to be consistent with the simulation step size, the model can synchronously receive the rotational speed command , inertial sensor data, pressure sensor data, motor encoder data, etc. from the visualization interface.

[0218] Meanwhile, add the UDP Send module and set its sampling time to be consistent with the simulation step size, then the identified dynamic parameters of the digital twin model and the optimized controller parameters can be synchronously sent back to the system.

[0219] Through real-time synchronization and data update, the digital twin model of the present invention can dynamically adjust the model parameters by combining the real-time data collected by sensors, such as inertial sensor and pressure sensor data. This feedback mechanism enables the system to adapt to changes in the actual environment and improves the dynamic response ability and self-adaptive ability of the system.

[0220] Step S4: Construct the dynamic model of the flight simulator based on the principle of virtual work, update, identify, and adjust the dynamic model parameters of the flight simulator through a non-linear optimization algorithm, and conduct a fidelity test on the digital twin model of the flight simulator.

[0221] Figure 5 Discloses a flow chart of the operation process for identifying the parameters of the motion platform of a flight simulator according to an embodiment of the present invention, as Figure 5 shown, and the step S4 further includes:

[0222] Step S41: Construct the dynamic model of the Stewart platform of the flight simulator based on the principle of virtual work: ;

[0223]

[0224]

[0225]

[0226]

[0227]

[0228]

[0229]

[0230]

[0231]

[0232] Wherein, is the velocity Jacobian matrix of the upper platform, is the driving force of the outrigger, is the external and inertial torque of the simulator cockpit and the upper platform, , are respectively the transposes of the velocity Jacobian matrices of the th lower limb and upper limb, , are respectively the external and inertial torques of the th lower limb and upper limb. is the external disturbing force, is the mass of the platform, is the acceleration due to gravity, is the acceleration of the centroid of the simulator cockpit, is the external disturbing torque, is the rotation matrix of the moving platform, is the moment of inertia of the simulator cockpit and the upper platform about the fixed coordinate system, is the angular acceleration, is the centroid of the simulator cockpit and the upper platform, is the moment of inertia of the simulator cockpit and the upper platform about its centroid, , are respectively the inertial forces of the th lower limb and upper limb, , are respectively the The inertial torques of the lower and upper limbs is the acceleration of the th lower leg, is the mass of the th lower leg, is the moment of inertia of the th lower leg about the fixed coordinate system, is the angular velocity of the th leg, is the moment of inertia of the lower limb about its center of mass, is the acceleration of the upper leg, is the mass of the th lower leg, is the moment of inertia of the upper leg about the fixed coordinate system, is the moment of inertia of the lower limb about its center of mass. are respectively the centers of gravity of the th lower leg and upper leg, is the cross - product matrix of the unit vectors of the th leg, are the coordinates of the th hinge point of the upper platform, is the length of the

[0233] The parameters identified by the dynamic model based on the principle of virtual work through nonlinear optimization are: , , , , , , , .

[0234] Step S42: Construct a particle swarm nonlinear optimization algorithm to update identification and adjust the parameters of the digital twin model;

[0235] A parameter identification system uses the inertial sensor data and the leg displacement sensor data as the input of the flight simulator dynamic model, takes the driving force of each leg as the output of the flight simulator dynamic model, and uses the error between the output value and the actual leg pressure sensor data as the optimization objective function:

[0236] where is the deviation value between the driving force of the th leg of the th identified dynamic model and the force measured by the pressure sensor. Define the optimization constraint condition as: .

[0237] In this embodiment, the parameter identification system updates, identifies, and adjusts the dynamic model parameters of the flight simulator through a particle swarm non-linear optimization algorithm.

[0238] The present invention optimizes the dynamic model parameters of the digital twin system using non-linear optimization algorithms such as particle swarm optimization. The current feedforward signal calculated by the dynamic model of the digital twin system can be dynamically adjusted according to the actual performance of the system, effectively improving the motion control accuracy of the flight simulator. By gradually optimizing the dynamic model of the digital twin system, precise control of the flight simulator in different load motion scenarios is ensured, and precise controller adjustment and optimization are achieved.

[0239] Furthermore, the parameter identification system uses the following particle swarm non-linear optimization algorithm to identify and optimize the parameters of the flight simulator dynamic model based on the principle of virtual work, specifically including the following steps:

[0240] Obtain the sensor data set saved in the visualization interface, where the sensor data set includes inertial sensor, pressure sensor data, and motor displacement sensor data; Determine the target flight simulator dynamic model and the parameters m of the flight simulator dynamic model that need to be optimized and identified, , , , , , , , , Each leg uses the same parameters, for a total of 17 parameters;

[0241] Determine the particle swarm dimension Dim = 17, the particle swarm size SwarmSize = 51, the inertia factor, the acceleration constant, and randomly initialize the positions and velocities of the particles;

[0242] According to the optimization objective function, calculate the fitness value of each example and update the positions of the individual optimal and global optimal;

[0243] Iterate the above steps until the termination condition is met, such as reaching the maximum number of iterations, the improvement of the solution is less than the preset threshold, or the fitness reaches a satisfactory level;

[0244] Output the global optimal position as the optimal solution of the parameters.

[0245] It should be noted that the process of identifying and optimizing the parameters of the dynamic model based on the principle of virtual work is dynamic, and data needs to be continuously collected to verify and optimize the model.

[0246] Step S43: Transmit the parameters identified by particle swarm optimization to the digital twin model, and calculate the fidelity R of the digital twin model. Among them, if the fidelity R reaches the preset value , then save the parameters; otherwise, re-identify and correct the parameters.

[0247] The parameter identification system transmits the optimized and identified model parameters to the digital twin system, modifies the upper platform structure inertia parameters and limb inertia parameters of the digital twin model, and simultaneously monitors the torque information output by the digital twin system during operation and the pressure information collected by the actual operation pressure sensor, and calculates the fidelity R of the digital twin model through the following expression:

[0248]

[0249] where is the measured force of the th leg pressure sensor in the th acquisition. If the fidelity of the model meets the preset value , then save the corresponding model parameters; otherwise, re-identify and correct the parameters of the digital twin model.

[0250] The control systems in the prior art usually adopt servo drive and PID control algorithms. By adjusting the input signals in the joint space, it is ensured that the motion platform can achieve accurate trajectory tracking and dynamic stability. However, these control algorithms usually assume that the dynamic parameters are constant and do not consider the problem of dynamic parameter drift that may be caused by long-term operation of the system or changes in working conditions (such as mechanical wear, friction changes), and cannot provide online correction or adaptive optimization for parameter changes. Although this solution shows good stability during short-term operation, during long-term operation, parameter drift may lead to a decrease in control accuracy and system performance degradation.

[0251] The parameter identification system of the present invention introduces dynamic parameter online identification and correction technology, realizes the performance optimization of the flight simulator during long-term operation, and overcomes the problem of decreased control accuracy caused by parameter changes in the prior art.

[0252] Step S4 of the present invention performs parameter identification through the principle of virtual work and non-linear optimization algorithm, can accurately identify the dynamic characteristics of the flight simulator, and continuously adjusts the model parameters through the optimization algorithm, making the behavior of the digital twin model highly consistent with that of the actual system, greatly improving the fidelity and control accuracy of the model, and realizing accurate dynamic modeling and parameter identification.

[0253] Step S5: Build a digital twin model controller and optimize the controller parameters.

[0254] The parameter optimization system verifies the optimized controller through a digital twin model and migrates it to the actual model for deployment, thereby optimizing the control performance and avoiding potential impacts on the hardware. This not only improves the control accuracy of the flight simulator but also enhances the safety and motion performance of the device.

[0255] In one embodiment, step S5 further includes:

[0256] Step S51: Build a digital twin model controller based on the identified and adjusted digital twin model;

[0257] Step S52: Optimize the controller parameters through a non - linear optimization algorithm, where the controller parameters include the proportional and integral terms of the current loop and the speed loop;

[0258] Step S53: Establish the constraint conditions for the optimized controller parameters;

[0259] Step S54: Transmit the optimized controller parameters to the current - loop controller and the speed - loop controller.

[0260] In this embodiment, based on the digital twin model, the construction and parameter optimization of the controller of the flight simulator motion control system are completed, specifically including the following steps:

[0261] The parameter optimization system, based on the identified and adjusted digital twin model, designs the PI controller (including the current loop and the speed loop) of the digital twin model and verifies its structure and performance through model simulation;

[0262] The parameter optimization system uses a non - linear optimization algorithm to optimize the parameters of the current - loop controller and the speed - loop controller, and defines the amplitudes of sinusoidal motions with different degrees of freedom (lateral translation, longitudinal translation, vertical, pitch, roll, yaw) through weighted summation and frequency tracking performance , and constitutes the total objective function to measure the motion control performance of the flight simulator. The corresponding expression is as follows: ; ; ;

[0263] Among them, is the frequency of the sinusoidal motion, are the weighting factors of the six degrees of freedom at each frequency, are the weighting factors of the six degrees of freedom.

[0264] In the overall objective function, the frequency of the sinusoidal motion and the weighting factors of each degree of freedom are comprehensively considered to ensure that the optimization results can accurately reflect the motion fidelity of the flight simulator.

[0265] During the optimization process, the constraint conditions of the model include the following aspects:

[0266] The stability of the controller system, ensuring the poles of the closed-loop system , to ensure that the poles of the closed-loop system are located in the stable region;

[0267] Motion platform range limitations, including displacement , speed and acceleration ranges;

[0268] Displacement range: ;

[0269] Speed range: ;

[0270] Acceleration range: ;

[0271] Controller parameter limitations, ensuring that the controller parameters are within the empirically set range: ; Among them, is the minimum displacement, is the maximum displacement, is the minimum speed, is the maximum speed, is the minimum acceleration, is the maximum acceleration, is the minimum controller parameter, is the maximum controller parameter.

[0272] The parameter optimization system passes the optimized PI controller parameters and the current loop feedforward term to the actual control software of the controller to achieve more efficient control performance.

[0273] At the same time, the dynamic coefficients obtained by parameter identification are passed to the current feedforward controller to ensure the accuracy and dynamic response of motor control.

[0274] When the controller performance does not meet the requirements, the parameter optimization system will re-tune the parameters of the current loop and speed loop controllers until the control performance is met.

[0275] So far, the construction of the flight simulator motion control system and the parameter optimization model based on digital twin technology provided by the present invention have been completed, ensuring the efficiency and accuracy of the flight simulator motion control system.

[0276] The flight simulator motion control system based on a digital twin model and its construction method provided by the present invention can optimize and verify controller parameters in a virtual environment, avoiding a large number of experiments directly on actual hardware, reducing hardware risks, and being able to comprehensively evaluate controller performance during the optimization process.

[0277] The flight simulator motion control system based on a digital twin model provided by the present invention can comprehensively test and optimize the control system in a virtual environment through the establishment and optimization of the digital twin model, reducing the need for physical testing, accelerating the hardware development process, and reducing development and testing costs. Especially in high-precision and high-complexity systems such as flight simulators, the application of digital twin technology greatly shortens the system integration and verification cycle, and reduces the hardware development cycle and costs.

[0278] The digital twin model established by the flight simulator motion control system based on a digital twin model provided by the present invention can not only simulate the existing structure of the flight simulator, but also expand new functions or adjust the existing model according to requirements, providing flexible technical support for the future upgrade and performance improvement of the flight simulator, reflecting the scalability and flexibility of the system.

[0279] As used in this application and the claims, unless the context clearly indicates otherwise, words such as "a", "an", "one", and / or "the" are not specifically singular and may also include the plural. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of the clearly identified steps and elements, and these steps and elements do not constitute an exclusive list. A method or device may also include other steps or elements.

[0280] Those skilled in the art will further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in conjunction with the embodiments disclosed herein can be implemented as electronic hardware, computer software, or a combination of the two. To clearly illustrate this interchangeability of hardware and software, the various illustrative components, blocks, modules, circuits, and steps are described above in terms of their functionality. Whether such functionality is implemented as hardware or software depends on the specific application and the design constraints imposed on the overall system. Skilled artisans may implement the described functionality in different ways for each specific application, but such implementation decisions should not be construed as causing a departure from the scope of the present invention.

[0281] The steps of the methods or algorithms described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. The software module may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such that the processor can read from, and write to, the storage medium. In an alternative, the storage medium may be integrated into the processor. The processor and the storage medium may reside in an ASIC. The ASIC may reside in a user terminal. In an alternative, the processor and the storage medium may reside as discrete components in a user terminal.

[0282] The above embodiments are provided for those skilled in the art to implement or use the present invention. Those skilled in the art can make various modifications or changes to the above embodiments without departing from the inventive concept of the present invention. Therefore, the protection scope of the present invention is not limited by the above embodiments, but should be the maximum scope that conforms to the innovative features mentioned in the claims.

Claims

1. A motion control system for a flight simulator based on a digital twin model, characterized in that, It includes a physical platform module, a digital twin system, a parameter identification system, and a parameter optimization system: The physical platform module includes at least a host computer, a motion control module, and a flight simulator motion execution module; The host computer is used to run the digital twin system, the parameter identification system, and the parameter optimization system; The motion control module is used to execute the host computer instructions, perform motion control on the flight simulator motion execution module, and achieve safe motion; The flight simulator motion execution module performs relevant motion actions on the flight simulator and feeds back status parameters; The digital twin system is a digital twin model of the flight simulator set in the host computer, and at least includes a mechanical system digital twin model and a drive system digital twin model. The mechanical system digital twin model is used for real-time visualization of the mechanical motion of the flight simulator, and the drive system digital twin model is used to verify and optimize the controller parameters and feed back the control effect in real time; The parameter identification system is set in the host computer and performs dynamic parameter identification, adjustment, and correction on the digital twin model of the flight simulator based on the status parameters fed back by the flight simulator motion execution module; The parameter optimization system is set in the host computer and optimizes the controller parameters of the motion control module based on the simulation results of the identified digital twin system.

2. The motion control system of a flight simulator based on a digital twin model according to claim 1, characterized in that, The host computer also includes: A visual host computer interface, located in the middle layer between the digital twin system and the motion control module, is used to display the operation status and motion trajectory information of the flight simulator.

3. The motion control system of a flight simulator based on a digital twin model according to claim 1, characterized in that, The flight simulator motion execution module includes at least a motor, a flight simulator mechanical structure, and several sensors. The motion control module includes a controller and a driver: The controller performs real-time motion control on the flight simulator motion execution module based on the instructions of the host computer; The driver is used to drive the current magnitude of the servo motor to achieve servo tracking control of the motor.

4. The motion control system of the flight simulator based on the digital twin model according to claim 1, characterized in that, The mechanical system digital twin model of the flight simulator is built and implemented through the following steps: Build a mechanical system model according to the mechanical system structure of the flight simulator, and import the mechanical system model into the visual simulation tool environment to build a digital twin model of the flight simulator mechanical system.

5. The motion control system of a flight simulator based on a digital twin model according to claim 4, characterized in that, The mechanical system digital twin model is built and implemented through the following steps: Step S11: According to the mechanical system structure of the flight simulator, build a corresponding 3D model, and define the attributes of each component model in the 3D model. The attribute definition includes material attributes and geometric shapes; Step S12: Assemble each component model in the 3D model into a mechanical system model, and ensure that the mechanical structure and motion characteristics of the mechanical system model are consistent with the actual mechanical system structure of the aircraft simulator by adding corresponding assembly constraints; Step S13: Convert the mechanical system model into a specified format file, and the specified format file contains mechanical structure, assembly constraint, and motion characteristic information; Step S14: Import the specified format file into the visual simulation tool to generate a corresponding multi-body dynamics model, and the multi-body dynamics model is used as the digital twin model of the flight simulator mechanical system.

6. The motion control system of a flight simulator based on a digital twin model according to claim 1, wherein The digital twin model of the drive system includes a mechatronics digital twin model and a drive control system digital twin model, which are built through the following steps: Step S21: Establish a digital twin model of the motor body according to the physical characteristics of the servo motor, and couple the digital twin model of the motor body with the digital twin model of the mechanical system based on the transmission relationship of the drive system to establish a mechatronics digital twin model; Step S22: Establish a digital twin model of the drive control system according to the drive control architecture of the flight simulator; Among them, the mechatronics digital twin model and the drive control system digital twin model form the digital twin model of the drive system of the flight simulator through signal interaction.

7. The motion control system of a flight simulator based on a digital twin model according to claim 6, characterized in that, The digital twin model of the motor body is constructed by electrical equations, electromagnetic torque equations, and mechanical transmission equations.

8. The motion control system of a flight simulator based on a digital twin model according to claim 6, characterized in that, In step S21, coupling the digital twin model of the motor body with the digital twin model of the mechanical system based on the transmission relationship of the drive system further includes: Based on the transmission relationship of the drive system, the screw telescopic amount L is used as the input of the digital twin model of the mechanical system, and the digital twin model of the mechanical system outputs the driving force. As the load torque of the digital twin model of the motor body, it realizes the physical coupling of the mechanical system and the drive system of the flight simulator.

9. The motion control system of a flight simulator based on a digital twin model according to claim 6, wherein, The digital twin model of the drive control system includes a current loop control model and a speed loop control model; The current loop control model is a digital twin model of the current loop controller established according to the current loop PI control structure of the driver, adopting the discrete form of the PI controller and setting a voltage limiter; The speed loop control model is a digital twin model of the speed loop controller established according to the speed loop PI control structure of the driver, adopting the discrete form of the PI controller and setting a current limiter.

10. The motion control system of a flight simulator based on a digital twin model according to claim 1, characterized in that, The digital twin system sets the sampling time to be the same as the simulation step size to achieve synchronization and real-time data interaction between the digital twin system and the flight simulator.

11. The motion control system of a flight simulator based on a digital twin model according to claim 1, wherein, The digital twin model of the flight simulator includes a flight simulator dynamics model; The parameter identification system constructs a flight simulator dynamics model through the principle of virtual work, updates, identifies, and adjusts the parameters of the flight simulator dynamics model through a nonlinear optimization algorithm, and conducts a fidelity test on the digital twin model of the flight simulator.

12. The motion control system of a flight simulator based on a digital twin model according to claim 11, characterized in that, The parameter identification system updates, identifies, and adjusts the parameters of the flight simulator dynamics model through a particle swarm nonlinear optimization algorithm.

13. The motion control system of a flight simulator based on a digital twin model according to claim 3, characterized in that, The parameter optimization system builds a digital twin model controller based on the digital twin model after identification and adjustment; Optimizes the controller parameters through a nonlinear optimization algorithm; Establishes the constraint conditions for optimizing the controller parameters; Transfers the optimized controller parameters to the controller.

14. The motion control system of a flight simulator based on a digital twin model according to claim 11, characterized in that, The expression of the flight simulator dynamics model constructed by the parameter identification system through the principle of virtual work is: ； wherein, is the velocity Jacobian matrix of the upper platform, is the driving force of the outrigger, is the external and inertial torque of the simulator cockpit and the upper platform, , and are respectively the transposes of the velocity Jacobian matrices of the -th lower limb and upper limb, and are respectively the external and inertial torques of the -th lower limb and upper limb.

15. The motion control system of a flight simulator based on a digital twin model according to claim 11, wherein The parameter identification system takes the inertial sensor data and the leg displacement sensor data as the input of the flight simulator dynamics model, takes the driving force of each leg as the output of the flight simulator dynamics model, and takes the error between the output value and the actual leg pressure sensor data as the optimization objective function. The expression of the optimization objective function is: Among them, is the deviation value between the driving force of the th leg of the flight simulator dynamics model identified for the th time and the force measured by the pressure sensor, and the constraint condition is defined as: .

16. The motion control system of a flight simulator based on a digital twin model according to claim 11, characterized in that, The parameter identification system uses the following steps to identify and optimize the parameters of the flight simulator dynamics model: Obtain the sensor data set saved in the visualization interface; Determine the dynamic model of the target flight simulator and the parameters of the flight simulator dynamic model that need to be optimized and identified; Determine the particle swarm dimension, particle swarm size, inertia factor, acceleration constants, and initialize the positions and velocities of the particles; Calculate the fitness value of each example according to the optimized objective function, and update the positions of the individual best and global best; Iterate the above steps until the termination condition is met; Output the global best position as the optimal solution of the parameters.

17. The motion control system of a flight simulator based on a digital twin model according to claim 11, wherein, The parameter identification system transmits the model parameters obtained by optimized identification to the digital twin system, modifies the upper platform structure inertia parameters and limb inertia parameters of the digital twin model, and simultaneously monitors the torque information output by the digital twin system during operation and the pressure information collected by the actual operation pressure sensor, and calculates the digital twin model fidelity R through the following expression: Among them, is the measurement force of the th leg pressure sensor collected for the th time.

18. The motion control system of a flight simulator based on a digital twin model according to claim 13, characterized in that, The parameter optimization system optimizes the parameters of the current loop controller and the speed loop controller through a non-linear optimization algorithm, defines the amplitude and frequency tracking performance of sinusoidal motion for different degrees of freedom by weighted summation, and constructs a total objective function to measure the motion control performance of the flight simulator.

19. The motion control system of a flight simulator based on a digital twin model according to claim 3, wherein The several sensors include a pressure sensor and an inertial sensor: The pressure sensor is used to monitor and feedback the force condition of the mechanical structure of the flight simulator; The inertial sensor is used to monitor and feedback the attitude and motion state of the mechanical structure of the flight simulator.

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