A flight simulator motion control system based on digital twin model

Abstract

The present invention relates to the field of digital twin technology, and more specifically, to a flight simulator motion control system based on a digital twin model. The present invention comprises: a physical platform module, a digital twin system, a parameter identification system and a parameter optimization system. The physical platform module comprises at least a host computer, a motion control module and a flight simulator motion execution module; the digital twin system is used for real-time visualization of the mechanical motion of the flight simulator, verification and optimization of controller parameters, and real-time feedback of the control effect; the parameter identification system identifies, adjusts and corrects the dynamic parameters of the digital twin model of the flight simulator; the parameter optimization system optimizes the controller parameters of the motion control module based on the simulation results of the identified digital twin system. The present invention can optimize the control performance and improve the equipment safety and motion performance of the flight simulator by building and optimizing the mechatronic digital twin model.

Description

Technical Field

[0001] The present invention relates to the field of digital twin technology, and more particularly, to a flight simulator motion control system 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 effectiveness of simulation training and the level of aviation safety.

[0003] However, existing flight simulator motion control systems still face significant challenges in practical applications. While the widely adopted servo-driven PID control method boasts a simple structure and easy debugging, it has significant limitations when dealing with the complex electromechanical systems of flight simulators. First, the system's dynamic characteristics exhibit strong coupling and high nonlinearity. Traditional PID control, based on empirical parameter tuning, struggles to achieve precise decoupling control and is prone to problems such as response lag and overshoot. Second, factors such as wear and tear of mechanical components over long periods of use and changes in ambient temperature and humidity can cause system dynamic parameter drift. Traditional PID algorithms, lacking online adaptive adjustment capabilities, are unable to effectively compensate for these changes, resulting in a decrease in control accuracy over time and threatening system stability.

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

[0005] At the modeling level, existing research has primarily established theoretical simulation models based on the mechanical dynamics of the Stewart platform (such as mass, inertia, and friction parameters). While these models can assist with platform trajectory planning, they neglect the modeling of the dynamic characteristics of the motor and drive system. For example, the electromagnetic equations of the permanent magnet synchronous motor and the dynamic response characteristics of the drive's current and velocity loops are not incorporated into the model framework. This "mechanical-electrical separation" modeling approach prevents the digital twin system from replicating the coupling characteristics of the actual electromechanical system, making it difficult to accurately predict the impact of complex operating conditions such as harmonic vibration and sudden load changes on control performance.

[0006] In addition, existing digital twin models mostly rely on sensor data (such as displacement and acceleration) to achieve virtual-reality mapping of mechanical systems, but their application scope is often limited to state monitoring and visualization display. They have not yet penetrated into the core links of control system design and have failed to build a closed-loop twin framework covering controller parameter optimization and electromechanical interaction testing.

[0007] At the same time, the existing flight simulator control design is still mainly based 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 use real-time simulation data to dynamically adjust the controller parameters, and it is impossible to adapt to the dynamic changes caused by parameter drift or external interference during long-term operation of the system.

[0008] The limitations of existing technologies and the urgency of practical needs indicate that a more complete flight simulator motion control system is urgently needed. Summary of the Invention

[0009] The purpose of the present invention is to provide a flight simulator motion control system based on a digital twin model to solve the problem that the existing flight simulator has reduced motion accuracy due to the separation of electromechanical models and 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 the controller parameters of existing flight simulators are difficult to optimize.

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

[0012] The physical platform module at least includes 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, parameter identification system and parameter optimization system;

[0014] 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;

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

[0016] The digital twin system is a digital twin model of the flight simulator set in the host computer, which includes at least 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 controller parameters and provide real-time feedback on control effects.

[0017] 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 state parameters fed back by the flight simulator motion execution module;

[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] The visual 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 flight simulator's operating status and motion trajectory information.

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

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

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

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

[0025] A mechanical system model is constructed based on the mechanical system structure of the flight simulator, and the mechanical system model is imported into the visual simulation tool environment to build a digital twin model of the flight simulator mechanical system.

[0026] In one embodiment, the mechanical system digital twin model is constructed by the following steps:

[0027] Step S11: construct a corresponding three-dimensional model according to the mechanical system structure of the flight simulator, and define properties of each component model in the three-dimensional model, wherein the property definition includes material properties and geometric shapes;

[0028] Step S12: assembling the component models in the three-dimensional model into a mechanical system model, and adding corresponding assembly constraints to 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;

[0029] Step S13: converting the mechanical system model into a specified format file, wherein the specified format file includes mechanical structure, assembly constraints and motion characteristic information;

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

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

[0032] Step S21: establishing a digital twin model of the motor body according to the physical characteristics of the servo motor, 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 to establish a mechatronics digital twin model;

[0033] Step S22: establishing a digital twin model of the drive control system based on 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 drive system digital twin model of the flight simulator through signal interaction.

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

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

[0037] Based on the transmission relationship of the drive system, the extension and contraction amount of the screw L is used as the input of the mechanical system digital twin model, and the mechanical system digital twin model 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 drive control system digital twin model 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 by adopting a discrete form of the PI controller and setting a voltage limiter based on the current loop PI control structure of the driver;

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

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

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

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

[0044] In one embodiment, the parameter identification system updates, identifies and adjusts the flight simulator dynamics model parameters using a particle swarm nonlinear 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] Optimize controller parameters through nonlinear optimization algorithm;

[0047] Establish constraints for optimizing controller parameters;

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

[0049] In one embodiment, the parameter identification system constructs a flight simulator dynamics model based on the principle of virtual work, and the corresponding expression is:

[0050] ;

[0051] in, is the velocity Jacobian matrix of the upper platform, is the driving force of the outrigger, The external and inertial torques of the simulator cockpit and upper platform, , Respectively The transpose of the velocity Jacobian matrices of the lower and upper limbs, , Respectively External and inertial torques of the lower and upper limbs.

[0052] In one embodiment, the parameter identification system uses inertial sensor data and outrigger displacement sensor data as inputs to the flight simulator dynamics model, uses the driving force of each outrigger as output of the flight simulator dynamics model, and uses 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:

[0053]

[0054] in, For the The first identification of the flight simulator dynamics model The deviation between the driving force of the legs and the force measured by the pressure sensor is calculated, and the constraint conditions are defined as: .

[0055] In one embodiment, the parameter identification system uses the following steps to perform parameter identification and optimization on the flight simulator dynamics model:

[0056] Get the sensor data set saved in the visualization interface;

[0057] Determine the target flight simulator dynamics model and the flight simulator dynamics model parameters that need to be optimized and identified;

[0058] Determine the particle swarm dimension, particle swarm size, inertia factor, acceleration constant, and initialize the particle position and velocity;

[0059] According to the optimized objective function, the fitness value of each particle is calculated, and the individual optimal and global optimal positions are updated;

[0060] Iterate the above steps until the termination condition is met;

[0061] Output the global optimal position as the optimal solution for the parameters.

[0062] In one embodiment, the parameter identification system transmits the model parameters obtained through 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. The fidelity R of the digital twin model is calculated using the following expression:

[0063]

[0064]

[0065] in, For the The first collection Pressure sensors in the legs measure the force.

[0066] In one embodiment, the parameter optimization system optimizes the parameters of the current loop controller and the velocity loop controller through a nonlinear optimization algorithm, defines the amplitude and frequency tracking performance of sinusoidal motion in different degrees of freedom through a weighted summation method, and constitutes an overall objective function to measure the motion control performance of the flight simulator.

[0067] In one embodiment, the flight simulator mechanical structure includes: an upper platform, a simulator cockpit, a Hooke's hinge, an inner cylinder, an outer cylinder, a motor, a base, and a lead screw.

[0068] In one embodiment, the plurality of sensors include pressure sensors and inertial sensors:

[0069] Pressure sensors, used to monitor and provide feedback on the stress conditions of the flight simulator's mechanical structure;

[0070] Inertial sensors are used to monitor and provide feedback on the attitude and motion status of the flight simulator's mechanical structure.

[0071] The digital twin model-based flight simulator motion control system provided by the present invention can comprehensively test and tune the control system in a virtual environment by building and optimizing a mechatronic digital twin model, thereby reducing the need for physical testing, accelerating the hardware development process, and lowering development and testing costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] The above and other features, properties and advantages of the present invention will become more apparent from the following description taken in conjunction with the accompanying drawings and embodiments, in which like reference numerals denote like features throughout, wherein:

[0073] Figure 1 A block diagram of a flight simulator motion control system based on a digital twin model according to an embodiment of the present invention is disclosed;

[0074] Figure 2 A block diagram of the physical platform module structure according to an embodiment of the present invention is disclosed;

[0075] Figure 3 A schematic diagram of information interaction between a digital twin model and an actual model according to an embodiment of the present invention is disclosed;

[0076] Figure 4 A diagram of the steps for building a flight simulator motion control system based on a digital twin model according to an embodiment of the present invention is disclosed;

[0077] Figure 5 A flow chart of a flight simulator motion platform parameter identification operation process according to an embodiment of the present invention is disclosed.

[0078] For the sake of clarity, a brief description of the reference numerals is given below, and the meanings of the reference numerals are as follows:

[0079] 100 physical platform modules;

[0080] 110 digital twin system;

[0081] 101 Mechanical System Digital Twin Model;

[0082] 102 drive system digital twin model;

[0083] 120 parameter identification system;

[0084] 130 parameter optimization system;

[0085] 20 simulator cockpits;

[0086] 21 Hooke hinge;

[0087] 22 inner tube;

[0088] 23 outer cylinder;

[0089] 24 motors;

[0090] 25 bases;

[0091] 310 host computer;

[0092] 311 host computer visual interface;

[0093] 320 motion control module;

[0094] 321 controller;

[0095] 322 motion control unit;

[0096] 323 drive;

[0097] 330 flight simulator motion execution module;

[0098] 331 Flight simulator mechanical structure;

[0099] 332 pressure sensor;

[0100] 333 inertial sensor;

[0101] 334 motor. DETAILED DESCRIPTION

[0102] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, 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 intended to limit the invention.

[0103] Prior art modeling and simulation of flight simulator mechanical systems typically relies on a Stewart motion platform, also known as a six-degree-of-freedom (6-DOF) platform. This parallel-connected platform is commonly used in simulation, virtual reality, and flight simulators. Six adjustable support rods connect the platform's base and platform chassis. Precisely controlling the length of each support rod enables the platform to move in three translational degrees of freedom (X, Y, and Z) and three rotational degrees of freedom (pitch, roll, and yaw).

[0104] Existing simulation models based on Stewart motion platforms, used for control system design and motion trajectory planning, primarily rely on theoretical CAD parameters, such as dynamic parameters like mass, inertia, and friction. Dynamic modeling primarily focuses on mechanical structure and dynamic characteristics, neglecting the dynamic characteristics of the motor and drive system. This results in a lack of comprehensive mechatronic considerations in the overall modeling.

[0105] Figure 1 The block diagram of the flight simulator motion control system based on the digital twin model according to an embodiment of the present invention is disclosed. Figure 1 As shown, the flight simulator motion control system may include: a physical platform module 100, a digital twin system 110, a visual host computer interface, a parameter identification system 120, a motion control module and a parameter optimization system 130.

[0106] The physical platform module 100 may include a host computer, a motion control module, and a flight simulator motion execution module, which are used for flight simulator motion control, data transmission, and status monitoring.

[0107] The host computer is used to run the digital twin system 110, the parameter identification system 120 and the parameter optimization system 130.

[0108] 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.

[0109] In this application, the motion control module is mainly used to execute the motion instructions sent by the visual host computer, and control the operating signals of the servo motor through the finite state machine to support the multi-functional operation of the motor.

[0110] Among them, multifunctional operations may include enabling, motion control, emergency stop protection, etc., which are used to flexibly achieve safe and reliable motion control.

[0111] The flight simulator motion execution module performs relevant motion actions on the flight simulator and feeds back state parameters.

[0112] In this embodiment, the flight simulator motion execution module at least includes a motor, a flight simulator mechanical structure and a number of sensors.

[0113] The digital twin system 110 is a digital twin model of a flight simulator set in a host computer, which includes at least a mechanical system digital twin model 101 and a drive system digital twin model 102. 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 controller parameters and provide real-time feedback on control effects.

[0114] The visual 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 dynamic feedforward compensation signal and optimized controller parameters verified by the digital twin system 110, and send the operating status and motion trajectory information of the flight simulator. The visual host computer interface provides real-time visual display.

[0115] The parameter identification system 120 is set in the host computer and identifies, adjusts and corrects the dynamic parameters of the digital twin model of the flight simulator based on the state parameters fed back by the flight simulator motion execution module.

[0116] The parameter identification system 120 may include: a data acquisition system 121, a dynamic parameter identification module 122, and a digital twin model verification module 123:

[0117] The data acquisition system 121 collects real-time data of the digital twin system 110, processes and calculates dynamic parameters through the dynamic 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.

[0118] The present invention obtains sensor data in real time through the parameter identification system 120, and online identifies and updates the inertia parameters in the digital twin model, thereby 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 dynamic feedforward control performance.

[0119] In one embodiment, the flight simulator digital twin model includes a flight simulator dynamics model. The parameter identification system 120 constructs the flight simulator dynamics model through the principle of virtual work, updates, identifies and adjusts the flight simulator dynamics model parameters through a nonlinear optimization algorithm, and performs a realism test on the flight simulator digital twin model.

[0120] The parameter identification system 120 can update, identify and adjust the flight simulator dynamic model parameters through a particle swarm nonlinear optimization algorithm.

[0121] 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.

[0122] In one embodiment, the parameter optimization system 130 builds a digital twin model controller based on the identified and adjusted digital twin model;

[0123] Optimize controller parameters through nonlinear optimization algorithm;

[0124] Establish constraints for optimizing controller parameters;

[0125] Pass the optimized controller parameters to the controller.

[0126] Figure 2 The physical platform module structure diagram according to an embodiment of the present invention is disclosed. 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.

[0127] The physical platform module 100 provides the basic hardware for the flight simulator motion control system, including the host computer, controller, driver, motor, flight simulator mechanical structure, inertial sensor and pressure sensor, etc., which are used for flight simulator motion control, data transmission and status monitoring.

[0128] Among them, the host computer is a Windows PC host computer, which is used to run the digital twin system 110 and the visual host computer interface system.

[0129] One controller and six drivers form the motion control module;

[0130] Six motors, a flight simulator mechanical structure, six pressure sensors, and one inertial sensor constitute the flight simulator motion execution module.

[0131] More specifically, the controller communicates with the host computer's visual interface to operate the motion control system. Specifically, the controller is responsible for executing speed control instructions from the drive in the motion control system and communicating with the host computer's visual interface via the ADS (Automation Device Specification) protocol, processing motion control instructions in real time.

[0132] The driver is used to drive the current of the servo motor to achieve servo tracking control of the motor.

[0133] The six motors are servo motors, connected to the drives using CAN bus and communicating via EtherCAT network. They are responsible for performing precise motion control and powering the flight simulator.

[0134] The mechanical structure of the flight simulator is a Stewart platform, driven by a motor 24, simulating actual flight motion, and may include: an upper platform, a simulator cockpit 20, a Hook hinge 21, an inner cylinder 22, an outer cylinder 23, a lead screw, and a base 25:

[0135] Among them, the upper platform is connected to the base 25 through six support rods, and the upper platform is used to carry the simulated device;

[0136] The simulator cockpit 20 is a part of the flight simulator and provides a place for simulated flight operations.

[0137] Hooke's hinge 21, as a component of the mechanical structure of the flight simulator, participates in realizing functions such as motion connection of the mechanical structure;

[0138] The inner cylinder 22 cooperates with the outer cylinder 23 in the mechanical structure of the flight simulator to provide certain support or movement conditions for realizing simulated flight movement;

[0139] The outer cylinder 23, in the mechanical structure of the flight simulator, cooperates with the inner cylinder 22 and others to participate in the movement of the mechanical structure and help simulate actual flight movements;

[0140] The base 25 supports the entire mechanical structure of the flight simulator;

[0141] The lead screw, in conjunction with the motor, participates in the movement of the flight simulator's mechanical structure.

[0142] Six pressure sensors are located at the connection between the motor and the lead screw of the Stewart platform to monitor and provide feedback on the force conditions of the mechanical structure.

[0143] 1 inertial sensor, installed at the center point of the Stewart platform, is used to monitor and provide real-time feedback on the posture and motion status of the mechanical structure.

[0144] The present invention provides a flight simulator motion control system based on a digital twin model. It adds modeling of motors and drive systems to the digital twin model of traditional mechanical systems, and pre-designs and verifies controllers in the virtual twin. This can optimize control performance and avoid the potential impact of direct deployment on hardware, thereby improving the equipment safety and motion performance of the flight simulator, realizing a mechatronic digital twin model, and better reflecting the inherent coupling relationship between motor drive and mechanical systems.

[0145] Figure 3 The information interaction diagram between the digital twin model and the actual model is revealed, such as Figure 3 The flight simulator motion control system based on digital twin technology shown in the figure, wherein the physical platform module may include: a host computer 310, a motion control module 320 and a flight simulator motion execution module 330.

[0146] The following will be combined Figures 1 to 3 Further describe how information interacts between the digital twin model and the actual model.

[0147] In practical applications, the host computer 310 can run on a 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;

[0148] The digital twin system 110 communicates with the host computer visualization interface 311, the parameter identification system 120 and the parameter optimization system 130 through the UDP protocol.

[0149] Among them, UDP (User Datagram Protocol) is a datagram mode that provides packet-switched computer communications in a group of interconnected computer network environments. Simply put, UDP is a network communication protocol that is suitable for scenarios that require fast transmission but do not require high reliability.

[0150] The motion control module 320 is set in the control cabinet and 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 host computer. The driver 323 is used to drive the current size of the servo motor to realize servo tracking control of the motor.

[0151] The controller 321 communicates with the driver 323 and the motor 334 via the Ethercat protocol to control the operation of the flight simulator.

[0152] In this embodiment, the controller 321 includes at least a motion control unit 322 .

[0153] The motion control unit 322 is an embedded controller PLC, which is responsible for accurately controlling the speed command of the servo motor.

[0154] The embedded controller PLC is a controller specially used to control mechanical motion systems. It is based on a programmable logic controller and achieves precise control of mechanical motion systems by writing control programs. It has the advantages of high reliability, high precision, and high flexibility.

[0155] The flight simulator motion execution module 330 is a part of the flight simulator and may include: a flight simulator mechanical structure 331, a pressure sensor 332, and an inertial sensor 333.

[0156] 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 via the Ethercat protocol to obtain real-time data and perform precise motion control.

[0157] Furthermore, the flight simulator mechanical structure 331 , the pressure sensor 332 , the inertial sensor 333 , and the motor 334 are mechanically connected to each other to perform motion.

[0158] The flight simulator motion control system based on the digital twin model provided by the present invention adopts mechatronic modeling and digital twin solutions, combines motor characteristics and mechanical dynamic characteristics to achieve higher-precision simulation and control, and combines the real-time correction and optimization algorithm of the dynamic model to improve the controller's adaptability to dynamic changes and achieve higher robustness and stability.

[0159] Figure 4 The following is a diagram showing the steps for building a flight simulator motion control system based on a digital twin model according to an embodiment of the present invention. Figure 4 As shown, the flight simulator motion control system construction method includes the following steps:

[0160] Step S1: Construct a mechanical system model based on the mechanical system structure of the flight simulator, import the mechanical system model into the Simulink environment, and build a digital twin model of the flight simulator mechanical system;

[0161] Step S2: Building a digital twin model of the flight simulator drive system. Specifically, the digital twin model of the drive system includes a mechatronics digital twin model and a drive control system digital twin model.

[0162] Step S3: Set the sampling time and simulation step size to be consistent to achieve synchronization and real-time data interaction between the digital twin system and the flight simulator;

[0163] Step S4: constructing a flight simulator dynamics model using the principle of virtual work, updating, identifying, and adjusting the flight simulator dynamics model parameters using a nonlinear optimization algorithm, and performing a fidelity test on the flight simulator digital twin model;

[0164] Step S5: Build a digital twin model controller and optimize controller parameters.

[0165] Among them, step S1 is used to build a digital twin model of the mechanical system.

[0166] More specifically, the mechanical system digital twin model is built and implemented through the following steps:

[0167] A mechanical system model is constructed based on the mechanical system structure of the flight simulator, and the mechanical system model is imported into the visual simulation tool environment to build a digital twin model of the flight simulator mechanical system.

[0168] In this embodiment, the mechanical system digital twin model is built and implemented through the following steps:

[0169] Step S11: construct a corresponding three-dimensional model according to the mechanical system structure of the flight simulator, and define the properties of each component model in the three-dimensional model, wherein the property definition includes material properties and geometric shapes.

[0170] Specifically, based on the mechanical structure of the flight simulator defined and constructed by the flight simulator motion platform component model, the corresponding component models are constructed;

[0171] Among them, various components include but are not limited to the upper platform, base, motor, lead screw, drive, Hooke's hinge, outer and inner cylinders, and simulator cockpit;

[0172] The material properties include: density, elastic modulus and Poisson's ratio;

[0173] The geometry includes size, shape and volume characteristics.

[0174] Step S12: Assemble the component models in the three-dimensional 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.

[0175] In one embodiment, SolidWorks software can be used to assemble the component models in the three-dimensional model into a mechanical system model, and by adding corresponding assembly constraints, it is ensured that the mechanical structure and motion characteristics of the mechanical system model are consistent with the mechanical system structure of the aircraft simulator, wherein the assembly constraints include matching relationships such as concentricity and / or overlap between the components.

[0176] Step S13: converting the mechanical system model into a specified format file, wherein the specified format file contains mechanical structure, assembly constraints and motion characteristic information.

[0177] The specified format file may be an XML format file.

[0178] In one embodiment, the Simscape Multibody Link plug-in in MATLAB software can be used to convert the SolidWorks mechanical system model into an XML format file, where the XML format file contains mechanical structure, assembly constraints, and motion characteristics information.

[0179] Step S14: import the specified format file into a visual simulation tool to generate a corresponding multi-body dynamics model, and the multi-body dynamics model serves as a digital twin model of the mechanical system of the flight simulator.

[0180] The visual simulation tool may be Simulink software.

[0181] In one embodiment, in a MATLAB environment, the XML format file is imported into Simulink via the Simscape Multibody module to generate a corresponding Simscape multibody dynamics model, which serves as a digital twin model of the mechanical system of the flight simulator.

[0182] Step S2: Build a digital twin model of the flight simulator drive system. Specifically, the drive system digital twin model includes a mechatronics digital twin model and a drive control system digital twin model.

[0183] The drive system digital twin model includes a mechatronics digital twin model and a drive control system digital twin model, which are built and implemented through the following steps:

[0184] Step S21, establishing a mechatronics digital twin model: establishing a motor body digital twin model based on the physical characteristics of the servo motor, physically coupling the motor model with the mechanical system digital twin model based on the drive system transmission relationship, and establishing a mechatronics digital twin model.

[0185] The motor body digital twin model constructed in step S21 includes: electrical equations, electromagnetic torque equations, and mechanical transmission equations;

[0186] The electrical equation is expressed as:

[0187] ,

[0188] ,

[0189] The expression of the electromagnetic torque equation is:

[0190]

[0191] The expression of the mechanical transmission equation is:

[0192]

[0193]

[0194]

[0195] in, The stator voltage is Axis component, , The stator current is Axis component, are the stator flux Axis component, is the stator winding, , For stator Shaft inductance, Electrical angular velocity, is the permanent magnet flux;

[0196] is the output torque of the motor, Pole pairs is the motor mechanical angle speed, is the load torque of the motor, is the total viscous friction coefficient of the screw and the motor;

[0197] is the moment of inertia of the motor, is the screw lead, is the motor driving force, is the motor rotation angle, is the extension and contraction of the screw.

[0198] Specifically, the parameters of the motor digital twin model are , , , , , Find it according to the motor model and the corresponding manual.

[0199] In step S21, the motor model is physically coupled with the mechanical system digital twin model based on the drive system transmission relationship, further comprising:

[0200] In Simulink software, the screw extension L is used as the input of the mechanical system digital twin model, and the mechanical system digital twin model outputs the driving force As the load torque of the motor, the mechanical system and drive system of the flight simulator are physically coupled.

[0201] More specifically, based on the transmission relationship of the drive system, the Prismatic Joint and Simulink-PSConverter modules are used to take the screw extension and contraction amount 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, thereby realizing the physical connection between the two and reflecting the inherent coupling relationship between the motor drive and the mechanical system.

[0202] Among them, the Prismatic Joint and Simulink-PS Converter modules are built-in modules in the Simulink software. The Simulink-PS Converter module is used to convert digital input into physical input of the mechanical system, while the Prismatic Joint is a linear motion joint.

[0203] Step S22: Establishing a digital twin model of the drive control system: establishing a digital twin model of the drive control system according to the drive control architecture of the flight simulator, wherein the digital twin model of the drive control system includes a current loop control model and a speed loop control model;

[0204] Among them, the mechatronics digital twin model and the drive control system digital twin model constitute the drive system digital twin model of the flight simulator through signal interaction.

[0205] The step S22 further includes:

[0206] S221. Establishing a current loop control model: The current loop control model is based on the current loop PI control structure of the driver, adopts a discrete form of the PI controller, and sets a voltage limiter, thereby establishing a digital twin model of the current loop controller;

[0207] S222. Establishing a speed loop control model: The speed loop control model is a digital twin model of the speed loop controller established by using a discrete form of a PI controller and setting a current limiter according to the speed loop PI control structure of the driver.

[0208] The digital twin model of the current loop controller corresponds to the expression:

[0209]

[0210]

[0211]

[0212] in, 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, 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.

[0213] The digital twin model of the speed loop controller corresponds to the expression:

[0214]

[0215]

[0216]

[0217]

[0218] in, 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 velocity error at the previous moment, ) is the speed tracking signal sent by the motion control PLC, is the actual speed of the motor, is the current feedforward signal calculated according to the dynamic model, is the tracking signal of the driver current loop, , are the minimum and maximum values ​​of the motor's q-axis reference current.

[0219] Existing technologies use sensors (such as displacement sensors, velocity sensors, and accelerometers) to capture system status data (including position, velocity, and acceleration) in real time, driving the synchronous operation of virtual and physical models to achieve digital twins. Existing digital twin models are primarily used for real-time system status monitoring and motion visualization, helping to assess the platform's operating status. However, they fail 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.

[0220] 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 controller parameters, the dynamic behavior of the flight simulator can be simulated in real time, which significantly improves the accuracy of the control system, ensures that the motion control of the flight simulator is accurate and reliable, and realizes high-precision motion control.

[0221] Step S3: Set the sampling time and simulation step size to be consistent to achieve synchronization and real-time data interaction between the digital twin system and the flight simulator.

[0222] The present invention ensures 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 rapid response and precise execution of control commands.

[0223] Step S3 further comprises:

[0224] Step S31: Synchronize the simulation step in the visual simulation tool. Specifically, synchronize the simulation step in Simulink through the Real-Time Synchronization module, and set its parameters to be consistent with the simulation step, so as to achieve accurate synchronization between the digital twin model and the actual system.

[0225] Step S32: Receive the actual system data, speed instructions, sensor data, and motor encoder data of the flight simulator through the data interaction interface, and send the identified digital twin model dynamic parameters and optimized controller parameters back to the actual system.

[0226] The flight simulator is received through the UDP Receive module. The actual system data includes: speed command, sensor data and motor encoder data;

[0227] The identified dynamic parameters of the digital twin model and the optimized controller parameters are sent back to the actual system through the UDP Send module.

[0228] In this embodiment, by introducing the UDP Receive module, its sampling time is set to be consistent with the simulation step size, and the model can synchronously receive the speed command from the visualization interface. , inertial sensor data and pressure sensor data, motor encoder data, etc.

[0229] At the same time, by adding a UDP Send module and setting its sampling time to be consistent with the simulation step size, the identified dynamic parameters of the digital twin model and the optimized controller parameters can be sent back to the system synchronously.

[0230] The digital twin model of the present invention dynamically adjusts model parameters through real-time synchronization and data updates, combined with real-time data collected by sensors, such as inertial and pressure sensors. This feedback mechanism enables the system to adapt to changes in the real environment, improving its dynamic response and adaptability.

[0231] Step S4: construct a flight simulator dynamics model using the principle of virtual work, update, identify, and adjust the flight simulator dynamics model parameters using a nonlinear optimization algorithm, and perform a fidelity test on the flight simulator digital twin model.

[0232] Figure 5 The flow chart of the flight simulator motion platform parameter identification operation process according to an embodiment of the present invention is disclosed. Figure 5 As shown, the step S4 further includes:

[0233] Step S41: Construct a Stewart platform dynamics model of the flight simulator based on the principle of virtual work:

[0234] ;

[0235]

[0236]

[0237]

[0238]

[0239]

[0240]

[0241]

[0242]

[0243]

[0244]

[0245] Where, is the velocity Jacobian matrix of the upper platform, is the driving force of the outrigger, The external and inertial torques of the simulator cockpit and upper platform, , Respectively The transpose of the velocity Jacobian matrices of the lower and upper limbs, , Respectively External and inertial torques of the lower and upper limbs. is the external disturbance force, For the quality of the platform, is the acceleration due to gravity, is the acceleration of the simulator cockpit center of mass, is the external disturbance torque, is the motion platform rotation matrix, is the moment of inertia of the simulator cockpit and upper platform around the fixed coordinate system, is the angular acceleration, is the center of mass of the simulator cockpit and upper platform, is the moment of inertia of the simulator cockpit and upper platform around their center of mass, , Respectively The inertial forces of the lower and upper limbs, , Respectively The moment of inertia of the lower and upper limbs, For the The acceleration of the lower leg, For the The quality of the lower leg, For the The moment of inertia of the lower limb around the fixed coordinate system, For the The angular velocity of the legs, For the The moment of inertia of the lower limb about its center of mass, is the acceleration of the upper leg, For the The quality of the lower leg, For the The moment of inertia of the upper limb around the fixed coordinate system, is the moment of inertia of the lower limb about its center of mass. Respectively The center of gravity of the lower and upper legs, For the The cross product matrix of the unit vectors of the legs, For the platform The coordinates of the hinge points, For the The length of the outriggers.

[0246] The parameters of the dynamic model based on the principle of virtual work are identified through nonlinear optimization for: , , , , , , , .

[0247] Step S42: construct a particle swarm nonlinear optimization algorithm to update the identification and adjust the parameters of the digital twin model;

[0248] The parameter identification system uses the inertial sensor data and the outrigger displacement sensor data as the input of the flight simulator dynamics model, and uses the driving force of each leg as the output of the flight simulator dynamics model. The output value and the error between the actual outrigger pressure sensor data are used as the optimization objective function:

[0249]

[0250] in For the The first identified dynamic model The deviation between the driving force of the legs and the force measured by the pressure sensor is used to define the optimization constraints as follows: .

[0251] In this embodiment, the parameter identification system updates, identifies and adjusts the flight simulator dynamics model parameters through a particle swarm nonlinear optimization algorithm.

[0252] This method uses nonlinear optimization algorithms, such as particle swarm optimization, to optimize the dynamic model parameters of the digital twin system. The current feedforward signal calculated by the digital twin system's dynamic model can be dynamically adjusted based on the system's actual performance, effectively improving the flight simulator's motion control accuracy. By gradually optimizing the digital twin system's dynamic model, precise control of the flight simulator under different load motion scenarios is ensured, enabling precise controller adjustment and optimization.

[0253] Furthermore, the parameter identification system uses the following particle swarm nonlinear optimization algorithm to perform parameter identification and optimization on the flight simulator dynamics model based on the virtual work principle, specifically including the following steps:

[0254] Acquire a sensor data set saved in a visualization interface, wherein the sensor data set includes inertial sensor data, pressure sensor data, and motor displacement sensor data;

[0255] Determine the target flight simulator dynamics model and the flight simulator dynamics model parameters m that need to be optimized and identified. , , , , , , , ,Each leg uses the same parameters, a total of 17 parameters;

[0256] Determine the particle swarm dimension Dim = 17, the particle swarm size SwarmSize = 51, the inertia factor, the acceleration constant, and then initialize the particle position and velocity;

[0257] According to the optimization objective function, the fitness value of each particle is calculated, and the individual optimal and global optimal positions are updated;

[0258] Iterate the above steps until the termination conditions are 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;

[0259] Output the global optimal position as the optimal solution for the parameters.

[0260] It is worth noting that the process of parameter identification and optimization of the dynamic model of the virtual work principle is dynamic, and continuous data collection is required to verify and optimize the model.

[0261] Step S43: pass the parameters obtained by particle swarm optimization to the digital twin model, and calculate the fidelity R of the digital twin model. If the fidelity R reaches the preset value, , then save the parameters, otherwise re-identify and correct the parameters.

[0262] The parameter identification system transfers the model parameters obtained through optimization and identification to the digital twin system, modifies the upper platform structure inertia parameters and limb inertia parameters of the digital twin model, 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 using the following expression:

[0263]

[0264]

[0265] in, For the The first collection The pressure sensors on the legs measure the force. If the fidelity of the model meets the preset value, , the corresponding model parameters are saved, otherwise the parameters of the digital twin model are re-identified and corrected.

[0266] Existing control systems typically employ servo drives and PID control algorithms, ensuring precise trajectory tracking and dynamic stability of the motion platform by adjusting input signals within the joint space. However, these control algorithms typically assume constant dynamic parameters and fail to account for dynamic parameter drift that may occur with long-term system operation or changes in operating conditions (such as mechanical wear and friction). Consequently, they fail to provide online correction or adaptive optimization for parameter changes. While such solutions offer good stability in the short term, parameter drift over the long term can lead to reduced control accuracy and system performance degradation.

[0267] The parameter identification system of the present invention introduces dynamic parameter online identification and correction technology, realizes the performance optimization of the flight simulator in long-term operation, and overcomes the problem of decreased control accuracy caused by parameter changes in the prior art.

[0268] Step S4 of the present invention performs parameter identification through the principle of virtual work and nonlinear optimization algorithm, which can accurately identify the dynamic characteristics of the flight simulator and continuously adjust the model parameters through the optimization algorithm to make the digital twin model highly consistent with the behavior of the actual system, greatly improving the realism and control accuracy of the model, and realizing accurate dynamic modeling and parameter identification.

[0269] Step S5: Build a digital twin model controller and optimize controller parameters.

[0270] The parameter optimization system verifies and optimizes the controller through the digital twin model and migrates it to the actual model for deployment, thereby optimizing control performance and avoiding potential impacts on hardware. This not only improves the control accuracy of the flight simulator, but also enhances the safety and motion performance of the equipment.

[0271] In one embodiment, step S5 further includes:

[0272] Step S51: Building a digital twin model controller based on the identified and adjusted digital twin model;

[0273] Step S52: Optimizing controller parameters using a nonlinear optimization algorithm, wherein the controller parameters include proportional and integral terms of the current loop and the speed loop;

[0274] Step S53: establishing constraints for optimizing controller parameters;

[0275] Step S54: transferring the optimized controller parameters to the current loop controller and the speed loop controller.

[0276] In this embodiment, based on the digital twin model, the controller construction and parameter optimization of the flight simulator motion control system were completed, which specifically included the following steps:

[0277] The parameter optimization system designs the PI controller (including the current loop and speed loop) of the digital twin model based on the identified and adjusted digital twin model, and verifies its structure and performance through model simulation;

[0278] The parameter optimization system uses a nonlinear optimization algorithm to optimize the parameters of the current loop controller and the speed loop controller, and defines the amplitude of the sinusoidal motion of different degrees of freedom (lateral, longitudinal, vertical, pitch, roll, yaw) by weighted summation. and frequency tracking performance , forming the overall objective function To measure the flight simulator motion control performance, the corresponding expression is as follows:

[0279] ;

[0280] ;

[0281] ;

[0282] in, is the frequency of the sinusoidal motion, is the weighting factor of the six degrees of freedom at each frequency, are the weighting factors for the six degrees of freedom.

[0283] 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.

[0284] During the optimization process, the model constraints include the following aspects:

[0285] The stability of the controller system ensures the closed-loop system extremes , ensuring that the poles of the closed-loop system are located in the stable region;

[0286] Motion platform range limitations, including displacement ,speed and acceleration scope;

[0287] Displacement range: ;

[0288] Speed ​​range: ;

[0289] Acceleration range: ;

[0290] Controller parameter limits ensure that controller parameters Within the range set by experience:

[0291] ;

[0292] in, 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.

[0293] The parameter optimization system transfers the optimized PI controller parameters and current loop feedforward items to the actual control software of the controller to achieve more efficient control performance.

[0294] At the same time, the dynamic coefficients obtained by parameter identification are transferred to the current feedforward controller to ensure the accuracy and dynamic response of the motor control.

[0295] When the controller performance does not meet the requirements, the parameter optimization system will re-adjust the current loop and speed loop controller parameters until the control performance is met.

[0296] At this point, 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.

[0297] The digital twin model-based flight simulator motion control system 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 enabling comprehensive evaluation of controller performance during the optimization process.

[0298] The flight simulator motion control system based on the digital twin model provided by the present invention can comprehensively test and tune 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 cost.

[0299] The flight simulator motion control system based on the digital twin model provided by the present invention can establish a digital twin model that can not only simulate the existing structure of the flight simulator, but also expand new functions or adjust the existing model according to needs, providing flexible technical support for future upgrades and performance improvements of the flight simulator, and reflecting the scalability and flexibility of the system.

[0300] As used in this application and the claims, unless the context clearly indicates otherwise, the words "a," "an," "an," and / or "the" are not intended to refer to the singular but may include the plural. Generally speaking, the terms "comprises" and "include" only indicate the inclusion of the steps and elements specifically identified, and these steps and elements do not constitute an exclusive list. A method or apparatus may also include other steps or elements.

[0301] Those skilled in the art will further appreciate that the various illustrative logic blocks, modules, circuits, and algorithmic 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, various illustrative components, blocks, modules, circuits, and steps are generally 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. A skilled person may implement the described functionality in different ways for each specific application, but such implementation decisions should not be interpreted as resulting in a departure from the scope of the present invention.

[0302] The steps of the methods or algorithms described in conjunction 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 so that the processor can read and write information from / to the storage medium. In an alternative, the storage medium may be integrated into the processor. The processor and storage medium may reside in an ASIC. The ASIC may reside in a user terminal. In an alternative, the processor and storage medium may reside in a user terminal as discrete components.

[0303] The above embodiments are provided to persons familiar with the art for implementing or using the present invention. Personnel familiar with the art may make various modifications or changes to the above embodiments without departing from the inventive concept of the present invention. Therefore, the scope of protection of the present invention is not limited to the above embodiments, but should be the maximum scope of the innovative features mentioned in the claims.

Claims

1. A flight simulator motion control system based on a digital twin model, characterized in that: Including physical platform module, digital twin system, parameter identification system and parameter optimization system: The physical platform module at least includes 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, parameter identification system and 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 executes relevant motion actions on the flight simulator and feeds back state parameters; The digital twin system is a digital twin model of the flight simulator set in the host computer, which includes at least 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 controller parameters and provide real-time feedback on control effects. 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 state 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; The drive system digital twin model includes a drive control system digital twin model, and the drive control system digital twin model 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 by adopting a discrete form of the PI controller and setting a voltage limiter based on the current loop PI control structure of the driver; The speed loop control model is a digital twin model of the speed loop controller established by using a discrete form of the PI controller and setting a current limiter based on the speed loop PI control structure of the drive; The drive system digital twin model also includes a mechatronics digital twin model, which is built and implemented through the following steps: Step S21: establishing a digital twin model of the motor body according to the physical characteristics of the servo motor, 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 to establish a mechatronics digital twin model; Step S22: establishing a digital twin model of the drive control system based on the drive control architecture of the flight simulator; Among them, the mechatronics digital twin model and the drive control system digital twin model constitute the drive system digital twin model of the flight simulator through signal interaction.

2. The flight simulator motion control system based on the digital twin model according to claim 1, characterized in that: The host computer also includes: The visual 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 flight simulator's operating status and motion trajectory information.

3. The flight simulator motion control system based on the 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, and 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 instructions from the host computer; The driver is used to drive the current of the servo motor to achieve servo tracking control of the motor.

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

5. The flight simulator motion control system based on the digital twin model according to claim 4 is characterized in that: The mechanical system digital twin model is built and implemented through the following steps: Step S11: construct a corresponding three-dimensional model according to the mechanical system structure of the flight simulator, and define properties of each component model in the three-dimensional model, wherein the property definition includes material properties and geometric shapes; Step S12: assembling the component models in the three-dimensional model into a mechanical system model, and adding corresponding assembly constraints to 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; Step S13: converting the mechanical system model into a specified format file, wherein the specified format file includes mechanical structure, assembly constraints and motion characteristic information; Step S14: import the specified format file into a visual simulation tool to generate a corresponding multi-body dynamics model, and the multi-body dynamics model serves as a digital twin model of the mechanical system of the flight simulator.

6. The flight simulator motion control system based on the digital twin model according to claim 1, characterized in that: The motor body digital twin model is constructed through electrical equations, electromagnetic torque equations and mechanical transmission equations.

7. The flight simulator motion control system based on digital twin model according to claim 1, characterized in that: The step S21 further includes coupling the motor body digital twin model with the mechanical system digital twin model based on the drive system transmission relationship: Based on the transmission relationship of the drive system, the extension and contraction amount of the screw L is used as the input of the mechanical system digital twin model, and the mechanical system digital twin model 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.

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

9. The flight simulator motion control system based on digital twin model according to claim 1, characterized in that: The flight simulator digital twin model 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 flight simulator dynamics model parameters through a nonlinear optimization algorithm, and performs a fidelity test on the flight simulator digital twin model.

10. The flight simulator motion control system based on digital twin model according to claim 9, characterized in that: The parameter identification system updates, identifies and adjusts the flight simulator dynamics model parameters through a particle swarm nonlinear optimization algorithm.

11. The flight simulator motion control system based on digital twin model according to claim 3, characterized in that: The parameter optimization system builds a digital twin model controller based on the identified and adjusted digital twin model; Optimize controller parameters through nonlinear optimization algorithm; Establish constraints for optimizing controller parameters; Pass the optimized controller parameters to the controller.

12. The flight simulator motion control system based on digital twin model according to claim 9, characterized in that: The flight simulator dynamics model constructed by the parameter identification system using the principle of virtual work has the following expression: ； in, is the velocity Jacobian matrix of the upper platform, is the driving force of the outrigger, The external and inertial torques of the simulator cockpit and upper platform, , Respectively The transpose of the velocity Jacobian matrices of the lower and upper limbs, , Respectively External and inertial torques of the lower and upper limbs.

13. The flight simulator motion control system based on digital twin model according to claim 9, characterized in that: The parameter identification system uses the inertial sensor data and the outrigger displacement sensor data as the input of the flight simulator dynamics model, and the outrigger driving force as the output of the flight simulator dynamics model. The output value and the error between the actual outrigger pressure sensor data are used as the optimization objective function. The expression of the optimization objective function is: in, For the The first identification of the flight simulator dynamics model The deviation between the driving force of the legs and the force measured by the pressure sensor is calculated, and the constraint conditions are defined as: .

14. The flight simulator motion control system based on digital twin model according to claim 9, characterized in that: The parameter identification system uses the following steps to perform parameter identification and optimization on the flight simulator dynamics model: Get the sensor data set saved in the visualization interface; Determine the target flight simulator dynamics model and the flight simulator dynamics model parameters that need to be optimized and identified; Determine the particle swarm dimension, particle swarm size, inertia factor, acceleration constant, and initialize the particle position and velocity; According to the optimized objective function, the fitness value of each particle is calculated, and the individual optimal and global optimal positions are updated; Iterate the above steps until the termination condition is met; Output the global optimal position as the optimal solution for the parameters.

15. The flight simulator motion control system based on digital twin model according to claim 9, characterized in that: The parameter identification system transfers the model parameters obtained through 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. The fidelity R of the digital twin model is calculated using the following expression: in, For the The first collection Pressure sensors in the legs measure the force.

16. The flight simulator motion control system based on digital twin model according to claim 11, characterized in that: 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 with different degrees of freedom through a weighted summation method, and constitutes an overall objective function to measure the motion control performance of the flight simulator.

17. The flight simulator motion control system based on digital twin model according to claim 3, characterized in that: The sensors include pressure sensors and inertial sensors: Pressure sensors, used to monitor and provide feedback on the stress conditions of the flight simulator's mechanical structure; Inertial sensors are used to monitor and provide feedback on the attitude and motion status of the flight simulator's mechanical structure.

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