A method and system for coordinated vibration control of multiple actuators in a flight simulator

Abstract

This invention belongs to the field of flight simulation and motion control technology, and relates to a method and system for coordinated vibration control of multiple actuators in a flight simulator. It collects flight attitude / state / event information, generates low-frequency attitude commands for a six-degree-of-freedom platform, and matches them with virtual vibration sources. Based on the airframe-cabin transfer relationship, it constructs multi-sensor point frequency-band target vibration responses and ergonomic perception weights. Based on the excitation of the previous control cycle and the current measured response, it online corrects the frequency response matrix and combines actuator travel margin to form vibration resource constraints. Under these constraints, it optimizes the optimal vibration excitation for the platform, seat, joystick, foot pedals, etc., in the current control cycle, converts it into a time-domain signal, and executes it synchronously. The platform implements decoupled superposition of low-frequency attitude and high-frequency vibration. This invention enables dynamic allocation and migration of vibration energy across actuators according to real-time capabilities, reduces the risk of channel saturation, and significantly improves the consistency of body sensation and training realism across multiple parts.

Description

Technical Field

[0001] This invention belongs to the field of flight simulation and motion control technology, specifically relating to a method and system for coordinated vibration control of multiple actuators in a flight simulator. Background Technology

[0002] Full-motion flight simulators (FFS) are flight training devices used to simulate the flight experience of a real aircraft on the ground. Existing FFS typically employs a Stewart six-degree-of-freedom motion platform, which provides pilots with pitch, roll, yaw, and three-way translational motions through the extension and retraction of six actuators, superimposed with some vibration effects. A typical system architecture includes a flight simulator host, a motion control computer (MCC), servo drives, six-degree-of-freedom platform actuators, as well as local vibration actuators such as the seat and joystick, and various sensors.

[0003] Existing vibration simulation methods for flight simulators mainly include: vibration modeling based on power spectral density (PSD) or flight test data, generating vibration reference signals during simulation; using a fixed frequency band division method, allocating low-frequency components to the six-degree-of-freedom platform for execution, and allocating high-frequency components to the seat or joystick for execution; and each actuator independently executing its corresponding vibration signal.

[0004] However, six-degree-of-freedom platforms differ significantly from various local vibration actuators in terms of installation location, driving capability, and frequency response characteristics. Furthermore, in actual operation, the travel margin, load state, and structural resonance point of different actuators change over time. Therefore, allocating vibration reference signals through fixed frequency band divisions is insufficient to reflect the real-time states of each actuator, such as travel margin, torque margin, and structural resonance. It also fails to flexibly transfer and coordinate the utilization of vibration energy based on the real-time state of each actuator, easily leading to a lack of overall coordination among the actuators. This can result in platform or local actuator overload or vibration distortion, causing a discrepancy between the pilot's overall experience during training and that of the actual aircraft, thus affecting flight training effectiveness. Summary of the Invention

[0005] Firstly, a method for coordinated vibration control of multiple actuators in a flight simulator is provided, comprising the following steps: acquiring flight attitude information, flight state information, and vibration event information output by the flight simulation host; generating low-frequency attitude commands for a six-degree-of-freedom motion platform based on flight attitude parameters and flight state parameters; matching vibration parameters from a preset vibration parameter library according to the flight event information, and converting the vibration parameters into virtual vibration source signals; mapping the virtual vibration source signals to multiple sensing points within the cabin according to the vibration transmission relationship between the airframe structure and the cabin structure, and establishing target vibration response vectors for each sensing point at different frequency bands; establishing sensing weight matrices corresponding to multiple sensing points at different frequency bands based on ergonomic characteristics; and, based on the vibration excitation vector of the previous control cycle and the measured vibration response signal of the current control cycle, analyzing the vibration excitation transmission... The frequency response matrix of the sensing point is corrected online. Based on the stroke margin of the actuator cylinder of each vibration actuator, the maximum available amplitude of each vibration actuator in each frequency band is determined, and the vibration resource state is generated. Using the vibration excitation vector as the optimization variable, a body-sensing error model including the sensing weight matrix, the target vibration response vector, and the frequency response matrix is ​​constructed. Under the constraint of the vibration resource state, the body-sensing error model is solved to obtain the optimal vibration excitation vector of each vibration actuator in each frequency band in the current control cycle. The optimal vibration excitation vector is converted into a time-domain vibration excitation signal. For a six-degree-of-freedom motion platform, the low-frequency attitude command and the corresponding high-frequency time-domain vibration excitation signal are sequentially separated in the frequency domain and superimposed in the time domain to generate motion commands. For each local vibration actuator, the corresponding time-domain vibration excitation signal is converted into displacement or torque commands and executed synchronously.

[0006] Secondly, a multi-actuator vibration coordinated control system for a flight simulator is provided, comprising: The data acquisition module is used to acquire flight attitude information, flight status information, and vibration event information output by the flight simulation host. The low-frequency attitude command generation module is used to generate low-frequency attitude commands for a six-degree-of-freedom motion platform based on flight attitude parameters and flight state parameters. The virtual vibration source signal generation module is used to match vibration parameters from a preset vibration parameter library based on flight event information and convert the vibration parameters into virtual vibration source signals. The target vibration response vector generation module is used to map virtual vibration source signals to multiple sensing points inside the cabin based on the vibration transmission relationship between the body structure and the cabin structure, and to establish the target vibration response vector of each sensing point in different frequency bands. The perception weight matrix generation module is used to combine ergonomic characteristics to establish perception weight matrices corresponding to multiple sensing points in different frequency bands. The frequency response matrix correction module is used to correct the frequency response matrix describing the vibration excitation transmitted to the sensing point online based on the vibration excitation vector of the previous control cycle and the measured vibration response signal of the current control cycle. The vibration resource status generation module is used to determine the maximum available amplitude of each vibration actuator in each frequency band based on the stroke margin of the actuator cylinder of each vibration actuator, and generate the vibration resource status. The somatosensory error model generation module is used to construct a somatosensory error model containing a sensing weight matrix, a target vibration response vector, and a frequency response matrix, using the vibration excitation vector as the optimization variable. The expression of the somatosensory error model is: ;in, f For frequency, W h ( f () is the perception weight matrix. y ref ( f ) represents the target vibration response vector. G ( f () represents the corrected frequency response matrix. u ( f Let be the vibration excitation vector to be solved; the constraints are: ; u max ( i , f () is the first determined based on the vibration resource status. i Each actuator at frequency f The maximum available amplitude at that location; The optimal vibration excitation vector generation module is used to solve the body perception error model under the constraints of vibration resource state to obtain the optimal vibration excitation vector of each vibration actuator in each frequency band during the current control cycle. The vibration excitation signal generation module is used to convert the optimal vibration excitation vector into a time-domain vibration excitation signal; The first motion command generation module is used to generate motion commands for a six-degree-of-freedom motion platform by sequentially performing frequency domain separation and time domain superposition of low-frequency attitude commands and corresponding high-frequency time-domain vibration excitation signals. The second motion command generation module is used to convert the corresponding time-domain vibration excitation signal into displacement or torque commands for each local vibration actuator and execute them synchronously.

[0007] Thirdly, a computer device is proposed, comprising a memory, a processor, and a transceiver connected in sequence, wherein the memory is used to store a computer program, the transceiver is used to send and receive data, and the processor is used to read the computer program and execute a multi-actuator vibration coordinated control method for a flight simulator as described in the first aspect.

[0008] Fourthly, a computer-readable storage medium is proposed, on which instructions are stored, which, when executed on a computer, perform a multi-actuator vibration coordinated control method for a flight simulator as described in any of the first aspects.

[0009] Fifthly, a computer program product containing instructions is proposed, which, when executed on a computer, causes the computer to perform a multi-actuator vibration coordinated control method for a flight simulator as described in the first aspect; the computer includes: a general-purpose computer, a special-purpose computer, or a programmable device.

[0010] Compared with existing technologies, this invention has the following advantages and beneficial effects: Compared to existing technologies that typically employ vibration modeling based on PSD / flight test data and distribute vibration signals to different actuators according to fixed frequency bands, where each actuator operates relatively independently and it is difficult to flexibly transfer energy based on travel margin and structural state, this solution takes "overall consistency of sensation across multiple sensing points" as an explicit goal. By acquiring flight attitude, flight state, and vibration event information output by the flight simulation host, this method can simultaneously establish a unified input foundation for attitude motion background and event-driven vibration semantics within the same control cycle. Based on attitude and state parameters, low-frequency attitude commands for a six-degree-of-freedom motion platform are generated, enabling the platform to stably bear low-frequency attitude / maneuver outputs and provide a controllable base for high-frequency vibration superposition. Then, based on flight events, virtual vibration source signals are matched from a vibration parameter library and generated. Combining the airframe-cabin interior structural transmission relationship, the virtual vibration source is mapped into target vibration response vectors for multiple sensing points in different frequency bands. Ergonomics is introduced to form a sensing weight matrix, thereby enabling control... The objective has been upgraded from traditional single-channel or fixed frequency band allocation to a quantitative objective of "overall consistency of the pilot's body sensation across multiple parts." Furthermore, the frequency response matrix is ​​corrected online using the vibration excitation vector from the previous control cycle and the measured vibration response of the current control cycle. A vibration resource state with the maximum available amplitude is constructed based on the stroke margin of each actuator's actuator cylinder, enabling the optimization model to reflect the true transmission characteristics and real-time resource boundaries. On this basis, a body sensation error model is constructed using the vibration excitation vector as the optimization variable, and the optimal vibration excitation vector for each actuator and frequency band in the current control cycle is obtained under resource constraints. After frequency-to-time domain conversion, the six-degree-of-freedom platform undergoes frequency-domain separation and time-domain superposition of low-frequency attitude and high-frequency vibration to generate motion commands. Displacement or torque commands are generated for local actuators and executed synchronously. This achieves dynamic transfer and collaborative sharing of vibration energy between the platform and multiple actuators such as the seat, joystick, and foot pedals, significantly improving the consistency of body sensation, time synchronization, and training realism across multiple sensing points while reducing the risk of single-channel saturation. Attached Figure Description

[0011] The accompanying drawings, which are included to provide a further understanding of embodiments of the invention and form part of this application, do not constitute a limitation thereof. In the drawings: Figure 1 This is a schematic diagram of the execution flow of a multi-actuator vibration coordinated control method for a flight simulator provided in Embodiment 1 of the present invention. Detailed Implementation

[0012] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to embodiments. The illustrative embodiments and descriptions of this invention are for illustrative purposes only and are not intended to limit the invention. The embodiments described below are some, but not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0013] In the following description, numerous specific details are set forth to provide a thorough understanding of the invention. However, it will be apparent to those skilled in the art that these specific details are not necessary to practice the invention. In other embodiments, well-known structures, materials, or methods are not specifically described to avoid obscuring the invention. Unless otherwise specified, the materials, instruments, and reagents used in the following embodiments are commercially available. Unless otherwise specified, the techniques used in the embodiments are conventional methods well known to those skilled in the art.

[0014] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0015] Example 1: This example provides a multi-actuator vibration coordinated control method for a flight simulator, implemented based on the existing full-motion flight simulator system architecture. The existing full-motion flight simulator system architecture includes: 1. Flight simulation host, used to output aircraft flight attitude information, flight status information and vibration trigger event information; 2. A six-degree-of-freedom motion platform and its corresponding servo drivers are used to generate low-frequency attitude motion and vibration; 3. Local vibration actuators, including: seat vibration actuators, joystick vibration actuators, and foot pedal vibration actuators; 4. Multi-point vibration sensors, including: acceleration sensors arranged in the seat cushion, backrest, foot pedal and control lever grip; 5. Multimodal state sensors, including: actuator cylinder displacement sensor.

[0016] Based on the aforementioned full-motion flight simulator system, this method cyclically executes a control link consisting of "vibration source signal input, target vibration response construction, vibration resource status assessment, vibration excitation collaborative optimization allocation, and vibration command execution" within each control cycle, thereby forming a control method based on "human-machine sympathetic consistency".

[0017] In the control link described above: 1. Vibration source signal input refers to: generating low-frequency attitude commands for the six-degree-of-freedom motion platform based on the flight attitude information, flight status information and vibration event information provided by the flight simulation host, and searching for and generating virtual vibration source signals from the vibration parameter library.

[0018] 2. Target vibration response construction refers to mapping virtual vibration source signals to multiple sensing points such as seat cushions, backrests, foot pedals, and joystick grips based on the structural relationship between the aircraft body and the cabin, thereby constructing a multi-sensor point target vibration response.

[0019] 3. Vibration resource status assessment refers to: based on the vibration excitation of the previous control cycle and the vibration response measured at multiple sensing points, correcting the human-machine sympathetic model, and estimating the vibration resource status of each vibration actuator based on the position of the actuator cylinder.

[0020] 4. Vibration excitation collaborative optimization allocation refers to solving a weighted optimization problem in the frequency domain that minimizes the somatosensory error of multiple sensing points, and solving the vibration excitation allocation of each vibration actuator in each frequency band under the amplitude constraints given by the vibration resource state.

[0021] 5. Vibration command execution refers to: converting frequency domain vibration excitation into time domain signals, realizing frequency domain separation and frequency domain superposition of low-frequency attitude and high-frequency vibration for the six-degree-of-freedom motion platform channel, directly outputting vibration commands to each vibration actuator, and controlling each vibration actuator to synchronously execute vibration commands at the same control cycle boundary.

[0022] Corresponding to the control link described above, this embodiment provides a multi-actuator vibration coordinated control method for a flight simulator, which executes the following within each control cycle: Figure 1 The following steps are shown: Step 1: Obtain flight attitude information, flight status information, and vibration event information output by the flight simulation host; generate low-frequency attitude commands for the six-degree-of-freedom motion platform based on the flight attitude parameters and flight status parameters; match vibration parameters from a preset vibration parameter library according to the flight event information, and convert the vibration parameters into virtual vibration source signals.

[0023] The purpose of this step is to acquire the latest flight attitude information, flight status information, and vibration event information in each control cycle, and to provide the six-degree-of-freedom motion platform with low-frequency attitude commands that match the current flight status information; at the same time, based on the flight attitude information, flight status information, and vibration event information, to generate a virtual vibration source signal consistent with the real aircraft, and to provide raw data for the subsequent construction of the target vibration response of multiple sensing points and the coordinated allocation of vibration excitation of each vibration actuator in each frequency band of the virtual vibration source signal.

[0024] The specific implementation method for this step is as follows: Step 1.1: Convert the flight attitude parameters and flight state parameters into low-frequency attitude commands for the six-degree-of-freedom motion platform.

[0025] By receiving and processing data packets sent by the flight simulation host at 60Hz or other set frequencies, flight attitude parameters, flight state parameters, and vibration trigger event information are obtained. The flight attitude parameters include pitch angle, roll angle, and yaw angle; the flight state parameters include acceleration, airspeed, altitude, and angle of attack; and the vibration trigger event information includes landing gear status, turbulence level, flap status, and stall warning.

[0026] For the collected parameters: First, based on the relationship between flight mechanics and kinematics, the flight attitude parameters and flight state parameters are converted into six-degree-of-freedom pose in the coordinate system of the six-degree-of-freedom motion platform; then, the high-frequency components in the six-degree-of-freedom pose are filtered out by a low-pass filter to obtain the low-frequency attitude command of the six-degree-of-freedom motion platform. This low-frequency attitude command is used to control the six-degree-of-freedom motion platform to perform smooth attitude motion.

[0027] It should be noted that the above-mentioned generation of six-DOF pose and conversion of six-DOF pose into low-frequency attitude commands are existing technologies. For details, please refer to the following technical documents: (1) Boeing’s official maintenance manual for the 737 flight simulator describes in detail the specific steps of “flight status parameters, platform attitude calculation, and low-pass filtering (cutoff frequency is usually 5-10Hz)” in the “Motion System Control Logic” chapter.

[0028] (2) The paper “Research on Attitude Control Algorithm of Six-DOF Platform of Full-Motion Flight Simulator” published in Volume 39 of the Journal of Aeronautics in 2018 details the kinematic transformation matrix of “flight attitude angle (pitch, roll) and platform six-DOF pose (X / Y / Z translation, α / β / γ rotation)” and verifies the application effect of “Butterworth low-pass filter (cutoff frequency 8Hz)” in attitude command smoothing.

[0029] (3) The Master's thesis of Nanjing University of Aeronautics and Astronautics in 2022, "Research on the Coordinated Control Technology of Motion and Vibration of Full-Motion Flight Simulator", Chapter 3 "Design of Low-Frequency Attitude Command Generation Module" describes in detail the code implementation logic of flight simulation host data reception, attitude calculation, low-pass filtering (using Chebyshev Type I filter) and command output.

[0030] Step 1.2: Select the vibration parameter corresponding to the vibration triggering event information from the vibration parameter library, and define the vibration parameter as a virtual vibration source signal consistent with the real aircraft.

[0031] (1) Vibration parameter library The vibration parameter library is an existing technical resource, and can be directly referenced from the "Standardized Vibration Parameters" in the following industry standard manuals: 1) The appendix of RTCA DO-183C, "Performance Standards for Full-Motion Flight Simulators", clearly gives the vibration PSD range for typical scenarios such as "turbulence, engine steady-state operation, and landing gear retraction and extension" (such as the upper limit of vertical turbulence PSD in the 1-10Hz frequency band during cruise phase), which is the primary basis for global flight simulator manufacturers to build vibration parameter libraries.

[0032] 2) Boeing / Airbus's "Aircraft Flight Load and Vibration Manual" details the dominant frequency distribution of fuselage vibration at different engine speeds and the frequency range of wing section flutter during stall. These data can be directly entered into the vibration parameter library to match the simulation requirements of the corresponding aircraft model.

[0033] 3) The Civil Aviation Administration of China's CCAR-60 technical bulletin for domestically produced simulators clarifies the "effective range of acceleration values ​​for seat vibration during takeoff / landing," providing a basis for the adaptation of vibration parameter libraries.

[0034] 4) Vibration characteristic data can also be extracted from publicly available literature and datasets to supplement the vibration parameter library. For example, the appendix of Nanjing University of Aeronautics and Astronautics' "Research on Vibration Control of Multi-Actuator in Flight Simulator" (2022) publishes a "Vibration Parameter Table containing 12 types of flight scenarios" (including PSD templates, dominant frequency, and amplitude ratio); the article "Research on Vibration Transmission Characteristics of Full-Motion Flight Simulator" in the "Acta Aeronautica Sinica" gives the "transmission coefficient of the vibration of the fuselage center of mass to the seat and control stick" (e.g., the amplitude of engine vibration on the control stick is 1.2 times that of the fuselage), etc.

[0035] (2) Select the vibration parameter corresponding to the vibration triggering event information from the vibration parameter library.

[0036] It should be noted that defining vibration parameters as virtual vibration source signals is essentially "vibration modeling based on flight scenarios." Selecting vibration parameters from a vibration parameter library is a prerequisite for generating virtual vibration source signals. Specifically, based on vibration triggering events such as landing gear status, turbulence level, flap status, and stall warnings, preset vibration parameters are called from the vibration parameter library. Random signal generation techniques (such as filtered white noise and narrowband sine synthesis) are then used to construct virtual vibration source signals consistent with those of a real aircraft. For example, under moderate turbulence conditions, a preset vertical random vibration PSD template of the airframe's center of mass is selected; at a certain engine speed, the corresponding dominant frequency and harmonic frequency narrowband vibration parameters are selected; when the angle of attack approaches stall and a stall warning occurs, a high-frequency narrowband vibration component is selected.

[0037] (3) Define the vibration parameters as virtual vibration source signals that are consistent with the real aircraft.

[0038] The vibration parameters from the above different sources are defined as different virtual vibration source signals. For example, the PSD template is converted into a random vibration signal by filtering white noise; a narrowband sine or narrowband random vibration signal is generated based on the main frequency and harmonic frequency narrowband vibration parameters; and a simulated airfoil or tail fin flutter signal is generated based on the high-frequency narrowband vibration component.

[0039] Similarly, generating virtual vibration source signals is also an existing technology, and industry standard manuals can be consulted for further information. 1) Boeing's official "Boeing 737 Flight Simulator Maintenance Manual" provides the vibration frequency parameters and virtual vibration source synthesis method at different engine speeds in the "Vibration Simulation Module" section.

[0040] 2) The article “PSD matching generation method for turbulent virtual vibration source of flight simulator” published in Volume 38 of Vibration and Shock in 2019 discloses “the generation steps of turbulent virtual vibration source based on filtered white noise”.

[0041] 3) The Master's thesis of Nanjing University of Aeronautics and Astronautics in 2022, "Research on Cooperative Control Technology of Motion and Vibration of Full-Motion Flight Simulator", Chapter 4 "Modeling of Virtual Vibration Sources" gives the generation algorithms and MATLAB simulation code for three types of virtual sources: turbulence, stall chattering and engine vibration.

[0042] In summary, step 1, as the starting point of the entire control chain, outputs low-frequency attitude commands and virtual vibration source signals, which serve as the foundational input data for constructing the target vibration response and generating vibration excitation at multiple sensing points in subsequent steps. The low-frequency attitude commands and virtual vibration source signals generated in step 1 ensure that the low-frequency attitude changes of the six-degree-of-freedom motion platform are consistent with the actual aircraft attitude, free from vibration signal interference, and guarantee that the spectral characteristics and intensity of the virtual vibration source match the current flight state and events. This provides a physical vibration source for subsequent motion-sensing control, improving the realism of the simulation.

[0043] Step 2: Based on the vibration transmission relationship between the body structure and the cabin structure, the virtual vibration source signal is mapped to multiple sensing points inside the cabin, and the target vibration response vector of each sensing point in different frequency bands is established; combined with ergonomic characteristics, a sensing weight matrix corresponding to multiple sensing points in different frequency bands is established.

[0044] The purpose of this step is to map the virtual vibration source signal at the airframe level into the target vibration response that the pilot can feel at multiple specific sensory locations (such as seat cushion, backrest, foot, hand, etc.), and to combine ergonomics to determine the weight of different sensory locations and frequency bands, forming a quantitative control target "oriented towards human body sensation".

[0045] The specific implementation method for this step is as follows: Step 2.1: Establish the vibration transmission relationship between the airframe structure and the cabin structure.

[0046] The purpose of this step is to provide a set of signal transmission rules for distributing virtual vibration source signals to each sensing point, based on the inherent laws governing the transmission of virtual vibration source signals from the aircraft body to various parts of the cockpit (such as seats and control sticks), combined with multi-dimensional measured data collected during real aircraft test flights. According to these rules, the virtual vibration source signals can be projected onto each sensing point, thereby obtaining the target vibration response at each sensing point in the frequency domain. This allows the pilot to experience vibrations consistent with real flight at each sensing location. The multi-dimensional measured data collected during test flights includes: vibration excitation of various parts of the aircraft body (such as the dominant vibration frequency of the engine mounts and the vibration amplitude of the aircraft's center of mass), vibration responses at various sensing points within the cockpit (such as the acceleration and frequency of the seats and control sticks), and flight scenario parameters (such as turbulence level, engine speed, and whether a stall has occurred).

[0047] The vibration transmission relationships described in this embodiment include: distribution path mapping relationship, vibration amplitude proportion mapping relationship, and vibration energy proportion mapping relationship. Step 2.1 includes: Step 2.1.1: Generate the distribution paths of different virtual vibration source signals and establish the distribution path relationships.

[0048] The core allocation criteria include: the physical characteristics of the virtual vibration source signal, the laws of human perception, and ergonomics.

[0049] Basis 1: Physical characteristics of virtual vibration source signals.

[0050] The different frequencies and generation mechanisms of different virtual vibration source signals determine their different transmission paths and sensing locations on a real aircraft. This is the underlying physical basis for allocating virtual source vibration signals.

[0051] From the perspective of frequency characteristics: low-frequency vibrations (1-50Hz, such as turbulence and landing gear ground impact) are easily transmitted through rigid structures such as the fuselage frame and floor; high-frequency vibrations (200-500Hz, such as engine vibration and stall vibration) are easily transmitted through slender / rigid structures such as the control stick and instrument panel.

[0052] From the perspective of generation mechanism: engine vibration originates from rotating parts, and the transmission path covers: engine mount → fuselage → control stick / instrument panel; turbulence vibration originates from fuselage turbulence, and the transmission path covers: fuselage as a whole → seat / foot pedals; stall flutter originates from airflow separation on the wing, and the transmission path is close to the wing → fuselage → seat back / control stick.

[0053] Basis 2: Human Perception Laws and Ergonomics Based on the differences in human sensitivity to vibration signals at different body parts and frequencies, virtual vibration source signals are preferentially assigned to "sensitive areas" to ensure clear tactile sensation and conformity to physiological habits. Specifically, the laws of human perception can be referenced in standards such as ISO 2631-1, which discloses that "the human body has a lower perception threshold for low-frequency vibrations of 1-8Hz in the buttocks and for mid-frequency vibrations of 8-16Hz in the hands...". Sensitivity analysis is then performed on corresponding body parts: the buttocks (seat) and soles of the feet (pedal) are sensitive to low-frequency vibrations (bumps); the hands (joystick) are sensitive to mid-to-high-frequency vibrations (shaking).

[0054] Based on criteria 1 and 2 above, the distribution paths of different virtual vibration source signals are shown in Table 1 below.

[0055] Table 1 shows the distribution path mapping relationship of signals from different virtual vibration sources: Virtual vibration source type Priority allocation of perception points Allocation basis Turbulent vibration (characteristics: low frequency, wideband random) Seat cushions, footrests 1. Turbulence is the overall shaking of the machine, and low-frequency vibrations are easily transmitted to the buttocks and feet through the floor; 2. These two parts are sensitive to low-frequency vibrations and can clearly perceive the intensity of the shaking. Engine vibration (characteristics: high frequency, narrow-band sinusoidal) joystick grip, dashboard 1. Engine vibration is a high-frequency rotational excitation, which is transmitted to the control lever and instrument panel through a rigid structure and attenuates less; 2. The hands are sensitive to high-frequency vibration and can sense changes in engine speed (such as increased vibration when the speed increases). Stall chatter (characteristics: high-frequency narrowband, sudden) joystick grip, seat back 1. Stall flutter originates from airflow separation on the wing and is transmitted through the seat back and control stick. 2. The combined perception of the hands (gripping the stick) and back (touching the seat) can simulate the warning experience of "stick flutter + back flutter" during a real stall. Landing gear retraction / grounding vibration (characteristics: low frequency, impact type) Foot pedals, seat cushions 1. Landing gear vibration is transmitted directly to the feet (foot pedals) and buttocks (seat) through the fuselage floor, and these two parts are the most strongly felt during actual flight; 2. Impact vibration requires a large torque output, and the torque margin of the six-degree-of-freedom platform and seat actuators meets the requirements to avoid local actuator saturation. In addition, the allocation path for different virtual vibration source signals can also be referenced in the patent document with publication number CN117413243A, which further refines the allocation basis, including "the orientation of the vibration source, the distance from the oscillator, and the physical characteristics of the propagation path", and also clarifies "to define the oscillator combination and the sensing origin separately for different body parts of the human body".

[0056] Step 2.1.2: Based on the allocation path mapping table, generate the proportion of signal vibration amplitude of different frequency bands of different virtual vibration source signals mapped to each sensing point, and establish a vibration amplitude proportion mapping table.

[0057] Includes the following steps: Step 2.1.2.1: Establish the transmission coefficient matrix of the virtual vibration source signal from the body structure to the cabin structure.

[0058] The transmission coefficient matrix is ​​used to characterize the complete link of the "variation law of vibration amplitude, frequency and phase" formed when the "external vibration source" (such as turbulence, engine operation, landing gear retraction and extension) is transmitted through the airframe structure (fuselage frame, skin, etc.) to the various vibration mechanisms in the cabin (seat, control stick, foot pedal, instrument panel, etc.). That is, the transmission process of the vibration signal at the airframe level after attenuation, amplification or change of characteristics is felt by the pilot's various sensory parts (hips, hands, feet, etc.) in the cabin.

[0059] Numerous existing documents disclose methods for constructing the aforementioned transfer coefficient matrix, which can be summarized as follows: S1: Analyze the transmission path.

[0060] For the actual aircraft model corresponding to the simulator, the transmission path of the core vibrations is clearly defined. For example, the transmission path of engine vibration signals is: engine mount → fuselage frame → cabin floor / control stick connecting rod → seat bracket / foot pedal mounting base → seat / control stick / foot pedal; the transmission path of turbulence vibration signals is: fuselage center of mass → fuselage skin / floor beam → various cabin structures (seat, instrument panel); the transmission path of stall flutter signals is: wing / tail → fuselage frame → control stick / seat back.

[0061] S2: Define the sensing points and associated core parameters.

[0062] The sensing points described in this embodiment include: the center of the seat cushion, the middle of the backrest, the left and right foot pedals, the joystick grip, and the instrument panel. The core parameters associated with each sensing point include: the amplitude ratio in the frequency domain, the PSD transmission coefficient; the phase difference in the time domain; and the transmission difference in the vibration direction (vertical and horizontal).

[0063] S3: Based on the physical data of real aircraft, the basic data used to construct the transfer relationship is obtained by reusing public resources and supplementing the measured data.

[0064] Reusable publicly available data includes: Industry standards and aircraft manuals: For example, the appendix of RTCAO-183C (Full Motion Flight Simulator Performance Standard) clearly gives the vibration transmission ratio of "airframe-cabin interior" under scenarios such as "turbulence and engine steady-state operation" (e.g., vertical turbulence vibration of the airframe center of mass, the amplitude ratio of seat cushion to foot pedal is 1:0.8); Boeing / Airbus's "Aircraft Vibration Manual" (e.g., Chapter 21 of the Boeing 737 AMM Manual) discloses the high-frequency vibration transmission coefficient of "fuselage-control stick" at different engine speeds.

[0065] Academic literature and datasets: The study on the vibration transfer function of Boeing 737 fuselage-cabin provides frequency response function (FRF) data (i.e., transfer efficiency at different frequencies); Case Western Reserve University (CWRU) and NASA have publicly available flight vibration datasets that can extract synchronous vibration data of "airframe measuring points" and "cabin measuring points" for deriving the transfer relationship.

[0066] Simulator toolkits: The flight simulation modules of dSPACE and LabVIEW have pre-set "vibration transmission parameter templates" for typical aircraft models (such as "general transmission coefficient table for civil passenger aircraft"), which can be used directly as initial references.

[0067] Additional measured data could include: installing accelerometers (sampling frequency ≥ 1 kHz) at key parts of the airframe (airframe center of mass, near engine mounts) and at various sensing points inside the cabin, and synchronously collecting vibration data under typical scenarios (such as idling, takeoff, turbulence, stall); performing frequency domain analysis on the collected data (such as converting the time domain signal to frequency domain PSD through FFT), calculating "cabin sensing point PSD / airframe measuring point PSD", and obtaining the transmission coefficient for each frequency band (such as a transmission coefficient of 0.9 at 10 Hz and a transmission coefficient of 0.6 at 100 Hz).

[0068] S4: Construct the transfer coefficient matrix.

[0069] Based on the acquired basic data, the scattered data is transformed into a transfer coefficient matrix that can be called by the simulator in real time through "classification modeling".

[0070] The classification modeling refers to establishing vibration signal transmission coefficients for multiple vibration scenarios, multiple vibration signal frequency bands, and multiple sensing points according to "vibration scenario (such as turbulence, engine, stall and chattering), frequency band (such as 1-10Hz, 10-50Hz, 50-200Hz, 200-500Hz), and sensing point," and directly storing the signal transmission coefficient matrix in the system for later use. Taking the turbulence scenario as an example, the constructed signal transmission coefficient matrix is ​​shown in Table 2 below.

[0071] Table 2 shows the transfer coefficient matrix under turbulent flow scenarios: frequency band Seat cushion Seat back Foot pedal joystick Dashboard 1-10Hz 1.0 0.9 0.8 0.5 0.4 10-50Hz 0.9 0.8 0.7 0.6 0.5 50-200Hz 0.7 0.6 0.5 0.8 0.7 200-500Hz 0.4 0.5 0.3 0.9 0.8 In Table 2, the signal transmission coefficient of the seat cushion is 1.0 in the signal frequency range of 1-10Hz, which means that when the virtual vibration source signal is transmitted to the sensing point of the seat cushion in the turbulent scenario, the virtual vibration source signal remains unchanged; in the signal frequency range of 1-10Hz, the signal transmission coefficient of the seat back is 0.9, which means that when the virtual vibration source signal is transmitted to the sensing point of the seat back in the turbulent scenario, the amplitude of the virtual vibration source signal becomes 0.9 times the amplitude of the original virtual vibration source signal.

[0072] For scenarios such as engine vibration and stall / bounce, corresponding transfer coefficient matrices can be established according to the method described in step 2.1.2.1 above. For engine vibration scenarios, the "engine transfer coefficient matrix" is called; for stall / bounce scenarios, the "stall transfer coefficient matrix" is called.

[0073] S5: Associate each transfer coefficient matrix with the corresponding flight scenario according to the vibration source type, and store the transfer coefficient matrix of each flight scenario in the simulator's vibration parameter library. Step 2.1.2.2: Based on the allocation path mapping relationship and the transfer coefficient matrix, obtain the proportion of vibration amplitude of each frequency band of the virtual vibration source signal mapped to each sensing point.

[0074] First, based on the types of virtual vibration source signals contained in the multi-dimensional measured data collected during the test flight, the allocation path relationship table is queried to determine the multiple sensing points to be allocated.

[0075] For example, multi-dimensional measured data shows that "the vertical turbulent vibration amplitude of the body's center of mass is 1.0 (reference value)". By querying the distribution path relationship table (as shown in Table 1 above), it can be seen that this vertical turbulent vibration signal corresponds to two sensing points, namely the seat cushion (sensing point 1) and the foot pedal (sensing point 2).

[0076] Then, based on the signal type of the virtual vibration source, the corresponding transmission coefficient relationship matrix is ​​queried to obtain the vibration amplitude of each sensing point to be assigned.

[0077] For example, by querying the transmission coefficient relationship matrix under turbulence scenarios (as shown in Table 2 above), it can be seen that for the 1-10Hz frequency band: the transmission coefficient of the seat cushion (sensing point 1) is 0.9, which means that the vibration amplitude of the vertical turbulence vibration signal distributed to the seat cushion (sensing point 1) = the vibration amplitude of the vertical turbulence vibration signal × 0.9; the transmission coefficient of the foot pedal (sensing point 2) is 0.8, which means that the vibration amplitude of the vertical turbulence vibration signal distributed to the foot pedal (sensing point 2) = the vibration amplitude of the vertical turbulence vibration signal × 0.8.

[0078] Step 2.1.3: Based on the allocation path mapping relationship, generate the vibration energy ratio of each frequency band of different virtual vibration source signals mapped to each sensing point, and establish a vibration energy ratio mapping relationship table.

[0079] For each vibration scenario: First, vibration signals at each sensing point are collected using accelerometers installed at each sensing point.

[0080] Then, an FFT transformation is performed on the vibration signal at each sensing point to obtain the power spectral density (PSD) integral for each frequency band (e.g., 1-10Hz, 10-50Hz, 50-200Hz, 200-500Hz) at each sensing point. The power spectral density integral for each frequency band is the vibration energy (m²) for that frequency band. 2 / s 3 ).

[0081] Next, for each frequency band, the frequency band weight (vibration energy percentage) of each sensing point is calculated.

[0082] For example, for the 1-10Hz frequency band, the frequency band weight of sensing point 1 = the PSD integral of sensing point 1 in the 1-10Hz frequency band ÷ the sum of the PSD integrals of sensing point 1 in each frequency band.

[0083] For example: According to calculations, the PSD integrals of the seat cushion (sensor point 1) in the 1-10Hz frequency band, 10-50Hz frequency band, 50-200Hz frequency band, and 200-500Hz frequency band are 4.5, 3.5, 1.0, and 1.0, respectively. Therefore, the frequency band weight of the seat cushion (sensor point 1) in the 1-10Hz frequency band is 4.5 ÷ (4.5 + 3.5 + 1.0 + 1.0) = 45%.

[0084] The vibration transmission relationships generated by steps 2.1.1 to 2.1.3 above can clarify the distribution paths of different virtual vibration source signals, as well as the proportion of vibration amplitude and vibration energy of each frequency band of the virtual vibration source signal mapped to each sensing point on each distribution path.

[0085] Step 2.2: Based on the vibration transmission relationship, map the virtual vibration source signal to each sensing point according to the frequency band to obtain the target vibration response of each sensing point in each frequency band.

[0086] Target vibration response refers to the "ideal vibration state" that is pre-set for each sensing point (such as the seat or control stick), taking into account the flight scenario, human sensitivity, and real flight patterns. It serves as the "target template" for subsequent allocation of vibration excitation and execution of vibration commands. The core includes three dimensions: "frequency band, amplitude, and energy," ensuring that the vibration of each part conforms to the real flight experience.

[0087] Step 2.3: Combine the target vibration response of each sensing point into a target vibration response vector according to the frequency band.

[0088] The purpose of this step is to organize the target vibration response of each sensing point in different frequency bands into an ordered "target vibration response vector" according to the dimension of "sensing point + frequency band", so that the system can call up the vibration target response of all sensing points and the entire frequency band at once.

[0089] Examples are given below: Taking vibration amplitude as an example, assuming the system has 5 sensing points and 3 frequency bands, the target vibration response set is shown in Table 3.

[0090] Table 3 is a dataset of the target vibration response (data is for illustrative purposes only): Serial Number Corresponding dimensions (sensing point + frequency band) Vibration amplitude (m / s²) 1 Seat cushion +1-50Hz 0.45 2 Seat cushion +50-200Hz 0.15 3 Seat cushion +200-500Hz 0.05 4 Seat backrest +1-50Hz 0.40 5 Seat backrest +50-200Hz 0.12 6 Seat backrest +200-500Hz 0.08 7 Joystick +1-50Hz 0.10 8 Joystick +50-200Hz 0.30 9 Joystick +200-500Hz 0.20 ... ... (other sensing points + frequency bands) ... Arrange the vibration amplitudes in Table 3 in sequential order to obtain the multi-sensor point target vibration response vector regarding vibration amplitude: [0.45, 0.15, 0.05, 0.40, 0.12, 0.08, 0.10, 0.30, 0.20, ...]. Similarly, a multi-sensor point target vibration response vector regarding vibration energy can be established.

[0091] Step 2.4: Assign sensing weights to the target vibration response of each frequency band of the virtual vibration source signal at each sensing point based on ergonomic characteristics, and establish a sensing weight matrix.

[0092] The purpose of this step is to develop a "perception weight matrix" by combining specific flight training subjects (such as takeoff, stall, and cruise) with the differences in human sensitivity to vibrations at different parts and frequencies. Using a structured numerical table, the perception weight of each sensing point (such as the seat or control stick) in each frequency band (such as 1-50Hz, 200-500Hz) of the virtual vibration source signal is clearly defined, so that the vibration distribution is more in line with training needs and human perception patterns.

[0093] The perception weight matrix is ​​a two-dimensional table. The rows and columns correspond to "sensory points" and "frequency bands," respectively. The values ​​in the cells (usually between 0 and 1) represent the weights. The closer the weight value is to 1, the more important the vibration of that "sensory point + frequency band" is to the training effect and the realism of the haptic feedback, and the more vibration energy is allocated to it. The closer the value is to 0, the lower the importance, and the less energy is allocated. An example of a perception weight matrix is ​​shown in Table 4 below.

[0094] Table 4 is the perception weight matrix: Sensing point / frequency band 1-50Hz (low frequency) 50-200Hz (Medium Frequency) 200-500Hz (high frequency) Seat cushion 0.9 0.3 0.1 Foot pedal 0.8 0.2 0.05 Seat back 0.6 0.2 0.1 joystick grip 0.3 0.4 0.2 Dashboard 0.2 0.1 0.05 It should be noted that the human body's sensitivity to vibrations in different parts and frequency bands is an objective physiological characteristic, which has been quantitatively defined by international standards and can be directly used as a basis for weighting. The specific method is as follows: Step 2.4.1: Refer to ISO2631-1 (Human Body Vibration Evaluation Standard) and ISO5349-1 (Hand Vibration Evaluation Standard) to obtain the objective sensitivity curve of "location-frequency band".

[0095] The sensitivity curve is an internationally standardized "frequency-sensitivity" relationship curve (the horizontal axis represents the vibration frequency, and the vertical axis represents the sensitivity coefficient) obtained through numerous human trials. The higher the curve, the more sensitive the human body is to vibrations at that frequency. For example, the sensitivity curve for the buttocks peaks at 1-8Hz (low frequency), while the curve for the hand is more pronounced at 200-500Hz (high frequency), which aligns with human physiological patterns.

[0096] Step 2.4.2: Convert the sensitivity curve into normalized weights.

[0097] The sensitivity coefficients for different sensing points and standards have different numerical ranges, making direct horizontal comparison and weight calculation impossible. By normalizing the sensitivity coefficients from different ranges, they are uniformly mapped to the 0-1 interval, giving "sensitivity" a unified quantitative standard.

[0098] Taking "seat cushion (buttocks)" and "joystick (hands)" as examples, and referring to the ISO2631-1 standard curve, the steps are as follows: First, read the sensitivity coefficient corresponding to each "sensing point + frequency band" from the standard sensitivity curve.

[0099] The sensitivity coefficient can be obtained directly from the frequency-sensitivity relationship curve, as shown in Table 5. The sensitivity coefficient has been verified through human trials.

[0100] Table 5 shows the correspondence between "sensing point + frequency band" and sensitivity coefficient: Sensing point + frequency band Sensitivity coefficient Seat cushion +1-50Hz 1.0 Seat cushion +200-500Hz 0.3 Joystick +1-50Hz 0.4 Joystick +200-500Hz 0.9 Then, calculate the sum of sensitivity coefficients at the same sensing point.

[0101] For each sensing point, the sensitivity coefficients of all its frequency bands are summed to obtain the total coefficient for that sensing point, ensuring that the sum of the weights within the same sensing point is 1, thus avoiding allocation conflicts. For example, the total coefficient of a seat cushion = 1.0 (1-50Hz) + 0.3 (200-500Hz) = 1.3; the total coefficient of a joystick = 0.4 (1-50Hz) + 0.9 (200-500Hz) = 1.3.

[0102] Finally, the weights are calculated using normalization.

[0103] The weight of "sensing point + frequency band" = sensitivity coefficient of the combination ÷ sum of sensitivity coefficients of the corresponding sensing points (the result automatically falls in the 0-1 range). Based on Table 5, the sensitivity curve is converted into normalized weights as shown in Table 6.

[0104] Table 6 shows the correspondence between "sensing point + frequency band" and normalized sensitivity coefficient: Sensing point + frequency band Sensitivity coefficient Sum of sensing point coefficients Normalized weights (retaining one decimal place) Seat cushion +1-50Hz 1.0 1.3 1.0÷1.3≈0.8 Seat seat +200-500Hz 0.3 1.3 0.3÷1.3≈0.2 Joystick +1-50Hz 0.4 1.3 0.4÷1.3≈0.3 Joystick +200-500Hz 0.9 1.3 0.9÷1.3≈0.7 In summary, step 2 takes the virtual vibration source generated in step 1 as input and outputs the target vibration response set and perception weight matrix of multi-sensor points under each vibration scenario. This transforms the abstract body vibration characteristics into multi-sensor point targets that are directly related to the pilot's actual perception, making the control target closer to the training requirements. Subsequent optimization allocation is no longer only aimed at single-point acceleration or PSD, but is optimized around the overall body sensation of multi-sensor points, thereby improving the consistency of the overall body sensation.

[0105] Step 3: Based on the vibration excitation vector of the previous control cycle and the measured vibration response signal of the current control cycle, the frequency response matrix describing the vibration excitation transmitted to the sensing point is corrected online; according to the stroke margin of the actuator cylinder of each vibration actuator, the maximum available amplitude of each vibration actuator in each frequency band is determined, and the vibration resource status is generated.

[0106] The purpose of this step is to combine the vibration excitation signal from the previous control cycle with the measured vibration response signal from the current control cycle. On the one hand, it corrects the frequency response matrix, which reflects the transmission value of the vibration excitation signal at multiple sensing points, online to ensure that the frequency response reflects the current state of the equipment and structure. On the other hand, it evaluates the travel margin of each vibration actuator to form the vibration resource status of the current control cycle, providing reliable constraints for the subsequent coordinated allocation of vibration excitation signals.

[0107] The specific implementation method for this step is as follows: Step 3.1: Drive each vibration actuator with the vibration excitation signal from the previous control cycle, and collect the vibration response signal of each sensing point in the current control cycle. Calculate the frequency transmission characteristics of the vibration excitation signal to each sensing point, and finally integrate them into an initial frequency response matrix to provide an objective basis for subsequent precise vibration control.

[0108] 1. Acquire vibration excitation signals The vibration excitation signal described in this embodiment uses either a "scanning sine wave signal" or a "multi-frequency excitation signal." These two signals are standard inputs for vibration system calibration. The scanning sine wave signal is a signal whose frequency continuously varies within a target range (e.g., 0.01-500Hz), allowing for testing of the system response at each frequency point. The multi-frequency excitation signal simultaneously contains multiple frequency components, enabling rapid coverage of the entire frequency band and improving calibration efficiency.

[0109] 2. Driver object The vibration excitation signal drives various vibration actuators, including: six-degree-of-freedom platforms and local vibration actuators (seats, backrests, joysticks, and foot pedals).

[0110] 3. Driving method For each actuator: input a vibration excitation signal separately (while keeping other vibrating actuators stationary) to ensure the uniqueness of the test results.

[0111] 4. Acquire actual vibration response signals from multiple sensing points in the frequency domain. Accelerometers are pre-installed at sensing points on each local vibration actuator to synchronously collect time-domain data of the vibration response signals output from each sensing point. Fourier transform (FFT) is then used to convert the time-domain data into frequency-domain data, obtaining the vibration amplitude and phase information at different frequencies for each sensing point. The maximum amplitude within each frequency band is extracted to obtain the amplitude for each frequency band. For example, after Fourier transforming the actual vibration response signal, the maximum amplitude within each frequency band is extracted, resulting in an amplitude of 0.62 for the 1-50Hz band and 0.15 for the 200-500Hz band.

[0112] 5. Obtain the frequency response of each vibration transmission channel across the entire frequency band. (1) Vibration transmission channel The vibration transmission channel described in this embodiment refers to the transmission path from the actuator to the sensing point. For example: six-degree-of-freedom platform → seat cushion, joystick actuator → grip.

[0113] (2) Frequency response The frequency response described in this embodiment refers to the quotient between the vibration response signal output by the sensing point and the vibration excitation signal input to the actuator at a certain frequency. That is, frequency response = vibration response signal ÷ vibration excitation signal. It directly reflects the efficiency of the actuator's vibration transmission to the sensing point at that frequency.

[0114] (3) Obtain the frequency response across the entire frequency band For each vibration transmission channel, the frequency response in each frequency band is used to obtain the corresponding transmission characteristic curve for each vibration transmission channel. If the amplitude of the frequency response is greater than 1, it indicates that the vibration transmission is amplified at that frequency; if the amplitude of the frequency response is less than 1, it indicates that the vibration is attenuated at that frequency.

[0115] 6. Construct the initial frequency response matrix The frequency responses of all vibration transmission channels across the entire frequency band are organized into a frequency response matrix. Each element in the frequency response matrix corresponds to the frequency response of a specific vibration transmission channel at a specific frequency, forming an initial frequency response matrix that includes the actuator, sensing point, and frequency response.

[0116] For example: Assuming the system has 2 actuators and 2 sensing points, the frequency response matrix at a certain frequency is shown in Table 7 below.

[0117] Table 7 is the frequency response matrix table: Execution agency / sensing point Seat cushion joystick grip Six Degrees of Freedom Platform 0.8 0.3 joystick actuator 0.2 0.9 The frequency response matrix shown in Table 7 indicates that the efficiency of the vibration transmission from the six-DOF platform to the seat cushion is 0.8, while the efficiency to the joystick grip is only 0.3; the efficiency of the vibration transmission from the joystick actuator to the grip is 0.9, while the efficiency to the seat cushion is only 0.2. This suggests that the six-DOF platform is more suitable for driving seat vibration, while the joystick actuator is more suitable for driving grip vibration.

[0118] By constructing a frequency response matrix, a realistic basis is provided for subsequent vibration allocation. The process of constructing the frequency response matrix involves standardized excitation testing to quantify the vibration transmission capability of the vibration excitation signal through the vibration actuator to each sensing point, ultimately forming a "transmission characteristic list" (frequency response matrix). Through this "transmission characteristic list," the objective vibration transmission characteristics from the vibration excitation signal to the sensing point can be obtained, which is the prerequisite and foundation for achieving high-precision and high-fidelity vibration control.

[0119] Step 3.2: Calculate the predicted vibration response of the current control cycle using the frequency response matrix and vibration excitation vector of the previous control cycle; collect the measured vibration response signals of each sensing point within the current control cycle and convert the measured vibration response signals into frequency domain data; compare the deviation between the predicted vibration response and the measured vibration response band by band; when the deviation of multiple consecutive control cycles exceeds a preset threshold, use the recursive least squares algorithm to iteratively update the elements of the frequency response matrix to make the predicted vibration response approximate the measured vibration response.

[0120] The purpose of this step is to offset the vibration transmission deviation caused by factors such as equipment aging, load changes, and environmental interference, and to ensure the realism of the tactile sensation during long-term operation.

[0121] By continuously comparing the difference between the predicted vibration response and the actual vibration response during flight simulation, when the predicted vibration effect and the actual effect of a certain frequency band are inconsistent for a long time, the frequency response of that frequency band is dynamically corrected using a recursive least squares algorithm, so that the vibration control always fits the current real characteristics of the equipment.

[0122] 1. Acquire vibration excitation vector The vibration excitation vector is the parameters (such as amplitude, frequency, and energy) input to the six-degree-of-freedom platform, seat vibrator, and other actuators at different frequency bands during the previous control cycle, essentially serving as an instruction to each actuator. The excitation vector of the previous control cycle is a one-dimensional array composed of the vibration excitation values ​​of each actuator during the previous control cycle. For example, the excitation vector of the previous cycle = [0.5, 0.3] represents "the vibration excitation value of the six-degree-of-freedom platform is 0.5" and "the vibration excitation value of the seat is 0.3", respectively.

[0123] The vibration excitation value is an "input control parameter" issued to each vibration actuator to quantify the "input intensity" of the vibration. The vibration excitation value is a component of the excitation vector, which is calculated as the inverse of the frequency response matrix multiplied by the target vibration response vector.

[0124] 2. Compare the predicted vibration response with the actual vibration response. (1) Predicting vibration response Predicting vibration response refers to calculating the theoretically expected vibration response based on the frequency response matrix of the current control cycle and the excitation vector of the previous control cycle.

[0125] Predicted vibration response = frequency response matrix × excitation vector.

[0126] Based on the frequency response matrix obtained in step 3.1 (shown in Table 7) and the excitation vector in this example (excitation vector of the previous cycle = [0.5, 0.3]), the following example illustrates the process: The predicted response of the seat cushion = (0.8 × 0.5) + (0.9 × 0.3) = 0.4 + 0.27 = 0.67; The predicted response of the joystick grip = (0.3 × 0.5) + (0.1 × 0.3) = 0.15 + 0.03 = 0.18; The final predicted response vector = [0.67, 0.18] indicates that, theoretically, the seat cushion should detect 67% of the vibration amplitude, and the joystick grip should detect 18% of the vibration amplitude.

[0127] (2) Comparison Logic The deviation between the predicted vibration response and the actual vibration response is obtained by comparing frequency bands one by one.

[0128] It should be noted that since the predicted vibration response and the measured vibration response can be obtained in each control cycle using the above method, the frequency band comparison described in this embodiment refers to comparing the deviation between the predicted vibration response and the measured vibration response for each frequency band over multiple consecutive control cycles. If the deviation is greater than or equal to a threshold over multiple consecutive control cycles, the frequency response matrix is ​​corrected. For example, for the 1-50Hz frequency band, if the deviation exceeds 10% over 100 consecutive control cycles, this deviation is usually caused by factors such as equipment aging (e.g., damping attenuation of seat cushions) or loose installation, and the frequency response matrix for that frequency band needs to be corrected.

[0129] 3. The frequency response matrix is ​​corrected using a recursive least squares algorithm. The recursive least squares algorithm is a parameter identification method suitable for real-time online computation. It can iteratively correct the frequency response parameters of a frequency band based on newly acquired excitation-response data.

[0130] For example, within multiple control cycles, the predicted vibration amplitude in the 1-50Hz frequency band is 0.45m / s², but the actual measured amplitude is only 0.35m / s². The least squares algorithm is used to fine-tune the frequency response parameters of this frequency band (e.g., from 0.8 to 0.9) so that the predicted vibration response in the next cycle is closer to the actual vibration response.

[0131] It should be noted that the entire process of "recording data, comparing data, and correcting parameters" described above will be executed cyclically in each control cycle, and the corrected frequency response parameters will serve as the prediction basis for the next control cycle. As the number of iterations increases, the deviation between the predicted vibration response and the measured vibration response will become smaller and smaller, eventually allowing the frequency response parameters to gradually approach the actual vibration transmission characteristics of the current equipment, rather than remaining at the initial calibrated theoretical value.

[0132] Step 3.3: Monitor the current position and stroke limit position of the actuator cylinder of each vibration actuator in real time; calculate the stroke margin; stroke margin = min(extension limit - current position, current position - shortening limit); adjust the maximum vibration amplitude of each frequency band according to preset rules, specifically including: when the stroke margin is greater than the first threshold, maintain the rated maximum vibration amplitude; when the stroke margin is between the first threshold and the second threshold, reduce the maximum vibration amplitude proportionally; when the stroke margin is less than the second threshold, limit the maximum vibration amplitude to the lower limit.

[0133] The purpose of this step is to dynamically limit the vibration amplitude of the vibration actuator by monitoring the key status parameters of the equipment and based on the stroke of the actuator cylinder of the six-degree-of-freedom motion platform, thereby determining the maximum usable amplitude of each vibration actuator in each frequency band and obtaining the vibration resource status.

[0134] Travel margin constraints are used to limit the upper limit of the maximum vibration amplitude and prevent mechanical hard limit collisions.

[0135] Key monitoring parameters: The current position and travel limit positions of the actuator, fed back by the servo drive (such as the extension / retraction limits of the actuator). Travel limit positions include: the extension limit position or the retraction limit position of the actuator.

[0136] Travel margin calculation: Travel margin = min(extension limit - current position, current position - shortening limit).

[0137] Constraint rules: The larger the stroke margin, the higher the upper limit of the allowable vibration amplitude; the smaller the stroke margin (e.g., close to the limit position), the lower the maximum vibration amplitude of the corresponding frequency band to prevent the actuator from hitting the mechanical limit and causing structural damage. Specifically: When the stroke margin ≥ the first stroke margin threshold, the maximum vibration amplitude is set as the upper limit of the vibration amplitude; when the second stroke margin threshold ≤ the stroke margin ≤ the first stroke margin threshold, the maximum vibration amplitude is reduced by the corresponding preset ratio; when the stroke margin < the second stroke margin threshold, the maximum vibration amplitude is reduced by the corresponding preset ratio.

[0138] For example, when the travel margin is ≥20% of the rated travel, the maximum vibration amplitude is set to the upper limit of the vibration amplitude (e.g., the upper limit of the vibration amplitude of a six-degree-of-freedom platform in the 1-50Hz frequency band is 0.5m / s²); when 10% of the rated travel ≤ the travel margin ≤ 20% of the rated travel, the upper limit of the vibration amplitude is set to 70% of the maximum vibration amplitude; when the travel margin < 10% of the rated travel, the upper limit of the vibration amplitude is set to 30% of the maximum vibration amplitude.

[0139] Step 4: Using the vibration excitation vector as the optimization variable, construct a body-sensing error model that includes the sensing weight matrix, the target vibration response vector, and the frequency response matrix; under the constraint of the vibration resource state, solve the body-sensing error model to obtain the optimal vibration excitation vector of each vibration actuator in each frequency band during the current control cycle.

[0140] The purpose of this step is to solve the optimal vibration excitation vector of multiple actuators such as the six-degree-of-freedom platform, seat, joystick, and foot pedal in the frequency domain by constructing a constrained optimization problem, given the target vibration response, frequency response matrix, and vibration resource status of the multi-sensor point. This aims to make the predicted response of the multi-sensor point as close as possible to the target response, while controlling the degree of use of each actuator to avoid insufficient resources and over-excitation of the structural resonance frequency band.

[0141] Step 4.1: For each frequency band, establish a somatosensory error model using the sensing weight matrix of multiple sensing points, the target vibration response vector, the initial frequency response matrix, and the vibration excitation vector as variables.

[0142] The expression for the somatosensory error model is: ;in, W h ( f () is the perception weight matrix. y ref ( f ) represents the target vibration response vector. G ( f ) is the initial frequency response matrix. u ( f ) is the vibration excitation vector.

[0143] The amplitude constraint is: ; u max ( i , f () represents the maximum available amplitude.

[0144] Step 4.2: Optimize the body perception error model to obtain the optimal vibration excitation vector for each frequency band.

[0145] Since the variable dimension is finite in each frequency band, the optimization problem can be formalized as a linear quadratic optimization or a weighted least squares problem, which can be solved quickly within the control cycle by calculating matrix decomposition. Within each control cycle, the above solution process is repeated for each frequency band to obtain the optimal vibration excitation vector for each frequency band.

[0146] Step 4 enables the vibration energy between different actuators to be dynamically allocated based on real-time resource status and sensory needs, rather than rigidly divided according to fixed frequency bands. This achieves a dynamic allocation where "the capable do more." Furthermore, while meeting the sensory goals of multiple sensing points, it naturally avoids the risk of stroke saturation, improving system safety and training.

[0147] Step 5: Convert the optimal vibration excitation vector into a time-domain vibration excitation signal; for a six-degree-of-freedom motion platform, sequentially separate the low-frequency attitude command and the corresponding high-frequency time-domain vibration excitation signal in the frequency domain and superimpose them in the time domain to generate motion commands; for each local vibration actuator, convert the corresponding time-domain vibration excitation signal into displacement or torque commands and execute them synchronously.

[0148] The purpose of this step is to convert the optimal excitation vector obtained by the coordinated allocation in the frequency domain into time-domain vibration commands that can be executed by each execution channel, and to realize the frequency domain separation and superposition of low-frequency attitude and high-frequency vibration on the six-degree-of-freedom platform channel, so as to generate the final control command under the premise of satisfying the travel margin.

[0149] Specifically, the following steps are included: Step 5.1: Perform an inverse Fourier transform on the optimal vibration excitation vector of each actuator to obtain the vibration excitation signal in the time domain.

[0150] The purpose of this step is to convert the frequency-domain vibration excitation parameters of the frequency bands into time-domain vibration excitation signals that can directly drive the actuator through inverse Fourier transform.

[0151] The excitation parameters for each actuator are defined in the frequency domain, including the amplitude, phase, and frequency range of each frequency band. An inverse Fourier transform (IFFT) is then performed on these frequency domain parameters to convert the discrete frequency domain information into a continuous time domain waveform. The output time domain signal is the electrical or force signal that drives the actuator.

[0152] For example, given that the amplitude of a six-degree-of-freedom platform in the 1-50Hz frequency band is 0.35m / s² and the phase is 0°, a time-domain vibration excitation signal with a frequency concentrated in the 1-50Hz range can be obtained by inverse Fourier transform.

[0153] The inverse Fourier transform ensures that the frequency components and amplitude of the time-domain signal are consistent with the previously calculated frequency-domain excitation parameters, thereby ensuring that the actual vibration of the sensing point conforms to the target response.

[0154] Step 5.2: Low-frequency attitude commands are low-pass filtered, vibration excitations assigned to the six-degree-of-freedom platform are high-pass filtered, and the processed low-frequency attitude signals are superimposed with high-frequency vibration increment signals in the time domain to form the position commands of the six-degree-of-freedom motion platform.

[0155] The purpose of this step is to separate low-frequency attitude signals through low-pass filtering and extract high-frequency vibration signals through high-pass filtering. These two signals are then superimposed in the time domain to generate precise position commands for the six actuators of the six-degree-of-freedom platform, achieving integrated control of "macroscopic attitude motion and microscopic vibration details." By separating signal components of different frequencies through low-frequency and high-frequency filtering, the low-frequency attitude commands and high-frequency vibration excitations do not interfere with each other, each retaining its corresponding motion characteristics.

[0156] 1. Perform low-pass filtering on low-frequency attitude commands. The goal is to preserve the attitude motion components in low-frequency attitude commands while filtering out high-frequency noise or interference signals. The principle is as follows: low-frequency attitude commands themselves simulate the slow motion signals of an aircraft's pitch, roll, and ascent / descent. The low-pass filter sets a cutoff frequency (e.g., 10Hz), allowing only signals below that frequency to pass through. After low-pass filtering, the attitude signal is smoother and will not cause platform jitter due to high-frequency interference.

[0157] 2. Apply high-pass filtering to the vibration excitation assigned to the six-degree-of-freedom platform. The aim is to extract the high-frequency vibration increment component from the vibration excitation and filter out the low-frequency components that overlap with attitude commands. The principle is as follows: the vibration excitation allocated to the six-degree-of-freedom platform contains both low-frequency and high-frequency components. The high-pass filter also uses 10Hz as the cutoff frequency, allowing only vibration signals above this frequency to pass through. After high-pass filtering, the resulting "high-frequency vibration increment signal" is specifically used to simulate microscopic vibrations such as turbulence and landing gear impacts.

[0158] 3. Temporal overlay The two filtered signals are directly superimposed in the time domain (i.e., the time dimension), which is essentially a combination of "macroscopic position reference and microscopic vibration increment". After the signals are superimposed, the final position command = low-frequency attitude signal after low-pass filtering (reference position) + high-frequency vibration increment signal after high-pass filtering (vibration offset).

[0159] For example, in a takeoff scenario, the low-frequency attitude command is filtered by a low-pass filter and outputs a reference position of "the six actuators extend to make the platform pitch up by 5°"; the vibration excitation assigned to the platform is filtered by a high-pass filter and outputs "small vertical vibration increments of 10-50Hz"; after superposition, the final position of the six actuators is "the reference position of pitching up by 5° + small vertical vibration offset", which allows the platform to simulate the slight bumps caused by engine vibration while pitching up.

[0160] It should be noted that the core function of the six-degree-of-freedom motion platform is to simultaneously simulate the overall attitude changes and structural vibration details of the aircraft. If only the attitude signal is retained, the platform motion is smooth but lacks vibration details, and the physical sensation is not realistic. If only the vibration signal is retained, the platform shakes slightly but has no macroscopic attitude, and the pilot cannot perceive the aircraft's motion state. By superimposing the two signals in the time domain, both macroscopic attitudes such as takeoff and turning are realized, and vibration details are incorporated, completely replicating the physical sensation of real flight.

[0161] Step 5.3: For the seat vibration actuator, the vibration excitation signal in the corresponding time domain is used as the displacement command of the seat; for the joystick vibration actuator, the vibration excitation signal in the corresponding time domain is converted into the displacement command of the grip; for the foot pedal vibration actuator, the vibration excitation signal in the corresponding time domain is converted into the displacement command of the foot pedal.

[0162] The purpose of this step is to convert a unified time-domain vibration excitation signal into a specific drive command that matches the motion pattern of the mechanism for three different types of vibration actuators: seats, joysticks, and foot pedals, so as to achieve precise tactile vibration output for each part.

[0163] 1. For the seat vibration actuator, the corresponding time-domain excitation signal is used as the command for seat vertical or multi-directional displacement. Movement patterns: Seats typically vibrate through linear displacement in the up-down, forward-backward, and left-right directions, while some high-end seats support multi-directional composite vibration.

[0164] Command conversion: Directly map the time-domain vibration excitation signal into the displacement parameters of the seat.

[0165] For example, if the time domain signal is a "random fluctuation signal of 1-50Hz and amplitude of 0.4m / s²", it is converted into a command of "seat vertical displacement ±5mm", which drives the seat vibrator to move according to the displacement law to simulate the feeling of turbulence.

[0166] 2. For the joystick vibration actuator, the corresponding excitation signal is converted into a small-amplitude angular displacement or torque command for the grip. Movement type: The vibration of the joystick is a small swing around the grip axis, or a vibration sensation is transmitted through torque changes, rather than linear displacement.

[0167] Command conversion: Convert the time-domain vibration excitation signal into the angular displacement angle of the joystick, or the torque of the actuator.

[0168] For example, the high-frequency jitter excitation signal in a stall scenario is converted into an "angular displacement command of ±2° around the X-axis of the control stick" or an "alternating torque command of 5 N·m", so that the pilot can feel obvious high-frequency jitter when gripping the stick, simulating the physical sensation of a stall warning.

[0169] 3. For the foot pedal vibration actuator, the corresponding excitation signal is converted into a slight forward / backward or up / down displacement command for the foot pedal. Movement pattern: The vibration of the foot pedal is a small movement in the forward and backward or up and down direction, which conforms to the pilot's foot perception habits.

[0170] Command conversion: The time-domain vibration excitation signal is converted into a displacement command for the foot pedal. The displacement is usually much smaller than that of the seat, characterized by "slight and delicate" movement.

[0171] For example, the excitation signal of the landing gear ground impact is converted into a command of "foot pedal forward and backward displacement ±3mm", so that the pilot's feet can feel the impact vibration when touching down, enhancing the realism of the takeoff and landing scenario.

[0172] Step 5 transforms the general time-domain vibration signal into displacement commands according to the motion characteristics of different actuators and the human perception requirements, ultimately enabling each part of the vibration actuator to accurately output the target body sensation.

[0173] In summary, this embodiment provides a multi-actuator vibration collaborative control method for flight simulators. With "overall consistency of body sensation across multiple sensing points" as the explicit objective, it maps event-driven virtual vibration sources to multi-sensor point frequency-band targets and introduces ergonomic weights. Based on online correction of the transfer model using the excitation from the previous cycle and the current measured response, it combines the actuator travel margin to form real-time resource constraints. Through collaborative optimization, it obtains the optimal excitation for each actuator in the current control cycle and executes it synchronously. Simultaneously, it decouples and superimposes low-frequency attitude and high-frequency vibration on the platform channel, enabling the vibration energy to be dynamically distributed and transferred between the platform and multiple actuators such as seats, joysticks, and foot pedals according to real-time capabilities. This significantly improves the consistency, temporal coordination, and training realism of body sensation across multiple parts while avoiding single-channel saturation and potential mismatch.

[0174] Example 2: Corresponding to Example 1, this example provides a multi-actuator vibration coordinated control system for a flight simulator, including: The data acquisition module is used to acquire flight attitude information, flight status information, and vibration event information output by the flight simulation host. The low-frequency attitude command generation module is used to generate low-frequency attitude commands for a six-degree-of-freedom motion platform based on flight attitude parameters and flight state parameters. The virtual vibration source signal generation module is used to match vibration parameters from a preset vibration parameter library based on flight event information and convert the vibration parameters into virtual vibration source signals. The target vibration response vector generation module is used to map virtual vibration source signals to multiple sensing points inside the cabin based on the vibration transmission relationship between the body structure and the cabin structure, and to establish the target vibration response vector of each sensing point in different frequency bands. The perception weight matrix generation module is used to combine ergonomic characteristics to establish perception weight matrices corresponding to multiple sensing points in different frequency bands. The frequency response matrix correction module is used to correct the frequency response matrix describing the vibration excitation transmitted to the sensing point online based on the vibration excitation vector of the previous control cycle and the measured vibration response signal of the current control cycle. The vibration resource status generation module is used to determine the maximum available amplitude of each vibration actuator in each frequency band based on the stroke margin of the actuator cylinder of each vibration actuator, and generate the vibration resource status. The somatosensory error model generation module is used to construct a somatosensory error model containing a sensing weight matrix, a target vibration response vector, and a frequency response matrix, using the vibration excitation vector as the optimization variable. The expression of the somatosensory error model is: ;in, f For frequency, W h ( f() is the perception weight matrix. y ref ( f ) represents the target vibration response vector. G ( f () represents the corrected frequency response matrix. u ( f Let be the vibration excitation vector to be solved; the constraints are: ; u max ( i , f () is the first determined based on the vibration resource status. i Each actuator at frequency f The maximum available amplitude at that location; The optimal vibration excitation vector generation module is used to solve the body perception error model under the constraints of vibration resource state to obtain the optimal vibration excitation vector of each vibration actuator in each frequency band during the current control cycle. The vibration excitation signal generation module is used to convert the optimal vibration excitation vector into a time-domain vibration excitation signal; The first motion command generation module is used to generate motion commands for a six-degree-of-freedom motion platform by sequentially performing frequency domain separation and time domain superposition of low-frequency attitude commands and corresponding high-frequency time-domain vibration excitation signals. The second motion command generation module is used to convert the corresponding time-domain vibration excitation signal into displacement or torque commands for each local vibration actuator and execute them synchronously.

[0175] Furthermore, the vibration transmission relationship between the airframe structure and the cabin structure includes: the distribution path mapping relationship, the vibration amplitude proportion mapping relationship, and the vibration energy proportion mapping relationship.

[0176] The target vibration response vector generation module includes: The target sensing point mapping unit is used to determine the target sensing point corresponding to the virtual vibration source signal based on the assigned path mapping relationship; The vibration amplitude change ratio generation unit is used to obtain the vibration amplitude attenuation ratio or amplification ratio when the virtual vibration source signal is transmitted from the body structure to each sensing point based on the vibration amplitude ratio mapping relationship. The target vibration amplitude generation unit is used to calculate the target vibration amplitude of each frequency band of the virtual vibration source signal when it is transmitted from the body structure to each sensing point according to the vibration amplitude attenuation ratio or amplification ratio. The vibration energy proportion calculation unit is used to calculate the power spectral density integral proportion of the virtual vibration source signal in different frequency bands at each sensing point based on the vibration energy proportion mapping relationship. The target vibration energy calculation unit is used to calculate the target vibration energy of each frequency band of the virtual vibration source signal when it is transmitted from the body structure to each sensing point based on the power spectral density integral ratio. The target vibration response combination unit is used to combine the target vibration amplitude and target vibration energy of each sensing point according to the frequency band to obtain the target vibration response vector of each sensing point in different frequency bands.

[0177] Furthermore, the perception weight matrix generation module includes: The sensitivity curve acquisition unit is used to acquire the sensitivity curve data of the human body to different body parts at different frequency bands; The sensitivity coefficient summation calculation unit is used to calculate the sum of the sensitivity coefficients of each sensing point across all frequency bands; The normalized weight calculation unit is used to divide the sensitivity coefficient of each sensing point in a specific frequency band by the sum of the sensitivity coefficients of that sensing point to obtain the normalized weight value. The normalized weight reconstruction unit is used to construct a two-dimensional sensing weight matrix from the normalized weight values ​​of all sensing points across all frequency bands.

[0178] Furthermore, the frequency response matrix correction module includes: The vibration response prediction calculation unit is used to calculate the predicted vibration response of the current control cycle using the frequency response matrix and vibration excitation vector of the previous control cycle. The vibration response signal conversion unit is used to collect the measured vibration response signals of each sensing point within the current control cycle and convert the measured vibration response signals into frequency domain data. The vibration response deviation acquisition unit is used to compare the deviation between the predicted vibration response and the measured vibration response on a frequency band-by-frequency basis. The frequency response matrix update unit is used to iteratively update the elements of the frequency response matrix using a recursive least squares algorithm when the deviation of multiple consecutive control cycles exceeds a preset threshold, so that the predicted vibration response approximates the measured vibration response.

[0179] Furthermore, the vibration resource status generation module includes: The stroke monitoring unit is used to monitor the current position and stroke limit position of the actuator of each vibration actuator in real time; The travel margin calculation unit is used to calculate the travel margin; the travel margin is the minimum distance from the current position to the extension limit position or the shortening limit position. The maximum vibration amplitude adjustment unit is used to adjust the maximum vibration amplitude of each frequency band according to preset rules, specifically including: maintaining the rated maximum vibration amplitude when the travel margin is greater than the first threshold; reducing the maximum vibration amplitude proportionally when the travel margin is between the first threshold and the second threshold; and limiting the maximum vibration amplitude to the lower limit when the travel margin is less than the second threshold.

[0180] Furthermore, the first motion command generation module includes: The low-pass filter unit is used to perform low-pass filtering on low-frequency attitude commands to obtain a smooth attitude reference signal. The high-pass filter unit is used to perform high-pass filtering on the time-domain vibration excitation signal allocated to the six-degree-of-freedom motion platform to extract the high-frequency vibration increment signal; The signal superposition unit is used to directly superimpose the attitude reference signal and the high-frequency vibration increment signal in the time domain to generate position control commands for each actuator of the six-degree-of-freedom motion platform.

[0181] Furthermore, the second motion command generation module includes: The first displacement command conversion unit is used to convert the corresponding time-domain vibration excitation signal into a multi-directional linear displacement command for the seat vibration actuator. The second displacement command conversion unit is used to convert the corresponding time-domain vibration excitation signal into an angular displacement command or torque output command around the grip axis for the joystick vibration actuator. The third displacement command conversion unit is used to convert the corresponding time-domain vibration excitation signal into a displacement command along the pedaling direction for the foot pedal vibration actuator.

[0182] Example 3: Based on the method provided in Example 1 and the system provided in Example 2, this example provides a computer device that executes the method described in Example 1 or any other method that may involve the method described in Example 1. The device includes a memory, a processor, and a transceiver connected in sequence. The memory stores a computer program, the transceiver sends and receives messages, and the processor reads the computer program and executes the method described in Example 1 or any other method that may involve the method described in Example 1. Specifically, the memory may include, but is not limited to, random-access memory (RAM), read-only memory (ROM), flash memory, first-in-first-out (FIFO) memory, and / or last-in-first-out (FILO) memory, etc.; the processor may include, but is not limited to, a microprocessor of the STM32F105 series. Furthermore, the computer device may also include, but is not limited to, a power module, a display screen, and other necessary components.

[0183] The working process, working details and technical effects of the aforementioned computer device provided in this embodiment can be found in the method described in Embodiment 1 or any method that may involve the method described in Embodiment 1, and will not be repeated here.

[0184] Example 4: This example provides a computer-readable storage medium that stores instructions that include the method described in Example 1 or any other method that may involve the method described in Example 1. Specifically, the computer-readable storage medium stores instructions that, when executed on a computer, perform the method described in Example 1 or any other method that may involve the method described in Example 1. The computer-readable storage medium refers to a data storage medium, which may include, but is not limited to, floppy disks, optical disks, hard disks, flash memory, USB flash drives, and / or Memory Sticks. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices.

[0185] The working process, working details and technical effects of the aforementioned computer-readable storage medium provided in this embodiment can be found in the method described in Embodiment 1 or any method that may involve the method described in Embodiment 1, and will not be repeated here.

[0186] Example 5: This example provides a computer program product containing instructions that, when executed on a computer, cause the computer to perform the method described in Example 1 or any method that may involve the method described in Example 1. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device.

[0187] It should be understood that the terms "system," "device," "unit," and / or "module" as used in this specification are a method of distinguishing different components, elements, parts, sections, or assemblies at different levels. However, if other terms can achieve the same purpose, they may be replaced by other expressions.

[0188] As indicated in this specification and claims, unless the context clearly indicates otherwise, the words "a," "an," "an," and / or "the" do not specifically refer to the singular and may also include the plural. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of expressly identified steps and elements, which do not constitute an exclusive list, and the method or apparatus may also include other steps or elements.

[0189] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for coordinated vibration control of multiple actuators in a flight simulator, characterized in that, Includes the following steps: The system acquires flight attitude information, flight status information, and vibration event information output by the flight simulation host; generates low-frequency attitude commands for the six-degree-of-freedom motion platform based on the flight attitude parameters and flight status parameters; and matches vibration parameters from a preset vibration parameter library according to the flight event information, converting the vibration parameters into virtual vibration source signals. Based on the vibration transmission relationship between the body structure and the cabin structure, the virtual vibration source signal is mapped to multiple sensing points in the cabin, and the target vibration response vector of each sensing point in different frequency bands is established; combined with ergonomic characteristics, a sensing weight matrix corresponding to multiple sensing points in different frequency bands is established. Based on the vibration excitation vector of the previous control cycle and the measured vibration response signal of the current control cycle, the frequency response matrix describing the vibration excitation transmitted to the sensing point is corrected online; based on the stroke margin of the actuator cylinder of each vibration actuator, the maximum available amplitude of each vibration actuator in each frequency band is determined, and the vibration resource status is generated. Using the vibration excitation vector as the optimization variable, a body-sensing error model is constructed, which includes a sensing weight matrix, a target vibration response vector, and a frequency response matrix. Under the constraint of vibration resource state, the body-sensing error model is solved to obtain the optimal vibration excitation vector of each vibration actuator in each frequency band during the current control cycle. The optimal vibration excitation vector is converted into a time-domain vibration excitation signal. For a six-degree-of-freedom motion platform, the low-frequency attitude command and the corresponding high-frequency time-domain vibration excitation signal are sequentially separated in the frequency domain and superimposed in the time domain to generate motion commands. For each local vibration actuator, the corresponding time-domain vibration excitation signal is converted into displacement or torque commands and executed synchronously.

2. The vibration coordinated control method for multiple actuators in a flight simulator according to claim 1, characterized in that, The vibration transmission relationship between the airframe structure and the cabin structure includes: the distribution path mapping relationship, the vibration amplitude proportion mapping relationship, and the vibration energy proportion mapping relationship. Mapping virtual vibration source signals to multiple sensing points within the cabin includes the following steps: Based on the allocation path mapping relationship, the target sensing point corresponding to the virtual vibration source signal is determined; Based on the vibration amplitude ratio mapping relationship, the vibration amplitude attenuation ratio or amplification ratio of the virtual vibration source signal when it is transmitted from the body structure to each sensing point is obtained; according to the vibration amplitude attenuation ratio or amplification ratio, the target vibration amplitude of each frequency band of the virtual vibration source signal when it is transmitted from the body structure to each sensing point is calculated. Based on the vibration energy proportion mapping relationship, the power spectral density integral proportion of the virtual vibration source signal in different frequency bands at each sensing point is calculated; according to the power spectral density integral proportion, the target vibration energy of each frequency band of the virtual vibration source signal is calculated when it is transmitted from the body structure to each sensing point. Establishing the target vibration response vector for each sensing point in different frequency bands includes the following steps: The target vibration amplitude and target vibration energy of each sensing point are combined according to frequency band to obtain the target vibration response vector of each sensing point in different frequency bands.

3. A method for coordinated vibration control of multiple actuators in a flight simulator according to claim 1 or 2, characterized in that, Establishing a sensing weight matrix corresponding to multiple sensing points in different frequency bands includes the following steps: Acquire human sensitivity curve data for different body parts at different frequency bands; Calculate the sum of the sensitivity coefficients of each sensing point across all frequency bands; Divide the sensitivity coefficient of each sensing point in each frequency band by the sum of the sensitivity coefficients of that sensing point in all frequency bands to obtain the normalized weight value of that sensing point in each frequency band. The normalized weight values ​​of all sensing points across all frequency bands are used to construct a two-dimensional sensing weight matrix.

4. The vibration coordinated control method for multiple actuators in a flight simulator according to claim 1, characterized in that, Online correction of the frequency response matrix describing the transmission of vibration excitation to the sensing point includes the following steps: Using the frequency response matrix and vibration excitation vector of the previous control cycle, the predicted vibration response of the current control cycle is calculated. Collect the measured vibration response signals of each sensing point within the current control cycle, and convert the measured vibration response signals into frequency domain data; Compare the deviation between the predicted vibration response and the measured vibration response on a frequency band-by-frequency basis; When the deviation of multiple consecutive control cycles exceeds the preset threshold, the recursive least squares algorithm is used to iteratively update the elements of the frequency response matrix so that the predicted vibration response approximates the measured vibration response.

5. The vibration coordinated control method for multiple actuators in a flight simulator according to claim 1, characterized in that, Generating vibration resource status includes the following steps: Real-time monitoring of the current position and stroke limit position of the actuator cylinder of each vibration actuator; Calculate the travel margin; travel margin = min(extension limit - current position, current position - shortening limit); The maximum vibration amplitude of each frequency band is adjusted according to preset rules, specifically including: when the travel margin is greater than the first threshold, the rated maximum vibration amplitude is maintained; when the travel margin is between the first threshold and the second threshold, the maximum vibration amplitude is reduced proportionally; when the travel margin is less than the second threshold, the maximum vibration amplitude is limited to the lower limit.

6. The vibration coordinated control method for multiple actuators in a flight simulator according to claim 1, characterized in that, The expression for the somatosensory error model is: ;in, f For frequency, W h ( f () is the perception weight matrix. y ref ( f ) represents the target vibration response vector. G ( f () represents the corrected frequency response matrix. u ( f () represents the vibration excitation vector to be solved. The constraints are: ; u max ( i , f () is the first determined based on the vibration resource status. i Each actuator at frequency f The maximum available amplitude at that location.

7. The vibration coordinated control method for multiple actuators in a flight simulator according to claim 1, characterized in that, The low-frequency attitude command and the corresponding high-frequency time-domain vibration excitation signal are sequentially separated in the frequency domain and superimposed in the time domain to generate a motion command, including the following steps: Low-frequency attitude commands are low-pass filtered to obtain a smooth attitude reference signal; The time-domain vibration excitation signal allocated to the six-degree-of-freedom motion platform is high-pass filtered to extract the high-frequency vibration increment signal; In the time domain, the attitude reference signal and the high-frequency vibration increment signal are directly superimposed to generate position control commands for each actuator of the six-degree-of-freedom motion platform. For each local vibration actuator, the corresponding time-domain vibration excitation signal is converted into a displacement or torque command, including the following steps: For the seat vibration actuator, the corresponding time-domain vibration excitation signal is converted into a multi-directional linear displacement command for the seat; For joystick vibration actuators, the corresponding time-domain vibration excitation signal is converted into an angular displacement command or torque output command around the grip axis; For the foot pedal vibration actuator, the corresponding time-domain vibration excitation signal is converted into a displacement command along the pedaling direction.

8. A vibration coordination control system for multiple actuators in a flight simulator, characterized in that, include: The data acquisition module is used to acquire flight attitude information, flight status information, and vibration event information output by the flight simulation host. The low-frequency attitude command generation module is used to generate low-frequency attitude commands for a six-degree-of-freedom motion platform based on flight attitude parameters and flight state parameters. The virtual vibration source signal generation module is used to match vibration parameters from a preset vibration parameter library based on flight event information and convert the vibration parameters into virtual vibration source signals. The target vibration response vector generation module is used to map virtual vibration source signals to multiple sensing points inside the cabin based on the vibration transmission relationship between the airframe structure and the cabin structure, and to establish the target vibration response vector of each sensing point in different frequency bands. The perception weight matrix generation module is used to combine ergonomic characteristics to establish perception weight matrices corresponding to multiple sensing points in different frequency bands. The frequency response matrix correction module is used to correct the frequency response matrix describing the vibration excitation transmitted to the sensing point online based on the vibration excitation vector of the previous control cycle and the measured vibration response signal of the current control cycle. The vibration resource status generation module is used to determine the maximum available amplitude of each vibration actuator in each frequency band based on the stroke margin of the actuator cylinder of each vibration actuator, and generate the vibration resource status. The somatosensory error model generation module is used to construct a somatosensory error model containing a sensing weight matrix, a target vibration response vector, and a frequency response matrix, using the vibration excitation vector as the optimization variable. The expression of the somatosensory error model is: ;in, f For frequency, W h ( f () is the perception weight matrix. y ref ( f ) represents the target vibration response vector. G ( f () represents the corrected frequency response matrix. u ( f Let be the vibration excitation vector to be solved; the constraints are: ; u max ( i , f () is the first determined based on the vibration resource status. i Each actuator at frequency f The maximum available amplitude at that location; The optimal vibration excitation vector generation module is used to solve the body perception error model under the constraints of vibration resource state to obtain the optimal vibration excitation vector of each vibration actuator in each frequency band during the current control cycle. The vibration excitation signal generation module is used to convert the optimal vibration excitation vector into a time-domain vibration excitation signal; The first motion command generation module is used to generate motion commands for a six-degree-of-freedom motion platform by sequentially performing frequency domain separation and time domain superposition of low-frequency attitude commands and corresponding high-frequency time-domain vibration excitation signals. The second motion command generation module is used to convert the corresponding time-domain vibration excitation signal into displacement or torque commands for each local vibration actuator and execute them synchronously.

9. A multi-actuator vibration coordinated control system for a flight simulator according to claim 8, characterized in that, The vibration transmission relationship between the airframe structure and the cabin structure includes: the distribution path mapping relationship, the vibration amplitude proportion mapping relationship, and the vibration energy proportion mapping relationship. The target vibration response vector generation module includes: The target sensing point mapping unit is used to determine the target sensing point corresponding to the virtual vibration source signal based on the assigned path mapping relationship; The vibration amplitude change ratio generation unit is used to obtain the vibration amplitude attenuation ratio or amplification ratio when the virtual vibration source signal is transmitted from the body structure to each sensing point based on the vibration amplitude ratio mapping relationship. The target vibration amplitude generation unit is used to calculate the target vibration amplitude of each frequency band of the virtual vibration source signal when it is transmitted from the body structure to each sensing point according to the vibration amplitude attenuation ratio or amplification ratio. The vibration energy proportion calculation unit is used to calculate the power spectral density integral proportion of the virtual vibration source signal in different frequency bands at each sensing point based on the vibration energy proportion mapping relationship. The target vibration energy calculation unit is used to calculate the target vibration energy of each frequency band of the virtual vibration source signal when it is transmitted from the body structure to each sensing point based on the power spectral density integral ratio. The target vibration response combination unit is used to combine the target vibration amplitude and target vibration energy of each sensing point according to the frequency band to obtain the target vibration response vector of each sensing point in different frequency bands.

10. A vibration coordination control system for multiple actuators in a flight simulator according to claim 8, characterized in that, The perceptual weight matrix generation module includes: The sensitivity curve acquisition unit is used to acquire the sensitivity curve data of the human body to different body parts at different frequency bands; The sensitivity coefficient summation calculation unit is used to calculate the sum of the sensitivity coefficients of each sensing point across all frequency bands; The normalized weight calculation unit is used to divide the sensitivity coefficient of each sensing point in each frequency band by the sum of the sensitivity coefficients of the sensing point in all frequency bands to obtain the normalized weight value of the sensing point in each frequency band. The normalized weight reconstruction unit is used to construct a two-dimensional sensing weight matrix from the normalized weight values ​​of all sensing points across all frequency bands.

11. A multi-actuator vibration coordinated control system for a flight simulator according to claim 8, characterized in that, The frequency response matrix correction module includes: The vibration response prediction calculation unit is used to calculate the predicted vibration response of the current control cycle using the frequency response matrix and vibration excitation vector of the previous control cycle. The vibration response signal conversion unit is used to collect the measured vibration response signals of each sensing point within the current control cycle and convert the measured vibration response signals into frequency domain data. The vibration response deviation acquisition unit is used to compare the deviation between the predicted vibration response and the measured vibration response on a frequency band-by-frequency basis. The frequency response matrix update unit is used to iteratively update the elements of the frequency response matrix using a recursive least squares algorithm when the deviation of multiple consecutive control cycles exceeds a preset threshold, so that the predicted vibration response approximates the measured vibration response.

12. The vibration coordination control system for multiple actuators of a flight simulator according to claim 8, characterized in that, The vibration resource status generation module includes: The stroke monitoring unit is used to monitor the current position and stroke limit position of the actuator of each vibration actuator in real time; The travel margin calculation unit is used to calculate the travel margin; travel margin = min(extension limit - current position, current position - shortening limit); The maximum vibration amplitude adjustment unit is used to adjust the maximum vibration amplitude of each frequency band according to preset rules, specifically including: maintaining the rated maximum vibration amplitude when the travel margin is greater than the first threshold; reducing the maximum vibration amplitude proportionally when the travel margin is between the first threshold and the second threshold; and limiting the maximum vibration amplitude to the lower limit when the travel margin is less than the second threshold.

13. A multi-actuator vibration coordinated control system for a flight simulator according to claim 8, characterized in that, The first motion command generation module includes: The low-pass filter unit is used to perform low-pass filtering on low-frequency attitude commands to obtain a smooth attitude reference signal. The high-pass filter unit is used to perform high-pass filtering on the time-domain vibration excitation signal allocated to the six-degree-of-freedom motion platform to extract the high-frequency vibration increment signal. The signal superposition unit is used to directly superimpose the attitude reference signal and the high-frequency vibration increment signal in the time domain to generate position control commands for each actuator of the six-degree-of-freedom motion platform. The second motion command generation module includes: The first displacement command conversion unit is used to convert the corresponding time-domain vibration excitation signal into a multi-directional linear displacement command for the seat vibration actuator. The second displacement command conversion unit is used to convert the corresponding time-domain vibration excitation signal into an angular displacement command or torque output command around the grip axis for the joystick vibration actuator. The third displacement command conversion unit is used to convert the corresponding time-domain vibration excitation signal into a displacement command along the pedaling direction for the foot pedal vibration actuator.

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