A multi-degree-of-freedom aircraft driving simulation training platform

Abstract

The present application discloses a multi-degree-of-freedom aircraft simulation driving training platform, comprising: a multi-degree-of-freedom motion platform; a control device for acquiring longitudinal and lateral translation acceleration signals and lift translation acceleration signals, and after washing out and pre-compensating the longitudinal and lateral translation acceleration signals and lift translation angular velocity signals, forming displacement signals, attitude signals, yaw angle signals, and lift signals respectively, with the goal of minimizing the error cost function of the simulated scene perception model and the motion platform perception model during washing out; and controlling the multi-degree-of-freedom motion platform according to the displacement signal, attitude signal, yaw angle signal, and lift signal. The present application minimizes the error cost function between the simulated scene perception model and the motion platform perception model by washing out and pre-compensating the acceleration signal output by the scene simulation software, thereby achieving a high degree of consistency between the simulated scene and the motion state, and effectively improving the effect of flight training.

Description

Technical Field

[0001] The present application relates to the field of simulation training technology, and in particular to a multi-degree-of-freedom aircraft simulation driving training platform. Background Art

[0002] Ground simulation training is a must for every pilot. Using ground-based simulation equipment, pilots can become familiar with aircraft operation in a safe environment and practice correct operations in simulated environments. Ground simulation training lays a solid foundation for subsequent in-flight training, significantly reduces training costs, and improves safety, leading to its widespread use.

[0003] At present, the equipment used in ground simulation training mainly consists of two parts: a multi-degree-of-freedom motion platform and scene simulation software. The scene simulation software controls the simulated scene displayed on the monitor according to the preset scene parameters, and also controls the motion state of the multi-degree-of-freedom motion platform to achieve the purpose of consistency between the simulated scene and the motion state, striving to achieve a high degree of consistency in the pilot's vision and physical perception.

[0004] However, due to the delay in mechanical control, the consistency between the visual simulation scene and the physical motion state control is not very high at present, resulting in differences between the pilot's physical sensation and vision, which can easily cause confusion in the pilot's perception and affect the training effect. Summary of the Invention

[0005] The embodiment of the present application provides a multi-degree-of-freedom aircraft simulation driving training platform to solve the problem of insufficient consistency between simulation scenes and motion states in the prior art.

[0006] In one aspect, an embodiment of the present application provides a multi-degree-of-freedom aircraft driving simulation training platform, comprising:

[0007] Multi-degree-of-freedom motion platform;

[0008] A control device for acquiring longitudinal and lateral translation acceleration signals and lift translation acceleration signals, performing washout and lead compensation on the longitudinal and lateral translation acceleration signals and lift translation angular velocity signals to generate displacement signals, attitude signals, yaw angle signals, and lift signals for driving the multi-degree-of-freedom motion platform in horizontal movement, pitch and roll, yaw angle, and lift, respectively. The longitudinal and lateral translation acceleration signals and lift translation angular velocity signals are washed out with the goal of minimizing an error cost function of a simulated scene perception model and a motion platform perception model. The multi-degree-of-freedom motion platform is controlled based on the displacement signals, attitude signals, yaw angle signals, and lift signals.

[0009] The motion acquisition unit is used to detect the motion status of each operating device during the pilot's operation, so as to know the pilot's movements in advance and make timely pre-control operations on the multi-degree-of-freedom motion platform to enable the multi-degree-of-freedom motion platform to move in advance.

[0010] The multi-degree-of-freedom aircraft driving simulation training platform in this application has the following advantages:

[0011] By washing out and pre-compensating the acceleration signal output by the scene simulation software, the error cost function between the simulated scene perception model and the motion platform perception model is minimized, achieving a high degree of consistency between the simulated scene and the motion state, and significantly improving the effectiveness of flight training. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0013] Figure 1 A schematic diagram of the overall structure of the multi-degree-of-freedom motion platform provided in an embodiment of the present application;

[0014] Figure 2 A schematic diagram of the structure of the upper platform provided in an embodiment of the present application;

[0015] Figure 3 A schematic diagram of the structure of the lower platform provided in an embodiment of the present application.

[0016] Description of the accompanying drawings: 100 - upper platform, 110 - upper connecting piece, 200 - lower platform, 210 - lower connecting piece, 300 - telescopic unit. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0018] The present invention provides a multi-degree-of-freedom aircraft simulation training platform, including:

[0019] Multi-degree-of-freedom motion platform;

[0020] A control device for acquiring longitudinal and lateral translation acceleration signals and lift translation acceleration signals, performing washout and lead compensation on the longitudinal and lateral translation acceleration signals and lift translation angular velocity signals to generate displacement signals, attitude signals, yaw angle signals, and lift signals for driving the multi-degree-of-freedom motion platform in horizontal movement, pitch and roll, yaw angle, and lift, respectively. The longitudinal and lateral translation acceleration signals and lift translation angular velocity signals are washed out with the goal of minimizing an error cost function of a simulated scene perception model and a motion platform perception model. The multi-degree-of-freedom motion platform is controlled based on the displacement signals, attitude signals, yaw angle signals, and lift signals.

[0021] The motion acquisition unit is used to detect the motion status of each operating device during the pilot's operation, so as to know the pilot's movements in advance and make timely pre-control operations on the multi-degree-of-freedom motion platform to enable the multi-degree-of-freedom motion platform to move in advance.

[0022] For example, Figure 1-3 As shown, the multi-degree-of-freedom motion platform includes a telescopic unit 300 and an upper platform 100 and a lower platform 200 rotatably connected to the upper end and the lower end of the telescopic unit 300 respectively.

[0023] In an embodiment of the present application, a training cabin can be installed on the top surface of the upper platform 100. A plurality of upper connectors 110 are provided on the bottom surface of the upper platform 100, and a plurality of lower connectors 210 are provided on the top surface of the lower platform 200. The upper connectors 110 and the lower connectors 210 have the same structure and can both be L-shaped metal plates, one side of which is fixedly connected to the upper platform 100 or the lower platform 200, and the other side is rotatably connected to the upper end or the lower end of the telescopic unit 300. For the rotational connection, a spherical bearing can be fixedly provided at each end of the telescopic unit 300, and the spherical bearing can be rotatably connected to the connecting rod on the upper connector 110 or the lower connector 210.

[0024] In this application, the number of telescopic units 300 is six, forming a Stewart parallel structure. The parallel-connected motion platform can select and combine six degrees of freedom (DOF) of roll, pitch, yaw, heave, longitudinal translation, and lateral translation to simulate motion with different degrees of freedom. It should be understood that in other embodiments, the number of telescopic units 300 may be greater or less, and this application does not limit the number of telescopic units 300 or DOF.

[0025] Furthermore, the telescopic unit 300 includes a telescopic execution unit, a telescopic driving unit and a telescopic control unit. The telescopic driving unit drives the telescopic execution unit to work so as to adjust the length of the telescopic execution unit. The telescopic control unit controls the working state of the telescopic driving unit.

[0026] The telescopic execution unit may adopt an electric cylinder, the telescopic driving unit may adopt an AC servo motor, and the telescopic control unit may adopt an AC servo driver.

[0027] The training platform in this application uses fully digital servo control technology. The control device obtains the simulated posture data output by the scene simulation software through the network or serial port in a specified protocol format, performs a spatial motion model transformation on the simulated posture data, and uses a washout algorithm to obtain the elongation of each telescopic unit. The elongation is transmitted to the telescopic control unit via the bus. The telescopic control unit precisely controls the working state of the telescopic drive unit in the position control mode, thereby causing the telescopic drive unit to drive the screw of the telescopic execution unit to rotate through the synchronous wheel, thereby accurately completing the telescopic movement and causing the upper platform to move to the specified position. At the same time, an encoder can also be provided on the telescopic drive unit. The encoder detects the torque, speed, and position information of the telescopic drive unit in real time, and transmits this torque, speed, and position information to the telescopic control unit, forming a closed-loop control of the telescopic execution unit.

[0028] Although the above method can improve the consistency between the pilot's vision and body perception, the multi-degree-of-freedom motion platform can only move after the control device outputs displacement signals, attitude signals, yaw angle signals, and lift signals. It cannot start moving without receiving these signals, resulting in a certain deviation between the pilot's body perception and vision. To address this problem, the training platform of this application also includes a motion acquisition unit. This motion acquisition unit detects the motion state of each operating device during the pilot's operation to know the pilot's movements in advance. Therefore, before the control device outputs the above signals, it can know the next control to be performed and perform pre-control operations in time, so that the multi-degree-of-freedom motion platform can move in advance, further improving the consistency between the pilot's body perception and vision.

[0029] Specifically, the motion acquisition unit can be a camera, preferably mounted above or in front of the pilot so that its monitoring range covers all operating devices. After the camera captures real-time images of the training cabin interior, the central processing unit (CPU) processes the images. During this processing, the CPU identifies key features in the image, such as hands and feet, and continuously monitors the movement direction of these key features. By determining the position and movement direction of these key features, the CPU can determine the operating device currently being operated by the pilot and the specific operation performed on that device. Since the operating device can only issue corresponding instructions after being operated by the pilot, monitoring the pilot's operation can pre-determine the pilot's operating intention. After determining the specific operation, the CPU can then perform pre-control of the multi-degree-of-freedom motion platform. During pre-control, the CPU only needs to determine the pilot's intention, that is, the general content of the specific operation, such as turning left or accelerating, without knowing the detailed content of the operation. After determining the general content of the operation, the CPU can immediately perform a certain amount of pre-control of the multi-degree-of-freedom motion platform, so that the multi-degree-of-freedom motion platform can perform more accurate movements under the control of the above signals after the pre-control occurs.

[0030] Furthermore, since there are many operating devices in the training cabin and they are distributed in multiple different locations, the central processor needs to traverse the entire image when determining the operating device that the pilot is operating. This process takes a lot of time. In order to speed up the processing speed, the present application can also set sensing units on each operating device, such as pressure sensors, touch sensors, etc. When the pilot touches or presses a certain operating device, the central processor can quickly determine the position of the operating device in the image, and then identify the image content at that position without traversing the image, which greatly speeds up the image processing speed.

[0031] In a possible embodiment, the control device decomposes the longitudinal and lateral translation acceleration signals into high-frequency signals and low-frequency signals, washes out and advance-compensates the high-frequency signals to form displacement signals, and processes the low-frequency signals to form attitude signals and yaw angle signals.

[0032] Exemplarily, the control device decomposes the low-frequency signal into an attitude angle prompt signal and a yaw angle prompt signal, filters and advance-compensates the attitude angle prompt signal to form an attitude signal, and washes out, filters and advance-compensates the yaw angle prompt signal to form a yaw angle signal.

[0033] At the same time, the control device filters, washes out and advance compensates the lifting and translation acceleration signals to form lifting signals.

[0034] The control device is equipped with control software that enables single-degree-of-freedom motion, compound motion, single-cylinder testing, and vibration testing of the multi-degree-of-freedom motion platform. Prior to motion control and testing, the pilot can also set platform parameters, including response speed, speed limit, and linearity. Under single-degree-of-freedom motion control, the control device can independently control any single degree of freedom of the multi-degree-of-freedom motion platform. The pilot can input a specified angle through the control software, and the multi-degree-of-freedom motion platform will move to the input angle. Under compound motion control, the control device can achieve combined control of the multi-degree-of-freedom motion platform's six degrees of freedom. The pilot can input a specified angle and translation through the control software, and the multi-degree-of-freedom motion platform will move to the corresponding position. Under single-cylinder testing, the control device can independently control a single telescopic actuator of the multi-degree-of-freedom motion platform. The pilot can input a specified telescopic amount through the control software, and the specified telescopic actuator will move to the specified position. Under vibration testing, the control device can vibrate the multi-degree-of-freedom motion platform at a specified frequency. The pilot can input the specified vibration frequency, degrees of freedom and motion range through the control software, and the multi-degree-of-freedom motion platform will perform vibration testing according to the set parameters.

[0035] The washout algorithm in this application includes four modes: longitudinal mode (including longitudinal and pitch degrees of freedom), lateral mode (including lateral and roll degrees of freedom), yaw mode, and up-down mode. The first two modes tilt the training cabin at a certain roll and pitch angle within a limited motion space, thereby generating a component of gravity acceleration, allowing the pilot to feel a continuous acceleration. The latter two modes can use high-pass filters to simulate the high-frequency dynamics of the aircraft. The following describes the derivation process of the washout algorithm using the longitudinal mode (X-axis direction) as an example.

[0036] Control input state variable μ f The linear acceleration α in the X-axis direction xf and the angular velocity θ around the X axis xf composition:

[0037]

[0038] μ f After washing out, μ ω :

[0039]

[0040] μ f 、μ ω They will be compared after passing through the human body sensory model.

[0041] For the human sensory model, the control input is:

[0042]

[0043] The rotational motion felt by the human body is obtained by μ1 through the semicircular canal model:

[0044]

[0045] Where:

[0046]

[0047] T3=G s τ a τ L T0, T4 = G s τ a T0

[0048] Written in state space form:

[0049] χ 1-3 =[χ1χ2χ3] r

[0050]

[0051] Where:

[0052]

[0053] C scc =[1 0 0], D scc =[T10]

[0054] The axial force (in the X-axis direction) felt by the human body is determined by the training cabin force f x Multiplying by the otolith model gives:

[0055]

[0056] On the training platform, since the center of the optional equipment is located at the center of the multi-degree-of-freedom motion platform, the specific force is:

[0057]

[0058] Where R ph is the length from the center of the multi-degree-of-freedom motion platform to the pilot's head. Performing Laplace transform on the above formula yields:

[0059]

[0060] After substitution, we get:

[0061]

[0062] Rearranging the equation and differentiating both sides of the equation gives:

[0063]

[0064] The above formula can be written as:

[0065]

[0066] a=(B0+B1),b=B0B1,c=G 02 ×(B0+B1-A0)

[0067] d=G 02 (g+R ph B0B1), e=G 02 gA0,f=G 02 , h=G 02 A0

[0068] Defined in the state space:

[0069] χ 4-8 =[χ4χ5χ6χ7χ8] r

[0070]

[0071] Where:

[0072]

[0073] C oto =[1 0 0 1 0], D otp =[-R ph 0]

[0074] The state space equations of the control signal μ and the otolith model and semicircular canal model are established respectively, and the state space of the human motion sensory model is obtained by merging the two state space equations:

[0075]

[0076] Where:

[0077]

[0078] From this we can get μ f 、μ ω The state equations of the human body sensory model are as follows:

[0079]

[0080] Assuming that the human sensory model can be applied to both the training cabin and the pilots in the training cabin, the state error χ is defined as e =χω -χ f , pilot perception error e:

[0081] χ e =A v χ e +B v μ ω -B v μ1

[0082] e=C v χ e +D v μ ω -D v μ f

[0083] The washed μ ω Introduced into the algorithm, the output angle, speed and displacement are optimized, and the training cabin is guaranteed to return to the neutral position after completing an action. The state variable χ is introduced d :

[0084] χ d =[χ9χ 10 χ 11 χ 12 ]≈[∫∫∫axdt 3 ∫∫axdt 2 ∫axdt 1 θ]

[0085] get:

[0086]

[0087] y d =x d

[0088] Where:

[0089]

[0090] The input signal μ of the system f The random input signal obtained by filtering white noise is written in state space form:

[0091] χ n =A n x n +B2ω

[0092] μ f =x n

[0093] Where:

[0094]

[0095] Merge to get a new state space:

[0096] χ=[χ c χ d χ n ]

[0097]

[0098] y=[ex d ] r =Cχ+Dμ ω

[0099] Where:

[0100]

[0101] H=[0 0B n ] f

[0102] In order to minimize the sensory error e and μ ω To meet the performance indicators of the motion platform, construct the cost function:

[0103]

[0104] Where E is the mean or expected value, and this cost function consists of three variables: sensory error e, added term χ d and μ ω , the three variables together define the linear and rotational motion of the multi-degree-of-freedom motion platform.

[0105] Convert the equation into standard optimal control form:

[0106]

[0107]

[0108] Where:

[0109]

[0110] R 12 =C T GD

[0111] when

[0112] μ′=-R′2B T Pχ

[0113] The cost function is minimized.

[0114] P is the solution of the following Riccati equation:

[0115]

[0116] Substituting into the equation we get:

[0117]

[0118] Assume the optimal feedback gain matrix is ​​F:

[0119] μ ω =-Vχ

[0120]

[0121] The state variable χ in the corresponding equation e 、v d and χ n , decompose F into the following form:

[0122]

[0123] Remove the state variable χ n get:

[0124]

[0125] Performing a pull transformation yields:

[0126] μ ω (s)=W(s)V f (s)

[0127] in:

[0128]

[0129] The optimal filter matrix is:

[0130]

[0131] Each W(s) is a high-order optimal filter. By choosing the appropriate weight matrix Q, R d and R are used to adjust the W(s) filter coefficients to achieve the desired motion response.

[0132] In a possible embodiment, the control device further detects the process specification, and locks the multi-degree-of-freedom motion platform when it is determined that the process specification does not meet the safety index.

[0133] For example, pilots need to follow standard procedures before training, such as wearing seat belts, etc., and there may be unsafe factors during the movement of the multi-degree-of-freedom motion platform. Therefore, the control device also needs to detect situations such as the moving distance exceeds the limit point, the starting point is not reached, and the software determines that the limit is exceeded, and stop the movement of the multi-degree-of-freedom motion platform in time.

[0134] In a possible embodiment, the control device further performs emergency braking on the multi-degree-of-freedom motion platform when a failure occurs in the multi-degree-of-freedom motion platform.

[0135] For example, when a malfunction or emergency occurs on the multi-degree-of-freedom motion platform, the pilot can perform emergency braking through the control device to protect people and property.

[0136] In a possible embodiment, the control device further performs fault detection on the multi-degree-of-freedom motion platform.

[0137] For example, during the movement of the multi-degree-of-freedom motion platform, the control device reads the data of the telescopic control unit and other control components through the Modbus RTU protocol to monitor the operating status of the multi-degree-of-freedom motion platform in real time. After a fault is discovered, it can respond in time and stop the multi-degree-of-freedom motion platform from moving further to ensure the safety of the pilot.

[0138] In a possible embodiment, a posture detection unit is provided on the multi-degree-of-freedom motion platform, which is used to collect actual posture data of the multi-degree-of-freedom motion platform. The control device also obtains simulated posture data of the simulated scene and compares the actual posture data with the simulated posture data.

[0139] For example, after data washing, the actual posture data can be solved to obtain the current posture and vibration data of the multi-degree-of-freedom motion platform. These posture and vibration data can be sent to the HMI (human-machine interface) of the training cabin through the network, and the current posture can be compared with the posture in the simulated scene simulated by the scene simulation software.

[0140] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present application.

[0141] Obviously, those skilled in the art may make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalents, this application is intended to include these modifications and variations.

Claims

1. A multi-degree-of-freedom aircraft driving simulation training platform, characterized in that: include: Multi-degree-of-freedom motion platform; a control device for acquiring longitudinal and lateral translation acceleration signals and a lift translation acceleration signal, performing washout and lead compensation on the longitudinal and lateral translation acceleration signals and the lift translation acceleration signals to generate displacement signals, attitude signals, yaw angle signals, and lift signals for respectively driving the multi-degree-of-freedom motion platform in horizontal movement, pitch and roll, yaw angle, and lift; wherein the washout of the longitudinal and lateral translation acceleration signals and the lift translation acceleration signals is performed with the goal of minimizing an error cost function of a simulated scene perception model and a motion platform perception model; and controlling the multi-degree-of-freedom motion platform based on the displacement signals, attitude signals, yaw angle signals, and lift signals; The motion acquisition unit is used to detect the motion status of each operating device during the pilot's operation, so as to know the pilot's action in advance and make pre-control operations on the multi-degree-of-freedom motion platform in time to make the multi-degree-of-freedom motion platform move in advance.

2. A multi-degree-of-freedom aircraft driving simulation training platform according to claim 1, characterized in that: The control device decomposes the longitudinal and lateral translation acceleration signals into high-frequency signals and low-frequency signals, washes out and advance-compensates the high-frequency signals to form the displacement signals, and processes the low-frequency signals to form the attitude signals and yaw angle signals.

3. A multi-degree-of-freedom aircraft driving simulation training platform according to claim 2, characterized in that: The control device decomposes the low-frequency signal into an attitude angle prompt signal and a yaw angle prompt signal, filters and advance-compensates the attitude angle prompt signal to form the attitude signal, and washes out, filters, and advance-compensates the yaw angle prompt signal to form the yaw angle signal.

4. The multi-degree-of-freedom aircraft driving simulation training platform according to claim 1, characterized in that: The control device filters, washes out and performs advance compensation on the lifting and translation acceleration signal to form the lifting signal.

5. The multi-degree-of-freedom aircraft driving simulation training platform according to claim 1, characterized in that: The control device also detects the process specification, and locks the multi-degree-of-freedom motion platform when it is determined that the process specification does not meet the safety index.

6. The multi-degree-of-freedom aircraft driving simulation training platform according to claim 1, characterized in that: The control device also performs emergency braking on the multi-degree-of-freedom motion platform when a fault occurs on the multi-degree-of-freedom motion platform.

7. The multi-degree-of-freedom aircraft driving simulation training platform according to claim 1, characterized in that: The control device also performs fault detection on the multi-degree-of-freedom motion platform.

8. The multi-degree-of-freedom aircraft driving simulation training platform according to claim 1, characterized in that: The multi-degree-of-freedom motion platform is provided with a posture detection unit, which is used to collect actual posture data of the multi-degree-of-freedom motion platform. The control device also obtains simulated posture data of a simulated scene and compares the actual posture data with the simulated posture data.

9. The multi-degree-of-freedom aircraft driving simulation training platform according to claim 1, characterized in that: The multi-degree-of-freedom motion platform comprises a telescopic unit (300), and an upper platform (100) and a lower platform (200) which are rotationally connected to the upper end and the lower end of the telescopic unit (300), respectively.

10. The multi-degree-of-freedom aircraft driving simulation training platform according to claim 9, characterized in that: The telescopic unit (300) comprises a telescopic execution unit, a telescopic driving unit and a telescopic control unit, wherein the telescopic driving unit drives the telescopic execution unit to operate so as to adjust the length of the telescopic execution unit, and the telescopic control unit controls the working state of the telescopic driving unit.

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