CN113359825A - Pilot model construction method based on flight simulator - Google Patents
Pilot model construction method based on flight simulator Download PDFInfo
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- CN113359825A CN113359825A CN202110608228.9A CN202110608228A CN113359825A CN 113359825 A CN113359825 A CN 113359825A CN 202110608228 A CN202110608228 A CN 202110608228A CN 113359825 A CN113359825 A CN 113359825A
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- 230000003595 spectral effect Effects 0.000 claims description 11
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- 238000005259 measurement Methods 0.000 claims description 4
- 238000003199 nucleic acid amplification method Methods 0.000 claims description 4
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- 238000013461 design Methods 0.000 description 5
- 230000006399 behavior Effects 0.000 description 4
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/10—Simultaneous control of position or course in three dimensions
- G05D1/101—Simultaneous control of position or course in three dimensions specially adapted for aircraft
Abstract
The application provides a pilot model construction method based on a flight simulator, which comprises the following steps: constructing a pilot model transfer function containing high-frequency characteristics: and simulating the driving process of the pilot on the airplane through the motion simulator to determine parameters in the transfer function of the pilot model, so as to obtain the transfer function of the pilot model. The pilot mathematical model identification method based on the six-degree-of-freedom motion simulator thoroughly solves the problem of differential modeling of the pilot mathematical model, and is simple, strong in operability, strong in universality and high in reliability.
Description
Technical Field
The application belongs to the technical field of flight quality assessment, and particularly relates to a pilot model construction method based on a flight simulator.
Background
The pilot mathematical model is a mathematical expression used for describing pilot behavior characteristics in the process of piloting the aircraft by a pilot, and is an important basis for designing a flight simulator, evaluating flight quality, designing human-computer efficiency, analyzing pilot operation behaviors and designing a control system. The airplane pilot model reflects the thinking and behavior process of the pilot as true as possible.
At present, a relatively wide mathematical model applied in the fields of flight control systems, flight quality assessment and the like is a simple pilot model consisting of a proportional link, a first-order lead-lag link and a pure delay link, and the model is simple and practical and is widely used by mass designers. However, there are many different views of the parameter settings in the model, and these empirical parameters are based on empirical data and do not give a specific proof of experiment process. In practice, for different design tasks, pilot models of different orders should be adopted, which is beneficial to simplifying the design process and simultaneously ensures that the pilot model information is not lost or ignored; for individualized design tasks, mathematical models of different pilot performances are different, and a special pilot model needs to be established according to specific situations of the pilot and the flight task.
For the reasons, a simple and rapid pilot model modeling method is very necessary in the fields of flight quality evaluation, pilot operation behavior analysis, control system design, flight simulator design and the like.
Disclosure of Invention
It is an object of the present application to provide a method of pilot model construction based on a flight simulator to solve or mitigate at least one of the problems described above.
In one aspect, the technical solution provided by the present application is: a method of constructing a pilot model based on a flight simulator, the method comprising:
constructing a pilot model transfer function containing high-frequency characteristics, wherein the transfer function is as follows:
wherein K is the amplification factor, e-τsIs a simple delay, TLAnd TITime constants for lead and lag, respectively, substituted by the pilot while manipulating the object; t is1、T2、
Respectively the time constant and the damping of the vibration link;
and simulating the driving process of the pilot on the airplane through the motion simulator to determine parameters in the transfer function of the pilot model, so as to obtain the transfer function of the pilot model.
Further, parameters in the pilot model transfer function are identified by a Fourier transform method or a spectral density method.
Further, the process of identifying the parameters in the pilot model transfer function by the fourier transform method comprises:
process measurements are performed over a time period T, with the pilot function evaluation expression being of the form:
in the formula: x (j ω) is the fourier transform of the calculated steering column deflection over the T period;
gamma (-j omega) is the Fourier transform of a given input signal in the compensation tracking task;
e (j omega) is the Fourier transform of the error signal;
and A (j omega) is Fourier transform of the input signal of the acceleration motion system.
Further, the process of identifying the parameters in the pilot model transfer function by the spectral density method comprises the following steps:
described by spectral density:
further, identifying the parameters in the pilot model transfer function by fourier transform or spectral density further includes the following steps:
constructing a harmonic input signal for forming a mark displayed on a display for tracking when a pilot is operating an aircraft, wherein the harmonic input signalThe number is:
wherein m is the number of harmonics, AmIs the amplitude of the harmonic input signal;
in order to be at the harmonic frequencies,
is the harmonic phase;
simulating, by a flight simulator, a pilot flying an aircraft to track the marker;
the flight simulator records data generated during the tracking process, and transfer function parameters of the pilot model are identified according to the data and the harmonic input signals.
In another aspect, the present application provides a data processing apparatus, the data processing including:
one or more processing devices;
a storage device for storing one or more programs,
the one or more programs, when executed by the one or more processing devices, cause the one or more processing devices to implement the method of any of claims 1-5.
Finally, the present application also provides a pilot model building system comprising: a flight simulator; a head-up display tracking signal generator; and a data processing apparatus as described above.
The pilot mathematical model identification method based on the six-degree-of-freedom motion simulator thoroughly solves the problem of differential modeling of the pilot mathematical model, and is simple, strong in operability, strong in universality and high in reliability.
Drawings
In order to more clearly illustrate the technical solutions provided by the present application, the following briefly introduces the accompanying drawings. It is to be expressly understood that the drawings described below are only illustrative of some embodiments of the invention.
FIG. 1 is a flow chart of a pilot model construction method of the present application.
Detailed Description
In order to make the implementation objects, technical solutions and advantages of the present application clearer, the technical solutions in the embodiments of the present application will be described in more detail below with reference to the drawings in the embodiments of the present application.
The method aims to provide a pilot mathematical model construction method based on a six-degree-of-freedom motion simulator so as to thoroughly solve the problem of differential modeling of the pilot mathematical model, and the method needs to have the advantages of simplicity, strong operability, strong universality and the like.
At low frequencies, the pilot model can be described by the following transfer functions:
k is the amplification factor, e-τsIs a simple delay, TLAnd TITime constants for the lead and lag respectively, substituted by the pilot while manipulating the object, S denotes the frequency domain and Y is the transfer dependent variable.
The above transfer function may be used to describe the pilot's maneuvering action throughout the frequency range when performing the compensated tracking task.
As shown in FIG. 1, two second-order links are added on the basis of the pilot model transfer function under the low frequency, so that the pilot model transfer function containing high-frequency characteristics is constructed, one is within the frequency range of 5-10 radians per second, and the other is within the frequency range of 12-20 radians per second, and the high-frequency characteristics of the central nervous system of the pilot are represented.
The transfer function of the pilot model has the following form:
where K is the amplification factor, e-τsIs a simple delay, TLAnd TIAre respectively flyingThe time constants of lead and lag substituted by the operator while manipulating the object; t is1、T2、
The time constant and the damping of the vibration link respectively determine the characteristics of mathematical models of different pilots.
In order to evaluate the characteristics of the pilot function, a frequency identification method is adopted for identifying the parameters of the pilot model, and a Fourier transform method and a spectral density method are used.
In particular, the fourier transform method is based on solving for the spectral density of pilot handling characteristics.
Process measurements are performed over a time period T, with the pilot function evaluation expression being of the form:
in the formula: x (j ω) is the fourier transform of the calculated steering column deflection over the T period;
gamma (-j omega) is the Fourier transform of a given input signal in the compensation tracking task;
e (j omega) is the Fourier transform of the error signal;
and A (j omega) is Fourier transform of the input signal of the acceleration motion system.
The above expression can also be described by spectral density:
to improve the accuracy of the results, when this method is employed, a set of harmonic signals of the form:
in the formula: m is the number of harmonics, m is 1, …,17 (or others);
Amis the amplitude of the harmonic input signal;
ωm＝2πnmthe/T is the harmonic frequency;
The number of harmonics making up the input signal and its frequency allocation should be such that the unpredictability requirements of the pilot signal and its characteristics approach those of the initial data. The value of the harmonic signal should conform to the normal distribution rule. To achieve a stable tracking state, a measurement start time delay t is introduced0At this point, the recording time is T + T for a total test procedure0。
In order to simplify calculation and quickly distinguish signal frequencies of all parts of the system, harmonic signal frequencies and test time adopted by the method are in one-to-one correspondence according to Fourier transform and need to be used in a coordinated mode.
The method for determining the pilot mathematical model based on the six-degree-of-freedom motion simulator is a complete set of pilot model modeling methods, and provides a low-order digital model and a high-order digital model general function of a pilot.
The parameter identification of the pilot mathematical model is obtained through a test method, and in order to obtain a complete pilot model, the test must be carried out on a conditional six-degree-of-freedom motion simulator, and the identification of a low-order model can be completed on the simulator without a motion platform.
On this basis, the present application also provides a data processing apparatus, the data processing including: one or more processing devices; storage means for storing one or more programs; the one or more programs, when executed by the one or more processing devices, cause the one or more processing devices to implement the methods as recited in any of the above.
Finally, the present application also provides a pilot model building system, comprising:
the high-precision flight simulator comprises a human feeling system (such as a steering column, a pedal and the like), a real-time simulation system, a vision system (such as a head-up display and a three-dimensional map) and a six-degree-of-freedom motion platform;
the head-up display tracking signal generator is used for tracking the harmonic signal set; and
the data processing device may be a computer or other device.
It should be noted that the high-order pilot model requires the test to be performed on a high-fidelity six-degree-of-freedom motion simulator.
The test implementation process and the data processing process are as follows:
in a specified time, a pilot uses a flight simulator to complete the environment tracking (keeping) task of the pilot, and records related data such as steering column displacement, aircraft incidence angle and three-axis Euler angle, aircraft three-axis overload and three-axis angular rate, tracked signals and tracking errors in detail according to the processing requirements of test data;
and (3) identifying the amplitude-phase-frequency characteristic of a 'low-order mathematical model' and the amplitude-phase-frequency characteristic of a 'high-order mathematical model' of the pilot according to the given pilot model transfer function and parameter identification method, further solving to obtain the high-order mathematical model and the low-order mathematical model of the pilot, and finally obtaining the pilot model suitable for low order and high order.
The pilot mathematical model identification method based on the six-degree-of-freedom motion simulator thoroughly solves the problem of differential modeling of the pilot mathematical model, and is simple, strong in operability, strong in universality and high in reliability. Compared with the existing pilot model which is generally a first-order mathematical model, the model identified by the method provided by the application is additionally provided with two second-order models, the defects of the existing pilot model in high-order research and design are overcome, the pilot model is obtained by accurately calculating the pilot model under an environmental test, and verification on the effectiveness and the correctness of the pilot model is indirectly included, so that the pilot model is different from the existing pilot model parameters depending on engineering experience, and the experience includes certain subjective factors to a certain extent. In addition, the pilot model identified by the method can reflect the difference of different pilots.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present application should be covered within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (7)
1. A pilot model construction method based on a flight simulator is characterized by comprising the following steps:
constructing a pilot model transfer function containing high-frequency characteristics, wherein the transfer function is as follows:
wherein K is the amplification factor, e-τsIs a simple delay, TLAnd TITime constants for lead and lag, respectively, substituted by the pilot while manipulating the object; t is1、T2、
Respectively the time constant and the damping of the vibration link;
and simulating the driving process of the pilot on the airplane through the motion simulator to determine parameters in the transfer function of the pilot model, so as to obtain the transfer function of the pilot model.
2. The flight simulator-based pilot model building method of claim 1, wherein the parameters in the pilot model transfer function are identified using fourier transform or spectral density.
3. The flight simulator-based pilot model building method of claim 2, wherein identifying the parameters in the pilot model transfer function by fourier transform comprises:
process measurements are performed over a time period T, with the pilot function evaluation expression being of the form:
in the formula: x (j ω) is the fourier transform of the calculated steering column deflection over the T period;
gamma (-j omega) is the Fourier transform of a given input signal in the compensation tracking task;
e (j omega) is the Fourier transform of the error signal;
and A (j omega) is Fourier transform of the input signal of the acceleration motion system.
4. The flight simulator-based pilot model building method of claim 3, wherein identifying the parameters in the pilot model transfer function by spectral density comprises:
described by spectral density:
5. a method of constructing a flight simulator based pilot model according to any one of claims 2 to 4, wherein identifying the parameters in the pilot model transfer function by Fourier transform or spectral density further comprises:
constructing a harmonic input signal for forming a marker displayed on a display for tracking by a pilot while maneuvering an aircraft, wherein the harmonic input signal is:
wherein m is the number of harmonics, AmIs the amplitude of the harmonic input signal;
in order to be at the harmonic frequencies,
is the harmonic phase;
simulating, by a flight simulator, a pilot flying an aircraft to track the marker;
the flight simulator records data generated during the tracking process, and transfer function parameters of the pilot model are identified according to the data and the harmonic input signals.
6. A data processing apparatus, characterized in that the data processing comprises:
one or more processing devices;
a storage device for storing one or more programs,
the one or more programs, when executed by the one or more processing devices, cause the one or more processing devices to implement the method of any of claims 1-5.
7. A pilot model building system, comprising:
a flight simulator;
a head-up display tracking signal generator; and
a data processing apparatus as claimed in claim 6.
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| CN105404152A (en) * | 2015-12-10 | 2016-03-16 | 中国人民解放军海军航空工程学院 | Flight quality prediction method for simulating subjective evaluation of pilot |
| CN107256278A (en) * | 2017-03-30 | 2017-10-17 | 南京航空航天大学 | The seamless interventional method of pilot and system under aircraft accident simulated environment |
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- 2021-06-01 CN CN202110608228.9A patent/CN113359825A/en active Pending
Patent Citations (3)
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|---|---|---|---|---|
| CN103594006A (en) * | 2013-11-15 | 2014-02-19 | 李宏图 | Aircraft simulation system and simulation method of aircraft simulation system |
| CN105404152A (en) * | 2015-12-10 | 2016-03-16 | 中国人民解放军海军航空工程学院 | Flight quality prediction method for simulating subjective evaluation of pilot |
| CN107256278A (en) * | 2017-03-30 | 2017-10-17 | 南京航空航天大学 | The seamless interventional method of pilot and system under aircraft accident simulated environment |
Non-Patent Citations (3)
| Title |
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| 王业光: "高频人机耦合振荡抑制方法", 《飞机设计》, pages 41 - 44 * |
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