Flying quality evaluation method, storage medium and program product

Abstract

The present application discloses a flight quality evaluation method, storage medium and program product, which relate to the field of aircraft technology. The flight quality evaluation method comprises: the present application responds to an evaluation instruction for a flight system, determines whether the evaluation instruction is an identification instruction, and if it is the identification instruction, obtains a flight signal, determines a corresponding flight system model based on the flight signal, and performs flight quality evaluation of the aircraft based on the flight system model to obtain an evaluation result; the flight signal is an excitation signal obtained and a response signal generated by the flight system during the flight of the aircraft, and the flight system model has a mapping relationship between the excitation signal and the response signal. Therefore, the present application can use the flight system model to evaluate the flight quality of the aircraft under the influence of flight environment factors and the aircraft's own state.

Description

Technical Field

[0001] The present application relates to the field of aircraft technology, and in particular to a flight quality evaluation method, a storage medium, and a program product. Background Art

[0002] Flying quality refers to the performance, stability and control characteristics of an aircraft during flight, and is related to the safety of the flight process. Currently, the main method is to establish a model in an ideal environment before the aircraft takes off, and use the established model to evaluate the flying quality. This method does not take into account the impact of environmental factors and the aircraft's own state on the flying quality, resulting in the current method being unable to evaluate the flying quality of the aircraft under the influence of flight environmental factors and the aircraft's own state. Summary of the invention

[0003] The main purpose of this application is to provide a flight quality evaluation method, storage medium and program product, aiming to solve the technical problem that the flight quality of an aircraft cannot be evaluated under the influence of flight environment factors and the aircraft's own status.

[0004] To achieve the above objectives, the present application proposes a flight quality evaluation method, the method comprising:

[0005] In response to an evaluation instruction for a flight system, determining whether the evaluation instruction is an identification instruction;

[0006] If it is the identification instruction, then obtaining a flight signal, wherein the flight signal is an excitation signal obtained and a response signal generated by the flight system during the flight of the aircraft;

[0007] Based on the flight signal, determining a corresponding flight system model, wherein the flight system model has a mapping relationship between the excitation signal and the response signal;

[0008] Based on the flight system model, the flight quality of the aircraft is evaluated to obtain an evaluation result.

[0009] In one embodiment, the step of determining the corresponding flight system model based on the flight signal comprises:

[0010] Performing a time-frequency domain transformation on the flight signal to obtain a flight frequency domain signal, wherein the flight frequency domain signal includes a flight frequency domain excitation signal and a flight frequency domain response signal;

[0011] Performing power spectrum estimation on the flight frequency domain excitation signal and the flight frequency domain response signal to obtain a target transfer function;

[0012] Based on a preset parameter tuning method, the target parameters of the flight system model are determined with the goal of minimizing the flight frequency domain response error, wherein the flight frequency domain response error is the difference between the measured frequency domain response data and the predicted frequency domain response data calculated by the target transfer function;

[0013] The target parameters are used as model parameters of the flight system model to determine the corresponding flight system model.

[0014] In one embodiment, the step of performing power spectrum estimation on the flight frequency domain excitation signal and the flight frequency domain response signal to obtain a target transfer function comprises:

[0015] Based on a preset overlap rate, segmenting the flight frequency domain excitation signal and the flight frequency domain response signal to obtain a flight frequency domain excitation signal and a flight frequency domain response signal with a preset number of segments;

[0016] Based on a preset window function, calculate a first autopower spectral density of each flight frequency domain excitation signal, a second autopower spectral density of each flight frequency domain response signal, and a cross-power spectral density between each flight frequency domain excitation signal and each flight frequency domain response signal;

[0017] Calculating average values ​​of the first autopower spectral density, the second autopower spectral density, and the cross-power spectral density to obtain a first average autopower spectral density, a second average autopower spectral density, and an average cross-power spectral density;

[0018] The target transfer function is determined based on the average cross power spectral density, the first average auto power spectral density, and the second average auto power spectral density.

[0019] In one embodiment, after the step of determining the corresponding flight system model based on the flight signal, the method further includes:

[0020] Based on the flight system model, determining observer parameters of a preset disturbance observer to obtain a first disturbance observer;

[0021] Receiving first attitude angle information and first disturbance value acquired by the first disturbance observer;

[0022] Disturbance control is performed based on the first attitude angle information and the first disturbance value.

[0023] In one embodiment, the step of performing disturbance control based on the first attitude angle information and the first disturbance value includes:

[0024] Acquire first desired attitude angle information of the aircraft controller;

[0025] Calculating a first attitude angle error based on the first expected attitude angle information and the first attitude angle information;

[0026] Based on the first attitude angle error, optimizing the aircraft controller by a preset nonlinear optimization method, wherein a gain of the nonlinear optimization method is negatively correlated with a magnitude of the first attitude angle error;

[0027] Based on the first disturbance value, disturbance compensation is performed on the aircraft controller to achieve disturbance control.

[0028] In one embodiment, after the step of responding to the evaluation instruction for the flight system and determining whether the evaluation instruction is an identification instruction, the method further includes:

[0029] If it is not the identification instruction, receiving the second attitude angle information and the second disturbance value sent by the preset disturbance observer;

[0030] Acquire second desired attitude angle information of the aircraft controller;

[0031] Calculating a second attitude angle error based on the second desired attitude angle information and the second attitude angle information;

[0032] Determining whether the second posture angle error is within a preset error range;

[0033] If the second attitude angle error is not within the preset error range, adjusting the observer parameters, and returning to the step of receiving the second attitude angle information and the second disturbance value sent by the preset disturbance observer, until the second attitude angle error is within the preset error range, and the parameter adjustment is completed;

[0034] The preset disturbance observer that has completed the observer parameter adjustment is used as the second disturbance observer.

[0035] In one embodiment, after the step of using the preset disturbance observer that has completed the observer parameter adjustment as the second disturbance observer, the method further includes:

[0036] receiving a target disturbance value sent by the second disturbance observer;

[0037] Calculating a disturbance difference between the target disturbance value and a preset reference disturbance value;

[0038] Determining whether the disturbance difference exceeds a preset model change threshold;

[0039] If the disturbance difference is higher than the preset model change threshold, it is determined that the flight system model has changed.

[0040] In one embodiment, the step of evaluating the flight quality of the aircraft based on the flight system model to obtain the evaluation result includes:

[0041] Get the control parameters of the aircraft controller;

[0042] determining a first transfer function of the aircraft controller based on the control parameter;

[0043] determining a second transfer function corresponding to the flight system model;

[0044] Based on the first transfer function and the second transfer function, a shear frequency and a phase margin are calculated;

[0045] Based on the shear frequency and the phase margin, the flight quality of the aircraft is evaluated to obtain an evaluation result.

[0046] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the flight quality evaluation method described above are implemented.

[0047] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the steps of the flight quality evaluation method described above are implemented.

[0048] One or more technical solutions proposed in this application have at least the following technical effects:

[0049] The present application responds to an evaluation instruction for a flight system and determines whether the evaluation instruction is an identification instruction. If it is the identification instruction, a flight signal is acquired, wherein the flight signal is an excitation signal obtained and a response signal generated by the flight system during the flight of the aircraft. Based on the flight signal, a corresponding flight system model is determined, wherein the flight system model has a mapping relationship between the excitation signal and the response signal. Based on the flight system model, the flight quality of the aircraft is evaluated to obtain an evaluation result.

[0050] In order to evaluate the flight quality of an aircraft under the influence of flight environmental factors and the aircraft's own state, it is necessary to establish a flight system model of the aircraft under the influence of environmental factors and its own state. The flight signal is the excitation signal obtained by the flight system and the response signal generated. Therefore, the flight signal generated during the flight of the aircraft can be obtained, and a flight system model with a mapping relationship between the excitation signal and the response signal can be obtained based on the flight signal. And because the flight signal is generated during the flight of the aircraft, the obtained flight system model can be used to describe the mapping relationship between the excitation signal and the response signal after the aircraft is affected by environmental factors and its own state during the flight, so that the flight quality of the aircraft can be evaluated under the influence of flight environmental factors and the aircraft's own state through the flight system model. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0052] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0053] Figure 1 A flowchart of the first embodiment of the flight quality evaluation method of the present application is provided;

[0054] Figure 2 A first scenario schematic diagram is provided for the first embodiment of the flight quality evaluation method of the present application;

[0055] Figure 3 A second scenario schematic diagram is provided for the first embodiment of the flight quality evaluation method of the present application;

[0056] Figure 4 A flow chart of the second embodiment of the flight quality evaluation method of the present application;

[0057] Figure 5 A flowchart of the third embodiment of the flight quality evaluation method of the present application is provided;

[0058] Figure 6 A first scenario schematic diagram is provided for the third embodiment of the flight quality evaluation method of the present application;

[0059] Figure 7 A second scenario schematic diagram is provided for the third embodiment of the flight quality evaluation method of the present application;

[0060] Figure 8A third scenario schematic diagram is provided for the third embodiment of the flight quality evaluation method of the present application.

[0061] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0062] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0063] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0064] It should be noted that the execution subject of this embodiment can be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, a flight quality evaluation device, etc. The following takes the flight quality evaluation device as an example to illustrate this embodiment and the following embodiments.

[0065] Based on this, the present application embodiment provides a flight quality evaluation method, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the flying quality evaluation method of the present application.

[0066] In this embodiment, the flight quality evaluation method includes steps S10 to S40:

[0067] Step S10, in response to an evaluation instruction for the flight system, determining whether the evaluation instruction is an identification instruction;

[0068] Flying qualities evaluation refers to the process of evaluating the handling characteristics, stability and responsiveness of an aircraft. Flying qualities evaluation ensures that the aircraft can operate safely and efficiently under various flight conditions, thereby ensuring flight safety and optimizing flight performance.

[0069] It is understandable that there are two methods for evaluating flight quality: those based on system identification and those not based on system identification. In order to accurately evaluate flight quality, it is necessary to accurately describe the dynamic characteristics of the flight system, and the dynamic characteristics of the flight system can be represented by a mathematical model. Therefore, when an evaluation instruction for the flight system is received, it is necessary to respond to the evaluation instruction and determine whether the evaluation instruction is an identification instruction.

[0070] Step S20, if it is the identification instruction, obtaining a flight signal, wherein the flight signal is an excitation signal obtained and a response signal generated by the flight system during the flight of the aircraft;

[0071] It should be noted that the flight signal can be divided into an excitation signal and a response signal. The excitation signal is a signal input into the flight system for controlling the aircraft or a signal of manual operation, such as a signal to change the thrust of the aircraft engine, or a specific signal such as a pulse or a sine wave applied in a laboratory or ground test. In this embodiment, the excitation signal is a swept frequency signal. The response signal is the output or reaction generated by the flight system after receiving the excitation signal. In this embodiment, the response signal is the output generated by the flight system after receiving the swept frequency signal.

[0072] The frequency sweep signal can be an automatic frequency sweep signal or a manual frequency sweep signal. The automatic frequency sweep signal is a signal whose frequency changes linearly or nonlinearly with time. Figure 2 The automatic frequency sweep signal may cause the aircraft to vibrate, resulting in potential safety hazards. Therefore, this embodiment uses a manual frequency sweep method.

[0073] Manual frequency sweeping actually requires the pilot to operate the remote control to simulate the frequency sweeping action manually. One of the reasons for doing so is to prevent the automatic frequency sweeping signal controller from being unable to withstand the pressure and causing the aircraft to crash. The disadvantage of manual frequency sweeping is often that the excitation is not sufficient and does not meet the requirements of the optimal input signal for identification, that is, the excitation signal generated by manual frequency sweeping is a weak excitation signal.

[0074] In this embodiment, the manual frequency sweep needs to meet the following requirements: 1. The starting point and the end point of the maneuver are in a trim state; 2. There are two high-quality low-frequency periodic inputs in the data; 3. The frequency increases regularly and smoothly.

[0075] It is understandable that most of the current flight quality evaluations rely on pre-flight modeling, which cannot reflect the actual state of the aircraft well. Even as the aircraft structure ages, the current evaluation system will gradually become ineffective. In addition, the current flight quality evaluation system is implemented by building a model under an ideal environment, and it is unable to evaluate the flight quality of the aircraft under conditions such as strong wind disturbances and structural damage.

[0076] In order to evaluate the flight quality of an aircraft under the influence of flight environment factors and the aircraft's own state, it is necessary to identify the aircraft's flight system under the influence of environmental factors and the aircraft's own state. Therefore, it is necessary to obtain the flight signal of the aircraft during actual flight, so as to identify the aircraft's flight system under this state.

[0077] Step S30, determining a corresponding flight system model based on the flight signal, wherein the flight system model has a mapping relationship between the excitation signal and the response signal;

[0078] It should be noted that the flight system model in this embodiment is a simplified model of the fixed-wing pitch angle after decoupling, and its expression is:

[0079]

[0080]

[0081] in, is the pitch angle, is the first-order derivative of the pitch angle with respect to time, q is the component of the angular velocity on the y-axis in the body coordinate system, that is, the pitch angle rate, is the first-order derivative of the pitch angular rate with respect to time, is the output of the controller, and is the identification coefficient of the flight system model, and The calculation expression is:

[0082]

[0083]

[0084] in, is the atmospheric density, V is the relative wind speed, S is the reference area, is the average aerodynamic chord length, is the moment of inertia of the aircraft around the y-axis, is the dimensionless longitudinal stability coefficient, is the dimensionless elevator control coefficient.

[0085] It is understandable that a complete flight system model usually contains multiple interrelated subsystems, and the interactions between these subsystems make the model very complex. Therefore, it is necessary to decouple and simplify the model of the flight system to improve computational efficiency, enhance the interpretability and applicability of the model, and simplify control design.

[0086] Since the present embodiment has obtained the excitation signal obtained by the flight system and the response signal generated during the flight of the aircraft, a flight system model having a mapping relationship between the excitation signal and the response signal can be obtained through the obtained excitation signal and response signal.

[0087] In a feasible implementation manner, a specific implementation manner of determining a corresponding flight system model based on the flight signal may also be:

[0088] Performing a time-frequency domain transformation on the flight signal to obtain a flight frequency domain signal, wherein the flight frequency domain signal includes a flight frequency domain excitation signal and a flight frequency domain response signal; performing power spectrum estimation on the flight frequency domain excitation signal and the flight frequency domain response signal to obtain a target transfer function; based on a preset parameter tuning method, determining the target parameters of the flight system model with the minimum flight frequency domain response error as the goal, wherein the flight frequency domain response error is the difference between the measured frequency domain response data and the predicted frequency domain response data calculated by the target transfer function; using the target parameters as model parameters of the flight system model to determine the corresponding flight system model.

[0089] It should be noted that, in this embodiment, the identification of the flight system is performed based on frequency domain identification. The time domain data can be converted into frequency domain data by Fourier transform or linear frequency modulation z transform. In this embodiment, linear frequency modulation z transform is used to convert the time domain data into frequency domain data in order to increase the spectral resolution.

[0090] It can be understood that compared with time domain data, frequency domain data can use fewer data points to describe the main features of the signal. Since frequency domain identification is based on the linear assumption, it is more suitable for the approximately linear flight system in this embodiment, thereby reducing the number of model parameters. Through Fourier transform, linear frequency modulation z transform or other frequency domain transformation techniques, redundant information and high-frequency noise in the time domain signal can be effectively removed, so that this embodiment has a stronger ability to resist noise.

[0091] It should also be noted that this embodiment determines the transfer function of the flight system model through power spectrum estimation to describe the mapping relationship between the excitation signal and the response signal in the flight system. The transfer function is a mathematical model used to describe the relationship between the input and output of a linear time-invariant system, and the basic principle of power spectrum estimation is that the transfer function is equal to the cross-power spectrum density divided by the self-power spectrum density, and its expression is:

[0092]

[0093] in, is the cross power spectral density of x and y, is the autopower spectral density of x, is the autopower spectral density of y, It is the power spectrum estimate, Estimation is a type of error estimate in numerical analysis and finite element methods for partial differential equations.

[0094] It is understandable that there will be a certain error between the frequency domain response data obtained by the target transfer function and the measured frequency domain response data. In order to more accurately describe the mapping relationship between the excitation signal and the response signal, it is necessary to determine the identification coefficient so that the difference between the frequency domain response data predicted by the target transfer function and the measured frequency domain response data is minimized.

[0095] Therefore, it is necessary to determine the target parameters of the flight system model, namely the identification coefficient, based on a preset parameter tuning method with the goal of minimizing the flight frequency domain response error. In this embodiment, the corresponding identification coefficient is obtained by the least squares method.

[0096] The target parameters are used as the model parameters of the flight system model, and the corresponding flight system model can be determined. Figure 3 .

[0097] In a feasible implementation manner, power spectrum estimation is performed on the flight frequency domain excitation signal and the flight frequency domain response signal to obtain an implementation manner of a target transfer function, which may also be:

[0098] Based on a preset overlap rate, segmenting the flight frequency domain excitation signal and the flight frequency domain response signal to obtain a flight frequency domain excitation signal and a flight frequency domain response signal with a preset number of segments;

[0099] Based on a preset window function, the first autopower spectral density of each flight frequency domain excitation signal, the second autopower spectral density of each flight frequency domain response signal, and the cross-power spectral density between each flight frequency domain excitation signal and each flight frequency domain response signal are calculated; the average values ​​of the first autopower spectral density, the second autopower spectral density, and the cross-power spectral density are calculated to obtain a first average autopower spectral density, a second average autopower spectral density, and an average cross-power spectral density; based on the average cross-power spectral density, the first average autopower spectral density, and the second average autopower spectral density, the target transfer function is determined.

[0100] It should be noted that the window function used in this embodiment may be a Hanning window, a Hamming window, etc. When the period of the signal does not completely match the sampling window length, it will cause spectrum leakage in which the energy is diffused to adjacent frequency components. This embodiment estimates each power spectrum by using the Wilson method of windowed Fourier transform.

[0101] It is understandable that spectrum leakage is mainly caused when the signal period does not completely match the sampling window length, causing energy to spread to adjacent frequency components. Through segmentation processing, the length of each segment can be selected more flexibly, so that more segments can contain complete or nearly complete periods. Combined with windowing processing, it can effectively reduce the energy diffusion caused by non-integer period sampling.

[0102] Therefore, this implementation segments and overlaps the signal, minimizes spectrum leakage by applying a window function, and then calculates and averages the power spectrum density of each segment, thereby determining the target transfer function based on the average cross-power spectrum density, the first average auto-power spectrum density, and the second average auto-power spectrum density.

[0103] Step S40: evaluating the flight quality of the aircraft based on the flight system model to obtain an evaluation result.

[0104] It can be understood that, since the flight system model has a mapping relationship between the excitation signal and the response signal, after the flight system model of the aircraft is obtained, the flight quality of the aircraft can be evaluated based on the flight system model.

[0105] In a feasible implementation manner, the flight quality evaluation of the aircraft is performed based on the flight system model, and the implementation manner of obtaining the evaluation result may also be:

[0106] The control parameters of the aircraft controller are obtained, and based on the control parameters, a first transfer function of the aircraft controller is determined, and a second transfer function corresponding to the flight system model is determined; based on the first transfer function and the second transfer function, a shear frequency and a phase margin are calculated; based on the shear frequency and the phase margin, a flight quality evaluation of the aircraft is performed to obtain an evaluation result.

[0107] It should be noted that the shear frequency is related to the response speed of the flight system, and the phase margin is related to the stability of the flight system. The shear frequency and phase margin can be calculated through the transfer function of the aircraft system model and the transfer function of the flight system controller. The calculation formula can be expressed as:

[0108]

[0109] in, is the model transfer function of the flight system, is the transfer function of the aircraft controller, is the transfer function of the loop.

[0110] The formula relationship of shear frequency is:

[0111]

[0112] Where j is the imaginary unit, is the shear frequency.

[0113]

[0114] in, is the phase margin (phase margin), Used to express the phase angle of a transfer function at a specific frequency.

[0115] The control parameters are the PID (Proportional-Integral-Derivative) parameters of the aircraft controller.

[0116] It is understandable that in order to calculate the shear frequency and the phase margin, it is necessary to determine the transfer function of the flight system model and the transfer function of the aircraft controller. The transfer function of the flight system model can be obtained by identifying the system, and the transfer function of the aircraft controller can be obtained by the PID parameters of the controller.

[0117] Therefore, this embodiment can calculate the shear frequency and the phase margin through the first transfer function of the aircraft controller and the second transfer function corresponding to the flight system model, and evaluate the flight quality of the aircraft based on the shear frequency and the phase margin to obtain an evaluation result.

[0118] In summary, the present embodiment responds to an evaluation instruction for a flight system and determines whether the evaluation instruction is an identification instruction. If it is the identification instruction, a flight signal is acquired, wherein the flight signal is an excitation signal obtained and a response signal generated by the flight system during the flight of the aircraft. Based on the flight signal, a corresponding flight system model is determined, wherein the flight system model has a mapping relationship between the excitation signal and the response signal. Based on the flight system model, the flight quality of the aircraft is evaluated to obtain an evaluation result.

[0119] In order to evaluate the flight quality of an aircraft under the influence of flight environmental factors and the aircraft's own state, it is necessary to establish a flight system model of the aircraft under the influence of environmental factors and its own state. The flight signal is the excitation signal obtained by the flight system and the response signal generated. Therefore, the flight signal generated during the flight of the aircraft can be obtained, and the flight signal is converted into the time-frequency domain. Based on the flight signal, a flight system model with a mapping relationship between the excitation signal and the response signal in the frequency domain is obtained.

[0120] The flight signal is generated during the flight of the aircraft, and the obtained flight system model can be used to describe the mapping relationship between the excitation signal and the response signal after the aircraft is affected by environmental factors and its own state during the flight. Therefore, this embodiment can evaluate the flight quality of the aircraft under conditions such as icing of the wings, mechanical aging, and failure. And because the flight information is obtained during the flight, this embodiment can identify the system online and apply the identification results to parameter adjustment, so that the flight quality of the aircraft can be evaluated online under the influence of flight environmental factors and the aircraft's own state through the flight system model.

[0121] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can refer to the above introduction, and will not be repeated later. Figure 4 After step S30, the flight quality evaluation method further includes steps S31 to S33:

[0122] Step S31, based on the flight system model, determining observer parameters of a preset disturbance observer to obtain a first disturbance observer;

[0123] It should be noted that the preset disturbance observer is a disturbance observer that has not yet been parameter adjusted, and the first disturbance observer is a disturbance observer obtained by using the identification parameters in the flight system model as the parameters of the preset disturbance observer. The simplified model formula of the aircraft is expressed in the disturbance observer as:

[0124]

[0125] Where y is the component of the angular velocity on the y-axis in the body coordinate system, that is, the pitch angular rate, is the first-order derivative of the pitch angular rate with respect to time, is the output of the controller, and is the identification coefficient of the flight system model, and equal, and Equal. Based on the aircraft system model, the disturbance value can be added, and its expression is:

[0126]

[0127] in, is the output of the controller, is the disturbance value, is the first-order derivative of the disturbance with respect to time, is the state vector, and its expression is , is the first-order derivative of the state vector with respect to time; A is the system matrix, B is the input matrix, C is the output matrix, and E is the disturbance matrix. The expressions of each matrix are:

[0128] , , , .

[0129] It is understandable that the disturbance observer relies on accurate modeling of the system dynamic characteristics. If there is a difference between the model and the actual system, the observer will not be able to accurately estimate the disturbance. Therefore, this embodiment determines the observer parameters of the preset disturbance observer based on the determined flight system model, obtains the first disturbance observer, and estimates the disturbance value through the first disturbance observer.

[0130] Step S32, receiving the first attitude angle information and the first disturbance value acquired by the first disturbance observer;

[0131] It should be noted that the disturbance observer of this embodiment is an attitude loop disturbance observer, so the first disturbance observer can estimate the attitude angle information of the aircraft in addition to the disturbance value. The attitude angle information is information such as the angle and angular velocity of the heading angle, pitch angle and roll angle of the aircraft. In this embodiment, the attitude angle information is the pitch angle rate of the aircraft.

[0132] Step S33: performing disturbance control based on the first attitude angle information and the first disturbance value.

[0133] It is understandable that various factors such as environmental changes and load fluctuations will cause disturbances, interfere with the normal operation of the system, and cause the output to deviate from the expected value. Therefore, in order to mitigate the impact of disturbances, it is necessary to obtain the disturbance value and the first attitude angle information for disturbance control.

[0134] In a feasible implementation manner, the implementation manner of performing disturbance control based on the first attitude angle information and the first disturbance value may also be:

[0135] Acquire first expected attitude angle information of an aircraft controller, calculate a first attitude angle error based on the first expected attitude angle information and the first attitude angle information, optimize the aircraft controller based on the first attitude angle error through a preset nonlinear optimization method, wherein a gain of the nonlinear optimization method is negatively correlated with a magnitude of the first attitude angle error, and perform disturbance compensation on the aircraft controller based on the first disturbance value to achieve disturbance control.

[0136] It should be noted that the first expected attitude angle information is the attitude angle information expected to be obtained when the flight system performs flight control of the aircraft, the first attitude angle information is the attitude angle information actually obtained by the first disturbance observer, and the first attitude angle error is the error between the expected attitude angle information and the actually generated attitude angle information.

[0137] It is understandable that when the control system is controlling, there will be an error between the expected control effect and the actual control effect, which will affect the flight quality. Therefore, it is necessary to optimize the flight quality of the aircraft based on a preset optimization method.

[0138] Since the robustness of the traditional linear attitude controller is poor, in order to improve its robustness, this embodiment performs nonlinear optimization on the error of the linear controller, and its expression is:

[0139]

[0140] Among them, they are Proportional gain, Integral gain and is the differential gain, all of which are positive values. is the pitch angular velocity error, and is the linear region gain, and is the nonlinear region gain, is the disturbance compensation corresponding to the disturbance value. fal is a nonlinear optimization function, which is essentially Apply some kind of transformation to achieve the goal of large error and small gain or small error and large gain.

[0141] When the system error is large, it means that the flight system state is far from the expected value. If a larger gain is used at this time, it may cause the system response to be too aggressive, resulting in excessive control actions, which may cause oscillation or even instability. When the system error is small, it means that the system is very close to the expected state. At this time, appropriately increasing the gain can help eliminate the remaining small errors more quickly, improve the steady-state accuracy, and enable the system to converge quickly to the set point.

[0142] Therefore, this embodiment uses nonlinear optimization methods and disturbance compensation. When the error is large, a small gain is used to make the control action more gentle, avoid over-adjustment, reduce the risk of overshoot and oscillation, and ensure that the system gradually approaches the target. When the error is small, a large gain is used to accelerate the adjustment process, reduce the steady-state error, and improve the overall performance of the system.

[0143] In summary, this embodiment determines the observer parameters of the preset disturbance observer based on the flight system model, obtains the first disturbance observer, receives the first attitude angle information and the first disturbance value acquired by the first disturbance observer, and performs disturbance control based on the first attitude angle information and the first disturbance value.

[0144] Since the disturbance interferes with the normal operation of the flight system, causing the output to deviate from the expected value, in order to make the output of the flight system close to the expected value, the disturbance value needs to be determined. The disturbance observer relies on the accurate modeling of the dynamic characteristics of the system. Therefore, this embodiment determines the observer parameters of the preset disturbance observer based on the flight system model to obtain the first disturbance observer, and obtains the first disturbance value through the first disturbance observer, thereby performing disturbance control.

[0145] The robustness of the traditional linear attitude controller is poor, therefore, this embodiment performs disturbance control based on the attitude angle error through nonlinear optimization. Since this embodiment performs nonlinear optimization based on a simplified model, the quality optimization method of this embodiment is more robust, can better adapt to various working modes of the aircraft, and greatly reduces the difficulty of parameter adjustment.

[0146] Based on the first embodiment of the present application and the second embodiment of the present application, the same or similar contents as the above-mentioned embodiment 1 and embodiment 2 can refer to the above introduction, and will not be repeated later. Figure 5 After step S10, the flight quality evaluation method further includes steps A11 to A16:

[0147] Step A11, if it is not the identification instruction, receiving the second attitude angle information and the second disturbance value sent by the preset disturbance observer;

[0148] It should be noted that the second attitude angle information and the second disturbance value are obtained by a preset disturbance observer when flight system identification is not required.

[0149] It is understandable that if the evaluation instruction is not an identification instruction, there is no need to identify the system, and the quality evaluation is performed only through the disturbance observer. Figure 6 Therefore, when the evaluation instruction is not an identification instruction, this embodiment receives the second attitude angle information and the second disturbance value sent by the preset disturbance observer.

[0150] Step A12, obtaining second desired attitude angle information of the aircraft controller;

[0151] It should be noted that the second expected attitude angle information is the attitude angle information of the aircraft controller obtained when the flight system identification is not required.

[0152] Step A13, calculating a second attitude angle error based on the second expected attitude angle information and the second attitude angle information;

[0153] It is understandable that, since the flight system is not identified, the preset disturbance observer cannot accurately estimate the attitude angle and the disturbance value. Therefore, it is necessary to calculate the second attitude angle error through the second expected attitude angle information and the second attitude angle information to optimize the parameters of the preset disturbance observer.

[0154] Step A14, determining whether the second posture angle error is within a preset error range;

[0155] It is understandable that when the disturbance observer estimates more accurately, the second attitude angle error will be smaller. Therefore, it can be determined whether the disturbance observer has made a more accurate estimate by determining whether the second attitude angle error is within a preset error range.

[0156] Step A15, if the second attitude angle error is not within the preset error range, adjusting the observer parameters, and returning to the step of receiving the second attitude angle information and the second disturbance value sent by the preset disturbance observer, until the second attitude angle error is within the preset error range, and the parameter adjustment is completed;

[0157] It is understandable that, since it is possible to determine whether the disturbance observer has made a relatively accurate estimate by determining whether the second attitude angle error is within a preset error range, when system identification is not performed, the parameters of the disturbance observer can be adjusted, and it can be determined whether the adjusted disturbance observer has made an accurate disturbance value and attitude angle estimate. If it is determined that the disturbance observer's estimate is not accurate enough, the parameters of the disturbance observer are re-adjusted until the disturbance observer meets the estimation accuracy requirement. At this time, it can be determined that the disturbance observer has converged. The convergence of the disturbance observer can be referred to. Figure 7 .

[0158] Step A16: using the preset disturbance observer after the observer parameter adjustment as the second disturbance observer.

[0159] It can be understood that the preset disturbance observer that completes the observer parameter adjustment can accurately estimate the attitude angle and the disturbance value. Therefore, it can be used as the second disturbance observer, and the flight quality can be evaluated through the disturbance value obtained by the second disturbance observer.

[0160] In a feasible implementation manner, the implementation manner after using the preset disturbance observer that completes the observer parameter adjustment as the second disturbance observer may also be:

[0161] Receive the target disturbance value sent by the second disturbance observer, calculate the disturbance difference between the target disturbance value and a preset reference disturbance value, determine whether the disturbance difference exceeds a preset model change threshold, and if the disturbance difference is higher than the preset model change threshold, determine that the flight system model has changed.

[0162] It should be noted that the preset reference disturbance value is the disturbance value obtained when the aircraft is flying in the best state, that is, the low disturbance value when there is no interference from other factors that causes the disturbance value to change. Figure 8 .

[0163] It is understandable that, without the influence of other factors, the disturbance value of the aircraft during flight will fluctuate within a certain range. When there are factors such as strong wind disturbance or changes in the structure of the aircraft itself, the model of the flight system will change, thereby causing the generated disturbance value to change. Therefore, this embodiment determines whether the disturbance difference between the target disturbance value and the preset reference disturbance value is within a preset range. If the disturbance difference is higher than the preset model change threshold, it is determined that the flight system model has changed.

[0164] In summary, in this embodiment, when the evaluation instruction is not an identification instruction, the second attitude angle information and the second disturbance value sent by the preset disturbance observer are received, the second expected attitude angle information of the aircraft controller is obtained, and the second attitude angle error is calculated based on the second expected attitude angle information and the second attitude angle information, and it is determined whether the second attitude angle error is within a preset error range. If the second attitude angle error is not within the preset error range, the observer parameters are adjusted, and the step of receiving the second attitude angle information and the second disturbance value sent by the preset disturbance observer is returned until the second attitude angle error is within the preset error range. The parameter adjustment is completed, and the preset disturbance observer that has completed the observer parameter adjustment is used as the second disturbance observer, and the flight quality is evaluated by the disturbance value estimated by the second disturbance observer.

[0165] Because strong wind disturbances and structural changes of the aircraft itself will cause the model of the flight system to change, so that the disturbance value obtained by the disturbance observer changes. Therefore, it is possible to judge whether the flight system model has changed by the disturbance value. In order to accurately estimate the model, it is necessary to adjust the parameters of the disturbance observer so that the disturbance observer can accurately estimate the disturbance. Therefore, this embodiment calculates the difference between the expected attitude angle information and the actual attitude angle information to obtain the attitude angle error, and adjusts the parameters of the disturbance observer based on whether the attitude angle error is within the preset range. Therefore, by determining whether the difference between the disturbance value obtained by the disturbance observer and the reference disturbance value is within the preset range, it is determined whether there are other factors that cause the aircraft system model to change. Therefore, this embodiment can judge whether the flight system model has changed only by the disturbance value without system identification.

[0166] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the flight quality evaluation method of the present application. More simple transformations based on this technical concept are all within the scope of protection of the present application.

[0167] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the flight quality evaluation method in the above-mentioned embodiment.

[0168] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM: Random Access Memory), a read-only memory (ROM: Read Only Memory), an erasable programmable read-only memory (EPROM: Erasable Programmable Read Only Memory or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM: CD-Read Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency: Radio Frequency), etc., or any suitable combination of the above.

[0169] The computer-readable storage medium may be included in the flying quality evaluation device; or may exist independently without being assembled into the flying quality evaluation device.

[0170] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the flying quality evaluation device, the flying quality evaluation device executes the flying quality evaluation method.

[0171] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0172] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to each embodiment of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0173] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0174] The readable storage medium provided by the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned flight quality evaluation method, and can solve the technical problem that the flight quality of the aircraft cannot be evaluated under the influence of flight environment factors and the aircraft's own state. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by the present application are the same as the beneficial effects of the flight quality evaluation method provided by the above-mentioned embodiment, and will not be repeated here.

[0175] The present application also provides a computer program product, including a computer program, which implements the steps of the above-mentioned flight quality evaluation method when executed by a processor.

[0176] The computer program product provided by the present application can solve the technical problem that the flight quality of an aircraft cannot be evaluated under the influence of flight environment factors and the aircraft's own state. Compared with the prior art, the beneficial effects of the computer program product provided by the present application are the same as the beneficial effects of the flight quality evaluation method provided by the above embodiment, and will not be repeated here.

[0177] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A method for evaluating flight quality, characterized in that: The method includes: In response to an evaluation instruction for a flight system, determining whether the evaluation instruction is an identification instruction; If it is the identification instruction, then obtaining a flight signal, wherein the flight signal is an excitation signal obtained and a response signal generated by the flight system during the flight of the aircraft; Based on the flight signal, determining a corresponding flight system model, wherein the flight system model has a mapping relationship between the excitation signal and the response signal; Wherein, the step of determining the corresponding flight system model based on the flight signal comprises: Performing a time-frequency domain transformation on the flight signal to obtain a flight frequency domain signal, wherein the flight frequency domain signal includes a flight frequency domain excitation signal and a flight frequency domain response signal; Performing power spectrum estimation on the flight frequency domain excitation signal and the flight frequency domain response signal to obtain a target transfer function; The step of performing power spectrum estimation on the flight frequency domain excitation signal and the flight frequency domain response signal to obtain a target transfer function comprises: Based on a preset overlap rate, segmenting the flight frequency domain excitation signal and the flight frequency domain response signal to obtain a flight frequency domain excitation signal and a flight frequency domain response signal with a preset number of segments; Based on a preset window function, calculate a first autopower spectral density of each flight frequency domain excitation signal, a second autopower spectral density of each flight frequency domain response signal, and a cross-power spectral density between each flight frequency domain excitation signal and each flight frequency domain response signal; Calculating average values ​​of the first autopower spectral density, the second autopower spectral density, and the cross-power spectral density to obtain a first average autopower spectral density, a second average autopower spectral density, and an average cross-power spectral density; determining the target transfer function based on the average cross power spectral density, the first average auto power spectral density, and the second average auto power spectral density; Based on a preset parameter tuning method, the target parameters of the flight system model are determined with the goal of minimizing the flight frequency domain response error, wherein the flight frequency domain response error is the difference between the measured frequency domain response data and the predicted frequency domain response data calculated by the target transfer function; Using the target parameters as model parameters of the flight system model to determine the corresponding flight system model; Based on the flight system model, the flight quality of the aircraft is evaluated to obtain an evaluation result.

2. The method according to claim 1, characterized in that After the step of determining the corresponding flight system model based on the flight signal, the method further includes: Based on the flight system model, determining observer parameters of a preset disturbance observer to obtain a first disturbance observer; Receiving first attitude angle information and first disturbance value acquired by the first disturbance observer; Disturbance control is performed based on the first attitude angle information and the first disturbance value.

3. The method according to claim 2, characterized in that: The step of performing disturbance control based on the first attitude angle information and the first disturbance value comprises: Acquire first desired attitude angle information of the aircraft controller; Calculating a first attitude angle error based on the first expected attitude angle information and the first attitude angle information; Based on the first attitude angle error, optimizing the aircraft controller by a preset nonlinear optimization method, wherein a gain of the nonlinear optimization method is negatively correlated with a magnitude of the first attitude angle error; Based on the first disturbance value, disturbance compensation is performed on the aircraft controller to achieve disturbance control.

4. The method according to claim 2, characterized in that: After the step of responding to the evaluation instruction for the flight system and determining whether the evaluation instruction is an identification instruction, the method further includes: If it is not the identification instruction, receiving the second attitude angle information and the second disturbance value sent by the preset disturbance observer; Acquire second desired attitude angle information of the aircraft controller; Calculating a second attitude angle error based on the second desired attitude angle information and the second attitude angle information; Determining whether the second posture angle error is within a preset error range; If the second attitude angle error is not within the preset error range, adjusting the observer parameters, and returning to the step of receiving the second attitude angle information and the second disturbance value sent by the preset disturbance observer, until the second attitude angle error is within the preset error range, and the parameter adjustment is completed; The preset disturbance observer that has completed the observer parameter adjustment is used as the second disturbance observer.

5. The method according to claim 4, characterized in that: After the step of using the preset disturbance observer that has completed the observer parameter adjustment as the second disturbance observer, the method further includes: receiving a target disturbance value sent by the second disturbance observer; Calculating a disturbance difference between the target disturbance value and a preset reference disturbance value; Determining whether the disturbance difference exceeds a preset model change threshold; If the disturbance difference is higher than the preset model change threshold, it is determined that the flight system model has changed.

6. The method according to claim 1, characterized in that: The step of evaluating the flight quality of the aircraft based on the flight system model to obtain the evaluation result comprises: Get the control parameters of the aircraft controller; determining a first transfer function of the aircraft controller based on the control parameter; determining a second transfer function corresponding to the flight system model; Based on the first transfer function and the second transfer function, a shear frequency and a phase margin are calculated; Based on the shear frequency and the phase margin, the flight quality of the aircraft is evaluated to obtain an evaluation result.

7. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the flight quality evaluation method according to any one of claims 1 to 6 are implemented.

8. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the flying quality evaluation method according to any one of claims 1 to 6 are implemented.

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