Flight qualities evaluation method, storage medium and program product

Abstract

A flight qualities evaluation method, a storage medium and a program product. The flight qualities evaluation method comprises: in response to an evaluation instruction for a flight system, determining whether the evaluation instruction is an identification instruction (S10); if the evaluation instruction is an identification instruction, acquiring flight signals, wherein the flight signals are an excitation signal obtained by the flight system and a response signal generated by the flight system during the flight of an aircraft (S20); on the basis of the flight signals, determining a corresponding flight system model, wherein the flight system model has a mapping relationship between the excitation signal and the response signal (S30); and on the basis of the flight system model, performing flight qualities evaluation on the aircraft to obtain an evaluation result (S40).

Description

Flight quality evaluation methods, storage media and program products

[0001] Related applications

[0002] This application claims priority to Chinese patent application No. 202510047134.7, filed on January 13, 2025, the entire contents of which are incorporated herein by reference. Technical Field

[0003] This application relates to the field of aircraft technology, and in particular to flight quality evaluation methods, storage media, and program products. Background Technology

[0004] Flight quality refers to the performance, stability, and handling characteristics of an aircraft during flight, and is related to flight safety. Currently, the main approach is to establish a model under ideal conditions before the aircraft takes flight and then evaluate flight quality using this model. However, this method does not consider the impact of environmental factors and the aircraft's own condition on flight quality, making it impossible to evaluate flight quality under the influence of flight environment factors and the aircraft's own condition. Summary of the Invention

[0005] The main objective of this application is to provide a flight quality evaluation method, storage medium, and program product, which aims to solve the technical problem of being unable to evaluate the flight quality of an aircraft under the influence of flight environmental factors and the aircraft's own condition.

[0006] To achieve the above objectives, this application proposes a flight quality evaluation method, the method comprising:

[0007] In response to an evaluation command for the flight system, determine whether the evaluation command is an identification command;

[0008] If the identification command is given, then the flight signal is acquired, wherein the flight signal is the excitation signal and response signal obtained by the flight system during the flight of the aircraft;

[0009] 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;

[0010] Based on the flight system model, the flight quality of the aircraft is evaluated, and the evaluation results are obtained.

[0011] In one embodiment, the step of determining the corresponding flight system model based on the flight signal includes:

[0012] The flight signal is transformed in the time-frequency domain 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;

[0013] Power spectrum estimation is performed on the flight frequency domain excitation signal and the flight frequency domain response signal to obtain the target transfer function;

[0014] Based on the preset parameter tuning method, with the goal of minimizing the flight frequency domain response error, the target parameters of the flight system model are determined, 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.

[0015] The target parameters are used as model parameters for the flight system model to determine the corresponding flight system model.

[0016] 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 the target transfer function includes:

[0017] Based on a preset overlap rate, the flight frequency domain excitation signal and the flight frequency domain response signal are segmented to obtain a flight frequency domain excitation signal and a flight frequency domain response signal with a preset number of segments.

[0018] Based on a preset window function, the first self-power spectral density of each segment of the flight frequency domain excitation signal, the second self-power spectral density of each segment of the flight frequency domain response signal, and the cross-power spectral density between each segment of the flight frequency domain excitation signal and each segment of the flight frequency domain response signal are calculated.

[0019] Calculate the average value of the first self-power spectral density, the second self-power spectral density, and the cross-power spectral density to obtain the first average self-power spectral density, the second average self-power spectral density, and the average cross-power spectral density.

[0020] The target transfer function is determined based on the average cross power spectral density, the first average self power spectral density, and the second average self power spectral density.

[0021] In one embodiment, after the step of determining the corresponding flight system model based on the flight signal, the method further includes:

[0022] Based on the flight system model, the observer parameters of the preset disturbance observer are determined to obtain the first disturbance observer;

[0023] Receive the first attitude angle information and the first disturbance value obtained by the first disturbance observer;

[0024] Disturbance control is performed based on the first attitude angle information and the first disturbance value.

[0025] In one embodiment, the step of performing disturbance control based on the first attitude angle information and the first disturbance value includes:

[0026] Obtain the first desired attitude angle information of the aircraft controller;

[0027] Based on the first desired attitude angle information and the first attitude angle information, the first attitude angle error is calculated;

[0028] Based on the first attitude angle error, the aircraft controller is optimized using a preset nonlinear optimization method, wherein the gain of the nonlinear optimization method is negatively correlated with the magnitude of the first attitude angle error.

[0029] Based on the first disturbance value, disturbance compensation is performed on the aircraft controller to achieve disturbance control.

[0030] In one embodiment, after the step of determining whether an evaluation command is an identification command in response to an evaluation command for a flight system, the method further includes:

[0031] If it is not the identification instruction, then the second attitude angle information and the second disturbance value sent by the preset disturbance observer are received;

[0032] Obtain the second desired attitude angle information of the aircraft controller;

[0033] Based on the second desired attitude angle information and the second attitude angle information, the second attitude angle error is calculated;

[0034] Determine whether the second attitude angle error is within the preset error range;

[0035] If the second attitude angle error is not within the preset error range, the observer parameters are adjusted, and the process returns 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, thus completing the parameter adjustment.

[0036] The preset disturbance observer, whose observer parameters have been adjusted, is used as the second disturbance observer.

[0037] In one embodiment, after the step of using the preset perturbation observer with completed observer parameter adjustment as the second perturbation observer, the method further includes:

[0038] Receive the target disturbance value sent by the second disturbance observer;

[0039] Calculate the perturbation difference between the target perturbation value and the preset reference perturbation value;

[0040] Determine whether the disturbance difference exceeds a preset model change threshold;

[0041] If the disturbance difference is higher than the preset model change threshold, it is determined that the flight system model has changed.

[0042] In one embodiment, the step of evaluating the flight quality of the aircraft based on the flight system model and obtaining the evaluation results includes:

[0043] Obtain the control parameters of the aircraft controller;

[0044] Based on the control parameters, the first transfer function of the aircraft controller is determined;

[0045] Determine the second transfer function corresponding to the flight system model;

[0046] Based on the first transfer function and the second transfer function, the shear frequency and phase margin are calculated;

[0047] Based on the cutoff frequency and the phase margin, the flight quality of the aircraft is evaluated, and the evaluation results are obtained.

[0048] In addition, to achieve the above objectives, this application also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the flight quality evaluation method described above.

[0049] In addition, to achieve the above objectives, this application also provides a computer program product, which includes a computer program that, when executed by a processor, implements the steps of the flight quality evaluation method described above.

[0050] One or more technical solutions proposed in this application have at least the following technical effects:

[0051] This application responds to an evaluation command for a flight system, determines whether the evaluation command is an identification command, and if it is an identification command, acquires flight signals, wherein the flight signals are the excitation signals and response signals obtained by the flight system during the flight of the aircraft, determines the corresponding flight system model based on the flight signals, wherein the flight system model has a mapping relationship between the excitation signals and the response signals, and evaluates the flight quality of the aircraft based on the flight system model to obtain an evaluation result.

[0052] To evaluate aircraft flight quality under the influence of environmental factors and the aircraft's own condition, it is necessary to establish a flight system model of the aircraft under these conditions. Flight signals are the excitation signals acquired and the response signals generated by the flight system. Therefore, the flight signals generated during aircraft flight can be acquired, and a flight system model with a mapping relationship between excitation and response signals can be obtained based on these signals. Furthermore, since flight signals are generated during aircraft flight, the resulting flight system model can be used to describe the mapping relationship between excitation and response signals after the aircraft is affected by environmental factors and its own condition during flight. Thus, the flight quality of the aircraft can be evaluated under the influence of environmental factors and the aircraft's own condition through this flight system model. Attached Figure Description

[0053] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0054] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0055] Figure 1 is a flowchart of the flight quality evaluation method provided in Embodiment 1 of this application;

[0056] Figure 2 is a schematic diagram of the first scenario provided in Embodiment 1 of the flight quality evaluation method of this application;

[0057] Figure 3 is a schematic diagram of the second scenario provided in Embodiment 1 of the flight quality evaluation method of this application;

[0058] Figure 4 is a flowchart of the flight quality evaluation method provided in Embodiment 2 of this application;

[0059] Figure 5 is a flowchart of the flight quality evaluation method provided in Embodiment 3 of this application;

[0060] Figure 6 is a schematic diagram of the first scenario provided in Embodiment 3 of the flight quality evaluation method of this application;

[0061] Figure 7 is a schematic diagram of the second scenario provided in Embodiment 3 of the flight quality evaluation method of this application;

[0062] Figure 8 is a schematic diagram of the third scenario provided in Embodiment 3 of the flight quality evaluation method of this application.

[0063] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0064] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0065] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0066] The executing entity in this embodiment can be a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, or mobile phone, or an electronic device or flight quality evaluation device capable of performing the above functions. The following description uses a flight quality evaluation device as an example to illustrate this embodiment and the subsequent embodiments.

[0067] Based on this, the present application provides a flight quality evaluation method. Referring to Figure 1, Figure 1 is a flowchart of the first embodiment of the flight quality evaluation method of the present application.

[0068] In this embodiment, the flight quality evaluation method includes steps S10 to S40:

[0069] Step S10: In response to an evaluation command for the flight system, determine whether the evaluation command is an identification command;

[0070] Flight quality evaluation is the process of assessing an aircraft's handling characteristics, stability, and responsiveness. Conducting flight quality evaluations ensures that aircraft can operate safely and efficiently under various flight conditions, thereby guaranteeing flight safety and optimizing flight performance.

[0071] Flight quality assessment can be based on system identification or not. To accurately assess flight quality, it is necessary to accurately describe the dynamic characteristics of the flight system, which can be represented by a mathematical model. Therefore, when an evaluation command for the flight system is received, it is necessary to respond to the command by determining whether it is an identification command.

[0072] Step S20: If it is the identification command, then acquire the flight signal, wherein the flight signal is the excitation signal and response signal obtained by the flight system during the flight of the aircraft;

[0073] Flight signals can be divided into excitation signals and response signals. Excitation signals are signals input into the flight system to control the aircraft or signals for human operation, such as signals that change the thrust of the aircraft engine, or specific signals such as pulses or sine waves applied in laboratory and ground tests. In this embodiment, the excitation signal is a frequency sweep 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 frequency sweep signal.

[0074] The frequency sweep signal can be either an automatic frequency sweep signal or a manual frequency sweep signal. An automatic frequency sweep signal is a signal whose frequency changes linearly or non-linearly with time, as shown in Figure 2. Automatic frequency sweep signals can cause vibrations in the aircraft, leading to safety hazards; therefore, this embodiment uses a manual frequency sweep method.

[0075] Manual frequency sweeping involves the pilot manually simulating the sweeping motion using the remote control. One reason for this is to prevent the automatic frequency sweeping signal controller from being overwhelmed, potentially leading to an aircraft crash. The drawback of manual frequency sweeping is often insufficient excitation, failing to meet the requirements of the optimal input signal for identification; in other words, the excitation signal generated by manual frequency sweeping is a weak excitation signal.

[0076] In this embodiment, the manual frequency sweep needs to meet the following requirements: 1. The start and end points of the maneuver are in a balanced state; 2. There are two high-quality low-frequency cycle inputs in the data; 3. The frequency increases regularly and smoothly.

[0077] Current flight quality assessments largely rely on pre-flight modeling, which cannot accurately reflect the actual state of an aircraft. Furthermore, as the aircraft's structure ages, the current assessment system will gradually become ineffective. Moreover, the current flight quality assessment system is implemented by building models in ideal environments, which cannot evaluate the flight quality of aircraft under conditions such as strong wind disturbances and structural damage.

[0078] To evaluate an aircraft's flight quality under the influence of environmental factors and its own condition, it is necessary to identify the aircraft's flight system under these conditions. Therefore, it is essential to acquire flight signals during actual flight to identify the aircraft's flight system under these conditions.

[0079] Step S30: Based on the flight signal, determine the corresponding flight system model, wherein the flight system model has a mapping relationship between the excitation signal and the response signal.

[0080] The flight system model in this embodiment is a simplified model of the fixed-wing pitch angle after decoupling, and its expression is:

[0081] Where θ is the pitch angle. Let q be the first derivative of the pitch angle with respect to time, and q be the y-component of the angular velocity in the body coordinate system, i.e., the pitch rate. Let δ be the first derivative of the pitch rate with respect to time. e M is the output of the controller. q and M represents the identification coefficients of the flight system model. q and The calculation expression is:

[0082] Where ρ is atmospheric density, V is relative wind speed, and S is the reference area. For the average aerodynamic chord length, I y Let be the moment of inertia of the aircraft about the y-axis. This is a dimensionless longitudinal stability coefficient. This is the dimensionless elevator control coefficient.

[0083] A complete flight system model typically comprises multiple interconnected subsystems, and the interactions between these subsystems make the model highly complex. Therefore, it is necessary to decouple and simplify the flight system model to improve computational efficiency, enhance its interpretability and applicability, and simplify control design.

[0084] Since this embodiment has obtained the excitation signals and response signals acquired by the flight system during flight, a flight system model with a mapping relationship between the excitation signals and the response signals can be obtained from the acquired excitation signals and response signals.

[0085] In one embodiment, determining the specific implementation of the corresponding flight system model based on the flight signal can also be:

[0086] The flight signal is transformed in the time-frequency domain to obtain a flight frequency domain signal, which includes a flight frequency domain excitation signal and a flight frequency domain response signal. Power spectrum estimation is performed 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, with the goal of minimizing the flight frequency domain response error, target parameters of the flight system model are determined, where the flight frequency domain response error is the difference between the measured frequency domain response data and the predicted frequency domain response data calculated using the target transfer function. The target parameters are used as model parameters of the flight system model to determine the corresponding flight system model.

[0087] In this embodiment, the identification of the flight system is based on frequency domain identification. Converting time-domain data to frequency-domain data can be done using either Fourier transform or linear frequency modulated (LFM) z-transform. This embodiment uses LFM z-transform to convert time-domain data to frequency-domain data in order to increase spectral resolution.

[0088] Compared to time-domain data, frequency-domain data can describe the main features of a signal with fewer data points. 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 modulated z-transform, or other frequency domain transformation techniques, redundant information and high-frequency noise in the time-domain signal can be effectively removed, making this embodiment more resistant to noise.

[0089] This embodiment determines the transfer function of the flight system model through power spectrum estimation to describe the mapping relationship between excitation and response signals 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. The basic principle of power spectrum estimation is that the transfer function equals the cross-power spectral density divided by the self-power spectral density, and its expression is:

[0090] Among them, P xy P is the cross-power spectral density of x and y. xx P is the self-power spectral density of x. yy H(w) is the power spectral density of y, and H(w) is the h1 estimate of the power spectrum. The h1 estimate is an error estimate in numerical analysis and the finite element method for partial differential equations.

[0091] There will be some error between the frequency domain response data obtained through 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 coefficients 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.

[0092] Therefore, it is necessary to determine the target parameters, i.e. the identification coefficients, of the flight system model based on the preset parameter tuning method with the goal of minimizing the flight frequency domain response error. In this embodiment, the corresponding identification coefficients are obtained by the least squares method.

[0093] By using the target parameters as model parameters for the flight system model, the corresponding flight system model can be determined. The identification effect under weak excitation in this embodiment can be seen in Figure 3.

[0094] In one embodiment, the method of obtaining the target transfer function by power spectrum estimation of the flight frequency domain excitation signal and the flight frequency domain response signal can also be:

[0095] Based on a preset overlap rate, the flight frequency domain excitation signal and the flight frequency domain response signal are segmented 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, the first self-power spectral density of each segment of the flight frequency domain excitation signal, the second self-power spectral density of each segment of the flight frequency domain response signal, and the cross-power spectral density between each segment of the flight frequency domain excitation signal and each segment of the flight frequency domain response signal are calculated. The average values ​​of the first self-power spectral density, the second self-power spectral density, and the cross-power spectral density are calculated to obtain the first average self-power spectral density, the second average self-power spectral density, and the average cross-power spectral density. Based on the average cross-power spectral density, the first average self-power spectral density, and the second average self-power spectral density, the target transfer function is determined.

[0096] The window function used in this embodiment can be a Hanning window or a Hamming window, etc. When the period of the signal does not perfectly match the sampling window length, it can lead to spectral leakage, where energy diffuses to adjacent frequency components. This embodiment estimates the power spectrum of each segment using the Wilson method with windowed Fourier transform.

[0097] Spectral leakage mainly occurs when the signal period does not perfectly match the sampling window length, causing energy to diffuse into adjacent frequency components. By segmenting the signal, the length of each segment can be chosen more flexibly, allowing more segments to contain complete or near-complete periods. Combined with windowing, this can effectively reduce energy diffusion caused by non-integer period sampling.

[0098] Therefore, this implementation segments and overlaps the signal, minimizes spectral leakage by applying a window function, calculates the power spectral density of each segment and averages them, and then determines the target transfer function based on the obtained average cross-power spectral density, first average self-power spectral density and second average self-power spectral density.

[0099] Step S40: Based on the flight system model, evaluate the flight quality of the aircraft and obtain the evaluation results.

[0100] Because the flight system model has a mapping relationship between excitation and response signals, the flight quality of the aircraft can be evaluated based on the flight system model after obtaining it.

[0101] In one embodiment, the implementation method for evaluating the flight quality of the aircraft based on the flight system model to obtain the evaluation results may also be:

[0102] The control parameters of the aircraft controller are obtained. 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, the cutoff frequency and phase margin are calculated. Based on the cutoff frequency and the phase margin, the flight quality of the aircraft is evaluated, and the evaluation result is obtained.

[0103] The cutoff frequency is related to the response speed of the flight system, while the phase margin is related to the stability of the flight system. The cutoff frequency and phase margin can be calculated using the transfer function of the aircraft system model and the transfer function of the flight system controller. The calculation formula can be expressed as: L(s)=P(s)C(s)

[0104] Where P(s) is the model transfer function of the flight system, C(s) is the transfer function of the aircraft controller, and L(s) is the transfer function of the loop.

[0105] The formula for the shear frequency is: |P(jw c )C(jw c )|=1

[0106] Where j is the imaginary unit, w c Let γ be the shear frequency. γ = 180 + ∠P(jw) c )C(jw c )

[0107] Where γ is the phase margin, and ∠ is used to represent the phase angle of the transfer function at a specific frequency.

[0108] The control parameters are the PID (Proportional-Integral-Derivative) parameters of the aircraft controller.

[0109] To calculate the crossover frequency and phase margin, it is necessary to determine the transfer functions of the flight system model and the aircraft controller. The transfer function of the flight system model can be obtained by identifying the system, while the transfer function of the aircraft controller can be obtained from the controller's PID parameters.

[0110] Therefore, in this embodiment, the shear frequency and phase margin can be calculated using the first transfer function of the aircraft controller and the second transfer function corresponding to the flight system model. Based on the shear frequency and the phase margin, the flight quality of the aircraft can be evaluated to obtain the evaluation result.

[0111] In summary, this embodiment responds to an evaluation command for the flight system, determines whether the evaluation command is an identification command, and if it is an identification command, acquires flight signals, wherein the flight signals are the excitation signals and response signals obtained by the flight system during the flight of the aircraft. Based on the flight signals, a corresponding flight system model is determined, wherein the flight system model has a mapping relationship between the excitation signals and the response signals. Based on the flight system model, the flight quality of the aircraft is evaluated, and an evaluation result is obtained.

[0112] To evaluate aircraft flight quality under the influence of environmental factors and the aircraft's own condition, it is necessary to establish a flight system model of the aircraft under these conditions. Flight signals are the excitation signals acquired and the response signals generated by the flight system. Therefore, the flight signals generated during aircraft flight can be acquired, and these signals can be converted from the flight signals to the time-frequency domain. Based on these flight signals, a flight system model with the mapping relationship between excitation and response signals in the frequency domain can be obtained.

[0113] Flight signals are generated during aircraft flight, and the resulting flight system model can be used to describe the mapping relationship between excitation and response signals after the aircraft is affected by environmental factors and its own state during flight. Therefore, this embodiment can evaluate flight quality under conditions such as wing icing, mechanical aging, and malfunctions. Furthermore, since flight information is obtained during flight, this embodiment can identify the system online and apply the identification results to parameter adjustments. Thus, the flight system model can be used to perform online flight quality evaluation of the aircraft under the influence of flight environmental factors and the aircraft's own state.

[0114] Based on the first embodiment of this application, in the second embodiment of this application, the content that is the same as or similar to that in the first embodiment described above can be referred to the above description and will not be repeated hereafter. Based on this, please refer to Figure 4. After step S30, the flight quality evaluation method further includes steps S31 to S33:

[0115] Step S31: Based on the flight system model, determine the observer parameters of the preset disturbance observer to obtain the first disturbance observer;

[0116] The preset disturbance observer is the disturbance observer before parameter adjustments. The first disturbance observer is the disturbance observer obtained by using the identified parameters from the flight system model as the parameters of the preset disturbance observer. The simplified aircraft model formula is expressed in the disturbance observer as follows:

[0117] Where y is the component of the angular velocity along the y-axis in the body coordinate system, i.e., the pitch rate. Let u be the first derivative of the pitch rate with respect to time, a0 and b0 be the identification coefficients of the flight system model, and a0 be the first derivative of the pitch rate with respect to time. q Equal, b0 and They are equal. Based on the aircraft system model, a disturbance value can be added, expressed as:

[0118] Where u is the controller output and f is the disturbance value. Let x be the first derivative of the perturbation value with respect to time, and let x be the state vector, expressed as x = [y, f]. T , Let A be the first 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 for each matrix are as follows:

[0119] Disturbance observers rely on accurate modeling of the system's dynamic characteristics. If there are discrepancies between the model and the actual system, the observer will be unable to accurately estimate the disturbance. Therefore, this embodiment determines the observer parameters of a preset disturbance observer based on a defined flight system model, obtaining a first disturbance observer, and then estimating the disturbance value through the first disturbance observer.

[0120] Step S32: Receive the first attitude angle information and the first disturbance value obtained by the first disturbance observer;

[0121] In this embodiment, the disturbance observer is an attitude loop disturbance observer. Therefore, in addition to estimating the disturbance value, the first disturbance observer can also estimate the aircraft's attitude angle information. The attitude angle information includes the aircraft's heading angle, pitch angle, and roll angle, as well as angular velocity information. In this embodiment, the attitude angle information is the aircraft's pitch rate.

[0122] Step S33: Based on the first attitude angle information and the first disturbance value, perform disturbance control.

[0123] Environmental changes and load fluctuations, among other factors, can cause disturbances that interfere with the normal operation of the system, leading to deviations from expected output values. Therefore, to mitigate the impact of disturbances, it is necessary to acquire the disturbance value and the initial attitude angle information for disturbance control.

[0124] In one embodiment, the method of performing disturbance control based on the first attitude angle information and the first disturbance value can also be:

[0125] The first desired attitude angle information of the aircraft controller is obtained. Based on the first desired attitude angle information and the first attitude angle information, the first attitude angle error is calculated. Based on the first attitude angle error, the aircraft controller is optimized by a preset nonlinear optimization method, wherein the gain of the nonlinear optimization method is negatively correlated with the 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.

[0126] The first desired attitude angle information is the attitude angle information that the flight system expects to obtain when performing flight control of the aircraft. The first attitude angle information is the attitude angle information actually obtained by the first disturbance observer. The first attitude angle error is the error between the desired attitude angle information and the actual attitude angle information.

[0127] When a control system performs its operation, there will be a discrepancy between the desired control effect and the actual control effect, which will affect flight quality. Therefore, it is necessary to optimize the aircraft's flight quality based on a pre-defined optimization method.

[0128] Because traditional linear attitude controllers have poor robustness, this embodiment performs nonlinear optimization on the error of the linear controller to improve its robustness. The expression is as follows:

[0129] Where, respectively, k p Proportional gain, k i Integral gain and k d e represents the differential gain, all of which are positive. l Let δ1 and δ2 represent the pitch angular velocity error, a1 and a2 represent the linear region gains, a1 and a2 represent the nonlinear region gains, and disturb represent the disturbance compensation corresponding to the disturbance value. fal is the nonlinear optimization function, which is essentially an optimization of e. l Apply a certain transformation to achieve the goal of large error, small gain, and small error, large gain.

[0130] When the system error is large, it means that the flight system state is far from the desired value. Using a large gain in this case may lead to an overly aggressive system response, resulting in excessive control actions, which could cause oscillations or even instability. When the system error is small, it indicates that the system is very close to the desired state. In this case, appropriately increasing the gain can help eliminate remaining small errors more quickly, improve steady-state accuracy, and enable the system to converge to the setpoint rapidly.

[0131] 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 steady-state error, and improve the overall performance of the system.

[0132] 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 obtained by the first disturbance observer, and performs disturbance control based on the first attitude angle information and the first disturbance value.

[0133] Because disturbances interfere with the normal operation of the flight system, causing the output to deviate from the expected value, it is necessary to determine the disturbance value in order to make the output of the flight system closer to the expected value. Since the disturbance observer relies on accurate modeling of the dynamic characteristics of the system, 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.

[0134] Traditional linear attitude controllers have poor robustness. Therefore, this embodiment uses nonlinear optimization based on attitude angle error to perform disturbance control. Because this embodiment uses a simplified model for nonlinear optimization, the quality optimization method of this embodiment is more robust, can better adapt to various operating modes of the aircraft, and greatly reduces the difficulty of parameter tuning.

[0135] Based on the first and second embodiments of this application, the content that is the same as or similar to the first and second embodiments described above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to Figure 5. After step S10, the flight quality evaluation method further includes steps A11 to A16:

[0136] Step A11: If it is not the identification instruction, then receive the second attitude angle information and the second disturbance value sent by the preset disturbance observer;

[0137] The second attitude angle information and the second disturbance value are obtained from a preset disturbance observer when flight system identification is not required.

[0138] If the evaluation command is not an identification command, then system identification is not required; quality evaluation is performed solely through the disturbance observer, as shown in Figure 6. Therefore, in this embodiment, when the evaluation command is not an identification command, the system receives the second attitude angle information and the second disturbance value sent by the preset disturbance observer.

[0139] Step A12: Obtain the second desired attitude angle information of the aircraft controller;

[0140] The second desired attitude angle information is the attitude angle information of the aircraft controller obtained when flight system identification is not required.

[0141] Step A13: Calculate the second attitude angle error based on the second desired attitude angle information and the second attitude angle information;

[0142] Since the flight system was not identified, the preset disturbance observer could not accurately estimate the attitude angle and disturbance value. Therefore, it is necessary to calculate the second attitude angle error using the second desired attitude angle information and the second attitude angle information, and then optimize the parameters of the preset disturbance observer.

[0143] Step A14: Determine whether the second attitude angle error is within the preset error range;

[0144] When the disturbance observer estimates relatively accurately, the second attitude angle error will be small. Therefore, it can be determined whether the disturbance observer has made a relatively accurate estimate by judging whether the second attitude angle error is within the preset error range.

[0145] Step A15: If the second attitude angle error is not within the preset error range, adjust the observer parameters and return 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 complete the parameter adjustment.

[0146] Since the accuracy of the disturbance observer's estimation can be determined by checking whether the second attitude angle error is within a preset error range, the parameters of the disturbance observer can be adjusted without system identification. The adjusted observer can then be assessed to determine if it has performed accurate disturbance value and attitude angle estimations. If the disturbance observer's estimation is deemed insufficiently accurate, its parameters are readjusted until the required estimation accuracy is achieved. At this point, the disturbance observer is considered to have converged. The convergence status of the disturbance observer can be seen in Figure 7.

[0147] Step A16: The preset disturbance observer with the completed observer parameter adjustment is used as the second disturbance observer.

[0148] The preset disturbance observer, after completing the observer parameter adjustment, can accurately estimate the attitude angle and disturbance value. Therefore, it can be used as a second disturbance observer, and the disturbance value obtained by the second disturbance observer can be used to evaluate the flight quality.

[0149] In one embodiment, the implementation method after using the preset perturbation observer with completed observer parameter adjustment as the second perturbation observer can also be:

[0150] The system receives the target disturbance value sent by the second disturbance observer, calculates the disturbance difference between the target disturbance value and the preset reference disturbance value, and determines whether the disturbance difference exceeds the preset model change threshold. If the disturbance difference is higher than the preset model change threshold, it determines that the flight system model has changed.

[0151] The preset baseline disturbance value is the disturbance value obtained when the aircraft is flying in the best condition, that is, the low disturbance value when there is no interference from other factors that causes the disturbance value to change, as shown in Figure 8.

[0152] Without the influence of other factors, the disturbance value of an aircraft during flight will fluctuate within a certain range. When there are disturbances such as strong winds or changes in the aircraft's structure, the flight system model will change, resulting in changes in the generated disturbance value. 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.

[0153] In summary, when the evaluation command is not an identification command, this embodiment receives the second attitude angle information and the second disturbance value sent by the preset disturbance observer, obtains the second desired attitude angle information of the aircraft controller, calculates the second attitude angle error based on the second desired attitude angle information and the second attitude angle information, determines whether the second attitude angle error is within the preset error range, and if the second attitude angle error is not within the preset error range, adjusts the observer parameters, and returns 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, completing the parameter adjustment. The preset disturbance observer that has completed the observer parameter adjustment is used as the second disturbance observer, and the flight quality is evaluated through the disturbance value estimated by the second disturbance observer.

[0154] Because strong wind disturbances and structural changes in the aircraft itself can alter the flight system model, the disturbance values ​​obtained by the disturbance observer will also change. Therefore, the disturbance values ​​can be used to determine whether the flight system model has changed. To accurately estimate the model, the parameters of the disturbance observer need to be adjusted so that it can precisely estimate the disturbance. Therefore, this embodiment calculates the difference between the desired attitude angle information and the actual attitude angle information to obtain the attitude angle error. The parameters of the disturbance observer are adjusted based on whether the attitude angle error is within a preset range. Thus, by comparing the difference between the disturbance value obtained by the disturbance observer and the reference disturbance value, it is determined whether other factors have altered the aircraft system model. Therefore, this embodiment can determine whether the flight system model has changed solely based on the disturbance values, without requiring system identification.

[0155] The above examples are only for understanding this application and do not constitute a limitation on the flight quality evaluation method of this application. Any simple modifications based on this technical concept are within the protection scope of this application.

[0156] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to execute the flight quality evaluation method in the above embodiments.

[0157] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0158] The aforementioned computer-readable storage medium may be included in the flight quality evaluation equipment; or it may exist independently and not be installed in the flight quality evaluation equipment.

[0159] The aforementioned computer-readable storage medium carries one or more programs, which, when executed by the flight quality evaluation device, cause the flight quality evaluation device to perform the aforementioned flight quality evaluation method.

[0160] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0161] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0162] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0163] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described flight quality evaluation method. This solves the technical problem of being unable to evaluate the flight quality of an aircraft under the influence of flight environmental factors and the aircraft's own condition. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the flight quality evaluation method provided in the above embodiments, and will not be repeated here.

[0164] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the flight quality evaluation method described above.

[0165] The computer program product provided in this application can solve the technical problem of being unable to evaluate the flight quality of an aircraft under the influence of flight environmental factors and the aircraft's own condition. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as those of the flight quality evaluation method provided in the above embodiments, and will not be repeated here.

[0166] The above description is only a part of the embodiments of this application and does not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A method for evaluating flight quality, wherein, The method includes: In response to an evaluation command for the flight system, determine whether the evaluation command is an identification command; If the identification command is given, then the flight signal is acquired, wherein the flight signal is the excitation signal and response signal obtained 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, and the evaluation results are obtained.

2. The method as described in claim 1, wherein, The step of determining the corresponding flight system model based on the flight signal includes: The flight signal is transformed in the time-frequency domain 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; Power spectrum estimation is performed on the flight frequency domain excitation signal and the flight frequency domain response signal to obtain the target transfer function; Based on the preset parameter tuning method, with the goal of minimizing the flight frequency domain response error, the target parameters of the flight system model are determined, 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. The target parameters are used as model parameters for the flight system model to determine the corresponding flight system model.

3. The method as described in claim 2, wherein, The step of performing power spectrum estimation on the flight frequency domain excitation signal and the flight frequency domain response signal to obtain the target transfer function includes: Based on a preset overlap rate, the flight frequency domain excitation signal and the flight frequency domain response signal are segmented 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, the first self-power spectral density of each segment of the flight frequency domain excitation signal, the second self-power spectral density of each segment of the flight frequency domain response signal, and the cross-power spectral density between each segment of the flight frequency domain excitation signal and each segment of the flight frequency domain response signal are calculated. Calculate the average value of the first self-power spectral density, the second self-power spectral density, and the cross-power spectral density to obtain the first average self-power spectral density, the second average self-power spectral density, and the average cross-power spectral density. The target transfer function is determined based on the average cross power spectral density, the first average self power spectral density, and the second average self power spectral density.

4. The method of claim 3, wherein, 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, the observer parameters of the preset disturbance observer are determined to obtain the first disturbance observer; Receive the first attitude angle information and the first disturbance value obtained by the first disturbance observer; Disturbance control is performed based on the first attitude angle information and the first disturbance value.

5. The method as described in claim 4, wherein, The step of performing disturbance control based on the first attitude angle information and the first disturbance value includes: Obtain the first desired attitude angle information of the aircraft controller; Based on the first desired attitude angle information and the first attitude angle information, the first attitude angle error is calculated; Based on the first attitude angle error, the aircraft controller is optimized using a preset nonlinear optimization method, wherein the gain of the nonlinear optimization method is negatively correlated with the 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.

6. The method of claim 4, wherein, After the step of determining whether the evaluation command is an identification command in response to an evaluation command for the flight system, the method further includes: If it is not the identification instruction, then the second attitude angle information and the second disturbance value sent by the preset disturbance observer are received; Obtain the second desired attitude angle information of the aircraft controller; Based on the second desired attitude angle information and the second attitude angle information, the second attitude angle error is calculated; Determine whether the second attitude angle error is within the preset error range; If the second attitude angle error is not within the preset error range, the observer parameters are adjusted, and the process returns 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, thus completing the parameter adjustment. The preset disturbance observer, whose observer parameters have been adjusted, is used as the second disturbance observer.

7. The method of claim 6, wherein, After the step of using the preset perturbation observer with adjusted observer parameters as the second perturbation observer, the method further includes: Receive the target disturbance value sent by the second disturbance observer; Calculate the perturbation difference between the target perturbation value and the preset reference perturbation value; Determine 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.

8. The method of claim 1, wherein, The steps for evaluating the flight quality of the aircraft based on the flight system model and obtaining the evaluation results include: Obtain the control parameters of the aircraft controller; Based on the control parameters, the first transfer function of the aircraft controller is determined; Determine the second transfer function corresponding to the flight system model; Based on the first transfer function and the second transfer function, the shear frequency and phase margin are calculated; Based on the cutoff frequency and the phase margin, the flight quality of the aircraft is evaluated, and the evaluation results are obtained.

9. A storage medium, wherein, 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, it implements the steps of the flight quality evaluation method as described in any one of claims 1 to 8.

10. A computer program product, wherein, The computer program product includes a computer program that, when executed by a processor, implements the steps of the flight quality evaluation method as described in any one of claims 1 to 8.

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