A method for identifying elastic frequency and suppressing elastic vibration of a large-aspect-ratio aircraft

Abstract

This invention discloses a method for elastic frequency identification and elastic vibration suppression of a large aspect ratio aircraft. The method involves real-time online elastic frequency identification of angular velocity information acquired by inertial navigation devices to obtain the current identified elastic vibration frequency value ω1. Based on ω1, the identification result is corrected to obtain the iterative correction value ω of the frequency identification. b Then, combining the prior information from the ground modal tests, the prior value ω of the elastic vibration frequency is obtained. a , for ω a and ω a The weighted value ω of the elastic vibration frequency is obtained, and a notch filter structure is designed based on ω so that the filter parameters are automatically adjusted to follow the change of elastic frequency. This invention can identify the elastic frequency with high accuracy and can effectively suppress elastic vibration.

Description

Technical Field

[0001] This invention belongs to the field of aircraft control technology, specifically relating to a method for identifying elastic frequencies and suppressing elastic vibrations in aircraft with large aspect ratios. Background Technology

[0002] To reduce drag, increase maximum speed, and extend range, aircraft tend to have a high length-to-diameter ratio (L / D ratio). Aircraft with an L / D ratio greater than 20 are generally referred to as high L / D aircraft. Furthermore, to increase engine propellant load and mission payload, lightweight composite materials are often used in the overall design, resulting in more pronounced elastic characteristics. During flight, the aircraft's inertial navigation system (INS) becomes sensitive to additional signals caused by elastic vibrations. These signals enter the control loop, causing high-frequency oscillations in the servos and accelerating their wear.

[0003] Meanwhile, due to the discrete nature of engine operation, flight environment changes, and the manufacturing process of the aircraft itself, the elastic vibration modes of the aircraft exhibit time-varying and uncertain characteristics. When these modes are close to the rigid body motion frequency, they pose challenges to the design of notch filters. When the notch width of the filter is insufficient, the elastic vibration frequency of the aircraft may exceed the notch range, causing filter failure. When the notch width of the filter is large, the resulting phase delay is significant, affecting the stability of rigid body motion control. Summary of the Invention

[0004] In view of this, the present invention provides a method for identifying elastic frequencies and suppressing elastic vibrations in aircraft with large aspect ratios, which can identify elastic frequencies with high accuracy and suppress elastic vibrations effectively.

[0005] The technical solution for implementing the present invention is as follows:

[0006] A method for elastic frequency identification and elastic vibration suppression of a large aspect ratio aircraft is proposed. The method involves real-time online elastic frequency identification based on angular velocity information acquired by inertial navigation devices to obtain the current identified elastic vibration frequency ω1. The identification result is then corrected based on ω1 to obtain the iterative correction value ω for frequency identification. b Then, combining the prior information from the ground modal tests, the prior value ω of the elastic vibration frequency is obtained. a , for ω b and ω a The weighted value ω of the elastic vibration frequency is obtained, and a notch filter structure is designed based on ω so that the filter parameters are automatically adjusted to follow the change of elastic frequency.

[0007] Furthermore, the elastic frequency identification of the angular velocity information collected by the inertial navigation device is performed in real time using a fast Fourier transform algorithm based on rolling time.

[0008] Furthermore, the iterative correction value ω for frequency identification b for:

[0009]

[0010] ω2 is the average value of the first 10 frequency identification results, Δ t denoted as the sampling step size of the inertial navigation device, and k is the maximum rate of change of the elastic frequency.

[0011] Furthermore, the prior value ω of the elastic vibration frequency a for:

[0012]

[0013] Where, ω min ω is the elastic frequency value under full load. max Let M(t) be the elastic frequency under no-load conditions, M(t) be the theoretical value of the aircraft mass as a function of flight time t, and interp1(.) be the one-dimensional linear interpolation function. max M represents the mass of the aircraft when fully loaded. min t1 represents the mass of the aircraft when unloaded, and t1 represents the end time of the engine's active phase.

[0014] Furthermore, the acceptance value ω is specifically:

[0015] ω=(1-a)·ω a +a·ω b

[0016] 'a' is the weighting coefficient (0 ≤ a ≤ 1), and the values ​​of 'a' are as follows:

[0017]

[0018] Furthermore, the transfer function G of the notch filter F (s) is:

[0019]

[0020] In the formula: s is the complex variable in the Laplace transform, ω j Let ξ be the center frequency of the notch filter. j is the damping ratio of the notch filter.

[0021] Furthermore, the notch filter parameter adjustment strategy is as follows: take ω j =ω, that is, the center frequency of the notch filter is selected as the final accepted value of the elastic vibration frequency of the aircraft; during the active phase of flight, ξ j A value of 0.5 to 0.7 can be used to increase the filter width; however, in the passive segment, ξ... j A value of 0.3 to 0.4 can be used to reduce system latency.

[0022] The method of the present invention has the following beneficial technical effects:

[0023] (1) This invention uses Fast Fourier Transform to identify the elastic frequency of the aircraft's angular velocity information and designs an iterative correction strategy to iteratively correct the current identification results.

[0024] (2) In order to improve the reliability of the elastic frequency identification value, this invention combines data from engine static test and ground modal test to calculate the prior value of the aircraft's elastic frequency. A weighting strategy for the prior value and the correction value is proposed, which improves the accuracy of the elastic frequency identification value.

[0025] (3) The present invention designs the structure and parameter adjustment scheme of the notch filter, and adaptively adjusts the parameters of the notch filter according to the flight state and elastic frequency identification results of the aircraft to suppress the elastic vibration of the aircraft.

[0026] (4) The simulation experiment verified that the method of the present invention has high frequency identification accuracy, little impact on the rigid motion of the aircraft, and good elastic vibration suppression effect. It solves the problem of adaptive suppression of elastic vibration under the ultra-wide elastic frequency variation range of large aspect ratio aircraft, and ensures the stability of servo elasticity. Attached Figure Description

[0027] Figure 1 This is a block diagram of the control system for the autonomous identification and adaptive suppression method of elastic vibration frequency of the present invention.

[0028] Figure 2 This is a flowchart of the elastic frequency identification process based on the Fast Fourier Transform algorithm with rolling time series.

[0029] Figure 3 This is a graph showing the changes in the actual frequency and the identified frequency of the aircraft over time during the simulation experiment.

[0030] Figure 4 This is a graph showing how the identification error changes over time in the simulation experiment.

[0031] Figure 5 This is a comparison chart of the pitch angular velocity curves from the simulation experiment.

[0032] Figure 6 This is a comparison chart of the pitch deflection curves from the simulation experiment. Detailed Implementation

[0033] The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0034] During flight, high aspect ratio aircraft are susceptible to elastic vibrations and structural flutter due to unsteady aerodynamic forces. A traditional approach to this problem involves designing a notch filter with fixed parameters based on predicted elasticity information. However, this requires a wide filter width to suppress all possible elastic frequencies, leading to significant phase lag. Therefore, this invention proposes a method for identifying elastic frequencies and suppressing elastic vibrations in high aspect ratio aircraft. This method can quickly and accurately identify elastic vibration frequencies and update filter parameters online in real time, achieving better elastic vibration suppression.

[0035] Figure 1 This is a control system block diagram of the elastic vibration frequency autonomous identification and adaptive suppression method of the present invention. The invention first utilizes a fast Fourier transform algorithm based on rolling time sequence to perform real-time online elastic frequency identification on the angular velocity information collected by the inertial navigation device. Then, combining prior information from ground modal tests, an iterative correction strategy based on prior information is designed. Finally, a notch filter structure and parameter adjustment scheme are designed to enable the filter parameters to automatically adjust in response to changes in the elastic frequency.

[0036] like Figure 2 As shown, the specific steps of the method of the present invention are as follows:

[0037] Step 1: Identification of Elastic Vibration Frequency

[0038] Step 1-1: Obtain the angular velocity data of the aircraft through the inertial navigation system as the input signal for frequency identification;

[0039] Steps 1-2: Store the input signals in the data buffer according to the first-in-first-out principle;

[0040] Steps 1-3: Use Fast Fourier Transform to identify the frequency of the input signal.

[0041] The formula for the Fast Fourier Transform is:

[0042]

[0043] In the formula, N is the number of samples in the Fast Fourier Transform, n is the index of the time-domain discrete signal (0≤n≤N-1), m is the index of the frequency-domain discrete signal (0≤m≤N-1), x(n) is a time series of length N, and X(m) is the frequency-domain signal in complex form obtained after Fast Fourier Transform.

[0044] Find the signal with the largest amplitude in X(m) and denote its corresponding index as X. p Then X p The corresponding frequency is the current identified value ω1 of the elastic vibration frequency.

[0045] The larger the number of samples N, the greater the computational load of the onboard computer, the higher the resolution of frequency identification, and the greater the delay error caused by sampling; the smaller N, the smaller the computational load of the onboard computer, the lower the resolution of frequency identification, and the smaller the delay error caused by sampling.

[0046] Table 1 Theoretical identification resolution and sampling delay for different sampling numbers N.

[0047] N 128 256 512 1024 Identify resolution / Hz 0.7813 0.3906 0.1953 0.0977 Sampling delay / s 0.32 0.64 1.28 2.56

[0048] During the active phase of engine operation, the elastic vibration frequency of the aircraft changes rapidly. To improve the speed of frequency identification, N can be selected as 256. In the passive phase of engine operation, the aircraft's mass remains constant, and the elastic vibration frequency changes less. Therefore, N can be selected as 512 to improve identification accuracy.

[0049] Step 2: Design an iterative correction strategy based on prior information.

[0050] Step 2-1: Combine the preliminary experiments to obtain the prior value information of the elastic vibration frequency;

[0051] During engine operation, as fuel is continuously consumed, the aircraft's mass decreases, and its elastic frequency increases. Let the mass of the aircraft at full load be M. max The mass of the aircraft when unloaded is M. min Then, combining the engine thrust test data, the mass-per-second consumption is set as... The theoretical value M(t) for the change of the aircraft's mass with flight time can be derived as follows:

[0052]

[0053] In the formula, t is the current flight time, and t1 is the end time of the engine's active phase.

[0054] Then, based on ground modal tests, the range of the aircraft's first-order elastic frequencies was obtained. Let the elastic frequency at full load be ω. min The elastic frequency value under no-load conditions is ω max The trend of the elastic vibration frequency of an aircraft is related to the trend of mass change, from which the prior value ω of the elastic vibration frequency can be obtained. a for:

[0055]

[0056] In the formula, the interp1() function is a one-dimensional linear interpolation function.

[0057] Step 2-2: Based on the frequency identification values ​​obtained in Step 1-3, correct the identification results and obtain the iterative correction values ​​for frequency identification;

[0058] The current identification value obtained from steps 1-3 is ω1, and the average value of the first 10 frequency identification results in steps 1-3 is ω2. The iterative correction formula is as follows:

[0059]

[0060] In the formula ω b The processed elastic vibration frequency identification value, where Δ t denoted as the sampling step size of the inertial navigation device, and k is the maximum rate of change of the elastic frequency.

[0061] Step 2-3: Combining the prior and correction values ​​from Step 2-1 and Step 2-2, set weighting coefficients to obtain the accepted value of the elastic vibration frequency.

[0062] The accepted value for the elastic vibration frequency is:

[0063] ω=(1-a)·ω a +a·ω b

[0064] In the formula, ω is the accepted value of the elastic vibration frequency, and a is the weighting coefficient (0≤a≤1). The values ​​of a are as follows:

[0065]

[0066] Step 3: Notch Filter Structure Design and Parameter Adjustment Strategy

[0067] Step 3-1: Notch Filter Structure Design

[0068] The transfer function G of a notch filter F (s) is:

[0069]

[0070] In the formula: s is the complex variable in the Laplace transform, ω is the accepted value of the elastic vibration in step 2-3, ω j Let ζ be the center frequency of the notch filter. j is the damping ratio of the notch filter.

[0071] Step 3-2: Notch Filter Parameter Adjustment Strategy

[0072] Take ω j =ω, meaning the center frequency of the notch filter is chosen as the final accepted value of the aircraft's elastic vibration frequency. And ξ j Increasing ξ will increase the filter width and depth, but it will also increase the phase delay of rigid motion, slowing down the system's response speed. During the active phase of flight, ξ j A value of 0.5 to 0.7 can be used to increase the filter width; however, in the passive segment, ξ...j A value of 0.3 to 0.4 can be used to reduce system latency.

[0073] Example:

[0074] To verify the effectiveness of the method of the present invention in elastic frequency identification and elastic vibration suppression, a six-degree-of-freedom model of a large aspect ratio aircraft was used as the basis. The simulation step size of the system was set to 5ms, and the sampling step size of the inertial navigation device was Δ. t The maximum elastic frequency change rate k is 1Hz / s, and a noise signal with an amplitude of 10deg / s is applied to the pitch angular velocity. The system is then verified in conjunction with the theoretical elastic vibration frequency of the aircraft.

[0075] The prior parameter values ​​of the aircraft can be obtained from the ground modal test, as shown in Table 2.

[0076] Table 2. Prior Parameter Values ​​of the Aircraft

[0077]

[0078] Based on the engine thrust test data, the theoretical mass change of the aircraft during the active phase is shown in Table 3.

[0079] Table 3. Changes in theoretical aircraft mass over time.

[0080]

[0081] Then, using the formula in step 2-1:

[0082]

[0083] The theoretical value of the elastic vibration frequency can be calculated as a function of time, as shown in Table 4.

[0084] Table 4. Theoretical values ​​of elastic vibration frequency as a function of time.

[0085]

[0086] During the active phase, the sampled value N is 256, and the notch filter damping ratio ξ... j The value is set to 0.6; in the passive segment, the sampled value N is 512, and the notch filter damping ratio ξ is... j Let N and ξ be 0.3. j The value can be selected by the designer according to the specific situation.

[0087] Simulation results demonstrate that the method of this invention exhibits high frequency identification accuracy and excellent elastic vibration suppression effect. The comparison curves of the theoretical elastic frequency and the identified elastic frequency over time are shown below. Figure 3 As shown. The elastic frequency identification error is as follows. Figure 4As shown in the figure. The comparison curves of pitch angular velocity before and after elastic vibration suppression are as follows. Figure 5 As shown in the figure. The comparison curves of pitch deflection angles before and after elastic vibration suppression are as follows. Figure 6 As shown.

[0088] In summary, the above are merely preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for elastic frequency identification and elastic vibration suppression of a large aspect ratio aircraft, characterized in that, The current identification value of the elastic vibration frequency is obtained by performing real-time online elastic frequency identification on the angular velocity information collected by the inertial navigation device ; Based on The recognition result is corrected to obtain an iterative correction value of frequency recognition Then, combined with prior information of the ground modal test, a prior value of the elastic vibration frequency is obtained , the prior value and are weighted to obtain a sensing value of the elastic vibration frequency Based on A notch filter structure is designed, so that the filter parameters automatically adjust with the change of the elastic frequency Iterative correction value for frequency identification for: This is the average of the first 10 frequency identification results. The sampling step size for the inertial navigation device. The maximum rate of change of elastic frequency; the prior value of elastic vibration frequency. for: in, This is the elastic frequency value under full load. This is the elastic frequency value under no-load conditions. For the mass of the aircraft as a function of flight time t The theoretical value of the change, interp1(.), is a one-dimensional linear interpolation function. The mass of the aircraft when fully loaded. The mass of the aircraft when unloaded. This is the end time of the engine's active phase.

2. The method for elastic frequency identification and elastic vibration suppression of a large aspect ratio aircraft as described in claim 1, characterized in that, The elastic frequency identification of angular velocity information acquired by inertial navigation devices is performed in real time using a fast Fourier transform algorithm based on rolling time.

3. The method for elastic frequency identification and elastic vibration suppression of a large aspect ratio aircraft as described in claim 1, characterized in that, Acceptance value Specifically: These are the weighting coefficients. , The values ​​are as follows:

4. The method for elastic frequency identification and elastic vibration suppression of a large aspect ratio aircraft as described in claim 3, characterized in that, Transfer function of notch filter for: In the formula: For complex variables in the Laplace transform, The center frequency of the notch filter is is the damping ratio of the notch filter.

5. The method for elastic frequency identification and elastic vibration suppression of a large aspect ratio aircraft as described in claim 4, characterized in that, The notch filter parameter adjustment strategy is as follows: take That is, the center frequency of the notch filter is selected as the final accepted value of the elastic vibration frequency of the aircraft; during the active phase of flight, A value of 0.5 to 0.7 can be used to increase the filter width; however, in the passive segment, A value of 0.3 to 0.4 can be used to reduce system latency.

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