A rate gyro adaptive weighting method and device based on Fourier transform

Abstract

The present invention proposes a Fourier transform-based adaptive weighting method and device for rate gyros, which belongs to the field of attitude control for heavy-lift launch vehicles. The method comprises: establishing a launch vehicle attitude dynamics model, wherein a rate gyro is disposed at the front and rear of the launch vehicle; constructing a rate gyro weighting weight estimation model based on the dynamics model; and estimating the weights based on the rate gyro weighting weight estimation model using a Fourier transform to obtain a rigid body signal estimation result for the launch vehicle. The present invention adaptively estimates weights from a frequency domain perspective, exhibiting significant accuracy and reliability advantages. Furthermore, the method is capable of continuously correcting weights even when the rigid body signal and elastic signal power are low, making it widely applicable to future heavy-lift launch vehicle missions.

Description

Technical Field

[0001] The present invention belongs to the field of heavy-lift launch vehicle attitude control technology of aerospace technology, and particularly proposes a rate gyro adaptive weighting method and device based on Fourier transform. Background Art

[0002] As space missions evolve towards large-scale space exploration, the demands placed on launch vehicles for their carrying capacity continue to increase. Currently, my country and other major space nations have begun developing heavy-lift launch vehicles, which will play an indispensable role in future missions such as deep space exploration, manned lunar landings, and manned Mars missions.

[0003] Attitude control is the core technology of heavy-lift launch vehicle flight. Due to the large aspect ratio of heavy-lift launch vehicles, their first-order elastic frequency is low (generally around 1 Hz), which is very close to the rigid body cutoff frequency. How to deal with the attitude control problem under the condition of severe coupling between rigid body and elasticity is a key technology that needs to be solved urgently and is also a very challenging research topic.

[0004] The combination of PD control and a correction network is a classic launch vehicle attitude control method, widely used in current launch vehicle attitude control system designs and boasting high reliability. During flight, due to changes in the launch vehicle's environment and state, correction networks designed based on ground testing often fail to fully suppress elastic signals. Therefore, to ensure control system stability, accurate rigid body rate signals must be used as control feedback, and the rate gyro observation signal must not contain a significant elastic component. Rate gyro weighting is a common approach to address this problem. However, due to changes in the rocket's mass and structural characteristics during flight, the actual rate gyro weighting values ​​deviate from the ground-based measurements, necessitating real-time correction of the weights. Traditional rate gyro weighting methods, which correct the weights based on signal integration, suffer from low correction accuracy and difficulty selecting the integral coefficient. Furthermore, they cannot address the problem of severe rigid body-elastic coupling. Summary of the Invention

[0005] The present invention aims to overcome the inability of traditional rate gyro weighting methods to address attitude control issues caused by severe coupling between rigid-body and elastic signals. A Fourier transform-based adaptive rate gyro weighting method and device are proposed. This method offers the advantages of simple computation, good real-time performance, and high estimation accuracy. It effectively updates the rate gyro weights online, obtaining accurate rigid-body signals for control feedback. This approach addresses attitude control issues in heavy-lift launch vehicles with severe coupling between rigid-body and elastic signals.

[0006] The first embodiment of the present invention provides a rate gyro adaptive weighting method based on Fourier transform, comprising:

[0007] Establishing a launch vehicle attitude dynamics model, wherein a rate gyroscope is arranged at the front and rear of the launch vehicle;

[0008] Based on the dynamic model, constructing a rate gyro weighted weight estimation model;

[0009] Based on the weight estimation model of the rate gyro weighting, the weight is estimated using Fourier transform to obtain a rigid body signal estimation result of the launch vehicle.

[0010] In a specific embodiment of the present invention, the carrier rocket attitude dynamics model is the carrier rocket pitch channel attitude dynamics model, which is expressed as follows:

[0011]

[0012] Y=CX (2)

[0013]

[0014] Among them, formula (1) is the state equation, formula (2) is the observation equation, A is the state matrix, B is the control matrix, and C is the output matrix; is the state variable, is the pitch angular velocity deviation, is the pitch angle deviation, Δθ is the trajectory inclination deviation, is the first-order generalized velocity, q1 is the first-order generalized displacement, b1, b2, c1, c2, c4 are the aerodynamic torque coefficients, b 11 is the coupling coefficient of the first-order generalized velocity to the pitch angular velocity deviation, b 21 is the coupling coefficient of the first-order generalized displacement to the pitch angle deviation, c 11 is the coupling coefficient of the first-order generalized velocity to the ballistic inclination velocity deviation, c 21 is the coupling coefficient of the first-order generalized displacement to the trajectory inclination deviation, D 11 is the coupling coefficient of the pitch angular velocity deviation to the first-order generalized velocity, D 21 is the coupling coefficient of the pitch angle deviation to the first-order generalized displacement, ω1 is the first-order elastic frequency, ξ1 is the damping ratio corresponding to the first-order elastic frequency, and the control input is the equivalent swing angle of the engine, b3 is the pitch angle deviation control gain, c3 is the trajectory inclination deviation control gain, D3 is the first-order elastic mode control gain, is the observed variable, is the pitch angle deviation measured by the inertial group, is the pitch rate deviation measured by the front rate gyro, is the pitch rate deviation measured by the rear rate gyro, is the modal slope of the first-order elastic mode at the inertia group, R z1 F is the modal slope of the first-order elastic mode at the front rate gyro, R z1 R is the slope of the vibration mode of the first-order elastic mode at the rear rate gyro.

[0015] In a specific embodiment of the present invention, the weight estimation model expression of the rate gyro weighting is as follows:

[0016]

[0017] Then the weight K of the rate gyro weighting satisfies:

[0018]

[0019] In a specific embodiment of the present invention, the weight estimation model based on the rate gyro weighting estimates the weight using Fourier transform, including:

[0020] 1) Set the time step to ΔT and the window time of each Fourier transform to ΔT window , set the sliding time to ΔT slide , ΔT slide ≥ΔT;

[0021] Let the initial time of the launch vehicle flight be time 0, and the time of the first Fourier transform be t start , t start ≥ΔT window And t start >ΔT slide ; The end time of the launch vehicle flight is t end , t end >t start ;

[0022] 2) Let the current time be time t and determine:

[0023] If t<t start , then go to step 3); if t≥t start , then go to step 4);

[0024] 3) Based on the ground full-rocket structural dynamic test results, the estimated values ​​of the mode slope at the corresponding front rate gyro position at time t are obtained respectively and the estimated value of the mode slope at the rate gyro position corresponding to time t Calculate the estimated value of the rate gyro weight at time t

[0025]

[0026] Then go to step 9);

[0027] 4) Judgment:

[0028] If (tt start )mod(ΔT slide )≠0, then the weight estimate at time t remains unchanged, that is: Then proceed to step 9), where mod represents a modulo operation;

[0029] If (tt start )mod(ΔT slide )=0, then the window time signal is sampled at time t, and [t-ΔT window The front rate gyro measurement signal in the time interval t] is recorded as The rate gyro measurement signal is recorded as

[0030] 5) Yes and Perform fast Fourier transform respectively to obtain the complex function corresponding to the front rate gyro measurement signal The complex function corresponding to the post-rate gyro measurement signal The expressions are as follows:

[0031]

[0032] Among them, the symbol F represents the fast Fourier transform of the signal. is the first-order generalized velocity The corresponding complex function after transformation;

[0033] 6) Based on the complex function obtained in step 5), calculate the complex function corresponding to the pure elastic signal:

[0034]

[0035] Find the maximum point in the amplitude-frequency curve corresponding to the complex function corresponding to the pure elastic signal, and the frequency corresponding to the maximum point is the first-order elastic frequency obtained by identification.

[0036] 7) Based on the result of step 6), the adaptive estimated intermediate value of the weight at time t is calculated as:

[0037]

[0038] 8) Adaptively estimate the intermediate value of the weight at time t and t-ΔT slide The estimated weight at the moment Perform smoothing to obtain the weight estimate at time t

[0039]

[0040] Where p≥1 is the smoothing coefficient;

[0041] 9) Based on the result of step 8), calculate the estimated value of the rigid body signal at time t As the control feedback in the time interval [t, t+Δt]:

[0042]

[0043] 10) Judgment:

[0044] If t<t end , then after a time step ΔT, return to step 2);

[0045] If t≥t end , the calculation ends.

[0046] A second embodiment of the present invention provides a rate gyro adaptive weighting device based on Fourier transform, comprising:

[0047] A dynamic model building module is used to establish a dynamic model of the launch vehicle attitude, wherein a rate gyroscope is arranged at the front and rear of the launch vehicle;

[0048] A weight estimation model construction module, configured to construct a weight estimation model for rate gyro weighting based on the dynamic model;

[0049] An adaptive weighting module is used to estimate the weights based on the weight estimation model of the rate gyro weighting by using Fourier transform to obtain a rigid body signal estimation result of the launch vehicle.

[0050] In a specific embodiment of the present invention, the carrier rocket attitude dynamics model is the carrier rocket pitch channel attitude dynamics model, which is expressed as follows:

[0051]

[0052] Y=CX (2)

[0053]

[0054] Among them, formula (1) is the state equation, formula (2) is the observation equation, A is the state matrix, B is the control matrix, and C is the output matrix; is the state variable, is the pitch angular velocity deviation, is the pitch angle deviation, Δθ is the trajectory inclination deviation, is the first-order generalized velocity, q1 is the first-order generalized displacement, b1, b2, c1, c2, c4 are the aerodynamic torque coefficients, b 11 is the coupling coefficient of the first-order generalized velocity to the pitch angular velocity deviation, b 21 is the coupling coefficient of the first-order generalized displacement to the pitch angle deviation, c 11 is the coupling coefficient of the first-order generalized velocity to the ballistic inclination velocity deviation, c 21 is the coupling coefficient of the first-order generalized displacement to the trajectory inclination deviation, D 11 is the coupling coefficient of the pitch angular velocity deviation to the first-order generalized velocity, D 21 is the coupling coefficient of the pitch angle deviation to the first-order generalized displacement, ω1 is the first-order elastic frequency, ξ1 is the damping ratio corresponding to the first-order elastic frequency, and the control input is the equivalent swing angle of the engine, b3 is the pitch angle deviation control gain, c3 is the trajectory inclination deviation control gain, D3 is the first-order elastic mode control gain, is the observed variable, is the pitch angle deviation measured by the inertial group, is the pitch rate deviation measured by the front rate gyro, is the pitch rate deviation measured by the rear rate gyro, is the modal slope of the first-order elastic mode at the inertia group, R z1 F is the modal slope of the first-order elastic mode at the front rate gyro, R z1 R is the slope of the vibration mode of the first-order elastic mode at the rear rate gyro.

[0055] In a specific embodiment of the present invention, the weight estimation model expression of the rate gyro weighting is as follows:

[0056]

[0057] Then the weight K of the rate gyro weighting satisfies:

[0058]

[0059] In a specific embodiment of the present invention, the weight estimation model based on the rate gyro weighting estimates the weight using Fourier transform, including:

[0060] 1) Set the time step to ΔT and the window time of each Fourier transform to ΔT window , set the sliding time to ΔT slide , ΔT slide ≥ΔT;

[0061] Let the initial time of the launch vehicle flight be time 0, and the time of the first Fourier transform be t start , t start ≥ΔT window And t start >ΔT slide ; The end time of the launch vehicle flight is t end , t end >t start ;

[0062] 2) Let the current time be time t and determine:

[0063] If t<t start , then go to step 3); if t≥t start , then go to step 4);

[0064] 3) Based on the ground full-rocket structural dynamic test results, the estimated values ​​of the mode slope at the corresponding front rate gyro position at time t are obtained respectively and the estimated value of the mode slope at the rate gyro position corresponding to time t Calculate the estimated value of the rate gyro weight at time t

[0065]

[0066] Then go to step 9);

[0067] 4) Judgment:

[0068] If (tt start )mod(ΔT slide )≠0, then the weight estimate at time t remains unchanged, that is: Then proceed to step 9), where mod represents a modulo operation;

[0069] If (tt start )mod(ΔT slide )=0, then the window time signal is sampled at time t, and [t-ΔT window The front rate gyro measurement signal in the time interval t] is recorded as The rate gyro measurement signal is recorded as

[0070] 5) Yes and Perform fast Fourier transform respectively to obtain the complex function corresponding to the front rate gyro measurement signal The complex function corresponding to the post-rate gyro measurement signal The expressions are as follows:

[0071]

[0072] Among them, the symbol F represents the fast Fourier transform of the signal. is the first-order generalized velocity The corresponding complex function after transformation;

[0073] 6) Based on the complex function obtained in step 5), calculate the complex function corresponding to the pure elastic signal:

[0074]

[0075] Find the maximum point in the amplitude-frequency curve corresponding to the complex function corresponding to the pure elastic signal, and the frequency corresponding to the maximum point is the first-order elastic frequency obtained by identification.

[0076] 7) Based on the result of step 6), the adaptive estimated intermediate value of the weight at time t is calculated as:

[0077]

[0078] 8) Adaptively estimate the intermediate value of the weight at time t and t-ΔT slide The estimated weight at the moment Perform smoothing to obtain the weight estimate at time t

[0079]

[0080] Where p≥1 is the smoothing coefficient;

[0081] 9) Based on the result of step 8), calculate the estimated value of the rigid body signal at time t As the control feedback in the time interval [t, t+Δt]:

[0082]

[0083] 10) Judgment:

[0084] If t<t end , then after a time step ΔT, return to step 2);

[0085] If t≥t end , the calculation ends.

[0086] A third embodiment of the present invention provides an electronic device, including:

[0087] at least one processor; and a memory communicatively coupled to the at least one processor;

[0088] The memory stores instructions that can be executed by the at least one processor, and the instructions are configured to execute the above-mentioned rate gyro adaptive weighting method based on Fourier transform.

[0089] A fourth aspect of the present invention provides a computer-readable storage medium storing computer instructions for enabling the computer to execute the aforementioned Fourier transform-based rate gyro adaptive weighting method.

[0090] The characteristics and beneficial effects of the present invention are:

[0091] 1. The present invention extracts the first-order elastic frequency information from the rate gyro observation signal based on Fourier transform, fully utilizes the amplitude-frequency curve distribution characteristics of the rigid body signal and the elastic signal, and adaptively estimates the weight from the frequency domain perspective. Compared with traditional rate gyro adaptive weighting methods, this method has the advantages of high calculation accuracy and stable and reliable algorithm.

[0092] 2. The present invention processes rate gyro observation signals based on Fourier transform. This method does not rely on the actual power of the rigid-body signal and the elastic signal, but only on the amplitude ratio of the rigid-elastic signal at the first-order elastic frequency. This method can effectively overcome the defect of traditional rate gyro adaptive weighting methods that cannot continuously correct the weights when the rigid-elastic signal power is low, and provides a potential technical solution for rigid-body signal acquisition in the attitude control of heavy-lift launch vehicles.

[0093] 3. The present invention adaptively estimates weights from a frequency domain perspective, with significant advantages in accuracy and reliability. It also has the ability to continuously correct weights even when the power of rigid body signals and elastic signals is low. It can be applied to the field of attitude control of heavy-lift carrier rockets, providing strong support for my country's development of attitude control methods for heavy-lift carrier rockets. BRIEF DESCRIPTION OF THE DRAWINGS

[0094] Figure 1 This is an overall flow chart of a rate gyro adaptive weighting method based on Fourier transform in an embodiment of the present invention.

[0095] Figure 2 It is a schematic diagram of the rigid body signal estimation result in a specific embodiment of the present invention.

[0096] Figure 3 It is a schematic diagram of rigid body signal estimation error in a specific embodiment of the present invention.

[0097] Figure 4 It is a schematic diagram of the weight adaptive estimation result in a specific embodiment of the present invention. DETAILED DESCRIPTION

[0098] The embodiment of the present invention provides a method and device for adaptive weighting of a rate gyro based on Fourier transform, which is described in detail below with reference to the accompanying drawings and an embodiment.

[0099] An embodiment of the present invention provides a rate gyro adaptive weighting method based on Fourier transform, comprising:

[0100] Establishing a launch vehicle attitude dynamics model, wherein a rate gyroscope is arranged at the front and rear of the launch vehicle;

[0101] Based on the dynamic model, constructing a rate gyro weighted weight estimation model;

[0102] Based on the weight estimation model of the rate gyro weighting, the weight is estimated using Fourier transform to obtain a rigid body signal estimation result of the launch vehicle.

[0103] In a specific embodiment of the present invention, the rate gyro adaptive weighting method based on Fourier transform has the following overall process: Figure 1 As shown, the following steps are included:

[0104] 1) Establish the launch vehicle pitch channel attitude dynamics model;

[0105] In this embodiment, based on the idea of ​​small-disturbance linearization, the pitch channel of the launch vehicle is decoupled separately, and only the influence of the first-order elastic mode is considered. A rate gyroscope is placed at the front and rear positions of the launch vehicle, and the attitude dynamics model of the pitch channel of the launch vehicle is expressed in state space as follows:

[0106]

[0107] Y=CX (2)

[0108]

[0109] Among them, formula (1) is the state equation, formula (2) is the observation equation, A is the state matrix, B is the control matrix, and C is the output matrix. is the state variable, is the pitch angular velocity deviation, is the pitch angle deviation, Δθ is the trajectory inclination deviation, is the first-order generalized velocity, q1 is the first-order generalized displacement, b1, b2, c1, c2, c4 are the aerodynamic torque coefficients, b 11 is the coupling coefficient of the first-order generalized velocity to the pitch angular velocity deviation, b 21 is the coupling coefficient of the first-order generalized displacement to the pitch angle deviation, c 11 is the coupling coefficient of the first-order generalized velocity to the ballistic inclination velocity deviation, c 21is the coupling coefficient of the first-order generalized displacement to the trajectory inclination deviation, D 11 is the coupling coefficient of the pitch angular velocity deviation to the first-order generalized velocity, D 21 is the coupling coefficient of the pitch angle deviation to the first-order generalized displacement (the above coefficients can be obtained according to actual conditions), ω1 is the first-order elastic frequency, ξ1 is the damping ratio corresponding to the first-order elastic frequency, and the control input is the equivalent swing angle of the engine, b3 is the pitch angle deviation control gain, c3 is the trajectory inclination deviation control gain, D3 is the first-order elastic mode control gain, is the observed variable, is the pitch angle deviation measured by the inertial group, and are the pitch rate deviations measured by the front and rear rate gyros, is the modal slope of the first-order elastic mode at the inertia group, R z1 F and R z1 R are the vibration mode slopes of the first-order elastic mode at the front and rear rate gyroscopes, respectively.

[0110] 2) Based on the model established in step 1), a weight estimation model for rate gyro weighting is constructed;

[0111] Assume that there is a weight value K, so that the weighted signal of the pitch angular velocity deviation signal measured by the front and rear rate gyros is an accurate rigid body signal, that is:

[0112]

[0113] Then the weight K should satisfy:

[0114]

[0115] Considering that in actual flight, the mode slope R z1 F and R z1 R They will change with the change of rocket mass and structural parameters. Therefore, the weight K calculated by using the vibration mode slope value measured by the ground full-rocket structural dynamics test is inaccurate. The weight K must be estimated online to eliminate the influence of the first-order elastic signal in real time and obtain an accurate rigid body signal.

[0116] 3) Based on the rate gyro weighted weight estimation model, the Fourier transform is used to adaptively estimate the weights to obtain the rigid body signal estimation results of the launch vehicle at each time. The specific steps are as follows:

[0117] 3-1) Set the time step to ΔT (the value of ΔT depends on the computing power of the onboard computer. The smaller the value, the higher the calculation accuracy). Set the window time of each Fourier transform to ΔT. window (ΔT window >6π / ω1), set the sliding time to ΔT slide , ΔT slide ≥ΔT.

[0118] Let the initial time of the launch vehicle flight be time 0, and the time of the first Fourier transform be t start , t start ≥ΔT window And t start >ΔT slide ; The end time of the launch vehicle flight is t end (t end >t start )time.

[0119] 3-2) Let the current time be time t and determine:

[0120] If t<t start , then go to step 3-3); if t≥t start , then go to step 3-4).

[0121] 3-3) Based on the ground full-rocket structural dynamic test results, the estimated values ​​of the mode slopes at the forward and aft rate gyro positions corresponding to time t are obtained respectively. and According to formula (6), the estimated value of the rate gyro weight at time t is calculated Then proceed to step 3-9).

[0122]

[0123] 3-4) Judgment:

[0124] If (tt start )mod(ΔT slide )≠0 (where mod represents the modulo operation), keeping the current weight estimate unchanged, that is: Then proceed to step 3-9);

[0125] If (tt start )mod(ΔT slide )=0, then the window time signal is sampled at the current moment and [t-ΔT window ,t] time interval, the front and rear rate gyro measurement signals are recorded as and

[0126] 3-5) Fast Fourier transform;

[0127] right and Perform fast Fourier transform respectively to obtain the complex function corresponding to the front rate gyro measurement signal The complex function corresponding to the post-rate gyro measurement signal The expressions are as follows:

[0128]

[0129] Among them, the symbol F represents the fast Fourier transform of the signal. is the first-order generalized velocity The corresponding complex function after transformation.

[0130] 3-6) First-order elastic frequency identification;

[0131] Subtract the two complex functions obtained in steps 3-5) to obtain the complex function corresponding to the pure elastic signal:

[0132]

[0133] The purely elastic signal corresponds to a complex function Find the maximum point in the corresponding amplitude-frequency curve, and the frequency corresponding to the maximum point is the first-order elastic frequency obtained by identification.

[0134] 3-7) Weight adaptive estimation;

[0135] Since the rigid body signal is mainly distributed in the low frequency band, at the first-order elastic frequency, it can be considered that the amplitude of the rigid body signal is much smaller than the amplitude of the first-order elastic signal, that is, it satisfies the following formula:

[0136]

[0137] Then the adaptive estimated intermediate value of the weight at time t is:

[0138]

[0139] 3-8) Smoothing;

[0140] The adaptive estimated intermediate value of the weight at time t and t-ΔT slide The estimated weight at the moment Perform smoothing to obtain the weight estimate at time t

[0141]

[0142] Where p≥1 is the smoothing coefficient.

[0143] 3-9) Based on the result of step 3-8), use formula (12) to weight and obtain the estimated value of the rigid body signal at time t The result is used as control feedback and introduced into the controller in the time interval [t, t+ΔT].

[0144]

[0145] 3-10) Judgment:

[0146] If t<t end , then after a time step ΔT, return to step 3-2);

[0147] If t≥t end , then the calculation ends.

[0148] In a specific embodiment of the present invention, it is assumed that the overall parameters of the rocket attitude dynamics model are as follows:

[0149]

[0150] Other parameter values ​​are as follows:

[0151] The modal slope of the first-order elastic mode at the location of the inertia group The modal slope R of the first-order elastic mode at the location of the front rate gyro z1 F =0.0214(2-e -t ), the modal slope R of the first-order elastic mode at the location of the rear rate gyro z1 F =-0.005(0.7+0.3e -t ), time step ΔT = 0.001s, window time ΔT window =5s, sliding time ΔT slide = 0.1s, the time t at which the Fourier transform is first performed start =10s, flight end time t end =60s, smoothing coefficient p=60.

[0152] Figure 2 Schematic diagram of the rigid body signal estimation result in this embodiment. Figure 2The observation signal output by the front rate gyro (represented by a dotted line), the observation signal output by the rear rate gyro (represented by a dashed line), and the estimated rigid body signal obtained based on the method of the present invention (represented by a solid line) in this embodiment are shown and compared with the true rigid body signal (represented by a double-dash line). The locally enlarged diagram shows the signal curves from 21s to 24s. It can be seen that the estimated rigid body signal obtained based on the method of the present invention is closest to the true rigid body signal, indicating that the method of the present invention can effectively eliminate the influence of the first-order elastic mode on the output signal of the rate gyro and obtain an accurate rigid body signal. Figure 3 Schematic diagram of the rigid body signal estimation error in this embodiment. Figure 3 The estimation error of the rigid body signal is given. The local magnified figure shows the error curve of the last 10s of the flight time. It can be seen that after the introduction of the method of the present invention, the estimation error of the rigid body signal decreases rapidly and finally converges to 5×10 -6 rad / s, which effectively proves that the method has high accuracy. Figure 4 Schematic diagram of the weight adaptive estimation result in this embodiment. Figure 4 The estimated weight change curve (indicated by a dotted line) and the true weight change curve (indicated by a solid line) obtained based on the method of the present invention during flight are given. Figure 4 It can be seen from the figure that after the weight adaptive estimation is performed at 10s, the estimated weight curve is smooth and can converge quickly. The relative error in the steady state is 1.3887%, which reflects the accuracy of the weight estimation method of the present invention.

[0153] To illustrate the computational accuracy and continuous correction advantages of the method of the present invention, a traditional rate gyro adaptive weighting method based on integral correction was used for comparative simulation, where the integral coefficient was 100 and the integration time was 1s, the period of the first-order elastic mode. Table 1 shows the comparison results of the two methods. The continuous correction time is defined as the difference between the time when the weight enters the steady-state value within the error band of ±1% and the time when the weight estimation is just started. Compared with the traditional method, the continuous correction time of the method of the present invention is significantly longer. Even when the rigid-elastic signal converges quickly, it still has the ability to adaptively estimate the weight and can continue to correct the weight, thereby significantly reducing the steady-state error of the weight and the final error of the rigid body velocity estimation. In addition, the maximum error of the rigid body velocity estimation of the method of the present invention is small, indicating that the algorithm stability of the method of the present invention is better. The above comparison results effectively illustrate the advantages of the method of the present invention in computational accuracy, continuous correction effect, and algorithm stability.

[0154] Table 1 Comparison of simulation results between the method of the present invention and the traditional method

[0155]

[0156] In summary, this embodiment employs the Fourier transform-based adaptive weighting method for rate gyros proposed in this invention and applies it to heavy-lift launch vehicle attitude control missions. Compared to traditional methods, it offers significant advantages in accuracy, stability, and continuous correction. This embodiment addresses the heavy-lift launch vehicle attitude controller's demand for accurate rigid-body signals by using two rate gyros for weighting, thereby accurately estimating the rigid-body signal. This estimated signal can be used as control feedback to achieve elastic and stable control of the rocket's attitude, making it easily applicable to heavy-lift launch vehicle flight missions.

[0157] To implement the above embodiment, a second embodiment of the present invention provides a rate gyro adaptive weighting device based on Fourier transform, comprising:

[0158] A dynamic model building module is used to establish a dynamic model of the launch vehicle attitude, wherein a rate gyroscope is arranged at the front and rear of the launch vehicle;

[0159] A weight estimation model construction module, configured to construct a weight estimation model for rate gyro weighting based on the dynamic model;

[0160] An adaptive weighting module is used to estimate the weights based on the weight estimation model of the rate gyro weighting by using Fourier transform to obtain a rigid body signal estimation result of the launch vehicle.

[0161] In a specific embodiment of the present invention, the carrier rocket attitude dynamics model is the carrier rocket pitch channel attitude dynamics model, which is expressed as follows:

[0162]

[0163] Y=CX (2)

[0164]

[0165] Among them, formula (1) is the state equation, formula (2) is the observation equation, A is the state matrix, B is the control matrix, and C is the output matrix; is the state variable, is the pitch angular velocity deviation, is the pitch angle deviation, Δθ is the trajectory inclination deviation, is the first-order generalized velocity, q1 is the first-order generalized displacement, b1, b2, c1, c2, c4 are the aerodynamic torque coefficients, b 11 is the coupling coefficient of the first-order generalized velocity to the pitch angular velocity deviation, b 21 is the coupling coefficient of the first-order generalized displacement to the pitch angle deviation, c 11 is the coupling coefficient of the first-order generalized velocity to the ballistic inclination velocity deviation, c 21is the coupling coefficient of the first-order generalized displacement to the trajectory inclination deviation, D 11 is the coupling coefficient of the pitch angular velocity deviation to the first-order generalized velocity, D 21 is the coupling coefficient of the pitch angle deviation to the first-order generalized displacement, ω1 is the first-order elastic frequency, ξ1 is the damping ratio corresponding to the first-order elastic frequency, and the control input is the equivalent swing angle of the engine, b3 is the pitch angle deviation control gain, c3 is the trajectory inclination deviation control gain, D3 is the first-order elastic mode control gain, is the observed variable, is the pitch angle deviation measured by the inertial group, is the pitch rate deviation measured by the front rate gyro, is the pitch rate deviation measured by the rear rate gyro, is the modal slope of the first-order elastic mode at the inertia group, R z1 F is the modal slope of the first-order elastic mode at the front rate gyro, R z1 R is the slope of the vibration mode of the first-order elastic mode at the rear rate gyro.

[0166] In a specific embodiment of the present invention, the weight estimation model expression of the rate gyro weighting is as follows:

[0167]

[0168] Then the weight K of the rate gyro weighting satisfies:

[0169]

[0170] In a specific embodiment of the present invention, the weight estimation model based on the rate gyro weighting estimates the weight using Fourier transform, including:

[0171] 1) Set the time step to ΔT and the window time of each Fourier transform to ΔT window , set the sliding time to ΔT slide , ΔT slide ≥ΔT;

[0172] Let the initial time of the launch vehicle flight be time 0, and the time of the first Fourier transform be t start , t start ≥ΔT window And t start >ΔT slide ; The end time of the launch vehicle flight is t end , t end >t start ;

[0173] 2) Let the current time be time t and determine:

[0174] If t<t start , then go to step 3); if t≥t start , then go to step 4).

[0175] 3) Based on the ground full-rocket structural dynamic test results, the estimated values ​​of the mode slope at the corresponding front rate gyro position at time t are obtained respectively and the estimated value of the mode slope at the rate gyro position corresponding to time t Calculate the estimated value of the rate gyro weight at time t

[0176]

[0177] Then go to step 9);

[0178] 4) Judgment:

[0179] If (tt start )mod(ΔT slide )≠0, then the weight estimate at time t remains unchanged, that is: Then proceed to step 9), where mod represents a modulo operation;

[0180] If (tt start )mod(ΔT slide )=0, then the window time signal is sampled at time t, and [t-ΔT window The front rate gyro measurement signal in the time interval t] is recorded as The rate gyro measurement signal is recorded as

[0181] 5) Yes and Perform fast Fourier transform respectively to obtain the complex function corresponding to the front rate gyro measurement signal The complex function corresponding to the post-rate gyro measurement signal The expressions are as follows:

[0182]

[0183] Among them, the symbol F represents the fast Fourier transform of the signal. is the first-order generalized velocity The corresponding complex function after transformation;

[0184] 6) Based on the complex function obtained in step 5), calculate the complex function corresponding to the pure elastic signal:

[0185]

[0186] Find the maximum point in the amplitude-frequency curve corresponding to the complex function corresponding to the pure elastic signal, and the frequency corresponding to the maximum point is the first-order elastic frequency obtained by identification.

[0187] 7) Based on the result of step 6), the adaptive estimated intermediate value of the weight at time t is calculated as:

[0188]

[0189] 8) Adaptively estimate the intermediate value of the weight at time t and t-ΔT slide The estimated weight at the moment Perform smoothing to obtain the weight estimate at time t

[0190]

[0191] Where p≥1 is the smoothing coefficient;

[0192] 9) Based on the result of step 8), calculate the estimated value of the rigid body signal at time t As the control feedback in the time interval [t, t+Δt]:

[0193]

[0194] 10) Judgment:

[0195] If t<t end , then after a time step ΔT, return to step 2);

[0196] If t≥t end , the calculation ends.

[0197] It should be noted that the aforementioned explanation of a Fourier transform-based adaptive weighting method for rate gyros also applies to the Fourier transform-based adaptive weighting device for rate gyros in this embodiment and will not be repeated here. A Fourier transform-based adaptive weighting device for rate gyros, according to an embodiment of the present invention, establishes a launch vehicle attitude dynamics model, wherein a rate gyro is positioned at the front and rear of the launch vehicle; constructs a rate gyro weighting weight estimation model based on the dynamics model; and estimates the weights using a Fourier transform based on the rate gyro weighting weight estimation model to obtain a rigid body signal estimation result for the launch vehicle. This allows for efficient online updating of the rate gyro weights, obtaining accurate rigid body signals for control feedback, and thereby solving the attitude control problem of heavy-duty launch vehicles in situations where the rigid body and elastic signals are severely coupled.

[0198] To implement the above embodiment, a third aspect of the present invention provides an electronic device, including:

[0199] at least one processor; and a memory communicatively coupled to the at least one processor;

[0200] The memory stores instructions that can be executed by the at least one processor, and the instructions are configured to execute the above-mentioned rate gyro adaptive weighting method based on Fourier transform.

[0201] To implement the above embodiment, a fourth aspect of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the above-mentioned rate gyro adaptive weighting method based on Fourier transform.

[0202] It should be noted that the computer-readable medium mentioned above in the present disclosure may be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or component, 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), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present disclosure, a computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, device, or component. In the present disclosure, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. Such a propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the computer-readable 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.

[0203] The computer-readable medium may be included in the electronic device, or may exist independently and not incorporated into the electronic device. The computer-readable medium carries one or more programs. When executed by the electronic device, the one or more programs cause the electronic device to perform the Fourier transform-based rate gyro adaptive weighting method of the above embodiment.

[0204] Computer program code for performing the operations of the present disclosure 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 stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on the remote computer or server. In cases involving 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., through the Internet using an Internet service provider).

[0205] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification and features of different embodiments or examples without contradiction.

[0206] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of the technical features being referred to. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of such features. Throughout the description of this application, "plurality" means at least two, for example, two, three, etc., unless otherwise specifically defined.

[0207] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code comprising one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may be performed out of the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present application belong.

[0208] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and programmable read-only memory (EPROM or flash memory), fiber optic devices, and a portable compact disc read-only memory (CDROM). Furthermore, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or otherwise processing it in a suitable manner if necessary, and then storing it in a computer memory.

[0209] It should be understood that various parts of the present application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used to implement: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0210] Those skilled in the art will understand that all or part of the steps in the method of the above embodiment can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiment.

[0211] In addition, the functional units in the various embodiments of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into a module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0212] The storage medium mentioned above may be a read-only memory, a magnetic disk, or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application. Persons skilled in the art may make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims

1. A rate gyro adaptive weighting method based on Fourier transform, characterized in that: include: Establishing a launch vehicle attitude dynamics model, wherein a rate gyroscope is arranged at the front and rear of the launch vehicle; Based on the dynamic model, constructing a rate gyro weighted weight estimation model; Based on the weight estimation model of the rate gyro weighting, the weight is estimated by using Fourier transform to obtain a rigid body signal estimation result of the launch vehicle; The carrier rocket attitude dynamics model is the carrier rocket pitch channel attitude dynamics model, which is expressed as follows: Y=CX (2) Among them, formula (1) is the state equation, formula (2) is the observation equation, A is the state matrix, B is the control matrix, and C is the output matrix; is the state variable, is the pitch angular velocity deviation, is the pitch angle deviation, Δθ is the trajectory inclination deviation, is the first-order generalized velocity, q1 is the first-order generalized displacement, b1, b2, c1, c2, c4 are the aerodynamic torque coefficients, b 11 is the coupling coefficient of the first-order generalized velocity to the pitch angular velocity deviation, b 21 is the coupling coefficient of the first-order generalized displacement to the pitch angle deviation, c 11 is the coupling coefficient of the first-order generalized velocity to the ballistic inclination velocity deviation, c 21 is the coupling coefficient of the first-order generalized displacement to the trajectory inclination deviation, D 11 is the coupling coefficient of the pitch angular velocity deviation to the first-order generalized velocity, D 21 is the coupling coefficient of the pitch angle deviation to the first-order generalized displacement, ω1 is the first-order elastic frequency, ξ1 is the damping ratio corresponding to the first-order elastic frequency, and the control input is the equivalent swing angle of the engine, b3 is the pitch angle deviation control gain, c3 is the trajectory inclination deviation control gain, D3 is the first-order elastic mode control gain, is the observed variable, is the pitch angle deviation measured by the inertial group, is the pitch rate deviation measured by the front rate gyro, is the pitch rate deviation measured by the rear rate gyro, is the modal slope of the first-order elastic mode at the inertia group, R z1 F is the modal slope of the first-order elastic mode at the front rate gyro, R z1 R is the mode slope of the first-order elastic mode at the rear rate gyro; The weight estimation model expression of the rate gyro weighting is as follows: Then the weight K of the rate gyro weighting satisfies:

2. The method according to claim 1, characterized in that The weight estimation model based on the rate gyro weighting estimates the weight using Fourier transform, including: 1) Set the time step to ΔT and the window time of each Fourier transform to ΔT window , set the sliding time to ΔT slide , ΔT slide ≥ΔT; Let the initial time of the launch vehicle flight be time 0, and the time of the first Fourier transform be t start , t start ≥ΔT window And t start >ΔT slide ; The end time of the launch vehicle flight is t end , t end >t start ; 2) Let the current time be time t and determine: If t<t start , then go to step 3); if t≥t start , then go to step 4); 3) Based on the ground full-rocket structural dynamic test results, the estimated values ​​of the mode slope at the corresponding front rate gyro position at time t are obtained respectively and the estimated value of the mode slope at the rate gyro position corresponding to time t Calculate the estimated value of the rate gyro weight at time t Then go to step 9); 4) Judgment: If (tt start )mod(ΔT slide )≠0, then the weight estimate at time t remains unchanged, that is: Then proceed to step 9), where mod represents a modulo operation; If (tt start )mod(ΔT slide )=0, then the window time signal is sampled at time t, and [t-ΔT window The front rate gyro measurement signal in the time interval t] is recorded as The rate gyro measurement signal is recorded as 5) Yes and Perform fast Fourier transform respectively to obtain the complex function corresponding to the front rate gyro measurement signal The complex function corresponding to the post-rate gyro measurement signal The expressions are as follows: Among them, the symbol Indicates the fast Fourier transform of the signal. is the first-order generalized velocity The corresponding complex function after transformation; 6) Based on the complex function obtained in step 5), calculate the complex function corresponding to the pure elastic signal: Find the maximum point in the amplitude-frequency curve corresponding to the complex function corresponding to the pure elastic signal, and the frequency corresponding to the maximum point is the first-order elastic frequency obtained by identification. 7) Based on the result of step 6), the adaptive estimated intermediate value of the weight at time t is calculated as: 8) Adaptively estimate the intermediate value of the weight at time t and t-ΔT slide The estimated weight at the moment Perform smoothing to obtain the weight estimate at time t Where p≥1 is the smoothing coefficient; 9) Based on the result of step 8), calculate the estimated value of the rigid body signal at time t As the control feedback in the time interval [t, t+ΔT]: 10) Judgment: If t<t end , then after a time step ΔT, return to step 2); If t≥t end , the calculation ends.

3. A rate gyro adaptive weighting device based on Fourier transform, characterized in that: include: A dynamic model building module is used to establish a dynamic model of the launch vehicle attitude, wherein a rate gyroscope is arranged at the front and rear of the launch vehicle; A weight estimation model construction module, configured to construct a weight estimation model for rate gyro weighting based on the dynamic model; an adaptive weighting module, configured to estimate the weights based on the rate gyro weighting weight estimation model using Fourier transform to obtain a rigid body signal estimation result of the launch vehicle; The carrier rocket attitude dynamics model is the carrier rocket pitch channel attitude dynamics model, which is expressed as follows: Y=CX (2) Among them, formula (1) is the state equation, formula (2) is the observation equation, A is the state matrix, B is the control matrix, and C is the output matrix; is the state variable, is the pitch angular velocity deviation, is the pitch angle deviation, Δθ is the trajectory inclination deviation, is the first-order generalized velocity, q1 is the first-order generalized displacement, b1, b2, c1, c2, c4 are the aerodynamic torque coefficients, b 11 is the coupling coefficient of the first-order generalized velocity to the pitch angular velocity deviation, b 21 is the coupling coefficient of the first-order generalized displacement to the pitch angle deviation, c 11 is the coupling coefficient of the first-order generalized velocity to the ballistic inclination velocity deviation, c 21 is the coupling coefficient of the first-order generalized displacement to the trajectory inclination deviation, D 11 is the coupling coefficient of the pitch angular velocity deviation to the first-order generalized velocity, D 21 is the coupling coefficient of the pitch angle deviation to the first-order generalized displacement, ω1 is the first-order elastic frequency, ξ1 is the damping ratio corresponding to the first-order elastic frequency, and the control input is the equivalent swing angle of the engine, b3 is the pitch angle deviation control gain, c3 is the trajectory inclination deviation control gain, D3 is the first-order elastic mode control gain, is the observed variable, is the pitch angle deviation measured by the inertial group, is the pitch rate deviation measured by the front rate gyro, is the pitch rate deviation measured by the rear rate gyro, is the modal slope of the first-order elastic mode at the inertia group, R z1 F is the modal slope of the first-order elastic mode at the front rate gyro, R z1 R is the mode slope of the first-order elastic mode at the rear rate gyro; The weight estimation model expression of the rate gyro weighting is as follows: Then the weight K of the rate gyro weighting satisfies:

4. The device according to claim 3, characterized in that The weight estimation model based on the rate gyro weighting estimates the weight using Fourier transform, including: 1) Set the time step to ΔT and the window time of each Fourier transform to ΔT window , set the sliding time to ΔT slide , ΔT slide ≥ΔT; Let the initial time of the launch vehicle flight be time 0, and the time of the first Fourier transform be t start , t start ≥ΔT window And t start >ΔT slide ; The end time of the launch vehicle flight is t end , t end >t start ; 2) Let the current time be time t and determine: If t<t start , then go to step 3); if t≥t start , then go to step 4); 3) Based on the ground full-rocket structural dynamic test results, the estimated values ​​of the mode slope at the corresponding front rate gyro position at time t are obtained respectively and the estimated value of the mode slope at the rate gyro position corresponding to time t Calculate the estimated value of the rate gyro weight at time t Then go to step 9); 4) Judgment: If (tt start )mod(ΔT slide )≠0, then the weight estimate at time t remains unchanged, that is: Then proceed to step 9), where mod represents a modulo operation; If (tt start )mod(ΔT slide )=0, then the window time signal is sampled at time t, and [t-ΔT window The front rate gyro measurement signal in the time interval t] is recorded as The rate gyro measurement signal is recorded as 5) Yes and Perform fast Fourier transform respectively to obtain the complex function corresponding to the front rate gyro measurement signal The complex function corresponding to the post-rate gyro measurement signal The expressions are as follows: Among them, the symbol Indicates the fast Fourier transform of the signal. is the first-order generalized velocity The corresponding complex function after transformation; 6) Based on the complex function obtained in step 5), calculate the complex function corresponding to the pure elastic signal: Find the maximum point in the amplitude-frequency curve corresponding to the complex function corresponding to the pure elastic signal, and the frequency corresponding to the maximum point is the first-order elastic frequency obtained by identification. 7) Based on the result of step 6), the adaptive estimated intermediate value of the weight at time t is calculated as: 8) Adaptively estimate the intermediate value of the weight at time t and t-ΔT slide The estimated weight at the moment Perform smoothing to obtain the weight estimate at time t Where p≥1 is the smoothing coefficient; 9) Based on the result of step 8), calculate the estimated value of the rigid body signal at time t As the control feedback in the time interval [t, t+ΔT]: 10) Judgment: If t<t end , then after a time step ΔT, return to step 2); If t≥t end , the calculation ends.

5. An electronic device, characterized in that: include: at least one processor; and, a memory communicatively coupled to the at least one processor; The memory stores instructions that can be executed by the at least one processor, and the instructions are configured to execute the method according to any one of claims 1 to 2.

6. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the method according to any one of claims 1 to 2.

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