A method, device, equipment and medium for vibration suppression of an on-orbit imaging system
By combining an improved GRU neural network and the FFRLS algorithm, the problem of balancing convergence speed and control effect in vibration suppression of on-orbit imaging systems is solved, achieving rapid vibration suppression and efficient imaging quality assurance.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- XIAN INST OF OPTICS & PRECISION MECHANICS CHINESE ACAD OF SCI
- Filing Date
- 2026-03-06
- Publication Date
- 2026-06-16
AI Technical Summary
Existing vibration suppression methods for on-orbit imaging systems suffer from the problem of balancing convergence speed and control performance. The LMS adaptive algorithm has a slow convergence speed, while the RLS adaptive algorithm has good control performance when there is a lot of historical data but a slow convergence speed and poor performance when there is little historical data.
An improved GRU neural network and the Forgetting Factor Least Squares (FFRLS) algorithm are used to measure the signal through a vibration sensor, predict the target forgetting factor using the improved GRU neural network, and calculate the motor drive signal using the FFRLS algorithm to suppress vibration.
It achieves the ability to approach the optimal solution in a shorter time, cancel out specific frequency or narrowband vibrations in real time, and balances fast convergence and good control performance.
Smart Images
Figure CN122219655A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of vibration suppression technology, and provides a method, apparatus, equipment and medium for vibration suppression in an on-orbit imaging system. Background Technology
[0002] As is well known, during the on-orbit imaging process of remote sensing satellites, the operation of components such as the cooling system generates vibrations, which can cause image blurring and distortion. Therefore, to ensure imaging quality and resolution, it is necessary to suppress the vibration level of the cooling system and minimize vibration as much as possible.
[0003] Currently, vibration suppression in on-orbit imaging systems mainly includes two methods: passive suppression and active suppression. Passive suppression typically employs structural vibration isolation, while active suppression utilizes a motor control system to provide feedback adjustment to the acquired vibration signals and achieve vibration suppression through vibration suppression algorithms. Existing active control algorithms often employ Least Mean Square (LMS) adaptive algorithms and Recursive Least Squares (RLS) adaptive algorithms. The LMS adaptive algorithm dynamically adjusts the weighting coefficients of the input signals and then superimposes the signals to generate the output signal. The adjustment of the weighting coefficients uses the gradient of the squared error for iterative optimization, ultimately minimizing the error between the desired signal and the output signal. Therefore, LMS-type algorithms have a relatively slow convergence speed. The RLS adaptive algorithm is significantly affected by the forgetting factor; more historical data results in better control performance but slower convergence speed, while less historical data results in faster convergence speed but poorer control performance. Summary of the Invention
[0004] This application provides a vibration suppression method, apparatus, device, and medium for an on-orbit imaging system, which addresses the technical problem of balancing convergence speed and control effect in the prior art.
[0005] On the one hand, a vibration suppression method for an on-orbit imaging system is provided, the method comprising: Vibration sensors are used to measure data from the on-orbit imaging system to obtain vibration measurement signals. The vibration measurement signal is processed by an algorithm to calculate the coefficients and obtain the target coefficient vector. The vibration measurement signal is input into an improved GRU neural network for prediction to obtain the target forgetting factor; wherein, the improved GRU neural network is obtained by setting an update gate and a normalized reset gate in an LSTM model, and the update gate is obtained by merging the forgetting gate and the input gate; Based on the Forgotten Factor Least Squares (FFRLS) algorithm, the target coefficient vector, and the target forgetting factor, a motor drive signal is obtained to suppress vibration in the on-orbit imaging system.
[0006] Optionally, the step of calculating the target coefficient vector by performing algorithmic coefficient calculation on the vibration measurement signal includes: The vibration measurement signal is digitally processed to obtain the processed vibration measurement signal; Based on the processed vibration measurement signal, determine whether vibration suppression should be performed; If vibration suppression is determined, the algorithm coefficients are calculated on the processed vibration measurement signal to obtain the target coefficient vector.
[0007] Optionally, the step of calculating the algorithm coefficients of the processed vibration measurement signal to obtain the target coefficient vector includes: The processed vibration measurement signal is subjected to algorithmic coefficient calculation using a preset coefficient vector calculation formula to obtain the target coefficient vector; wherein the preset coefficient vector calculation formula is expressed as follows:
[0008] in, Let be the coefficient vector at time n. Let be the coefficient vector at time n-1. Let be the gain vector at time n. Let be the error at the nth time step.
[0009] Optionally, the step of digitizing the vibration measurement signal to obtain the processed vibration measurement signal includes: The vibration measurement signal is amplified to obtain an amplified vibration measurement signal; An A / D circuit is used to digitize the amplified vibration measurement signal to obtain the processed vibration measurement signal.
[0010] Optionally, the target forgetting factor is expressed using the following formula:
[0011] in, Let be the forgetting factor at time n. Let the forgetting factor be the value at time n-1. This represents the candidate hidden state information at time n. To update the door.
[0012] Optionally, after obtaining the motor drive signal based on the Forgotten Factor Least Squares (FFRLS) algorithm, the target coefficient vector, and the target forgetting factor, and performing vibration suppression on the on-orbit imaging system, the method further includes: Based on the vibration measurement signal after vibration suppression, determine whether the vibration suppression is in place; If it is determined that the vibration suppression is inadequate, the algorithm coefficients of the vibration measurement signal are recalculated. If vibration suppression is confirmed to be in place, then vibration suppression is terminated.
[0013] Optionally, after obtaining the motor drive signal through the algorithm, the method further includes: A D / A circuit is used to perform analog processing on the motor drive signal to obtain the processed motor drive signal. The processed motor drive signal is amplified to obtain an amplified motor drive signal. The amplified motor drive signal is used to drive the vibration-absorbing motor to suppress vibration.
[0014] On the one hand, an on-orbit imaging system vibration suppression system is provided, characterized in that the system includes a downlink measurement channel, an uplink control channel, and a vibration absorption controller; The downlink measurement channel is used to transmit vibration measurement signals. The uplink control channel is used to upload motor drive signals; The vibration damping controller is used to suppress the vibration measurement signal and generate the motor drive signal.
[0015] Optionally, the vibration damping controller includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement any of the methods described above.
[0016] On the one hand, a storage medium is provided that stores computer program instructions thereon, which, when executed by a processor, implement any of the methods described above.
[0017] Compared with the prior art, the beneficial effects of this application are as follows: In this application, when performing vibration suppression on an on-orbit imaging system, firstly, a vibration sensor can be used to measure the data of the on-orbit imaging system to obtain a vibration measurement signal; then, the vibration measurement signal can be used to calculate the algorithm coefficients to obtain a target coefficient vector; next, the vibration measurement signal can be input into an improved GRU neural network for prediction to obtain a target forgetting factor; wherein, the improved GRU neural network is obtained by setting an update gate and a normalized reset gate in an LSTM model, and the update gate is obtained by merging the forgetting gate and the input gate; finally, a motor drive signal can be obtained based on the forgetting factor least squares algorithm FFRLS, the target coefficient vector, and the target forgetting factor to suppress vibration in the on-orbit imaging system.
[0018] Based on this, this application employs an improved GRU neural network with a forgetting gate structure, adaptively calculating the forgetting factor. Furthermore, during the learning process, this improved GRU neural network processes historical data in parallel. Therefore, compared to existing technologies, this application can approach the optimal solution in a shorter time, measure and counteract vibrations generated at specific frequencies or narrow bands in real time, and achieve faster convergence. In addition, since it also uses the forgetting factor least squares algorithm (FFRLS) for parameter recursion, this application also maintains the excellent control performance of the FFRLS algorithm. Attached Figure Description
[0019] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.
[0020] Figure 1 A framework diagram of an on-orbit imaging system vibration suppression system provided in an embodiment of this application; Figure 2 A schematic diagram of a vibration absorption controller provided in an embodiment of this application; Figure 3 A schematic flowchart of an on-orbit imaging system vibration suppression method provided in an embodiment of this application; Figure 4 A structural diagram of an improved GRU neural network provided in an embodiment of this application; Figure 5 This is a structural diagram of vibration suppression provided in an embodiment of this application.
[0021] The diagram is labeled as follows: 101-Processor, 102-Memory, 103-I / O interface, 104-Database. Detailed Implementation
[0022] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application. Unless otherwise specified, the embodiments and features in the embodiments of this application can be arbitrarily combined with each other. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than that shown here.
[0023] As is well known, during the on-orbit imaging process of remote sensing satellites, the operation of components such as the cooling system generates vibrations, which can cause image blurring and distortion. Therefore, to ensure imaging quality and resolution, it is necessary to suppress the vibration level of the cooling system and minimize vibration as much as possible.
[0024] Currently, vibration suppression in on-orbit imaging systems mainly includes two methods: passive suppression and active suppression. Passive suppression typically uses structural vibration isolation, while active suppression employs a motor control system to provide feedback adjustment to the acquired vibration signals and achieve vibration suppression through vibration suppression algorithms. Existing active control algorithms often use LMS adaptive algorithms and RLS adaptive algorithms. The LMS adaptive algorithm dynamically adjusts the weighting coefficients of the input signal and then superimposes the signals to generate the output signal. The adjustment of the weighting coefficients uses the gradient of the squared error for optimization iteration, ultimately minimizing the error between the desired signal and the output signal. Therefore, LMS-type algorithms have a relatively slow convergence speed. The RLS adaptive algorithm is greatly affected by the forgetting factor; more historical data results in better control performance but slower convergence speed, while less historical data results in faster convergence speed but poorer control effect.
[0025] Based on this, this application provides a vibration suppression method for an on-orbit imaging system. In this method, firstly, a vibration sensor is used to measure the data of the on-orbit imaging system to obtain a vibration measurement signal; then, the vibration measurement signal is used to calculate algorithm coefficients to obtain a target coefficient vector; next, the vibration measurement signal is input into an improved GRU neural network for prediction to obtain a target forgetting factor; wherein, the improved GRU neural network is obtained by setting an update gate and a normalized reset gate in an LSTM model, and the update gate is obtained by merging a forgetting gate and an input gate; finally, vibration suppression of the on-orbit imaging system is performed based on the forgetting factor least squares algorithm FFRLS, the target coefficient vector, and the target forgetting factor to obtain a motor drive signal.
[0026] Based on this, this application employs an improved GRU neural network with a forgetting gate structure, adaptively calculating the forgetting factor. Furthermore, during the learning process, this improved GRU neural network processes historical data in parallel. Therefore, compared to existing technologies, this application can approach the optimal solution in a shorter time, measure and counteract vibrations generated at specific frequencies or narrow bands in real time, and achieve faster convergence. In addition, since it also uses the forgetting factor least squares algorithm (FFRLS) for parameter recursion, this application also maintains the excellent control performance of the FFRLS algorithm.
[0027] After introducing the design concept of the embodiments of this application, the following is a brief introduction to the application scenarios to which the technical solutions of the embodiments of this application can be applied. It should be noted that the application scenarios described below are only for illustrating the embodiments of this application and are not intended to limit the scope. In specific implementation, the technical solutions provided by the embodiments of this application can be flexibly applied according to actual needs.
[0028] like Figure 1 The diagram shown is a framework diagram of an on-orbit imaging system vibration suppression system provided in an embodiment of this application. The system includes a downlink measurement channel, an uplink control channel, and a vibration absorption controller.
[0029] Specifically, the downlink measurement channel includes a vibration sensor, operational amplifier, and A / D acquisition circuit. The sensor measures the vibration signal of the system, which is amplified by the operational amplifier, converted by the A / D converter, and then sent to the vibration absorption controller. The vibration absorption controller processes the signal using the FFRLS algorithm and feeds it back to the motor through the uplink control channel. The uplink control channel consists of a D / A circuit, a power operational amplifier, and the vibration absorption motor.
[0030] In one possible implementation, such as Figure 2The diagram shown is a schematic of a vibration-absorbing controller provided in an embodiment of this application. The vibration-absorbing controller can be used to control vibration suppression in an on-orbit imaging system, and can be, for example, an onboard computer, a personal computer (PC), a server, or a laptop. The on-orbit imaging system vibration suppression device 10 may include one or more processors 101, a memory 102, an I / O interface 103, and a database 104. Specifically, the processor 101 may be a central processing unit (CPU) or a digital processing unit, etc. The memory 102 may be volatile memory, such as random-access memory (RAM); the memory 102 may also be non-volatile memory, such as read-only memory, flash memory, hard disk drive (HDD), or solid-state drive (SSD); or the memory 102 may be any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but is not limited thereto. The memory 102 may be a combination of the above-mentioned memories. The memory 102 can store some program instructions of the on-orbit imaging system vibration suppression method provided in the embodiments of this application. When these program instructions are executed by the processor 101, they can be used to implement the steps of the on-orbit imaging system vibration suppression method provided in the embodiments of this application, so as to solve the technical problems existing in the prior art, such as the difficulty in balancing convergence speed and control effect. The database 104 can be used to store data such as target forgetting factor, target coefficient vector, improved GRU neural network and FFRLS algorithm involved in the scheme provided in the embodiments of this application.
[0031] In this embodiment, the on-orbit imaging system vibration suppression device 10 can obtain vibration suppression instructions through the I / O interface 103. Then, the processor 101 of the on-orbit imaging system vibration suppression device 10 will solve the technical problems existing in the prior art, such as the difficulty in balancing convergence speed and control effect, according to the program instructions of the on-orbit imaging system vibration suppression method provided in this embodiment of the application stored in the memory 102. In addition, data such as target forgetting factor, target coefficient vector, improved GRU neural network and FFRLS algorithm can be stored in the database 104.
[0032] Of course, the methods provided in the embodiments of this application are not limited to... Figure 1 The application scenarios shown can also be used in other possible scenarios, and this application embodiment does not impose any limitations. Figure 1The functions that the various devices in the application scenarios shown can achieve will be described in subsequent method embodiments, and will not be elaborated on here. Below, the methods of the embodiments of this application will be described in conjunction with the accompanying drawings.
[0033] like Figure 3 The diagram shown is a flowchart illustrating a vibration suppression method for an on-orbit imaging system provided in this application. This method can... Figure 1 The vibration suppression device 10 of the on-orbit imaging system is used to perform this operation. Specifically, the process of this method is described below.
[0034] Step 301: Use a vibration sensor to measure data from the on-orbit imaging system and obtain vibration measurement signals.
[0035] Step 302: Digitize the vibration measurement signal to obtain the processed vibration measurement signal.
[0036] Specifically, such as Figure 1 As shown, in the downlink measurement channel, firstly, the vibration measurement signal can be amplified to obtain an amplified vibration measurement signal; then, an A / D circuit can be directly used to digitize the amplified vibration measurement signal to obtain the processed vibration measurement signal.
[0037] In this application, since the actual input vibration measurement signal is digitally processed and considered to be a sine / cosine basis function related to the vibration frequency, the processed vibration measurement signal... This can be expressed using a formula:
[0038] in, Let ω be the vibration angular frequency, and n be the algorithm variable.
[0039] Step 303: Determine whether to perform vibration suppression based on the processed vibration measurement signal.
[0040] Specifically, vibration suppression can be determined by judging whether the characteristics (magnitude, frequency, or stability) of the processed vibration measurement signal exceed the threshold range allowed by the imaging quality.
[0041] Step 304: If vibration suppression is determined, the algorithm coefficients are calculated on the processed vibration measurement signal to obtain the target coefficient vector.
[0042] Specifically, a preset coefficient vector calculation formula can be used to calculate the algorithm coefficients of the processed vibration measurement signal to obtain the target coefficient vector; wherein, the preset coefficient vector calculation formula is expressed as follows:
[0043] in, Let be the coefficient vector at time n. Let be the coefficient vector at time n-1. Let be the gain vector at time n. Let be the error at the nth time step.
[0044] Step 305: Input the processed vibration measurement signal into the improved GRU neural network for prediction to obtain the target forgetting factor.
[0045] In this application, the improved GRU neural network is obtained by setting an update gate and a normalized reset gate in an LSTM model. The update gate is obtained by merging a forget gate and an input gate, as shown below. Figure 4 The diagram shown is a structural diagram of an improved GRU neural network provided in an embodiment of this application, wherein the forgetting factor... The value range is [0,1]. Based on this, the weight of historical data is controlled so that the value of the forgetting factor is closer to 1, and the more the improved GRU neural network depends on past data.
[0046] like Figure 4 As shown, this improved GRU neural network is a variant of the LSTM model, and its network input is the processed vibration measurement signal. You can first process the input. Perform standardization preprocessing, as shown in the following formula:
[0047] in, for Standardized preprocessed values, The global mean of the sample components. denoted as the standard deviation of the sample components.
[0048] Then, parameters are trained based on the formulas shown below to obtain the target forgetting factor. :
[0049]
[0050]
[0051]
[0052] in, Let be the forgetting factor at time n. Let the forgetting factor be the value at time n-1. This represents the candidate hidden state information at time n. The update gate, which merges the forget gate and the input gate, determines the amount of information retained from the previous time step. The larger the value, the more information is retained; The normalized reset gate determines the amount of reset information in the previous moment, which helps control the participation of historical states; To update the weight matrix of the gate; To reset the weight matrix of the gate; Let be the weight matrix of the candidate states.
[0053] Step 306: Based on the FFRLS algorithm based on the forgetting factor, the target coefficient vector, and the target forgetting factor, vibration suppression is performed on the on-orbit imaging system to obtain the motor drive signal.
[0054] Specifically, the Forgot Factor Least Squares (FFRLS) algorithm can be used to recursively derive the RLS parameters. First, initial parameters can be set. ; where the initial parameter It is usually set to the zero vector to ensure the range of initial parameters.
[0055] Then, in each iteration, the actual motor drive signal is... With the desired motor drive signal The comparisons are then performed to calculate the error signal as shown in the following formula:
[0056] In this application, the desired motor drive signal It can be theoretically modeled as a combination of sine and cosine signals; therefore, the desired motor drive signal can be represented by the following formula:
[0057] Next, we can perform a "parameter update," which means updating the parameters based on the error. and the processed vibration measurement signal To adjust the coefficient vector Parameters are continuously updated. and To minimize the weighted sum of squared errors. Then through... , , The forgetting factor is adaptively adjusted to achieve rapid convergence in the early stage and stable tracking of vibration changes in the later stage.
[0058] Finally, as Figure 5The diagram shown is a structural diagram of vibration suppression provided in an embodiment of this application. After convergence, the final coefficient vector and forgetting factor can be obtained. The motor drive signal can be directly obtained based on the final coefficient vector and forgetting factor to suppress vibration in the on-orbit imaging system. The suppression process can be specifically represented by the following formula:
[0059] In one possible implementation, after vibration suppression is performed on the on-orbit imaging system and the motor drive signal is obtained, the vibration measurement signal can be used to determine whether the vibration suppression is in place. If the vibration suppression is not in place, the algorithm coefficients of the vibration measurement signal are recalculated. Otherwise, if the vibration suppression is in place, the vibration suppression is terminated.
[0060] In one possible implementation, after the vibration suppression ends, such as Figure 1 As shown, the vibration measurement signal can also be monitored in real time, and motor drive can be performed in the uplink control channel as needed.
[0061] Specifically, firstly, the vibration measurement signal is amplified, and then an A / D circuit is used to digitize the vibration measurement signal, so that the vibration absorption controller can monitor the vibration state of the system in real time.
[0062] Then, a D / A circuit can be used to process the motor drive signal into analog form, and the processed motor drive signal can be amplified to obtain the motor drive signal after operational amplifier operation.
[0063] Finally, the motor drive signal after the operational amplifier can be directly used to drive the vibration-absorbing motor to achieve vibration suppression.
[0064] In summary, this application combines the FFRLS algorithm and an improved GRU neural network for vibration suppression. The core of the FFRLS algorithm is its ability to recursively estimate parameters using recursive least squares, resulting in good control performance. Furthermore, the improved GRU neural network employs a forgetting gate structure for adaptive learning and calculation of the forgetting factor. Because it processes historical data in parallel through the neural network, it can approximate the optimal solution in a shorter time. Therefore, this application achieves faster convergence while maintaining the excellent control performance of the FFRLS algorithm.
[0065] In some possible implementations, various aspects of the methods provided in this application can also be implemented as a program product comprising program code that, when run on a computer device, causes the computer device to perform the steps of the methods according to the various exemplary embodiments of this application described above. For example, the computer device may perform actions such as... Figure 3 The method performed by the vibration suppression device of the on-orbit imaging system in the illustrated embodiment.
[0066] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks. Alternatively, if the integrated units of this application are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, or the parts that contribute to the prior art, can be embodied in the form of software products. These computer software products are stored in a storage medium and include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROM, RAM, magnetic disks, or optical disks.
[0067] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.
[0068] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.
Claims
1. A vibration suppression method for an on-orbit imaging system, characterized in that, The method includes: Vibration sensors are used to measure data from the on-orbit imaging system to obtain vibration measurement signals. The vibration measurement signal is processed by an algorithm to calculate the coefficients and obtain the target coefficient vector. The vibration measurement signal is input into an improved GRU neural network for prediction to obtain the target forgetting factor; wherein, the improved GRU neural network is obtained by setting an update gate and a normalized reset gate in an LSTM model, and the update gate is obtained by merging the forgetting gate and the input gate; Based on the Forgotten Factor Least Squares (FFRLS) algorithm, the target coefficient vector, and the target forgetting factor, a motor drive signal is obtained to suppress vibration in the on-orbit imaging system.
2. The method as described in claim 1, characterized in that, The step of calculating the target coefficient vector by performing algorithmic coefficient calculation on the vibration measurement signal includes: The vibration measurement signal is digitally processed to obtain the processed vibration measurement signal; Based on the processed vibration measurement signal, determine whether vibration suppression should be performed; If vibration suppression is determined, the algorithm coefficients are calculated on the processed vibration measurement signal to obtain the target coefficient vector.
3. The method as described in claim 2, characterized in that, The step of calculating the algorithm coefficients of the processed vibration measurement signal to obtain the target coefficient vector includes: The processed vibration measurement signal is subjected to algorithmic coefficient calculation using a preset coefficient vector calculation formula to obtain the target coefficient vector; wherein the preset coefficient vector calculation formula is expressed as follows: in, Let be the coefficient vector at time n. Let be the coefficient vector at time n-1. Let be the gain vector at time n. Let be the error at the nth time step.
4. The method as described in claim 2, characterized in that, The step of digitizing the vibration measurement signal to obtain the processed vibration measurement signal includes: The vibration measurement signal is amplified to obtain an amplified vibration measurement signal; An A / D circuit is used to digitize the amplified vibration measurement signal to obtain the processed vibration measurement signal.
5. The method as described in claim 1, characterized in that, The target forgetting factor is expressed by the following formula: in, Let be the forgetting factor at time n. Let the forgetting factor be the value at time n-1. This represents the candidate hidden state information at time n. To update the door.
6. The method as described in claim 1, characterized in that, After obtaining the motor drive signal based on the Forgotten Factor Least Squares (FFRLS) algorithm, the target coefficient vector, and the target forgetting factor, and performing vibration suppression on the on-orbit imaging system, the method further includes: Based on the vibration measurement signal after vibration suppression, determine whether the vibration suppression is in place; If it is determined that the vibration suppression is inadequate, the algorithm coefficients of the vibration measurement signal are recalculated. If vibration suppression is confirmed to be in place, then vibration suppression is terminated.
7. The method as described in claim 1, characterized in that, The method further includes: A D / A circuit is used to perform analog processing on the motor drive signal to obtain the processed motor drive signal. The processed motor drive signal is amplified by a power operational amplifier to obtain a power-amplified motor drive signal. The amplified motor drive signal is used to drive the vibration-absorbing motor to suppress vibration.
8. A vibration suppression system for an on-orbit imaging system, characterized in that, The system includes a downlink measurement channel, an uplink control channel, and a vibration absorption controller; The downlink measurement channel is used to transmit vibration measurement signals. The uplink control channel is used to upload motor drive signals; The vibration absorption controller is used to process the vibration measurement signal using an algorithm to generate the motor drive signal.
9. The system as described in claim 8, characterized in that, The vibration absorption controller includes: Memory, used to store program instructions; A processor is configured to invoke program instructions stored in the memory and execute the method described in any one of claims 1-7 according to the obtained program instructions.
10. A storage medium, characterized in that, The storage medium stores computer-executable instructions for causing a computer to perform the method described in any one of claims 1-7.