Trap vibration damping method and device for magnetic suspension system based on real-time frequency estimation, equipment and medium
By employing a real-time frequency estimation method in the magnetic levitation control system, constructing an error signal and a cost function, and using a gradient descent algorithm to update the notch filter parameters, the problems of discrete jumps in frequency identification results and high computational complexity are solved. This achieves continuous frequency tracking and efficient suppression, adapts to resource-constrained processors, and meets the requirements of hard real-time control.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- NAT UNIV OF DEFENSE TECH
- Filing Date
- 2026-06-23
- Publication Date
- 2026-07-21
AI Technical Summary
Existing frequency estimation methods in magnetic levitation control systems suffer from problems such as discrete and abrupt frequency identification results, high computational complexity, poor noise resistance and stability, and difficulty in real-time updates in resource-constrained embedded digital signal processors, which limits vibration suppression performance.
A notch filter vibration suppression method for magnetic levitation systems based on real-time frequency estimation is adopted. Vibration signals are collected by sensors, error signals and cost functions are constructed, and gradient descent algorithm is used to construct iterative state-space equations, solve for the frequency and update the notch filter parameters, so as to achieve continuous frequency tracking and efficient suppression.
It generates continuous frequency reference curves, avoids frequency jumps, improves computational efficiency, adapts to resource-constrained processors, meets the requirements of hard real-time control, and achieves efficient active suppression of unknown frequency vibrations.
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Figure CN122432452A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of signal processing, and in particular to a method, apparatus, device, and medium for notch wave vibration suppression in a magnetic levitation system based on real-time frequency estimation. Background Technology
[0002] In high-performance control systems such as magnetic levitation control, vibration acceleration signals are core indicators for evaluating the system's dynamic characteristics. By acquiring the frequency and amplitude parameters of the signal online, controller parameters can be adjusted in real time, thereby achieving targeted suppression of disturbances at specific frequencies. Currently, existing frequency estimation methods mainly cover classical time-frequency analysis techniques represented by Fast Fourier Transform and Short-Time Fourier Transform, adaptive analysis methods represented by Continuous Wavelet Transform, and parameter identification methods based on control theory.
[0003] However, the aforementioned existing technologies have significant limitations when facing magnetic levitation control systems with stringent real-time requirements and complex operating conditions. On the one hand, traditional methods are constrained by the Heisenberg uncertainty principle and the picket fence effect, requiring the maintenance of a fixed-length buffer zone. This results in discrete, abrupt "step-like" frequency identification results, failing to provide a smooth frequency reference. On the other hand, high-precision adaptive algorithms have extremely high computational complexity, making it difficult to achieve microsecond-level real-time updates in resource-constrained embedded digital signal processors. Furthermore, existing technologies often struggle to balance noise immunity and dynamic response speed. They are susceptible to electromagnetic interference in low signal-to-noise ratio environments and suffer from convergence hysteresis under rapidly changing frequency conditions, severely limiting their vibration suppression performance under rapidly changing conditions. Summary of the Invention
[0004] In view of this, the purpose of this invention is to provide a method, apparatus, device, and medium for notch wave vibration suppression in magnetic levitation systems based on real-time frequency estimation, which can achieve efficient vibration suppression while ensuring the accuracy of frequency estimation. The specific solution is as follows: In a first aspect, this application discloses a notch wave vibration suppression method for a magnetic levitation system based on real-time frequency estimation, applied to a magnetic levitation control system, comprising: The target magnetic levitation vibration signal is collected by a preset sensor, and the corresponding estimated signal is determined based on the target magnetic levitation vibration signal; An error signal is constructed between the target magnetic levitation vibration signal and the estimated signal, and a target cost function is constructed based on the error signal; A real-time iterative state space equation is constructed based on a preset gradient descent algorithm, the target cost function, and the estimated signal. The real-time iterative state space equation is then solved to determine the current estimated frequency of the target magnetic levitation vibration signal based on the target output signal obtained from the solution. The parameters of the preset notch filter are updated based on the current estimated frequency to obtain the target notch filter, and the target output signal is input to the target notch filter to suppress the target magnetic levitation vibration signal based on the obtained target compensation signal.
[0005] Optionally, the step of acquiring the target magnetic levitation vibration signal through a preset sensor and determining the corresponding estimated signal based on the target magnetic levitation vibration signal includes: The target magnetic levitation vibration signal is collected by a preset sensor and used as the target sine signal. Based on the target sinusoidal signal, corresponding quadrature and in-phase components are constructed to construct an estimated signal corresponding to the target magnetic levitation vibration signal.
[0006] Optionally, constructing the error signal between the target magnetic levitation vibration signal and the estimated signal, and constructing the target cost function based on the error signal, includes: An error signal between the target magnetic levitation vibration signal and the estimated signal is constructed based on the instantaneous difference between the estimated signal and the target magnetic levitation vibration signal, and a target cost function is constructed based on the error signal; the target cost function is half the square of the error signal.
[0007] Optionally, the step of constructing a real-time iterative state-space equation based on a preset gradient descent algorithm, the target cost function, and the estimated signal includes: The negative gradient of the target cost function is derived based on a preset gradient descent algorithm to determine the target parameter relationship between the rate of change of the signal parameters corresponding to the target magnetic levitation vibration signal and the negative gradient of the target cost function. A real-time iterative state-space equation is constructed based on the target parameter relationship, the target cost function, the estimated signal, and the auxiliary state variables corresponding to the estimated signal. The auxiliary state variable and the estimated signal form orthogonal components.
[0008] Optionally, the real-time iterative state-space equation is: ; in, ; in, μ For signal tracking step size, To update the step size for frequency, and To preset a fast convergence factor, ω To estimate the instantaneous angular frequency in the signal parameters, eThe estimation error determined based on the error signal, α For preset exponent parameters, δ This is a preset threshold.
[0009] Optionally, solving the real-time iterative state-space equation to determine the current estimated frequency of the target magnetic levitation vibration signal based on the solved target output signal includes: The real-time iterative state-space equation is discretized using the Euler method, and the target suspension vibration signal is taken as input. Then, the real-time iterative state-space equation is solved based on a preset sampling period to obtain the target output signal. Extract the signal frequency of the target output signal and use the signal frequency as the current estimated frequency of the target magnetic levitation vibration signal.
[0010] Optionally, the step of updating the parameters of the preset notch filter based on the current estimated frequency to obtain the target notch filter, and inputting the target output signal to the target notch filter to suppress the target magnetic levitation vibration signal based on the obtained target compensation signal, includes: The current estimated frequency is used as the center frequency of the preset notch filter to update the parameters of the preset notch filter and obtain the target notch filter. The target output signal is input to the target notch filter to obtain the target compensation signal, and the target compensation signal is input to the magnetic levitation control system to suppress the target magnetic levitation vibration signal.
[0011] Secondly, this application discloses a notch wave vibration suppression device for a magnetic levitation system based on real-time frequency estimation, applied to a magnetic levitation control system, comprising: The estimated signal determination module is used to collect the target magnetic levitation vibration signal through a preset sensor, and determine the corresponding estimated signal based on the target magnetic levitation vibration signal; The cost function construction module is used to construct an error signal between the target magnetic levitation vibration signal and the estimated signal, and to construct a target cost function based on the error signal; The frequency estimation module is used to construct a real-time iterative state space equation based on a preset gradient descent algorithm, the target cost function, and the estimated signal, and to solve the real-time iterative state space equation to determine the current estimated frequency of the target magnetic levitation vibration signal based on the target output signal obtained from the solution. The signal suppression module is used to update the parameters of the preset notch filter based on the current estimated frequency to obtain the target notch filter, and input the target output signal to the target notch filter to suppress the target magnetic levitation vibration signal based on the obtained target compensation signal.
[0012] Thirdly, this application discloses an electronic device, including: Memory, used to store computer programs; A processor is used to execute the computer program to implement the aforementioned method for notch wave vibration suppression of magnetic levitation systems based on real-time frequency estimation.
[0013] Fourthly, this application discloses a computer-readable storage medium for storing a computer program, wherein the computer program, when executed by a processor, implements the aforementioned method for notch wave vibration suppression of a magnetic levitation system based on real-time frequency estimation.
[0014] In this application, a target magnetic levitation vibration signal can be acquired using a preset sensor, and a corresponding estimated signal can be determined based on the target magnetic levitation vibration signal. An error signal between the target magnetic levitation vibration signal and the estimated signal is constructed, and a target cost function is constructed based on the error signal. A real-time iterative state-space equation is constructed based on a preset gradient descent algorithm, the target cost function, and the estimated signal, and the real-time iterative state-space equation is solved to determine the current estimated frequency of the target magnetic levitation vibration signal based on the solution result. Finally, the parameters of a preset notch filter are updated based on the current estimated frequency to obtain a target notch filter, and the target output signal is input to the target notch filter to suppress the target magnetic levitation vibration signal based on the obtained target compensation signal.
[0015] Therefore, the method of this application can determine the corresponding estimated signal based on the collected target magnetic levitation vibration signal, and then construct a target cost function based on the error signal between the target magnetic levitation vibration signal and the estimated signal. A real-time iterative state-space equation is constructed based on a preset gradient descent algorithm, the target cost function, and the estimated signal, and the equation is solved. The current estimated frequency of the target magnetic levitation vibration signal is determined based on the target output signal obtained from the solution. Then, the parameters of a preset notch filter are updated based on the current estimated frequency to obtain the target notch filter. The target output signal is input to the target notch filter to suppress the target magnetic levitation vibration signal based on the obtained target compensation signal. In this way, on the one hand, due to the use of a feedback evolution mechanism, the generated frequency reference curve is completely continuous, avoiding frequency jumps, and the computational efficiency is high, adaptable to resource-constrained processors, and meeting the requirements of hard real-time control; on the other hand, by using the adaptive notch control strategy with the frequency estimation result as the basis for parameter updates, the magnetic levitation control system achieves efficient active suppression of unknown frequency vibrations under complex operating conditions. Attached Figure Description
[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.
[0017] Figure 1 This is a flowchart of a notch wave vibration suppression method for a magnetic levitation system based on real-time frequency estimation disclosed in this application; Figure 2 This is a flowchart of a frequency estimation method disclosed in this application; Figure 3 This is a schematic diagram of a notch wave vibration suppression device for a magnetic levitation system based on real-time frequency estimation disclosed in this application. Figure 4 This is a structural diagram of an electronic device disclosed in this application. Detailed Implementation
[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0019] Currently, existing frequency estimation methods mainly cover classical time-frequency analysis techniques represented by Fast Fourier Transform and Short-Time Fourier Transform, adaptive analysis methods represented by continuous wavelet transform, and parameter identification methods based on control theory. However, traditional methods are limited by the Heisenberg uncertainty principle and the picket fence effect, and cannot provide a smooth frequency reference. On the other hand, high-precision adaptive algorithms have extremely high computational complexity, making it difficult to achieve microsecond-level real-time updates in resource-constrained embedded digital signal processors. Furthermore, the vibration suppression performance of current methods is easily affected.
[0020] To overcome the aforementioned technical problems, this application discloses a notch-wave vibration suppression method, apparatus, device, and medium for magnetic levitation systems based on real-time frequency estimation. It employs a feedback evolution mechanism, generating a completely continuous frequency reference curve that avoids frequency jumps. Furthermore, it boasts extremely high computational efficiency, adaptable to resource-constrained processors, and meets the requirements of hard real-time control. Moreover, by using an adaptive notch-wave control strategy that updates parameters based on the frequency estimation results, it achieves efficient and proactive suppression of unknown frequency vibrations in the magnetic levitation control system under complex operating conditions.
[0021] See Figure 1As shown, this invention discloses a notch wave vibration suppression method for magnetic levitation systems based on real-time frequency estimation, applied to magnetic levitation control systems, including: Step S11: Collect the target magnetic levitation vibration signal through a preset sensor, and determine the corresponding estimated signal based on the target magnetic levitation vibration signal.
[0022] In this embodiment, the corresponding estimated signal can be determined by collecting the target magnetic levitation vibration signal. Specifically, for example... Figure 2 As shown, it is necessary to collect the current signal to be estimated by the magnetic levitation control system, i.e., the target magnetic levitation vibration signal, through preset sensors, and use the target magnetic levitation vibration signal as the target sinusoidal signal. At this time, the target sinusoidal signal is an assumed single-frequency sinusoidal signal. Specifically, the collected target magnetic levitation vibration signal... Convert to amplitude angular frequency and phase constant The target sinusoidal signal is then used to construct corresponding quadrature and in-phase components. These components are then used to construct an estimated signal corresponding to the target magnetic levitation vibration signal. It should be noted that the estimated signal... The expression is as follows: ; in and Define the internal state containing amplitude and phase information. To reconstruct the signal value, auxiliary state variables are introduced. , .
[0023] Step S12: Construct an error signal between the target magnetic levitation vibration signal and the estimated signal, and construct a target cost function based on the error signal.
[0024] In this embodiment, as Figure 2 As shown, it is necessary to determine the error signal between the target magnetic levitation vibration signal and the estimated signal, and to construct a target cost function based on the error signal. Specifically, it is necessary to construct the error signal between the target magnetic levitation vibration signal and the estimated signal based on the instantaneous difference between the estimated signal and the target magnetic levitation vibration signal, and to construct a target cost function based on the error signal; the target cost function is half the square of the error signal. It should be noted that, in order to make the estimated value... infinitely close to the measured value The estimation error needs to be defined. Furthermore, the objective cost function is half the square of the error signal, which can be expressed as: According to the gradient descent principle, the rate of change of each parameter should be proportional to the negative gradient of the cost function relative to that parameter.
[0025] Step S13: Construct a real-time iterative state space equation based on the preset gradient descent algorithm, the target cost function, and the estimated signal, and solve the real-time iterative state space equation to determine the current estimated frequency of the target magnetic levitation vibration signal based on the target output signal obtained from the solution.
[0026] In this embodiment, a real-time iterative state-space equation needs to be constructed first. Specifically, the negative gradient of the target cost function needs to be derived based on a preset gradient descent algorithm to determine the target parameter relationship between the rate of change of the signal parameters corresponding to the target magnetic levitation vibration signal and the negative gradient of the target cost function. Then, a real-time iterative state-space equation is constructed based on the target parameter relationship, the target cost function, the estimated signal, and the auxiliary state variables corresponding to the estimated signal; wherein, the auxiliary state variables and the estimated signal constitute orthogonal components. It should be noted that, in order to ensure the consistency of the step size during the gradient update process, an adaptive gain is set. Then, the negative gradient of the target cost function is derived using a preset gradient descent algorithm to construct the real-time iterative state space equation, which is shown below: ; in, ; in, μ For signal tracking step size, To update the step size for frequency, and To preset a fast convergence factor, ω To estimate the instantaneous angular frequency in the signal parameters, e The estimation error determined based on the error signal, α For preset exponent parameters, δ This is a preset threshold.
[0027] In this way, through the flexible configuration of the adaptive step size, this method can achieve accurate convergence within seconds under operating conditions with rapidly changing frequencies, maintaining extremely high steady-state identification accuracy while ensuring fast dynamic response.
[0028] Furthermore, the real-time iterative state-space equation needs to be discretized using the Euler method, with the target levitation vibration signal as input. Then, the real-time iterative state-space equation is solved based on a preset sampling period to obtain the target output signal. The preset sampling period is used to solve the constructed iterative state-space equation within each sampling period, extract the signal frequency of the target output signal, and use this signal frequency as the current estimated frequency of the target magnetic levitation vibration signal. The controller can obtain the following outputs in real time by solving the real-time iterative state-space equation: frequency output, reconstructed signal, and amplitude output. The frequency output can be obtained by extracting state variables. The reconstructed signal can be obtained by extracting state variables. The signal is obtained, and high-frequency noise has been automatically filtered out. The amplitude output can be determined using the formula based on the orthogonal transformation relationship. Calculated.
[0029] In this way, the algorithm only includes basic scalar multiplication and addition operations, without involving complex complex domain transformations or large memory caches. Therefore, its microsecond-level computational efficiency is high, making it suitable for resource-constrained embedded digital signal processors and meeting the requirements of hard real-time control. Furthermore, it can synchronously output frequency, amplitude, and reconstructed signal components within a single iterative framework. Because state-space equations possess inherent filtering properties, they can achieve accurate signal identification and adaptive filtering in noisy environments.
[0030] Step S14: Update the parameters of the preset notch filter based on the current estimated frequency to obtain the target notch filter, and input the target output signal to the target notch filter to suppress the target magnetic levitation vibration signal based on the obtained target compensation signal.
[0031] In this embodiment, the parameters of a preset notch filter can be updated based on the determined current estimated frequency to obtain the target notch filter. It should be noted that the continuous-time transfer function of the preset notch filter is defined as: ; in, The center frequency of the notch filter. The bandwidth parameter (controls the width of the notch filter, a smaller one) This value allows for a narrower notch depth.
[0032] Specifically, the currently estimated frequency needs to be used as the center frequency of the preset notch filter to update the parameters of the preset notch filter and obtain the target notch filter. Specifically, the estimated frequency needs to be... Real-time assignment of notch filter center frequency (i.e., order) To facilitate application in digital controllers, the continuous-time transfer function of the aforementioned preset notch filter is discretized using a bilinear transform: ; Furthermore, in each control cycle, based on the latest... System sampling time and preset bandwidth parameters (For example, in this application, it is preferred to set as) Online updates of digital filter coefficients: ; ; ; ; ; ; Furthermore, the target output signal needs to be input to the target notch filter to obtain the target compensation signal, and then the target compensation signal is input to the magnetic levitation control system to suppress the target magnetic levitation vibration signal. That is, the controller's original output signal, i.e., the target output signal, is input to the parameter-updated discrete notch filter. The signal is filtered and used as a compensation signal for the control signal, directly added to the control system to obtain the final control signal to drive the electromagnet. Because the center frequency of the notch filter is always synchronized with the unknown external vibration frequency, precise tracking and adaptive suppression of unknown frequency vibrations in the magnetic levitation control system are achieved.
[0033] In this embodiment, a corresponding estimated signal can be determined based on the acquired target magnetic levitation vibration signal. Then, a target cost function is constructed based on the error signal between the target magnetic levitation vibration signal and the estimated signal. A real-time iterative state-space equation is constructed based on a preset gradient descent algorithm, the target cost function, and the estimated signal. The equation is solved to determine the current estimated frequency of the target magnetic levitation vibration signal based on the target output signal obtained from the solution. Then, the parameters of a preset notch filter are updated based on the current estimated frequency to obtain the target notch filter. The target output signal is input to the target notch filter to suppress the target magnetic levitation vibration signal based on the obtained target compensation signal. In this way, on the one hand, due to the use of a feedback evolution mechanism, the generated frequency reference curve is completely continuous, avoiding frequency jumps, and the computational efficiency is high, which can be adapted to resource-constrained processors and meet the requirements of hard real-time control. On the other hand, by using the adaptive notch control strategy with the frequency estimation result as the basis for parameter update, the magnetic levitation control system achieves efficient active suppression of unknown frequency vibrations under complex working conditions.
[0034] See Figure 3 As shown, this invention discloses a notch wave vibration suppression device for a magnetic levitation system based on real-time frequency estimation, applied to a magnetic levitation control system, comprising: The estimation signal determination module 11 is used to collect the target magnetic levitation vibration signal through a preset sensor and determine the corresponding estimation signal based on the target magnetic levitation vibration signal; The cost function construction module 12 is used to construct an error signal between the target magnetic levitation vibration signal and the estimated signal, and to construct a target cost function based on the error signal; The frequency estimation determination module 13 is used to construct a real-time iterative state space equation based on a preset gradient descent algorithm, the target cost function and the estimated signal, and solve the real-time iterative state space equation to determine the current estimated frequency of the target magnetic levitation vibration signal based on the target output signal obtained from the solution. The signal suppression module 14 is used to update the parameters of the preset notch filter based on the current estimated frequency to obtain the target notch filter, and input the target output signal to the target notch filter to suppress the target magnetic levitation vibration signal based on the obtained target compensation signal.
[0035] In some embodiments, the estimated signal determination module 11 may specifically include: The signal determination unit is used to collect the current target magnetic levitation vibration signal of the magnetic levitation control system through a preset sensor, and to use the target magnetic levitation vibration signal as the target sinusoidal signal; The signal construction unit is used to construct corresponding quadrature and in-phase components based on the target sinusoidal signal, so as to construct an estimated signal corresponding to the target magnetic levitation vibration signal according to the quadrature and in-phase components.
[0036] In some embodiments, the cost function construction module 12 may specifically include: The cost function construction unit is used to construct an error signal between the target magnetic levitation vibration signal and the estimated signal based on the instantaneous difference between the estimated signal and the target magnetic levitation vibration signal, and to construct a target cost function based on the error signal; the target cost function is half of the square of the error signal.
[0037] In some embodiments, the frequency estimation determination module 13 may specifically include: The parameter relationship determination unit is used to derive the negative gradient of the target cost function based on a preset gradient descent algorithm, so as to determine the target parameter relationship between the rate of change of the signal parameters corresponding to the target magnetic levitation vibration signal and the negative gradient of the target cost function; The space equation construction unit is used to construct a real-time iterative state space equation based on the target parameter relationship, the target cost function, the estimated signal, and the auxiliary state variables corresponding to the estimated signal. The auxiliary state variable and the estimated signal form orthogonal components.
[0038] In some embodiments, the real-time iterative state-space equation is: ; in, ; in, μ For signal tracking step size, To update the step size for frequency, and To preset a fast convergence factor, ω To estimate the instantaneous angular frequency in the signal parameters, e The estimation error determined based on the error signal, α For preset exponent parameters, δ This is a preset threshold.
[0039] In some embodiments, the frequency estimation determination module 13 may specifically include: The spatial equation solving unit is used to discretize the real-time iterative state-space equation using the Euler method, and takes the target suspension vibration signal as input. Then, it solves the real-time iterative state-space equation based on a preset sampling period to obtain the target output signal. The frequency estimation unit is used to extract the signal frequency of the target output signal and use the signal frequency as the current estimated frequency of the target magnetic levitation vibration signal.
[0040] In some embodiments, the signal suppression module 14 may specifically include: A notch filter construction unit is used to use the current estimated frequency as the center frequency of a preset notch filter to update the parameters of the preset notch filter and obtain the target notch filter. The signal suppression unit is used to input the target output signal to the target notch filter to obtain the target compensation signal, and input the target compensation signal to the magnetic levitation control system to suppress the target magnetic levitation vibration signal.
[0041] Furthermore, embodiments of this application also disclose an electronic device, Figure 4 This is a structural diagram of an electronic device 20 according to an exemplary embodiment. The content of the diagram should not be construed as limiting the scope of this application.
[0042] Figure 4This is a schematic diagram of the structure of an electronic device 20 provided in an embodiment of this application. Specifically, the electronic device 20 may include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. The memory 22 stores a computer program, which is loaded and executed by the processor 21 to implement the relevant steps in the notch wave vibration suppression method for magnetic levitation systems based on real-time frequency estimation disclosed in any of the foregoing embodiments. Alternatively, the electronic device 20 in this embodiment may specifically be an electronic computer.
[0043] In this embodiment, the power supply 23 is used to provide operating voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and external devices, and the communication protocol it follows can be any communication protocol applicable to the technical solution of this application, and is not specifically limited here; the input / output interface 25 is used to acquire external input data or output data to the outside world, and its specific interface type can be selected according to specific application needs, and is not specifically limited here.
[0044] In addition, the memory 22, as a carrier for resource storage, can be a read-only memory, random access memory, disk or optical disk, etc. The resources stored thereon can include operating system 221, computer program 222, etc., and the storage method can be temporary storage or permanent storage.
[0045] The operating system 221 is used to manage and control the various hardware devices on the electronic device 20 and the computer program 222, which may be Windows Server, Netware, Unix, Linux, etc. In addition to including a computer program capable of performing the notch wave vibration suppression method for a magnetic levitation system based on real-time frequency estimation, which is executed by the electronic device 20 according to any of the foregoing embodiments, the computer program 222 may further include computer programs capable of performing other specific tasks.
[0046] Furthermore, this application also discloses a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, it implements the aforementioned notch wave vibration suppression method for magnetic levitation systems based on real-time frequency estimation. Specific steps of this method can be found in the corresponding content disclosed in the foregoing embodiments, and will not be repeated here.
[0047] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to in the method section.
[0048] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.
[0049] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.
[0050] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.
[0051] The technical solutions provided in this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.
Claims
1. A notch wave vibration suppression method for a magnetic levitation system based on real-time frequency estimation, characterized in that, Applications in magnetic levitation control systems include: The target magnetic levitation vibration signal is collected by a preset sensor, and the corresponding estimated signal is determined based on the target magnetic levitation vibration signal; An error signal is constructed between the target magnetic levitation vibration signal and the estimated signal, and a target cost function is constructed based on the error signal; A real-time iterative state space equation is constructed based on a preset gradient descent algorithm, the target cost function, and the estimated signal. The real-time iterative state space equation is then solved to determine the current estimated frequency of the target magnetic levitation vibration signal based on the target output signal obtained from the solution. The parameters of the preset notch filter are updated based on the current estimated frequency to obtain the target notch filter, and the target output signal is input to the target notch filter to suppress the target magnetic levitation vibration signal based on the obtained target compensation signal.
2. The notch wave vibration suppression method for magnetic levitation systems based on real-time frequency estimation according to claim 1, characterized in that, The step of acquiring the target magnetic levitation vibration signal through a preset sensor and determining the corresponding estimated signal based on the target magnetic levitation vibration signal includes: The target magnetic levitation vibration signal is collected by a preset sensor and used as the target sine signal. Based on the target sinusoidal signal, corresponding quadrature and in-phase components are constructed to construct an estimated signal corresponding to the target magnetic levitation vibration signal.
3. The notch wave vibration suppression method for magnetic levitation systems based on real-time frequency estimation according to claim 1, characterized in that, The step of constructing an error signal between the target magnetic levitation vibration signal and the estimated signal, and constructing a target cost function based on the error signal, includes: An error signal between the target magnetic levitation vibration signal and the estimated signal is constructed based on the instantaneous difference between the estimated signal and the target magnetic levitation vibration signal, and a target cost function is constructed based on the error signal; the target cost function is half the square of the error signal.
4. The notch wave vibration suppression method for magnetic levitation systems based on real-time frequency estimation according to claim 1, characterized in that, The construction of the real-time iterative state-space equation based on the preset gradient descent algorithm, the target cost function, and the estimated signal includes: The negative gradient of the target cost function is derived based on a preset gradient descent algorithm to determine the target parameter relationship between the rate of change of the signal parameters corresponding to the target magnetic levitation vibration signal and the negative gradient of the target cost function. A real-time iterative state-space equation is constructed based on the target parameter relationship, the target cost function, the estimated signal, and the auxiliary state variables corresponding to the estimated signal. The auxiliary state variable and the estimated signal form orthogonal components.
5. The notch wave vibration suppression method for magnetic levitation systems based on real-time frequency estimation according to claim 1, characterized in that, The real-time iterative state-space equation is: ； in, ; in, μ For signal tracking step size, To update the step size for frequency, and To preset a fast convergence factor, ω To estimate the instantaneous angular frequency in the signal parameters, e The estimation error determined based on the error signal, α For preset exponent parameters, δ This is a preset threshold.
6. The notch wave vibration suppression method for magnetic levitation systems based on real-time frequency estimation according to claim 1, characterized in that, Solving the real-time iterative state-space equation to determine the current estimated frequency of the target magnetic levitation vibration signal based on the solved target output signal includes: The real-time iterative state-space equation is discretized using the Euler method, and the target suspension vibration signal is taken as input. Then, the real-time iterative state-space equation is solved based on a preset sampling period to obtain the target output signal. Extract the signal frequency of the target output signal and use the signal frequency as the current estimated frequency of the target magnetic levitation vibration signal.
7. The notch wave vibration suppression method for magnetic levitation systems based on real-time frequency estimation according to any one of claims 1 to 6, characterized in that, The step of updating the parameters of the preset notch filter based on the current estimated frequency to obtain the target notch filter, and inputting the target output signal to the target notch filter to suppress the target magnetic levitation vibration signal based on the obtained target compensation signal, includes: The current estimated frequency is used as the center frequency of the preset notch filter to update the parameters of the preset notch filter and obtain the target notch filter. The target output signal is input to the target notch filter to obtain the target compensation signal, and the target compensation signal is input to the magnetic levitation control system to suppress the target magnetic levitation vibration signal.
8. A notch wave vibration suppression device for a magnetic levitation system based on real-time frequency estimation, characterized in that, Applications in magnetic levitation control systems include: The estimated signal determination module is used to collect the target magnetic levitation vibration signal through a preset sensor, and determine the corresponding estimated signal based on the target magnetic levitation vibration signal; The cost function construction module is used to construct an error signal between the target magnetic levitation vibration signal and the estimated signal, and to construct a target cost function based on the error signal; The frequency estimation module is used to construct a real-time iterative state space equation based on a preset gradient descent algorithm, the target cost function, and the estimated signal, and to solve the real-time iterative state space equation to determine the current estimated frequency of the target magnetic levitation vibration signal based on the target output signal obtained from the solution. The signal suppression module is used to update the parameters of the preset notch filter based on the current estimated frequency to obtain the target notch filter, and input the target output signal to the target notch filter to suppress the target magnetic levitation vibration signal based on the obtained target compensation signal.
9. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor is configured to execute the computer program to implement the notch wave vibration suppression method for a magnetic levitation system based on real-time frequency estimation as described in any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that, Used to store a computer program, wherein the computer program, when executed by a processor, implements the notch wave vibration suppression method for a magnetic levitation system based on real-time frequency estimation as described in any one of claims 1 to 7.