Magnetorheological-electromagnetism cooperative driving intelligent vibration reduction control system

Abstract

The invention discloses a magneto-rheological-electromagnetic cooperative driving intelligent vibration reduction control system, which relates to the technical field of vibration control, and comprises a physical actuation module for providing variable damping force and active actuation force; the digital twinning and prediction module is used for receiving and processing the intrinsic state signal of the physical actuation module; the intelligent cooperative control module is used for predicting the state and an external vibration signal; and the power driving module is used for driving the physical actuation module to work according to the cooperative control instruction. According to the invention, direct sensing of the intrinsic state is realized through the piezoelectric fiber sensor network integrated in the actuator, and the future state and the nonlinear dynamic state of the system are accurately predicted in combination with a high-fidelity digital twin model based on online real-time identification and calibration; an adaptive cooperative control algorithm fusing predictive feedforward compensation and real-time feedback is adopted to generate an accurate cooperative instruction, and high-speed and high-fidelity execution is carried out through a customized special power driving unit.

Description

Technical Field

[0001] This invention relates to the field of vibration control technology, and in particular to an intelligent vibration reduction control system driven by magnetorheology and electromagnetic coordination. Background Technology

[0002] Vibration control is a key technology for improving the smoothness, ride comfort, and structural safety of mechanical equipment. Traditional vibration reduction methods mainly include passive control, semi-active control, and active control. Passive vibration reduction devices are simple and reliable in structure, but their parameters are fixed and cannot adapt to wide-frequency, time-varying vibration environments. Active control can achieve optimal control effects, but it usually requires a large external energy input, making the system complex and costly. Semi-active control, especially dampers based on magnetorheological fluids (MRF) or electrorheological fluids (ERF), has attracted widespread attention due to its low power consumption, large output, and rapid response (millisecond level). Magnetorheological dampers (MRDs) continuously and rapidly adjust the damping force by changing the magnetic field strength, but they are essentially energy-consuming components and cannot inject energy into the system to counteract vibration. On the other hand, electromagnetic actuators (EMAs), as a typical active actuator, can output bidirectional active power and have excellent dynamic performance, but their energy consumption and heat generation problems are prominent when operating at continuous high output. In order to balance performance and energy efficiency, a synergistic drive scheme combining MRDs and EMAs has become an important research direction. Among the existing technologies, there are already... Attempts have been made to use both MRD and EMA in parallel or series, allocating their operating ranges through simple control rules (such as switching logic based on velocity or acceleration feedback). However, such solutions have significant shortcomings: First, both MRD and EMA have strong nonlinear characteristics (such as hysteresis, saturation, and friction), and their dynamic characteristics vary with operating conditions, temperature, and other factors. Traditional control strategies based on linear models or empirical rules are difficult to achieve precise matching and seamless coordination of their outputs, easily leading to force conflicts or response delays, which in turn worsens the vibration reduction effect. Second, existing systems generally rely on external sensors (such as accelerometers and displacement sensors) to sense the vibration state of the controlled object, lacking direct and accurate perception of the actual mechanical state inside the actuator (such as piston rod stress and actuator force). This results in the controller relying on indirect and delayed information, unable to identify the actuator's own performance changes and nonlinearities in real time. Furthermore, control strategies mostly remain at the "feedback" level, i.e., responding to vibrations that have already occurred, unable to predict and compensate for the future dynamics of the system (including the actuator itself), making it difficult to cope with high-frequency and impact vibrations, thus limiting further improvement in coordinated performance.

[0003] However, current common solutions have many drawbacks, including: existing magnetorheological-electromagnetic coordinated vibration reduction systems mainly rely on external sensors for indirect and delayed state perception, and cannot know the true mechanical state inside the actuator; their control strategies are difficult to accurately model and compensate for the inherent strong nonlinearity and hysteresis characteristics of both, and are mostly limited to passive feedback and lack predictive feedforward capabilities, resulting in timing deviations and force conflicts in the coordinated output; at the same time, the drive hardware has not been optimized in an integrated manner for the different electrical characteristics of the two types of actuators, and the system as a whole lacks the intelligent ability to adaptively adjust according to working conditions and objectives, which limits the vibration reduction performance, response speed and energy efficiency. Summary of the Invention

[0004] The purpose of this section is to outline some aspects of embodiments of the present invention and to briefly describe some preferred embodiments. Simplifications or omissions may be made in this section, as well as in the abstract and title of this application, to avoid obscuring the purpose of these documents; however, such simplifications or omissions should not be construed as limiting the scope of the invention.

[0005] In view of the problems existing in the above-mentioned intelligent vibration reduction control system driven by magnetorheology and electromagnetic coordination, the present invention is proposed.

[0006] Therefore, the purpose of this invention is to provide an intelligent vibration reduction control system based on magnetorheological-electromagnetic coordinated drive. This system is applicable to solving the problems of existing magnetorheological-electromagnetic coordinated vibration reduction systems, which mainly rely on external sensors for indirect and delayed state perception, making it impossible to know the true mechanical state inside the actuators. Their control strategies are difficult to accurately model and compensate for the inherent strong nonlinearity and hysteresis characteristics of both actuators, and are mostly limited to passive feedback without predictive feedforward capabilities, resulting in timing deviations and force conflicts in the coordinated output. At the same time, the drive hardware fails to perform integrated optimization for the different electrical characteristics of the two types of actuators, and the system as a whole lacks the intelligent ability to adaptively adjust according to working conditions and objectives, resulting in limitations in vibration reduction performance, response speed, and energy efficiency.

[0007] To solve the above-mentioned technical problems, the present invention provides the following technical solution: In a first aspect, embodiments of the present invention provide an intelligent vibration reduction control system driven by magnetorheological-electromagnetic coordination, comprising a physical actuation module for providing variable damping force and active driving force, including a magnetorheological damper and an electromagnetic actuator; a digital twin and prediction module for receiving and processing the intrinsic state signal of the physical actuation module, identifying the nonlinear dynamic characteristics of the system and predicting its future state; an intelligent coordinated control module for generating coordinated control commands based on the predicted state and external vibration signals; and a power drive module for driving the physical actuation module to work according to the coordinated control commands.

[0008] As a preferred embodiment of the intelligent vibration reduction control system of magnetorheological-electromagnetic coordinated drive described in this invention, a piezoelectric fiber sensor network is integrated inside the piston rod of the magnetorheological damper and inside the mover of the electromagnetic actuator to sense stress, strain, or temperature information inside the actuator and output it as the intrinsic state signal.

[0009] As a preferred embodiment of the intelligent vibration reduction control system based on magnetorheological-electromagnetic coordinated drive described in this invention, the digital twin and prediction module specifically comprises the following: running a high-fidelity digital twin model including the Bingham model of the magnetorheological damper and the equivalent circuit-mechanical coupling model of the electromagnetic actuator; based on the received intrinsic state signal and external vibration signal, performing online real-time identification and calibration of key parameters in the digital twin model; and using the calibrated model to predict the vibration state of the system and the nonlinear hysteresis and response delay of each actuator within the next few milliseconds.

[0010] As a preferred embodiment of the intelligent vibration reduction control system based on magnetorheological-electromagnetic coordinated drive described in this invention, the intelligent coordinated control module specifically comprises the following: receiving future state prediction information from the digital twin and prediction module and real-time vibration signals from external sensors; calculating, based on the future state prediction information, a feedforward compensation control quantity to offset the nonlinear dynamics of the magnetorheological damper and the electromagnetic actuator; calculating, based on the real-time vibration signals, a feedback control quantity to track the dynamic characteristics of the target; and fusing the feedforward compensation control quantity and the feedback control quantity to generate the final coordinated control command, so that the output of the magnetorheological damper and the electromagnetic actuator are coordinated in timing and amplitude.

[0011] As a preferred embodiment of the intelligent vibration reduction control system of magnetorheological-electromagnetic coordinated drive described in this invention, the power drive module includes a first drive unit and a second drive unit; the first drive unit is an excitation current controller, which receives the portion of the coordinated control command corresponding to the magnetorheological damper and outputs a rapidly modulated DC current to precisely control the damping force of the magnetorheological damper; the second drive unit is a bidirectional power amplifier, which receives the portion of the coordinated control command corresponding to the electromagnetic actuator and outputs a drive current or voltage with controllable amplitude and direction to precisely control the magnitude and direction of the main force of the electromagnetic actuator.

[0012] As a preferred embodiment of the intelligent vibration reduction control system of magnetorheological-electromagnetic coordinated drive described in this invention, the excitation current controller adopts pulse width modulation technology, and its output current adjustment frequency is not less than 1kHz; the bidirectional power amplifier has an H-bridge topology, and its output current bandwidth is not less than twice the desired force output bandwidth of the electromagnetic actuator.

[0013] As a preferred embodiment of the intelligent vibration reduction control system driven by magnetorheology-electromagnetism in this invention, the intelligent collaborative control module integrates the feedforward compensation control quantity and the feedback control quantity using an adaptive weighting algorithm based on real-time vibration energy assessment; in the high-frequency band of vibration energy, the weight of the feedforward compensation control quantity is increased, and in the low-frequency band of vibration energy, the weight of the feedback control quantity is increased.

[0014] As a preferred embodiment of the intelligent vibration reduction control system of magnetorheological-electromagnetic coordinated drive described in this invention, the piezoelectric fiber sensor network is composed of multiple piezoelectric composite fibers spirally wound along the axis of the piston rod or mover, and the winding directions of adjacent fibers are opposite.

[0015] As a preferred embodiment of the intelligent vibration reduction control system driven by magnetorheology and electromagnetic coordination described in this invention, the online real-time identification and calibration process adopts the recursive least squares method with a forgetting factor, and the value of the forgetting factor is dynamically adjusted according to the frequency band energy of the external vibration signal.

[0016] As a preferred embodiment of the intelligent vibration reduction control system of magnetorheological-electromagnetic coordinated drive described in this invention, the system is configured to have at least two switchable operating modes, including a first mode primarily for comfort optimization and a second mode primarily for actuator travel protection and energy efficiency optimization; the intelligent coordinated control module switches between the two modes according to preset rules or external instructions.

[0017] In a second aspect, embodiments of the present invention provide a computer device, including a memory and a processor, wherein the memory stores a computer program, and the computer program, when executed by the processor, implements any step of the intelligent vibration reduction control system of magnetorheological-electromagnetic coordinated drive as described in the first aspect of the present invention.

[0018] Thirdly, embodiments of the present invention provide a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, it implements any step of the intelligent vibration reduction control system of magnetorheological-electromagnetic coordinated drive as described in the first aspect of the present invention.

[0019] The beneficial effects of this invention are as follows: This invention achieves direct sensing of intrinsic state through a piezoelectric fiber sensor network integrated inside the actuator. Combined with a high-fidelity digital twin model based on online real-time identification and calibration, it accurately predicts the future state of the system and its own nonlinear dynamics. On this basis, an adaptive cooperative control algorithm that integrates predictive feedforward compensation and real-time feedback is adopted to generate precise cooperative commands, which are executed at high speed and high fidelity through a customized dedicated power drive unit. This organically integrated intelligent closed loop enables the magnetorheological damper and the electromagnetic actuator to achieve unprecedented precision in timing and amplitude. Ultimately, the system exhibits significant beneficial effects such as strong broadband suppression capability, fast transient response, high vibration reduction accuracy, good adaptability, and excellent overall energy efficiency. It can also flexibly switch working modes to adapt to diverse performance requirements. Attached Figure Description

[0020] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein: Figure 1 This is a flowchart illustrating the implementation of the present invention in Example 1.

[0021] Figure 2 This is a flowchart illustrating the specific implementation of the present invention in Example 1. Detailed Implementation

[0022] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0023] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0024] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0025] Example 1 Reference Figure 1 and Figure 2This is the first embodiment of the present invention, which provides an intelligent vibration reduction control system driven by magnetorheology and electromagnetic coordination, comprising the following steps: S1: Physical actuation module, used to provide variable damping force and active driving force, which includes magnetorheological damper and electromagnetic actuator.

[0026] Preferably, the piston rod of the magnetorheological damper and the mover of the electromagnetic actuator are integrated with a piezoelectric fiber sensor network to sense stress, strain or temperature information inside the actuator and output it as an intrinsic state signal.

[0027] Furthermore, the piezoelectric fiber sensor network consists of multiple piezoelectric composite fibers spirally wound along the axis of the piston rod or mover, with adjacent fibers wound in opposite directions.

[0028] Specifically, the output of the piezoelectric fiber sensor network is led out through a micro wire embedded inside the piston rod / mover and connected to a charge amplifier with high input impedance. The piezoelectric signal is converted into a voltage signal and then sent to the digital twin and prediction module.

[0029] Preferably, by embedding a piezoelectric fiber sensor network in an anti-helical winding topology deep inside the core force-bearing component of the actuator, a "proprioceptive nervous system" of the system is constructed. This design realizes the leap from indirect and delayed motion signal perception to direct and real-time acquisition of the intrinsic signals of the real stress / strain field inside the actuator, which greatly improves the accuracy and timeliness of the perception dimension. The anti-helical structure effectively compensates for temperature drift and suppresses unidirectional interference, ensuring long-term signal stability and high signal-to-noise ratio. At the same time, this embedded sensing network provides a direct physical information source for online in-situ monitoring of the actuator's health status (such as magnetorheological fluid sedimentation and structural fatigue), laying an irreplaceable data foundation for subsequent control based on precise physical state.

[0030] For example, in an active vibration isolation system for a precision optical platform, the physical actuation module is coaxially integrated with a miniature magnetorheological damper and a voice coil electromagnetic actuator. The carbon fiber piston rod of the magnetorheological damper is etched with microgrooves along the axial direction in an alternating pattern of forward and reverse spirals using micromachining technology, and 50-micrometer-diameter lead zirconate titanate piezoelectric composite fibers are woven and embedded in it to form a three-dimensional sensing network. The actuator's mover is integrated with this network inside its aluminum alloy frame using a similar process. When the platform is excited by ground micro-vibration, the micro-strain generated inside the actuator is captured in real time by the piezoelectric fibers. The generated charge signal is transmitted to an external charge amplifier through embedded silver nanowires, thereby directly and synchronously obtaining the true shear stress of the damper rod and the precise back electromotive force information of the electromagnetic actuator's mover, providing the control system with an unprecedented intrinsic mechanical state sensing capability.

[0031] S2: Digital Twin and Prediction Module, used to receive and process the intrinsic state signals of the physical actuation module, identify the nonlinear dynamic characteristics of the system, and predict its future state.

[0032] The preferred digital twin and prediction module contains the following specific features: A high-fidelity digital twin model of the Bingham model containing magnetorheological dampers and the equivalent circuit-mechanical coupling model of electromagnetic actuators is generated. Based on the received intrinsic state signals and external vibration signals, key parameters in the digital twin model are identified and calibrated online in real time. Using the calibrated model, the vibration state of the system and the nonlinear hysteresis and response delay of each actuator are predicted in the next few milliseconds.

[0033] Specifically, the online real-time identification and calibration process uses a recursive least squares method with a forgetting factor, and the value of the forgetting factor is dynamically adjusted according to the frequency band energy of the external vibration signal.

[0034] Preferably, a dynamic calibration digital twin prediction engine that integrates a mechanistic model and real-time data-driven approach is constructed. Its core lies in using intrinsic state signals to perform online real-time parameter identification and calibration of a high-fidelity model containing Bingham nonlinearity and electromechanical coupling characteristics. This allows the digital twin to evolve from a static copy into a "dynamic mirror" that can evolve synchronously with the physical system. This fundamentally solves the problem of mismatch caused by the time-varying characteristics of the system in traditional models, and makes it possible to accurately predict the overall vibration state of the system and the nonlinear hysteresis and response delay of each actuator within the next few milliseconds. The dynamically adjusted forgetting factor algorithm further enhances the adaptability and robustness of the model under different vibration energy scenarios, providing an accurate prediction target for feedforward control.

[0035] For example, based on the aforementioned vibration isolation system, the digital twin and prediction module runs its real-time model in parallel on an FPGA chip. This model precisely couples the Bingham model describing the yielding characteristics of the magnetorheological fluid field with the lumped-parameter electromagnetic-mechanical model of the voice coil motor. The system uses the intrinsic stress signal obtained from the S1 module and the platform displacement measured by a laser interferometer at a frequency of 1 kHz. It employs the dynamic forgetting factor recursive least squares method to identify the four key parameters of the model (yield stress, post-yield viscosity, force constant, and electromechanical time constant) online. For instance, when the system detects that the voice coil temperature rises due to continuous operation, the force constant estimate in the model decays in real time. Using this continuously calibrated "digital mirror," the module can accurately predict the platform's velocity change trend 10 milliseconds in advance and simultaneously predict the approximately 1.5 millisecond rheological response hysteresis of the magnetorheological damper and the phase hysteresis of the electromagnetic actuator caused by inductance, providing an accurate time-domain target for feedforward compensation.

[0036] S3: Intelligent Cooperative Control Module, used to generate cooperative control commands based on predicted conditions and external vibration signals.

[0037] Preferably, the intelligent collaborative control module contains the following specific features: Receive future state prediction information from the digital twin and prediction module, as well as real-time vibration signals from external sensors; Based on future state prediction information, the feedforward compensation control quantity used to counteract the nonlinear dynamics of the magnetorheological damper and the electromagnetic actuator is calculated. Based on real-time vibration signals, the feedback control quantity used to track the dynamic characteristics of the target is calculated; The feedforward compensation control quantity and the feedback control quantity are integrated to generate the final coordinated control command, so that the output of the magnetorheological damper and the electromagnetic actuator are coordinated in terms of timing and amplitude.

[0038] Furthermore, in the intelligent collaborative control module, the fusion of feedforward compensation control quantity and feedback control quantity adopts an adaptive weighting algorithm based on real-time vibration energy assessment; in the frequency band with high vibration energy, the weight of the feedforward compensation control quantity is increased, and in the frequency band with low vibration energy, the weight of the feedback control quantity is increased.

[0039] Preferably, an intelligent collaborative decision-making mechanism based on the fusion of predictive feedforward compensation and adaptive feedback is proposed. It utilizes the accurate prediction of S2 to actively generate feedforward control quantities to offset the nonlinear dynamics of the actuator itself, thereby theoretically breaking through the "reaction time wall" formed by the inherent delay of the system, and significantly improving the suppression speed and effect of high-frequency and shock vibrations. By performing adaptive weighted fusion of this advanced control quantity and the feedback control quantity based on real-time state based on vibration energy assessment, the system can intelligently allocate control resources: emphasizing feedforward for rapid suppression during strong vibrations and emphasizing feedback for fine adjustment during weak vibrations. This not only achieves precise force coordination between the magnetorheological damper and the electromagnetic actuator in terms of timing and amplitude, avoiding force conflicts, but also globally optimizes control performance and energy efficiency.

[0040] For example, in the active suspension control of a high-speed maglev train carriage, the intelligent cooperative control module receives prediction information and real-time acceleration signals from S2. First, based on the predicted future swaying state of the carriage, it inversely calculates the ideal resultant force required to counteract this swaying. Then, based on the predicted dynamic delays of each actuator (such as the magnetic circuit establishment delay of the magnetorheological damper and the current response delay of the electromagnetic actuator), it calculates the feedforward compensation current command. Simultaneously, the module calculates the real-time feedback current command according to the ceiling damping control law. Subsequently, the module performs real-time analysis of the carriage vibration spectrum. If a sudden surge in high-frequency impact energy caused by track joints is detected, the feedforward weight is instantly increased to 0.9 to emphasize predictive suppression. During smooth operation, the weight is reduced to 0.3, focusing on feedback adjustment to maintain stability. Finally, the generated cooperative command ensures that the active restoring force provided by the electromagnetic actuator and the adjustable damping force provided by the magnetorheological damper reach the preset optimal ratio at the same time, achieving seamless coordination between vibration suppression and attitude control.

[0041] S4: Power drive module, used to drive the physical actuation module to work according to the cooperative control instructions.

[0042] Preferably, the power drive module includes a first drive unit and a second drive unit; The first drive unit is an excitation current controller, which receives the part of the coordinated control command corresponding to the magnetorheological damper and outputs a rapidly modulated DC current to precisely control the damping force of the magnetorheological damper. The second drive unit is a bidirectional power amplifier. It receives the part of the coordinated control command corresponding to the electromagnetic actuator and outputs a drive current or voltage with controllable amplitude and direction to precisely control the magnitude and direction of the main force of the electromagnetic actuator.

[0043] Specifically, the excitation current controller adopts pulse width modulation technology, and its output current adjustment frequency is not less than 1kHz; the bidirectional power amplifier has an H-bridge topology, and its output current bandwidth is not less than twice the expected force output bandwidth of the electromagnetic actuator.

[0044] Specifically, the excitation current controller can be implemented using a DC motor drive chip with integrated MOSFET and current sampling functions (such as DRV8870), and the H-bridge bidirectional power amplifier can be a full-bridge circuit composed of four IGBTs or MOSFETs, equipped with a current-closed-loop PID regulator to ensure the output current bandwidth requirements.

[0045] It should be noted that the system is configured to have at least two switchable operating modes, including a first mode that prioritizes comfort optimization and a second mode that prioritizes actuator travel protection and energy efficiency optimization; the intelligent collaborative control module switches between the two modes according to preset rules or external commands.

[0046] Preferably, a specialized high-performance drive architecture for heterogeneous actuators was designed. To address the different needs of magnetorheological dampers requiring rapid DC excitation modulation and electromagnetic actuators requiring wide-bandwidth bidirectional power drive, a high-frequency PWM excitation controller and a wide-bandwidth H-bridge power amplifier were used for independent optimized drive. This specialized design ensures that both actuators can be fully driven within their electrical and dynamic performance boundaries, avoiding the use of general-purpose drivers as a system bottleneck. The high regulation frequency (≥1kHz) and wide current bandwidth (≥2 times the force bandwidth) ensure high-speed and accurate conversion from intelligent control commands to high-fidelity physical force output. This is the key hardware foundation for the aforementioned advanced algorithms to be faithfully executed at the physical level, achieving optimal system-level performance through "software and hardware co-design".

[0047] For example, in the power drive module of the maglev train suspension system, the first drive unit adopts a synchronous Buck converter topology based on SiCMOSFET, which is dedicated to driving the magnetorheological damper. It receives the target excitation current command from S3 and adjusts the coil current from 0 to 2A within 0.1 milliseconds through peak current mode control at a fixed frequency of 50kHz, realizing millisecond-level stepless adjustment of the damping force. The second drive unit is a three-level T-type neutral point clamping inverter composed of four GaN HEMT devices, which is used to drive the high-power electromagnetic actuator. It receives complex current waveform commands from S3 and, with its current closed-loop bandwidth of more than 5kHz and multi-mode PWM strategy, outputs a sine wave or transient current that closely matches the command, accurately and quickly generating the required bidirectional active force. These two heterogeneous high-performance drive units are like a tailor-made "high-speed execution wrist" for the system, ensuring that the intention of the upper-level intelligent control strategy can be converted into actual damping force with extreme speed and precision.

[0048] In summary, this invention achieves direct sensing of intrinsic state through a piezoelectric fiber sensor network integrated within the actuator. Combined with a high-fidelity digital twin model based on online real-time identification and calibration, it accurately predicts the future state of the system and its own nonlinear dynamics. On this basis, an adaptive cooperative control algorithm integrating predictive feedforward compensation and real-time feedback is adopted to generate precise cooperative commands, which are then executed at high speed and with high fidelity by a custom-designed dedicated power drive unit. This organically integrated intelligent closed loop enables the magnetorheological damper and the electromagnetic actuator to achieve unprecedented precision in timing and amplitude. Ultimately, the system exhibits significant benefits such as strong broadband suppression capability, fast transient response, high vibration reduction accuracy, good adaptability, and excellent overall energy efficiency. It can also flexibly switch operating modes to adapt to diverse performance requirements.

[0049] Example 2 is an embodiment of the present invention, which differs from the previous embodiment in that: If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes 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 steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0050] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing 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 (such as a computer-based system, a processor-including system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0051] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0052] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0053] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A magnetorheological-electromagnetic coordinated driven intelligent vibration reduction control system, characterized in that: include: The physical actuation module, used to provide variable damping force and active driving force, includes a magnetorheological damper and an electromagnetic actuator. The digital twin and prediction module is used to receive and process the intrinsic state signal of the physical actuation module, identify the nonlinear dynamic characteristics of the system, and predict its future state. The intelligent collaborative control module is used to generate collaborative control commands based on the predicted state and external vibration signals; A power drive module is used to drive the physical actuation module to work according to the cooperative control command.

2. The intelligent vibration reduction control system based on magnetorheological-electromagnetic coordinated drive as described in claim 1, characterized in that: The piston rod of the magnetorheological damper and the mover of the electromagnetic actuator are integrated with a piezoelectric fiber sensor network to sense stress, strain, or temperature information inside the actuator and output it as the intrinsic state signal.

3. The intelligent vibration reduction control system based on magnetorheological-electromagnetic coordinated drive as described in claim 1, characterized in that: The specific contents of the digital twin and prediction module are as follows: A high-fidelity digital twin model of the Bingham model containing the magnetorheological damper and the equivalent circuit-mechanical coupling model of the electromagnetic actuator is run. Based on the received intrinsic state signals and external vibration signals, the key parameters in the digital twin model are identified and calibrated online in real time. Using the calibrated model, the vibration state of the system and the nonlinear hysteresis and response delay of each actuator are predicted in the next few milliseconds.

4. The intelligent vibration reduction control system based on magnetorheological-electromagnetic coordinated drive as described in claim 1, characterized in that: The specific contents of the intelligent collaborative control module are as follows: Receive future state prediction information from the digital twin and prediction module and real-time vibration signals from external sensors; Based on the future state prediction information, a feedforward compensation control quantity is calculated to counteract the nonlinear dynamics of the magnetorheological damper and the electromagnetic actuator. Based on the real-time vibration signal, the feedback control quantity used to track the dynamic characteristics of the target is calculated; The feedforward compensation control quantity and the feedback control quantity are fused to generate the final coordinated control command, so that the output of the magnetorheological damper and the electromagnetic actuator are coordinated in terms of timing and amplitude.

5. The intelligent vibration reduction control system based on magnetorheological-electromagnetic coordinated drive as described in claim 4, characterized in that: The power drive module includes a first drive unit and a second drive unit; The first drive unit is an excitation current controller, which receives the part of the cooperative control command corresponding to the magnetorheological damper and outputs a rapidly modulated DC current to precisely control the damping force of the magnetorheological damper. The second drive unit is a bidirectional power amplifier, which receives the portion of the coordinated control command corresponding to the electromagnetic actuator and outputs a drive current or voltage with controllable amplitude and direction to precisely control the magnitude and direction of the main force of the electromagnetic actuator.

6. The intelligent vibration reduction control system based on magnetorheological-electromagnetic coordinated drive as described in claim 5, characterized in that: The excitation current controller adopts pulse width modulation technology, and its output current adjustment frequency is not less than 1kHz; the bidirectional power amplifier has an H-bridge topology, and its output current bandwidth is not less than twice the expected force output bandwidth of the electromagnetic actuator.

7. The intelligent vibration reduction control system based on magnetorheological-electromagnetic coordinated drive as described in claim 4, characterized in that: In the intelligent collaborative control module, the fusion of the feedforward compensation control quantity and the feedback control quantity adopts an adaptive weighting algorithm based on real-time vibration energy assessment; in the frequency band with high vibration energy, the weight of the feedforward compensation control quantity is increased, and in the frequency band with low vibration energy, the weight of the feedback control quantity is increased.

8. The intelligent vibration reduction control system based on magnetorheological-electromagnetic coordinated drive as described in claim 2, characterized in that: The piezoelectric fiber sensor network consists of multiple piezoelectric composite fibers spirally wound along the axis of the piston rod or mover, with adjacent fibers wound in opposite directions.

9. The intelligent vibration reduction control system based on magnetorheological-electromagnetic coordinated drive as described in claim 3, characterized in that: The online real-time identification and calibration process employs a recursive least squares method with a forgetting factor, and the value of the forgetting factor is dynamically adjusted according to the frequency band energy of the external vibration signal.

10. The intelligent vibration reduction control system based on magnetorheological-electromagnetic coordinated drive as described in claim 1, characterized in that: The system is configured to have at least two switchable operating modes, including a first mode that prioritizes comfort optimization and a second mode that prioritizes actuator travel protection and energy efficiency optimization; the intelligent collaborative control module switches between the two modes according to preset rules or external commands.

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