A method and system for active vibration control based on multi-sensor information fusion

Abstract

The application belongs to the technical field of micro-vibration suppression, and specifically discloses an active vibration reduction control method and system based on multi-sensing information fusion, which comprises the following steps: collecting a load vibration absolute speed signal, a load vibration acceleration signal, a relative displacement signal between the load and the base, and a base vibration absolute speed signal; determining an active control force based on a multi-sensing information fusion controller model and the collected signals, wherein the active control force is used to offset the vibration interference suffered by the load; wherein the multi-sensing information fusion controller model is used to fuse the outputs of multiple controllers to determine the active control force, and the multiple controllers include a feedback controller for processing the load vibration absolute speed signal, a feedback controller for processing the load vibration acceleration signal, a feedback controller for processing the relative displacement signal, and a feedforward controller for processing the base vibration absolute speed signal. Through the application, the vibration suppression capability of the system can be greatly improved in a wide frequency domain range.

Description

Technical Field

[0001] This application belongs to the field of micro-vibration suppression technology, and more specifically, relates to an active vibration reduction control method and system based on multi-sensor information fusion. Background Technology

[0002] Micro-vibration suppression technology is a fundamental technology for ultra-precision machining, manufacturing, and measurement equipment. It is widely used in high-precision machinery to suppress external interference, ensuring the equipment's operational performance. Traditional vibration suppression methods are passive, but passive devices offer limited protection; therefore, active control is needed to meet the requirements for suppressing low-frequency and ultra-low-frequency vibrations.

[0003] Active vibration damping relies heavily on vibration measurement sensors. Among these, velocity sensors, based on the principle of electromagnetic induction, are crucial. They measure the absolute velocity of the load being damped relative to an inertial reference frame, providing absolute velocity feedback to the active vibration damping system. However, velocity sensors exhibit second-order high-pass characteristics in the frequency domain. Vibration signals below their natural frequencies are significantly attenuated in amplitude and lead in phase, leading to distortion in low-frequency signals. Furthermore, the amplitude of the vibration signal is attenuated after low-pass filtering by the damper itself, making it difficult for velocity sensors to meet the signal-to-noise ratio requirements for vibration control in high-frequency bands. This severely limits the control bandwidth of active vibration damping, making it difficult to further improve the effectiveness of active vibration damping using only a single sensor. Therefore, it is necessary to develop a multi-sensor control strategy to compensate for the shortcomings of velocity sensors in low- and high-frequency vibration measurement by using other types of sensors, thereby expanding the vibration measurement frequency range and further improving the system's control bandwidth.

[0004] On the other hand, vibration damping systems primarily suppress two types of disturbances: one is the vibration impact from the damper mounting base, transmitted to the load through supporting elements (springs, dampers, etc.), which is the main disturbance encountered by the vibration damping system; the other is the disturbance force acting directly on the load, such as disturbances caused by ambient airflow, sound waves, ribbon cables and pipes with parasitic stiffness, and fluids used for cooling or immersion technologies. The ability of a vibration damping system to suppress these two types of disturbances can be summarized as vibration damping performance and attitude stability performance, respectively. To effectively suppress base vibration, high-end vibration damping systems mostly adopt a low natural frequency structural design. A low natural frequency can extend the low-frequency damping bandwidth and greatly improve the system's vibration damping performance, but it will lead to a decrease in the system's attitude stability performance: when the load is subjected to the same direct disturbance force, a larger positional fluctuation will occur. Existing active vibration damping technologies face the problem of difficulty in simultaneously achieving vibration damping performance and attitude stability performance. As the requirements for environmental stability of ultra-precision equipment become increasingly stringent, the impact of direct disturbance forces from the external environment on the system can no longer be ignored. How to further improve the system's attitude stability performance while meeting vibration damping performance requirements is a pressing challenge that active vibration damping technology urgently needs to overcome. Summary of the Invention

[0005] To address the shortcomings of existing technologies, the purpose of this application is to provide an active vibration reduction control method and system based on multi-sensor information fusion, aiming to solve the problems of insufficient micro-vibration recognition bandwidth and difficulty in simultaneously achieving vibration reduction performance and attitude stabilization performance in existing active vibration reduction technologies.

[0006] To achieve the above objectives, in a first aspect, this application provides an active vibration reduction control method based on multi-sensor information fusion, comprising: Collect the absolute velocity signal of load vibration, the acceleration signal of load vibration, the relative displacement signal between the load and the base, and the absolute velocity signal of base vibration; Based on the multi-sensor information fusion controller model and the collected signals, the active control force is determined, which is used to counteract the vibration interference on the load. The multi-sensor information fusion controller model is used to fuse the outputs of multiple controllers to determine the active control force. These controllers include a feedback controller for processing the absolute velocity signal of the load vibration. Feedback controller for processing load vibration acceleration signals Feedback controller for processing relative displacement signals and a feedforward controller for processing the absolute velocity signal of the base vibration .

[0007] Understandably, the multi-sensor information fusion controller model, by using feedback control of the absolute velocity signal of load vibration, the acceleration signal of load vibration, and the relative displacement signal between the load and the base, as well as feedforward control using the absolute velocity signal of base vibration, can compensate for the vibration measurement deficiencies of velocity sensors in the low-frequency and high-frequency bands by using other types of sensors besides velocity sensors, thereby expanding the vibration measurement frequency band and realizing wide-frequency active vibration reduction.

[0008] Furthermore, by making reasonable use of the measurement signals from different sensors, the vibration reduction and attitude stabilization capabilities of the system can be greatly improved, taking into account both vibration reduction and attitude stabilization performance, and significantly enhancing the vibration suppression capability of the system over a wide frequency range.

[0009] In one possible implementation, the multi-sensor information fusion controller model is determined by the following formula: ; in, for Laplace transform, Indicates active control. express Laplace transform, This indicates the residual vibration of the load. express Laplace transform, represents the perturbation from the base, and s represents the Laplace operator.

[0010] In one possible implementation, a feedback controller The model is determined by the following formula: ; in, For absolute velocity feedback gain; For absolute displacement feedback gain; It is a low-pass filter used to limit high-frequency noise in the speed sensor signal.

[0011] In one possible implementation, a feedback controller The model is determined by the following formula: ; in, For acceleration feedback gain; It is a high-pass filter used to filter out low-frequency noise in the accelerometer signal; It is a low-pass filter used to filter out high-frequency noise in the accelerometer sensor signal; This represents the transfer function of the lag correction element.

[0012] In one possible implementation, a feedback controller The model is determined by the following formula: ; in, It is a low-frequency positive stiffness control gain; It is a low-frequency, positive stiffness-controlled frequency-division low-pass filter; It is a mid-to-high frequency negative stiffness control gain. The value of satisfies , It is the stiffness coefficient of the vibration reduction system; It is a frequency-division high-pass filter with mid-to-high frequency negative stiffness control; It is a low-frequency positive damping control gain; It is a low-frequency positive damping controlled frequency divider low-pass filter; It is a low-pass filter used to filter out high-frequency noise in relative displacement sensor signals.

[0013] In one possible implementation, a feedforward controller The model is determined by the following formula: ; in, For feedforward control gain; It is a low-pass filter used to limit high-frequency noise in the feedforward speed sensor signal.

[0014] In one possible implementation, , The passive damping coefficient of the vibration reduction system The estimated value.

[0015] In one possible implementation, before determining the active control force based on the multi-sensor information fusion controller model and the acquired signals, the following is also included: Based on the phase margin constraint and gain margin constraint of the open-loop transfer function of the control loop, the control parameters of the multi-sensor information fusion controller model are determined. The formula for the open-loop transfer function of the control loop is as follows: ; in, This is the equivalent model for the speed sensor; It is the total mass of the load being damped; and These are the damping coefficient and stiffness coefficient of the vibration reduction system, respectively; s represents the Laplace operator; The formula for the phase margin constraint is as follows: ; The formula for the gain margin constraint is as follows: ; in, It is the frequency at which the amplitude crosses 0dB; It is the frequency corresponding to a phase crossing ±180°; The minimum allowable phase margin; The minimum allowable gain margin; It is a function for finding angles; It is a modulus, and the unit is dB.

[0016] In one possible implementation, the equivalent model of the speed sensor It is determined by the following formula: ; in, It is the sensor's equivalent sensitivity; It is the inherent angular frequency of the speed sensor; It is the equivalent mechanical damping coefficient.

[0017] Secondly, this application provides an active vibration reduction control system based on multi-sensor information fusion, including: a load to be vibration reduced, an acceleration sensor, a relative displacement sensor, an active control unit, a feedforward velocity sensor, a base, a load velocity sensor, a force actuator, a stiffness element, and a damping element. The load is connected to the base through stiffness and damping elements, which provide static support and passive vibration reduction for the load. An accelerometer and a load velocity sensor are connected to the load and are used to measure the load vibration acceleration signal and the load vibration absolute velocity signal, respectively. A feedforward velocity sensor is mounted on the base to measure the absolute velocity signal of the base vibration; A relative displacement sensor is placed between the load and the base to measure the relative displacement signal between the load and the base; Force actuators are output devices for active vibration damping control, which counteract vibration interference on the load by outputting active control force; The active control unit is used to perform the method described in the first aspect or any possible implementation of the first aspect.

[0018] Specifically, the load being damped is the controlled object of active vibration damping; the base is located directly below the load being damped; stiffness and damping elements are located between the load being damped and the base, with one end connected to the load and the other end connected to the base, providing static support and passive vibration damping for the load; a load velocity sensor is connected to the load to measure the absolute velocity signal of the load vibration; an acceleration sensor is connected to the load to measure the acceleration signal of the load vibration; a relative displacement sensor is located between the load and the base to measure the relative displacement signal between the two; a feedforward velocity sensor is located on the base to measure the absolute velocity signal of the base vibration; a force actuator, an actively controlled output device, outputs force (active control force) to counteract the vibration interference on the load, located between the load and the base, with one end connected to the load and the other end connected to the base; and an active control unit, based on the active vibration damping control strategy, calculates the collected load vibration signal and base feedforward signal to obtain the output signal and control the force actuator.

[0019] Overall, the technical solutions conceived in this application have the following beneficial effects compared with the prior art: (1) By using a velocity sensor, an acceleration sensor and a relative displacement sensor to measure load vibration together, the system measurement bandwidth can be greatly broadened, and wide-frequency domain micro-vibration measurement can be realized.

[0020] (2) By proposing an active vibration reduction control method based on multi-sensor information fusion, the measurement signals of different sensors are rationally utilized, effectively solving the problem that the vibration reduction performance and attitude stabilization performance are difficult to balance in the existing active vibration reduction technology, and the vibration suppression capability of the system can be greatly improved in a wide frequency range. Attached Figure Description

[0021] Figure 1 This is a flowchart illustrating an active vibration reduction control method based on multi-sensor information fusion provided in an embodiment of this application. Figure 2 This is a schematic diagram of the principle of an active vibration reduction system based on multi-sensor information fusion provided in an embodiment of this application; Figure 3 This is a block diagram of an active vibration reduction system based on multi-sensor information fusion provided in an embodiment of this application; Figure 4 This is a block diagram of the control loop structure of the active vibration reduction control method based on multi-sensor information fusion provided in the embodiments of this application; Figure 5 The Bode plot of the open-loop transfer function of the active vibration reduction control method based on multi-sensor information fusion proposed in this application in the first embodiment is shown. Figure 6This is a schematic diagram of the vibration reduction performance of the active vibration reduction control method based on multi-sensor information fusion proposed in this application in the first embodiment; Figure 7 This is a schematic diagram of the attitude stabilization performance of the active vibration reduction control method based on multi-sensor information fusion proposed in this application in the first embodiment; Figure 8 The Bode plot of the open-loop transfer function of the active vibration reduction control method based on multi-sensor information fusion proposed in this application is shown when the low-frequency measurement performance of the speed sensor is improved in the second embodiment. Figure 9 This is a schematic diagram of the vibration reduction performance of the active vibration reduction control method based on multi-sensor information fusion proposed in this application when the low-frequency measurement performance of the velocity sensor is improved in the second embodiment; Figure 10 This is a schematic diagram of the attitude stabilization performance of the active vibration reduction control method based on multi-sensor information fusion proposed in this application when the low-frequency measurement performance of the velocity sensor is improved in the second embodiment; Figure 11 The Bode plot of the open-loop transfer function of the active vibration reduction control method based on multi-sensor information fusion proposed in this application is shown when the natural frequency of the passive system decreases in the third embodiment. Figure 12 This is a schematic diagram of the vibration reduction performance of the active vibration reduction control method based on multi-sensor information fusion proposed in this application when the natural frequency of the passive system decreases in the third embodiment. Figure 13 This is a schematic diagram of the attitude stabilization performance of the active vibration reduction control method based on multi-sensor information fusion proposed in this application when the natural frequency of the passive system decreases in the third embodiment. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0023] In the embodiments of this application, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design that is described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the terms "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0024] In the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more, for example, multiple processing units means two or more processing units, multiple elements means two or more elements, etc.

[0025] The embodiments of this application are described below with reference to the accompanying drawings.

[0026] like Figure 1 The diagram shown is a flowchart of an active vibration reduction control method based on multi-sensor information fusion proposed in this application. The control method includes the following steps: Step 1: Establish a dynamic model of the active vibration reduction system; Step 2: Based on the dynamic model, design a multi-sensor information fusion controller model; Step 3: Set control parameters (such as the filter order and cutoff frequency, the controller gain coefficient, etc.) based on the dynamic model and controller model. Step 4: Perform active vibration reduction control based on the controller model and control parameters.

[0027] like Figure 2 The diagram shown is a schematic diagram of an active vibration reduction system based on multi-sensor information fusion proposed in this application, including a load to be damped 1, an acceleration sensor 2, a relative displacement sensor 3, an active control unit 4, a feedforward velocity sensor 5, a base 6, a load velocity sensor 7, a force actuator 8, a stiffness element 9, and a damping element 10.

[0028] The load 1 is connected to the base 6 via stiffness element 9 and damping element 10, which provide static support and passive vibration reduction for the load. Accelerometer 2 and load velocity sensor 7 are connected to the load to measure the load's vibration acceleration and absolute velocity signals, respectively. Feedforward velocity sensor 5 is located on the base to measure the absolute velocity signal of the base. Relative displacement sensor 3 is located between the load and the base to measure their relative displacement. Force actuator 8 is the output device for active vibration reduction control, outputting force to counteract vibration interference on the load. Active control unit 4, based on the active vibration reduction control strategy, processes the acquired load vibration acceleration signal... Absolute velocity signal of load vibration Relative displacement signal and the absolute velocity signal of the base vibration The calculation is performed to obtain the output signal and control the force actuator.

[0029] In the following detailed implementation, this application will be based on Figure 2 The system shown is described in detail as an embodiment.

[0030] Specifically, refer to Figure 2 Based on the dynamic relationship, the dynamic model of the active vibration reduction system can be expressed as follows: ; In the formula, It is the total mass of the load being damped (the damped body). and These are the damping coefficient and stiffness coefficient of the vibration reduction system, respectively. It's a disturbance originating from the base; It is the residual vibration of the load; It is the absolute velocity of the base vibration; It is the absolute velocity of the load vibration; It is the vibration acceleration of the load; It is a direct disturbance force acting on the load; It is the active control force output by the force actuator.

[0031] Furthermore, when the disturbance experienced by the vibration reduction system is base vibration, the system reacts to the base vibration. to load vibration The transfer function is , The amplitude-frequency response curve is an indicator for measuring the vibration reduction performance of the system; when the vibration reduction system is subjected to a direct disturbance force, the system responds to the direct disturbance force. to load vibration The transfer function is , The amplitude-frequency response curve is an indicator for measuring the attitude stability performance of the system. , The specific expressions are as follows: ; ; In the formula, , and They are respectively , and The Laplace transform of ; s is the Laplace operator.

[0032] Specifically, the multi-sensor information fusion controller model is composed of a combination of multiple control strategies. In the control loop, each sensor corresponds to a controller, and the total controller output is the sum of the outputs of multiple controllers. Specifically, the control loop of the control method proposed in this application includes four controllers: a feedback controller based on the measured absolute velocity of the load vibration. Feedback controller based on measuring load vibration acceleration Feedback controller based on measuring the relative displacement between the load and the base Feedforward controller based on measuring the absolute velocity of the base vibration The multi-sensor information fusion controller model achieves wide-frequency active vibration reduction by using feedback control of the absolute velocity, acceleration, and relative displacement signals of the load vibration, as well as feedforward control using the velocity signal of the base.

[0033] like Figure 3 As shown, Figure 2 A block diagram of the active vibration damping system, which includes four controllers: Provides feedback control based on the measured absolute velocity of load vibration. Provides feedback control based on measured load vibration acceleration. Provides feedback control based on the relative displacement between the measured load and the base. Provides feedforward control based on the absolute velocity of the measured base vibration. , , , These represent the impact of noise from the corresponding sensors. Representing three corresponding controllers ( , and The sum of the outputs.

[0034] Furthermore, a feedback controller based on measuring the absolute velocity of load vibration. The design employs a proportional-integral (PI) controller. The proportional term applies absolute velocity feedback control (ceiling damping), which physically acts as a virtual damper between the load and the inertial reference, effectively suppressing vibration transmission near the resonance peak. The integral term applies absolute displacement feedback control (ceiling stiffness), which physically acts as a virtual positive stiffness spring between the load and the inertial reference, improving the system's vibration reduction and attitude stability in the low-to-mid frequency range. Because the load's vibration velocity signal is weak at high frequencies, and the signal-to-noise ratio of the velocity sensor is insufficient, the controller needs to filter to limit the influence of high-frequency noise. The controller model is designed as follows: ; In the formula, For absolute velocity feedback gain; For absolute displacement feedback gain; It is a low-pass filter used to limit high-frequency noise in the speed sensor signal.

[0035] Furthermore, a feedback controller based on measuring the vibration acceleration of the load. Designed as a proportional controller, it physically adds virtual mass to the load, simultaneously improving the system's high-frequency vibration damping and attitude stabilization performance. Due to the limited bandwidth of the accelerometer, the controller needs to filter out signal noise; therefore, the controller model is designed as follows: ; In the formula, For acceleration feedback gain; It is a high-pass filter used to filter out low-frequency noise in the accelerometer signal; It is a low-pass filter used to filter out high-frequency noise in the accelerometer sensor signal.

[0036] Furthermore, due to the time lag of the force actuator in practical applications, the phase lag of the system will gradually increase with the frequency, making the closed-loop system unstable. To prevent system instability, a series lag compensation circuit is used to reduce the controller's phase lag. The control gain at high frequencies is used to limit the system's control bandwidth. The transfer function expression for the lag compensation element is: ; In the formula, The zero-point angular frequency; The pole rotation frequency; This represents the order of the lag correction element.

[0037] Furthermore, the controller is connected in series with a lag correction element. It can be represented as: ; Furthermore, a feedback controller based on the relative displacement between the measured load and the base. Designed as a proportional-derivative controller.

[0038] Specifically, the controller The proportional term in the equation is used to apply relative displacement feedback control, which can physically change the equivalent stiffness of the system. Furthermore, in order to meet the performance requirements of the vibration reduction system for low-frequency attitude stability and mid-to-high-frequency vibration reduction, the proportional term is designed as a frequency-varying stiffness control strategy.

[0039] Specifically, the frequency-varying stiffness control strategy applies relative displacement negative feedback control in the low-frequency band through a frequency-division filter to increase the system's equivalent stiffness and improve its low-frequency attitude stability performance; and applies relative displacement positive feedback control in the mid-to-high frequency band through the same frequency-division filter to reduce the system's equivalent stiffness and improve its high-frequency vibration reduction performance. By applying positive stiffness control in the low-frequency band and negative stiffness control in the mid-to-high frequency band, the frequency-varying stiffness control strategy can simultaneously address the system's performance requirements for vibration reduction and attitude stability, adjusting the dynamic stiffness characteristics appropriately across different frequency bands. The transfer function expression of this control strategy is as follows: ; In the formula, It is a low-frequency positive stiffness control gain; It is a low-frequency, positive stiffness-controlled frequency-division low-pass filter; It is a mid-to-high frequency negative stiffness control gain. The value of satisfies , It is the stiffness coefficient of the vibration reduction system; It is a frequency-division high-pass filter with mid-to-high frequency negative stiffness control.

[0040] Furthermore, the controller The differential term in the equation is used to apply relative velocity negative feedback control, which can increase the system's equivalent damping and suppress low-frequency resonance, but it will weaken the vibration decay rate of the system in the high-frequency range. To limit its impact on the system's high-frequency vibration reduction performance, a frequency-divided low-pass filter is used to limit its control bandwidth, ensuring that the applied positive damping control only acts in the low-frequency range. The transfer function expression of its control strategy is: ; In the formula, It is a low-frequency positive damping control gain; It is a low-frequency divided low-pass filter with low-frequency positive damping control.

[0041] Furthermore, since the load's vibration displacement signal is relatively weak in the high-frequency range, resulting in insufficient signal-to-noise ratio compared to the displacement sensor, the controller needs to limit the influence of high-frequency noise through filtering. Combining the aforementioned frequency-varying stiffness control and low-frequency positive damping control, a controller is designed. The model is: ; In the formula, It is a low-pass filter used to filter out high-frequency noise in relative displacement sensor signals.

[0042] Furthermore, a feedforward controller based on measuring the absolute velocity of the base vibration. Designed as a proportional controller, it counteracts the influence of the relative damping term in the path of vibration transmission from the base to the load. Physically, this is equivalent to adding a "feedforward negative damper" in parallel to the vibration reduction system, further improving the system's vibration reduction performance in the mid-to-high frequency range. Since the velocity sensor has a limited measurement bandwidth, filtering is needed to limit the influence of high-frequency noise. Therefore, the controller model is designed as follows: ; In the formula, For feedforward control gain; It is a low-pass filter used to limit high-frequency noise in the feedforward speed sensor signal.

[0043] Furthermore, in order to minimize the influence of the relative damping term in the path of base vibration transmitted to the load, the feedforward control gain is set as follows: ; In the formula, The passive damping coefficient of the vibration reduction system The estimated value.

[0044] Furthermore, based on the established multi-sensor information fusion controller model, the active control force output by the force actuator can be expressed as: ; In the formula, for Laplace transform.

[0045] Furthermore, step three sets control parameters based on the dynamics model and the controller model, which includes verifying system stability through the open-loop transfer function of the control loop. The expression for the open-loop transfer function of the control loop is: ; In the formula, The equivalent model of the speed sensor, its position in the control loop is as follows: Figure 4 As shown. Since the speed sensor exhibits high-pass characteristics in the frequency domain, its dynamic characteristics in the low-frequency band cannot be ignored, so its impact on the system loop stability needs to be considered. The equivalent model of the speed sensor can be expressed as a second-order high-pass filter model, as shown in the following equation: ; In the formula, It is the sensor's equivalent sensitivity; It is the inherent angular frequency of the speed sensor; It is the equivalent mechanical damping coefficient.

[0046] Furthermore, to ensure system stability, the open-loop transfer function of the control loop must meet the system's stability requirements. These stability requirements are expressed through phase margin constraints and gain margin constraints, which can be represented as follows: ; ; In the formula, It is the frequency at which the amplitude crosses 0dB; It is the frequency corresponding to a phase crossing ±180°; The minimum allowable phase margin; The minimum allowable gain margin; It is a function for finding angles; It's a modulus calculation, measured in dB. It can usually be set... , This serves as a compromise between control effectiveness and stability in the system.

[0047] Furthermore, when the open-loop transfer function of the system control loop does not meet the stability requirements, the control parameters need to be reset and iteratively adjusted to meet the system stability requirements. The controller gain can be increased as much as possible while still satisfying the system stability requirements.

[0048] like Figure 4 The diagram shown is a block diagram of the control loop structure of the active vibration reduction control method based on multi-sensor information fusion proposed in this application. The Passive region represents the passive structure, which is connected to the feedback controller. , and Forming a feedback control loop, together with the feedforward controller This forms a feedforward control loop. When considering the low-frequency dynamic characteristics of the velocity sensor, the system is affected by base vibration. to load vibration The transfer function is From the direct interference force to load vibration The transfer function is , , The specific expressions are described below: ; ; In the following embodiments, this application will use a transfer function. and As an indicator to measure the system's vibration reduction and attitude stabilization performance, this study verifies the effectiveness of the control method proposed in this application.

[0049] In general, the technical solution adopted in this application is: an active vibration reduction control method and system based on multi-sensor information fusion. The control method and system utilize velocity or acceleration sensors to measure the absolute velocity or acceleration of the load being damped and the damper mounting base, respectively, and measure the relative displacement of the load relative to the base using a relative displacement sensor. All or a portion of the above signals undergo different filtering processes before being input into PID controllers with different parameter configurations. Finally, these signals are synthesized to form a vibration control signal based on multi-sensor information fusion, which drives a force actuator to generate a vibration control force with corresponding characteristics, acting on the damped body to significantly improve the system's vibration reduction and attitude stability performance over a wide frequency range. Using this method, high vibration reduction effects can be achieved in a wide frequency range, especially in the low-frequency range near 1Hz, by selecting sensors, configuring filters, and configuring controller parameters, based on the differences in vibration reduction requirements across different frequency bands.

[0050] The control method and system utilize velocity sensors, acceleration sensors, and relative displacement sensors to jointly measure load vibration, while using a feedforward velocity sensor to measure the absolute velocity of base vibration. This effectively broadens the system's measurement bandwidth and enables wide-frequency domain micro-vibration measurement. Specifically, for the aforementioned multi-sensor information fusion control, the noise spectrum characteristics of each vibration sensor in the vibration reduction system are first analyzed. Then, corresponding low-pass and high-pass filters are designed based on the signal-to-noise ratio advantage frequency bands of each sensor. The low-pass filter filters high-frequency noise from the relative displacement sensor signal and velocity sensor signal, while the high-pass filter filters low-frequency noise from the acceleration sensor signal. Considering the comprehensive performance requirements of the system's vibration reduction and attitude stabilization, the filtered sensor signals are input into PID controllers with different parameter configurations for feedback and feedforward control, outputting corresponding control forces to counteract the vibration interference experienced by the load.

[0051] Furthermore, the filtered velocity sensor signals and acceleration sensor signals are used for control. Absolute velocity feedback achieves "ceiling damping," absolute velocity integral feedback achieves "ceiling stiffness," and acceleration feedback increases the system's virtual mass. This introduces a virtual absolute mass-spring-damping system, which significantly improves the system's vibration reduction and attitude stabilization capabilities.

[0052] Furthermore, the filtered relative displacement sensor signal is used for control. Positive stiffness and positive damping control are applied through relative displacement negative feedback and relative velocity negative feedback in the low-frequency and ultra-low-frequency bands, while negative stiffness control is applied through relative displacement positive feedback in the mid-to-high-frequency bands. This approach can simultaneously meet the system's comprehensive performance requirements for vibration reduction and attitude stabilization, and optimize and match reasonable dynamic stiffness characteristics in different frequency bands.

[0053] Furthermore, the system can be controlled by using the filtered feedforward speed sensor signal. By feeding forward the speed signal, the vibration reduction performance of the system in the medium and high frequencies can be further improved.

[0054] The present application will be further illustrated below through more specific embodiments.

[0055] Example 1: This embodiment demonstrates the significant improvement in vibration reduction and attitude stability achieved by the control method and system proposed in this application over a wide frequency range.

[0056] In this embodiment, the passive structural parameters of the vibration reduction system used are shown in Table 1. Here, m, c, k, and f represent the load mass, damping coefficient, stiffness coefficient, and natural frequency of the structure, respectively.

[0057] Table 1 Passive structural parameters of the vibration reduction system used in Example 1

[0058] Considering the low-frequency dynamic characteristics of the speed sensor, the inherent angular frequency of the speed sensor used in this embodiment is 4.5Hz. To improve the low-frequency measurement performance of the speed sensor, its bandwidth is extended using the zero-pole cancellation method. The equivalent model of the extended speed sensor can still be regarded as a second-order high-pass filter model. The equivalent angular frequency of the speed sensor after spread spectrum is... The equivalent damping coefficient is 0.3Hz. It is 0.7.

[0059] In this embodiment, the filter parameters are shown in Table 2, and the control gain parameters are shown in Table 3.

[0060] Table 2 Filter parameters set in Example 1

[0061] Table 3 Control gain set in Example 1

[0062] Lag correction Used to reduce controller The high-frequency control gain is configured with a hysteresis correction stage in this embodiment as follows: ; To ensure the controller The control gain drops to 1 / 10 at 100Hz and to 1 / 20 at 200Hz.

[0063] According to the control parameters set in this embodiment, the Bode plot of the open-loop transfer function of the system control loop is as follows: Figure 5As shown in the figure, the minimum gain margin of the loop is 8.24 dB, and the minimum phase margin is 74.9°, which meets the system stability requirements.

[0064] According to the control parameters set in this embodiment, the vibration reduction effect expected to be achieved by the active vibration reduction control method and system based on multi-sensor information fusion proposed in this application is as follows: Figure 6 As shown, the expected posture stabilization effect is as follows: Figure 7 As shown. Figure 6 The transmission rate of the vibration reduction system from the base vibration to the load vibration attenuated to -20dB at the natural frequency of 1.6Hz, to -45dB at 5Hz, and to -67dB at 20Hz. The initial vibration reduction bandwidth of the system was extended to 0.7Hz, and the high-frequency vibration reduction bandwidth was extended to 97Hz. Figure 7 The vibration damping system showed a 51 dB decrease in the transmission rate from direct interference force to load vibration at the natural frequency of 1.6 Hz, and a 20 dB decrease in the ultra-low frequency range below 0.1 Hz.

[0065] Example 2: This embodiment demonstrates the control effect of the proposed control method and system under a more advanced speed sensor. Compared to Embodiment 1, Embodiment 2 uses a speed sensor with a lower natural angular frequency for control, and by adjusting the control parameters, further improvements in low-frequency control performance can be achieved.

[0066] The speed sensor used in this embodiment has a natural angular frequency of 2Hz. After spread spectrum, the equivalent angular frequency of the speed sensor is... The equivalent damping coefficient is 0.1 Hz. It is 0.7.

[0067] In this embodiment, the passive structural parameters of the vibration reduction system used are shown in Table 4. Here, m, c, k, and f represent the load mass, damping coefficient, stiffness coefficient, and natural frequency of the structure, respectively.

[0068] Table 4 Passive structural parameters of the vibration reduction system used in Example 2

[0069] In this embodiment, the filter parameters are shown in Table 5, and the control gain parameters are shown in Table 6.

[0070] Table 5 Filter parameters set in Example 2

[0071] Table 6 Control Gain Set in Example 2

[0072] Lag correction Used to reduce controller The high-frequency control gain is configured with a hysteresis correction stage in this embodiment as follows: ; According to the control parameters set in this embodiment, the Bode plot of the open-loop transfer function of the system control loop is as follows: Figure 8 As shown in the figure, the minimum gain margin of the loop is 6.69 dB, and the minimum phase margin is 64.1°, which meets the system stability requirements.

[0073] According to the control parameters set in this embodiment, the vibration reduction effect expected to be achieved by the active vibration reduction control method and system based on multi-sensor information fusion proposed in this application is as follows: Figure 9 As shown, the expected posture stabilization effect is as follows: Figure 10 As shown. Figure 9 The transmission rate of the vibration reduction system from the base vibration to the load vibration attenuated to -41dB at the natural frequency of 1.6Hz, to -64dB at 5Hz, and to -67dB at 20Hz. The initial vibration reduction bandwidth of the system was extended to 0.4Hz, and the high-frequency vibration reduction bandwidth was extended to 90Hz. Figure 10 The vibration damping system showed a 58 dB decrease in the transmission rate from direct interference force to load vibration at the natural frequency of 1.6 Hz, and a 26 dB decrease in the ultra-low frequency range below 0.1 Hz.

[0074] Example 3: This embodiment demonstrates the effectiveness of the control method and system proposed in this application in a vibration reduction system with a lower natural frequency. Compared to Embodiment 2, the passive structure of the vibration reduction system used in Embodiment 3 has a lower natural frequency.

[0075] In this embodiment, the passive structural parameters of the vibration reduction system used are shown in Table 7. Here, m, c, k, and f represent the load mass, damping coefficient, stiffness coefficient, and natural frequency of the structure, respectively.

[0076] Table 7 Passive structural parameters of the vibration reduction system used in Example 3

[0077] Considering the low-frequency dynamic characteristics of the speed sensor, the inherent angular frequency of the speed sensor used in this embodiment is 2Hz. After spread spectrum, the equivalent angular frequency of the speed sensor is... The equivalent damping coefficient is 0.1 Hz. It is 0.7.

[0078] In this embodiment, the filter parameters are shown in Table 8, and the control gain parameters are shown in Table 9.

[0079] Table 8 Filter parameters set in Example 3

[0080] Table 9 Control Gain Set in Example 3

[0081] Lag correction Used to reduce controller The high-frequency control gain is configured with a hysteresis correction stage in this embodiment as follows: ; According to the control parameters set in this embodiment, the Bode plot of the open-loop transfer function of the system control loop is as follows: Figure 11 As shown in the figure, the minimum gain margin of the loop is 6.66 dB, and the minimum phase margin is 77.3°, which meets the system stability requirements.

[0082] According to the control parameters set in this embodiment, the vibration reduction effect expected to be achieved by the active vibration reduction control method and system based on multi-sensor information fusion proposed in this application is as follows: Figure 12 As shown, the expected posture stabilization effect is as follows: Figure 13 As shown. Figure 12 The vibration reduction system shows that the transmission rate from base vibration to load vibration decreases to -29dB at the natural frequency of 0.8Hz, -71dB at 5Hz, and -74dB at 20Hz. The initial vibration reduction bandwidth of the system is extended to 0.3Hz, and the high-frequency vibration reduction bandwidth is extended to 100Hz. Figure 13 The vibration damping system showed a 60 dB decrease in the transmission rate from direct interference force to load vibration at the natural frequency of 1.6 Hz, and a 26 dB decrease in the ultra-low frequency range below 0.1 Hz.

[0083] As can be seen from the above embodiments, the active vibration reduction control method and system based on multi-sensor information fusion proposed in this application can effectively broaden the control bandwidth of active vibration reduction and achieve a significant improvement in vibration reduction performance and attitude stability performance in a wide frequency range.

[0084] It is understood that the various numerical designations used in the embodiments of this application are merely for the convenience of description and are not intended to limit the scope of the embodiments of this application.

[0085] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. An active vibration reduction control method based on multi-sensor information fusion, characterized in that, include: Collect the absolute velocity signal of load vibration, the acceleration signal of load vibration, the relative displacement signal between the load and the base, and the absolute velocity signal of base vibration; Based on the multi-sensor information fusion controller model and the collected signals, the active control force is determined, which is used to counteract the vibration interference on the load. The multi-sensor information fusion controller model is used to fuse the outputs of multiple controllers to determine the active control force. These controllers include a feedback controller for processing the absolute velocity signal of the load vibration. Feedback controller for processing load vibration acceleration signals Feedback controller for processing relative displacement signals and a feedforward controller for processing the absolute velocity signal of the base vibration ; The multi-sensor information fusion controller model is determined by the following formula: ； in, for Laplace transform, Indicates active control. express Laplace transform, This indicates the residual vibration of the load. express Laplace transform, represents the perturbation from the base, and s represents the Laplace operator; Feedback controller It is a proportional-integral controller, where the proportional term is used to apply absolute velocity feedback control and the integral term is used to apply absolute displacement feedback control. Feedback controller It is a proportional controller used to increase the virtual quality of the load; Feedback controller It is a proportional-derivative controller. The proportional term is used to apply relative displacement feedback control. The proportional term is designed as a frequency-varying stiffness control strategy. The frequency-varying stiffness control strategy applies positive stiffness control in the low frequency range and negative stiffness control in the medium and high frequency range. The derivative term is used to apply relative velocity negative feedback control. Feedforward controller It is a proportional controller used to counteract the effects of the relative damping term in the path of base vibration transmitted to the load.

2. The active vibration reduction control method based on multi-sensor information fusion according to claim 1, characterized in that, Feedback controller The model is determined by the following formula: ； in, For absolute velocity feedback gain; For absolute displacement feedback gain; It is a low-pass filter used to limit high-frequency noise in the speed sensor signal.

3. The active vibration reduction control method based on multi-sensor information fusion according to claim 1, characterized in that, Feedback controller The model is determined by the following formula: ； in, For acceleration feedback gain; It is a high-pass filter used to filter out low-frequency noise in the accelerometer signal; It is a low-pass filter used to filter out high-frequency noise in the accelerometer sensor signal; This represents the transfer function of the lag correction element.

4. The active vibration reduction control method based on multi-sensor information fusion according to claim 1, characterized in that, Feedback controller The model is determined by the following formula: ； in, It is a low-frequency positive stiffness control gain; It is a low-frequency, positive stiffness-controlled frequency-division low-pass filter; It is a mid-to-high frequency negative stiffness control gain. The value of satisfies , It is the stiffness coefficient of the vibration reduction system; It is a frequency-division high-pass filter with mid-to-high frequency negative stiffness control; It is a low-frequency positive damping control gain; It is a low-frequency positive damping controlled frequency divider low-pass filter; It is a low-pass filter used to filter out high-frequency noise in relative displacement sensor signals.

5. The active vibration reduction control method based on multi-sensor information fusion according to claim 1, characterized in that, Feedforward controller The model is determined by the following formula: ； in, For feedforward control gain; It is a low-pass filter used to limit high-frequency noise in the feedforward speed sensor signal.

6. The active vibration reduction control method based on multi-sensor information fusion according to claim 5, characterized in that, , The passive damping coefficient of the vibration reduction system The estimated value.

7. The active vibration reduction control method based on multi-sensor information fusion according to any one of claims 1-6, characterized in that, Before determining the active control force based on the multi-sensor information fusion controller model and the acquired signals, the following steps are also included: Based on the phase margin constraint and gain margin constraint of the open-loop transfer function of the control loop, the control parameters of the multi-sensor information fusion controller model are determined. The formula for the open-loop transfer function of the control loop is as follows: ； in, This is the equivalent model for the speed sensor; It is the total mass of the load being damped; and These are the damping coefficient and stiffness coefficient of the vibration reduction system, respectively; s represents the Laplace operator; The formula for the phase margin constraint is as follows: ； The formula for the gain margin constraint is as follows: ； in, It is the frequency at which the amplitude crosses 0dB; It is the frequency corresponding to a phase crossing ±180°; This is the minimum allowable phase margin; The minimum allowable gain margin; It is a function for finding angles; It is a modulus, and the unit is dB.

8. The active vibration reduction control method based on multi-sensor information fusion according to claim 7, characterized in that, Equivalent model of speed sensor It is determined by the following formula: ； in, It is the sensor's equivalent sensitivity; It is the inherent angular frequency of the speed sensor; It is the equivalent mechanical damping coefficient.

9. An active vibration reduction control system based on multi-sensor information fusion, characterized in that, include: The damped load, acceleration sensor, relative displacement sensor, active control unit, feedforward velocity sensor, base, load velocity sensor, force actuator, stiffness element and damping element; The load is connected to the base through stiffness and damping elements, which provide static support and passive vibration reduction for the load. An accelerometer and a load velocity sensor are connected to the load and are used to measure the load vibration acceleration signal and the load vibration absolute velocity signal, respectively. A feedforward velocity sensor is mounted on the base to measure the absolute velocity signal of the base vibration; A relative displacement sensor is placed between the load and the base to measure the relative displacement signal between the load and the base; Force actuators are output devices for active vibration damping control, which counteract vibration interference on the load by outputting active control force; The active control unit is used to execute the active vibration reduction control method based on multi-sensor information fusion as described in any one of claims 1-8.

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