Variable impedance vibration control method and system based on vibration dominant frequency estimation

Abstract

The invention belongs to the technical field of automatic control, and particularly relates to a variable impedance vibration control method and system based on vibration dominant frequency estimation, and the method comprises the steps: applying a broadband excitation signal, collecting a response signal, and determining a vibration system transfer function through system identification; analyzing transmission characteristics, dividing frequency bands and optimizing impedance parameter combinations to form a frequency band parameter mapping table; estimating the vibration dominant frequency of the vibration system in real time through an extended Kalman filtering algorithm, and determining a corresponding impedance parameter in combination with the mapping relation; and calculating a target control force and a target current instruction according to the real-time vibration information, and driving a motor to output a control force to realize variable impedance control. According to the method, the frequency domain adaptability defect of a traditional method under broadband excitation is overcome, the method is suitable for electromechanical systems such as vehicle suspensions and precise instrument vibration isolation which need to dynamically adjust the vibration characteristics, and key indexes such as the load acceleration root-mean-square value can be remarkably optimized.

Description

Technical Field

[0001] The present invention belongs to the field of automatic control technology, and specifically relates to a variable impedance vibration control method and system based on vibration main frequency estimation. The method and system are applicable to electromechanical systems that require dynamic adjustment of vibration characteristics, such as vehicle suspension, precision instrument vibration isolation and other broadband vibration control systems. Background Art

[0002] In the field of dynamic system control, traditional control methods face significant technical bottlenecks when dealing with frequency-dependent coupling characteristics (i.e., the nonlinear response caused by the change of vibration frequency over time): (1) Existing variable impedance control mechanisms have the problem of insufficient frequency domain adaptability. Speed-based variable impedance control adjusts impedance through linear mapping, but it is difficult to adapt to the nonlinear coupling effect under broadband excitation, resulting in insufficient adjustment accuracy in sensitive frequency bands. Although stability-based variable impedance control can ensure system stability, its conservative constraints limit the dynamic response bandwidth (i.e., the system's ability to respond to excitations of different frequencies).

[0003] (2) Traditional proportional-integral-derivative (PID) control often relies on fixed gain parameters in frequency domain performance optimization, which makes it difficult to adapt to the dynamic changes of wide-band vibration scenarios, resulting in overdamping in the low-frequency band and insufficient response in the high-frequency band. Traditional optimal control methods also have similar problems. For example, the linear quadratic regulator (LQR) control uses a quadratic cost function with fixed weights, which leads to mutual constraints between the performance indicators of each frequency band. The H∞ control method sacrifices the fine adjustment capability of a specific frequency band by optimizing the system's robustness to the worst case, making it difficult to achieve global optimization under wide-band excitation. Summary of the Invention

[0004] To solve the above technical problems, the present invention provides a variable impedance vibration control method and system based on vibration main frequency estimation. By constructing a dynamic mapping relationship between impedance parameters and vibration main frequency, combined with the extended Kalman filter algorithm to track frequency, and adjusting the impedance control parameters according to the constructed mapping relationship, the contradiction between vibration transfer gain in different frequency bands of traditional vibration control systems can be effectively solved. This method can be widely used in the field of electromechanical system control that requires frequency-varying characteristic adjustment. Typical application scenarios include but are not limited to vehicle active suspension, precision instrument vibration isolation platform, and industrial machinery vibration suppression system.

[0005] To achieve the above object, a first aspect of the present invention provides a variable impedance vibration control method based on vibration main frequency estimation, comprising the following steps: Install an acceleration sensor at the vibration part of the vibration system, and install a displacement sensor between the vibration part and the fixed base to collect the time domain vibration signal of the vibration system in real time. The sampling frequency should be no less than 2.5 times the maximum operating frequency of the system. Use the exciter to apply the target frequency band to the vibration system A broadband excitation signal, wherein the broadband excitation signal includes a linear sweep signal, a discrete multi-frequency synthesis signal and a pink noise signal, so as to excite the full-band response of the vibration system; collecting a response signal of the vibration system under the action of the broadband excitation signal, and extracting a transfer function of the vibration system based on a system identification method; Analyzing the transfer function and dividing the frequency band between frequency points where performance conflicts exist; According to the preset vibration control performance requirements, an impedance parameter combination that satisfies the control effect is determined for each divided frequency band, and a frequency band parameter mapping table is established, wherein the frequency band parameter mapping table represents the correspondence between the frequency bands and the impedance parameter combinations; The collected time-domain vibration signal is band-pass filtered, and the filtering range covers the effective working frequency band of the vibration system. Then, the filtered signal is subjected to outlier removal and sliding average processing; Using an extended Kalman filter algorithm to process the time domain signal after the sliding average processing, to obtain an estimated vibration main frequency of the vibration system; Based on the frequency band parameter mapping table, find the estimated value of the main vibration frequency Matched impedance parameters, including impedance stiffness coefficient , impedance damping coefficient and impedance inertia coefficient ; Real-time acquisition of displacement differences of vibration systems ,speed and acceleration ; Based on the impedance parameters and the collected displacement difference ,speed and acceleration , the target control force is calculated by the following formula : ; By formula , calculate the target current instruction ,in is the torque coefficient of the motor, in units of , which represents the ratio of the motor output torque to the input current; The output torque of the driving motor is controlled by the current loop PID, and the torque is converted into the target control force through the transmission mechanism. , applied to the vibration system to achieve variable impedance vibration control.

[0006] The second aspect of the present invention provides a variable impedance vibration control system based on vibration main frequency estimation, comprising a sensor, a processor, a driver, a motor and a transmission mechanism; the sensor is used to collect vibration signals of the vibration system and send the collected vibration signals to the processor; a preset frequency band parameter mapping table is stored in the processor, and the processor uses a signal conditioning algorithm, an extended Kalman filter algorithm and an adaptive noise matrix adjustment algorithm to process the collected vibration signal to obtain an estimated value of the vibration main frequency of the vibration system, and determines the corresponding impedance parameters according to the estimated value of the vibration main frequency and the frequency band parameter mapping table, and the impedance parameters include an impedance stiffness coefficient , impedance damping coefficient and impedance inertia coefficient , and according to the impedance parameters and the displacement difference of the vibration system ,speed and acceleration Information, through the formula Calculate the target control force , the processor controls the force according to the target , calculate the target current command of the motor The driver is based on the target current instruction , drives the motor to output torque, and the transmission mechanism converts the motor torque into the target control force that matches the vibration direction of the vibration system applied to the vibration system to achieve real-time frequency-domain adaptive vibration control.

[0007] The beneficial effects of the present invention are as follows: The present invention obtains the main vibration frequency of the vibration system through an extended Kalman filter, combines it with a preset frequency band parameter mapping table, and dynamically adjusts the impedance parameters to achieve precise vibration control. This method effectively improves vibration control accuracy, resolves the gain contradictions of traditional methods in different frequency bands, and enhances system stability. Based on frequency domain decoupling and a multi-modal switching architecture, it adapts to complex working conditions under broadband excitation, has good dynamic response and stability performance, and has wide applicability. It can be applied to a variety of fields such as vehicle active suspension, precision instrument vibration isolation platforms, and industrial machinery vibration suppression, reducing vibration hazards, improving equipment performance and service life, and improving the comfort of the working environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] The above and other features, advantages, and aspects of the embodiments of the present disclosure will become more apparent by referring to the accompanying drawings and the following detailed description. The accompanying drawings are intended to assist in understanding the present disclosure and do not limit the present disclosure. The same or similar numbers represent the same or similar elements, among which: Figure 1 A flow chart of a variable impedance vibration control method based on vibration main frequency estimation; Figure 2Schematic diagram of a variable impedance vibration control system based on vibration main frequency estimation; Figure 3 Schematic diagram of the vibration system structure; Figure 4 The amplitude-frequency characteristic curves of sprung mass acceleration with different impedance inertia coefficients; Figure 5 Amplitude-frequency characteristic curves of unsprung dynamic deformation with different impedance inertia coefficients; Figure 6 The amplitude-frequency characteristic curves of sprung mass acceleration with different impedance stiffness coefficients and impedance damping coefficients; Figure 7 Amplitude-frequency characteristic curves of unsprung dynamic deformation with different impedance stiffness coefficients and impedance damping coefficients; Figure 8 RMS value of sprung mass acceleration; Figure 9 Amplitude-frequency characteristic curve of sprung mass acceleration. DETAILED DESCRIPTION

[0009] In order to enable those skilled in the art to better understand the technical solutions and advantages of the present invention, the present application is described in detail below with reference to the accompanying drawings, but this is not intended to limit the scope of protection of the present invention.

[0010] like Figure 1 As shown in the method flow chart, this embodiment provides a variable impedance vibration control method based on vibration main frequency estimation, including the following steps: An acceleration sensor is installed at the vibration part of the vibration system, and a displacement sensor is installed between the vibration part and the fixed base to collect the time domain vibration signal of the vibration system in real time, with a sampling frequency of not less than 2.5 times the maximum operating frequency of the system; in some embodiments, such as Figure 3 The structure shown: the vibration system includes an upper structure 4, a lower structure 5 and a fixed base 11; the upper structure 4 is the upper vibration component of the system, and the lower structure 5 is the lower vibration component; the acceleration sensor 2 is installed on the upper structure 4, and is used to collect the acceleration signal of the upper structure 4 in real time; the displacement sensor 1 is arranged between the upper structure 4 and the lower structure 5, and is used to measure the relative displacement between the upper structure 4 and the lower structure 5; the displacement sensor 3 is arranged between the lower structure 5 and the fixed base 11, and is used to measure the relative displacement between the lower structure 5 and the fixed base 11; Use the exciter to apply the target frequency band to the vibration system The broadband excitation signal includes a linear sweep signal, a discrete multi-frequency synthesis signal and a pink noise signal to stimulate the full-band response of the vibration system; see Figure 3 , the exciter 10 is installed between the lower structure 5 and the fixed base 11; A response signal of the vibration system under the action of the broadband excitation signal is collected, and a transfer function of the vibration system is extracted based on a system identification method. In some embodiments, the response signal includes an acceleration signal of the upper structure 4, a relative displacement signal between the upper structure 4 and the lower structure 5, and a relative displacement signal between the lower structure 5 and the fixed base 11, respectively collected by the acceleration sensor 2, the displacement sensor 1, and the displacement sensor 3. For ease of description, the acceleration signal of the upper structure 4 is referred to as sprung mass acceleration, the relative displacement between the upper structure 4 and the lower structure 5 is referred to as sprung dynamic deformation, and the relative displacement between the lower structure 5 and the fixed base 11 is referred to as unsprung dynamic deformation. The transfer function includes transfer functions of the sprung mass acceleration, the sprung dynamic deformation, and the unsprung dynamic deformation with respect to the broadband excitation signal, and is expressed as follows: ; ; ; ; ; ; in, , and are the transfer functions of the sprung mass acceleration, the sprung dynamic deformation, and the unsprung dynamic deformation relative to the broadband excitation signal, represents a complex frequency domain variable, represents the common denominator of the three transfer functions, represents the force transfer function between the upper structure 4 and the lower structure 5, represents the force transfer function between the lower structure 5 and the fixed base 11, represents the mass of the superstructure 4, represents the mass of the substructure 5, represents the stiffness coefficient of spring 6, represents the damping coefficient of the damper 7, represents the stiffness coefficient of spring 9, such as Figure 3 As shown, the spring 6 and the spring 9 are respectively connected between the upper structure 4 and the lower structure 5, and between the lower structure 5 and the fixed base 11, for providing passive elastic support; the damper 7 is provided between the upper structure 4 and the lower structure 5, for providing passive damping effect; represents the Laplace transform of the control force of the active control actuator 8, which is installed between the upper structure 4 and the lower structure 5 and is used to apply active control force to the vibration system, represents the displacement of the superstructure 4, represents the displacement of the lower structure 5; The control force of the active control actuator 8 is calculated by the impedance control algorithm. Its expression is related to the selected impedance parameter. Its Laplace transform expression is: ; in, represents the stiffness coefficient in the impedance parameter, represents the damping coefficient in the impedance parameter, represents the inertia coefficient in the impedance parameter, represents the complex frequency domain variable; for the convenience of expression, is called the impedance stiffness coefficient, is called the impedance damping coefficient, It is called the impedance inertia coefficient; Analyze the transfer function and divide the frequency band between the frequency points where performance conflicts exist; in some embodiments, by changing the different impedance stiffness coefficients , the impedance damping coefficient and the impedance inertia coefficient , the responses of the different vibration systems can be obtained and analyzed; like Figure 4 The following are the amplitude-frequency characteristic curves of sprung mass acceleration with different impedance inertia coefficients. Figure 5 The following are the amplitude-frequency characteristics of the unsprung dynamic deformation for different impedance inertia coefficients. The arrow in the figure indicates an increase in the impedance inertia coefficient. It can be seen that within the frequency range below 1 Hz, the impedance inertia coefficient has little effect on the sprung mass acceleration. Within the frequency range of 1-8 Hz, the larger the impedance inertia coefficient, the smaller the sprung mass acceleration amplitude. In the frequency range of 8-12 Hz, the trend is the opposite: the smaller the impedance inertia coefficient, the smaller the sprung mass acceleration amplitude. Above 12 Hz, the impedance inertia coefficient has little effect on the unsprung dynamic deformation amplitude. Within the frequency range of 1-4 Hz, the larger the impedance inertia coefficient, the smaller the unsprung dynamic deformation amplitude. Within the frequency range of 4-14 Hz, the larger the impedance inertia coefficient, the larger the unsprung dynamic deformation amplitude. Above 14 Hz, the effect is minimal. like Figure 6The following are the amplitude-frequency characteristics of sprung mass acceleration for different impedance stiffness coefficients and impedance damping coefficients. The arrow in the figure indicates the increase of the impedance stiffness coefficient. It can be seen that as the impedance stiffness coefficient increases, the first-order resonance of the sprung mass acceleration mainly changes around 1 Hz; in the frequency range of 3-8 Hz, the amplitude minimum and its corresponding frequency both increase with the increase of the impedance stiffness coefficient; the second-order resonance frequency increases with the increase of the impedance stiffness coefficient, and the resonance amplitude decreases; in the frequency range below 1 Hz, the larger the impedance damping coefficient, the smaller the amplitude; in the frequency range of about 2-10 Hz, the smaller the impedance damping coefficient, the smaller the amplitude; near the second-order resonance frequency, the impedance damping coefficient and the amplitude are negatively correlated; in the frequency range above 12 Hz, the smaller the impedance damping coefficient, the smaller the amplitude; Figure 7 The following curves show the amplitude-frequency characteristics of unsprung dynamic deformation for different impedance stiffness coefficients and impedance damping coefficients. The arrows in the figure indicate an increase in the impedance stiffness coefficient. It can be seen that as the impedance stiffness coefficient increases, the first-order resonant frequency and amplitude of the unsprung dynamic deformation both increase, with the main changes occurring around 1 Hz. In the frequency range of 2-4 Hz, the minimum amplitude and its corresponding frequency increase with increasing impedance stiffness coefficient. In the frequency range above 9 Hz, the impedance stiffness coefficient has little effect. In the frequency range below 2 Hz, the amplitude decreases with increasing impedance damping coefficient. In the frequency range of approximately 2-8 Hz, the amplitude decreases with decreasing impedance damping coefficient. Near the second-order resonant frequency, the amplitude decreases with increasing impedance damping coefficient. Combined with the above analysis, the frequency band is divided into three segments: 0-4Hz, 4-15Hz and 15-25Hz; In some embodiments, based on preset vibration control performance requirements, an impedance parameter combination that satisfies a control effect is determined for each divided frequency band, and a frequency band parameter mapping table is established, wherein the mapping table represents a correspondence between frequency bands and impedance parameter combinations. To suppress vibrations of the vibration system and ensure stability of the vibration system, the preset vibration control performance requirements are that the sprung mass acceleration amplitude and the unsprung dynamic deformation amplitude be as small as possible. The impedance parameter combination selection strategy is as follows: within the 0-4 Hz frequency band, the amplitudes of both the sprung mass acceleration and the unsprung dynamic deformation are simultaneously suppressed, with a larger impedance inertia coefficient, a smaller impedance stiffness coefficient, and a medium impedance damping coefficient. Within the 4-15 Hz frequency band, the amplitude of the sprung mass acceleration is prioritized, with a smaller impedance inertia coefficient, a medium impedance stiffness coefficient, and a smaller impedance damping coefficient. Within the 15-25 Hz frequency band, the amplitude of the unsprung dynamic deformation is prioritized, with a larger impedance inertia coefficient, a larger impedance stiffness coefficient, and a smaller impedance damping coefficient. The specific frequency band parameter mapping table is shown in Table 1: Table 1 Frequency band parameter mapping table

[0011] The collected time-domain vibration signal is band-pass filtered, where the filtering range covers the effective operating frequency band of the vibration system, and then the filtered signal is subjected to outlier removal and sliding average processing; in some embodiments, the band-pass filter is a Chebyshev type I band-pass filter; and the window length used in the sliding average processing is 50 steps; The time domain signal after the sliding average processing is processed using an extended Kalman filter algorithm to obtain an estimated vibration main frequency of the vibration system; the extended Kalman filter algorithm includes a state space model, a state update rule of the extended Kalman filter algorithm cyclic iteration, and an observation noise matrix adaptively adjusted according to the signal-to-noise ratio. In some embodiments, the state space model includes a state vector, a state process function, a measurement variable, and a measurement function; the state vector is used to describe the state of the state space model at a certain moment, and its expression is: ; in, Indicates time, Indicates the duration of a step, Indicates the amplitude of the vibration process at the current moment, Indicates the amplitude of the vibration process at the last step, Indicates the frequency of the vibration process at the current moment, which is the main vibration frequency. Indicates the frequency of the vibration process at the last step, Represents the phase angle of the vibration process at the current moment, Indicates the phase angle of the vibration process at the last step, represents the state vector at the current moment, Represents the state vector No. A quantity, , Represents the sinusoidal component of the vibration displacement at the current moment, Represents the sinusoidal component of the vibration displacement at the last step, Represents the cosine component of the vibration displacement at the current moment, Represents the cosine component of the vibration displacement at the previous step, Indicates the main vibration frequency at the current moment; The state process function is used to describe the evolution process of the model state. Specifically, the state vector of the model at the current moment can be used to calculate the state vector at the next step. Its expression is: ; in, represents the state process function, Represents the state vector at the next step; The measured variable Represents the measurement value obtained by the sensor, which is defined as: ; The measurement function For establishing the measured variables With the state vector The relationship between them is expressed as: ; in, Representing the measurement function, rewritten in matrix form: ; in, represents the measurement matrix, whose dimension is , ; The state update rules of the extended Kalman filter algorithm cyclic iteration, in some embodiments, include a state transfer matrix update rule, a state vector estimate value update rule, an estimation error covariance matrix update rule and a Kalman gain matrix update rule; The state transfer matrix update rule is used to calculate the state transfer matrix at each moment , used to linearize the state process function , is the estimated value of the state vector The Jacobian matrix of is expressed as: ; in, represents the state transition matrix, represents the estimated value of the state vector at the current moment, Represents the estimated value of the state vector No. A quantity, ; The state vector estimated value update rule is used to calculate the state vector estimated value at each moment, and its expression is: ; in, represents the estimated value of the state vector at the last step, represents the measurement matrix, whose dimension is , Represents the state process function at the previous step, whose input is the estimated value of the state vector at the previous step , Represents the Kalman gain matrix at the last step, whose dimension is , Indicates the measurement value at the current moment; The estimation error covariance matrix update rule is used to calculate the estimation error covariance matrix at each moment, and its expression is: ; in, represents the identity matrix, whose dimensions are , represents the Kalman gain matrix at the current moment, represents the measurement matrix, Represents the estimated error covariance matrix at the current moment, whose dimension is , Represents the estimated error covariance matrix at the next step, represents the transposed matrix of the state transition matrix, Represents the process noise variance matrix at the current moment, and its dimension is ; The Kalman gain matrix update rule is used to calculate the Kalman gain matrix at each moment, and its expression is: ; in, represents the Kalman gain matrix at the next step, Represents the estimated error covariance matrix at the next step, represents the measurement matrix, represents the transpose of the measurement matrix, Represents the measurement noise variance matrix at the current moment, and its dimension is ; According to the calculated state vector estimate Get the estimated value of the main vibration frequency , the expression is: ; in, Indicates the estimated value of the main vibration frequency at the current moment, represents the estimated value of the state vector The fifth component of The measurement noise variance matrix is ​​adaptively adjusted according to the signal-to-noise ratio In some embodiments, the method includes calculating the vibration main frequency estimation error, calculating the estimation error of the measurement variable, calculating the signal-to-noise ratio, and adjusting the measurement noise variance matrix. ; Calculate the vibration main frequency estimation error The expression is: ; in, Represents the vibration main frequency estimation error, which is the difference between the two vibration main frequency estimates. Indicates the duration of a step, Indicates the estimated value of the main vibration frequency at the current moment, Indicates the estimated value of the main vibration frequency at the last step; The expression for calculating the estimated error of the measured variable is: ; in, represents the estimated error of the measured variable, represents the estimated value of the state vector The first component of represents the sinusoidal component of the vibration displacement at the current moment, Indicates the measurement value at the current moment; Based on the above two errors, calculate the signal-to-noise ratio , whose expression is: ; in, Indicates the signal-to-noise ratio of the signal at the current moment. In the above formula, the numerator represents the cumulative sum of squares of measurement errors, and the denominator represents the cumulative sum of squares of main frequency estimation errors, reflecting the relative strength between measurement noise and system process noise; Let the process noise variance matrix If is a known constant matrix, the measurement noise variance matrix at the current moment is adaptively adjusted according to the following formula: ; in, represents the measurement noise variance matrix at the current moment, represents the process noise variance matrix, Indicates the signal-to-noise ratio at the current moment; Based on the frequency band parameter mapping table, find the estimated value of the main vibration frequency Matched impedance parameters, including impedance stiffness coefficient , impedance damping coefficient and impedance inertia coefficient ; Real-time acquisition of displacement differences of vibration systems ,speed and acceleration In some embodiments, the displacement difference is the relative displacement between the upper structure 4 and the lower structure 5, the speed is the relative speed between the upper structure 4 and the lower structure 5, the acceleration Relative acceleration between the upper structure 4 and the lower structure 5; Based on the impedance parameters and the collected displacement difference ,speed and acceleration , the target control force is calculated by the following formula : ; By formula , calculate the target current instruction ,in is the torque coefficient of the motor, in units of , which represents the ratio of the motor output torque to the input current; The current loop PID control drives the motor to output torque, which is converted into the target control force through the transmission mechanism. , applied to the vibration system to achieve variable impedance vibration control.

[0012] like Figure 2 As shown, the present invention provides a variable impedance vibration control system based on vibration main frequency estimation, including a sensor, a processor, a driver, a motor and a transmission mechanism; the sensor is used to collect vibration signals of the vibration system and send the collected vibration signals to the processor; the processor stores a preset frequency band parameter mapping table, and the processor uses a signal conditioning algorithm, an extended Kalman filter algorithm and an adaptive noise matrix adjustment algorithm to process the collected vibration signal to obtain an estimated value of the vibration main frequency of the vibration system, and determines the corresponding impedance parameters according to the estimated value of the vibration main frequency and the frequency band parameter mapping table, and the impedance parameters include an impedance stiffness coefficient , impedance damping coefficient and impedance inertia coefficient , and according to the impedance parameters and the displacement difference of the vibration system ,speed and acceleration Information, through the formula Calculate the target control force , the processor controls the force according to the target , calculate the target current command of the motor The driver is based on the target current instruction , drives the motor to output torque, and the transmission mechanism converts the motor torque into the target control force that matches the vibration direction of the vibration system applied to the vibration system to achieve real-time frequency-domain adaptive vibration control.

[0013] In some embodiments, the sensor includes an acceleration sensor and a displacement sensor, the acceleration sensor is used to collect acceleration signals of the vibration system, and the displacement sensor is used to collect displacement signals of the vibration system.

[0014] In some embodiments, as Figure 2 The control method block diagram shown in FIG5 shows that the processor includes a signal conditioning module, a frequency domain estimation module, an impedance mapping module, a force generation module, and a current generation module; the signal conditioning module is used to receive acceleration sensor and displacement sensor signals, perform filtering and smoothing conditioning operations on them, and output the conditioned sensor signals; the frequency domain estimation module is used to output a real-time vibration main frequency estimation value. The impedance mapping module is used to output impedance parameters according to a preset frequency band parameter mapping table; the force generation module calculates the target control force based on the selected impedance parameters And output, the current generating module is used to receive the target control force , calculate the target control current instruction .

[0015] In some embodiments, the frequency domain estimation module includes an extended Kalman filter module and an adaptive noise matrix adjustment module, wherein the adaptive noise matrix adjustment module is used to receive the estimated state at the previous moment and the measurement signal at the current moment, and output the estimated noise matrix at the current moment; the extended Kalman filter module is used to receive the measurement signal at the current moment and the estimated noise matrix, and output the estimated value of the vibration main frequency at the current moment. .

[0016] like Figure 8 As shown in FIG, under the input of swept-frequency sinusoidal displacement disturbance, the root mean square value of the sprung mass acceleration of the variable impedance vibration control method of this embodiment is reduced by 28.2% compared with the passive vibration reduction, which is better than the traditional LQR control method. Figure 9 The amplitude-frequency characteristic curve of the sprung mass acceleration is further displayed (solid line), indicating that the amplitude of the sprung mass acceleration remains low within the operating frequency range of 0-25 Hz, verifying the effectiveness of real-time frequency identification and impedance parameter switching.

[0017] The above embodiment is only one embodiment of the present invention, not all, and cannot be used to limit the scope of protection of the present invention. Any equivalent changes or modifications made according to the spirit of the present invention should be included in the scope of protection of the present invention.

Claims

1. A variable impedance vibration control method based on vibration main frequency estimation, characterized in that: The following steps are involved: Install an acceleration sensor at the vibration part of the vibration system, and install a displacement sensor between the vibration part and the fixed base to collect the time domain vibration signal of the vibration system in real time. The sampling frequency should be no less than 2.5 times the maximum operating frequency of the system. Use the exciter to apply the target frequency band to the vibration system A broadband excitation signal, wherein the broadband excitation signal includes a linear sweep signal, a discrete multi-frequency synthesis signal and a pink noise signal, so as to excite the full-band response of the vibration system; collecting a response signal of the vibration system under the action of the broadband excitation signal, and extracting a transfer function of the vibration system based on a system identification method; Analyzing the transfer function and dividing the frequency band between frequency points where performance conflicts exist; According to the preset vibration control performance requirements, an impedance parameter combination that satisfies the control effect is determined for each divided frequency band, and a frequency band parameter mapping table is established, wherein the frequency band parameter mapping table represents the correspondence between the frequency bands and the impedance parameter combinations; The collected time-domain vibration signal is band-pass filtered, and the filtering range covers the effective working frequency band of the vibration system. Then, the filtered signal is subjected to outlier removal and sliding average processing; Using an extended Kalman filter algorithm to process the time domain signal after the sliding average processing, to obtain an estimated vibration main frequency of the vibration system; Based on the frequency band parameter mapping table, find the estimated value of the main vibration frequency Matched impedance parameters, including impedance stiffness coefficient , impedance damping coefficient and impedance inertia coefficient ; Real-time acquisition of displacement differences of vibration systems ,speed and acceleration ; Based on the impedance parameters and the collected displacement difference ,speed and acceleration , the target control force is calculated by the following formula : ； By formula , calculate the target current instruction ,in is the torque coefficient of the motor, in units of , which represents the ratio of the motor output torque to the input current; The output torque of the driving motor is controlled by the current loop PID, and the torque is converted into the target control force through the transmission mechanism. , applied to the vibration system to achieve variable impedance vibration control.

2. The variable impedance vibration control method based on vibration main frequency estimation according to claim 1, characterized in that: in, In the frequency band parameter mapping table, the impedance stiffness coefficient corresponding to the low frequency band 0-4Hz 15000N / m, impedance damping coefficient 1200Ns / m, impedance inertia coefficient 50kg; the impedance stiffness coefficient corresponding to the mid-frequency range of 4-15Hz is 18000N / m, impedance damping coefficient 800Ns / m, impedance inertia coefficient 30kg; the impedance stiffness coefficient corresponding to the high frequency band 15-25Hz 22000N / m, impedance damping coefficient 1500Ns / m, impedance inertia coefficient It is 70kg.

3. The variable impedance vibration control method based on vibration main frequency estimation according to claim 1, characterized in that: The extended Kalman filter algorithm is used to achieve real-time estimation of the main vibration frequency, including a state space model, a state update rule for the extended Kalman filter algorithm cyclic iteration, and an adaptive adjustment of the observation noise matrix according to the signal-to-noise ratio. .

4. The variable impedance vibration control method based on vibration main frequency estimation according to claim 3 is characterized in that: The state space model includes a state vector, a state process function, a measurement variable and a measurement function; The state vector is used to describe the state of the state space model at a certain moment, and its expression is: ； in, Indicates time, Indicates the duration of a step, Indicates the amplitude of the vibration process at the current moment, Indicates the amplitude of the vibration process at the last step, Indicates the frequency of the vibration process at the current moment, that is, the main frequency of vibration, Indicates the frequency of the vibration process at the last step, Represents the phase angle of the vibration process at the current moment, Indicates the phase angle of the vibration process at the last step, represents the state vector at the current moment, Represents the state vector No. A quantity, , Represents the sinusoidal component of the vibration displacement at the current moment, Represents the sinusoidal component of the vibration displacement at the last step, Represents the cosine component of the vibration displacement at the current moment, Represents the cosine component of the vibration displacement at the previous step, Indicates the main vibration frequency at the current moment; The state process function It is used to describe the evolution process of the model state, specifically to predict the state vector of the next step time through the state process function based on the state vector of the model at the current time. Its expression is: ； in, represents the state process function, Represents the state vector at the next step; The measured variable Represents the measurement value obtained by the sensor, which is defined as: ； The measurement function For establishing the measured variables With the state vector The relationship between them is expressed as: ； in, Representing the measurement function, rewritten in matrix form: ； in, represents the measurement matrix, whose dimension is , .

5. The variable impedance vibration control method based on vibration main frequency estimation according to claim 3, characterized in that: The state update rules of the extended Kalman filter algorithm cyclic iteration include a state transfer matrix update rule, a state vector estimate value update rule, an estimation error covariance matrix update rule and a Kalman gain matrix update rule; The state transfer matrix update rule is used to calculate the state transfer matrix at each moment , used to linearize the state process function , is the estimated value of the state vector The Jacobian matrix of is expressed as: ； in, represents the state transition matrix, represents the state process function, represents the estimated value of the state vector at the current moment, Represents the estimated value of the state vector No. A quantity, , Indicates time, Indicates the duration of a step; The state vector estimated value update rule is used to calculate the state vector estimated value at each moment, and its expression is: ； in, represents the estimated value of the state vector at the last step, represents the measurement matrix, whose dimension is , Represents the state process function at the previous step, whose input is the estimated value of the state vector at the previous step , Represents the Kalman gain matrix at the last step, whose dimension is , Indicates the measurement value at the current moment; The estimation error covariance matrix update rule is used to calculate the estimation error covariance matrix at each moment, and its expression is: ； in, represents the identity matrix, whose dimensions are , represents the Kalman gain matrix at the current moment, represents the measurement matrix, Represents the estimated error covariance matrix at the current moment, whose dimension is , Represents the estimated error covariance matrix at the next step, represents the transposed matrix of the state transition matrix, Represents the process noise variance matrix at the current moment, and its dimension is ; The Kalman gain matrix update rule is used to calculate the Kalman gain matrix at each moment, and its expression is: ； in, represents the Kalman gain matrix at the next step, Represents the estimated error covariance matrix at the next step, represents the measurement matrix, represents the transposed matrix of the measurement matrix, Represents the measurement noise variance matrix at the current moment, and its dimension is ; The state vector estimated value obtained by calculation Get the estimated value of the main vibration frequency , the expression is: ； in, Indicates the estimated value of the main vibration frequency at the current moment, represents the estimated value of the state vector The fifth component of .

6. The variable impedance vibration control method based on vibration main frequency estimation according to claim 3, characterized in that: The measurement noise variance matrix is ​​adaptively adjusted according to the signal-to-noise ratio , specifically including calculating the vibration main frequency estimation error, calculating the measurement variable estimation error, calculating the signal-to-noise ratio and adjusting the measurement noise variance matrix ; Calculate the vibration main frequency estimation error The expression is: ； in, Represents the vibration main frequency estimation error, which is the difference between the two vibration main frequency estimates. Indicates the duration of a step, Indicates the estimated value of the main vibration frequency at the current moment, Indicates the estimated value of the main vibration frequency at the last step; The expression for calculating the estimated error of the measured variable is: ； in, represents the estimated error of the measured variable, represents the estimated value of the state vector The first component of represents the sinusoidal component of the vibration displacement at the current moment, Indicates the measurement value at the current moment; Based on the above two errors, calculate the signal-to-noise ratio , whose expression is: ； in, Indicates the signal-to-noise ratio of the signal at the current moment. In the above formula, the numerator represents the cumulative sum of squares of measurement errors, and the denominator represents the cumulative sum of squares of main frequency estimation errors, reflecting the relative strength between measurement noise and system process noise; Let the process noise variance matrix If is a known constant matrix, the measurement noise variance matrix at the current moment is adaptively adjusted according to the following formula: ； in, represents the measurement noise variance matrix at the current moment, represents the process noise variance matrix, Indicates the signal-to-noise ratio at the current moment.

7. A variable impedance vibration control system based on vibration main frequency estimation, characterized in that: The system comprises a sensor, a processor, a driver, a motor and a transmission mechanism; the sensor is used to collect vibration signals of a vibration system and send the collected vibration signals to the processor; a preset frequency band parameter mapping table is stored in the processor, and the processor uses a signal conditioning algorithm, an extended Kalman filter algorithm and an adaptive noise matrix adjustment algorithm to process the collected vibration signals to obtain an estimated value of the vibration main frequency of the vibration system, and determines the corresponding impedance parameters according to the estimated value of the vibration main frequency and the frequency band parameter mapping table, wherein the impedance parameters include an impedance stiffness coefficient , impedance damping coefficient and impedance inertia coefficient , and according to the impedance parameters and the displacement difference of the vibration system ,speed and acceleration Information, through the formula Calculate the target control force , the processor controls the force according to the target , calculate the target current command of the motor The driver is based on the target current instruction , drives the motor to output torque, and the transmission mechanism converts the motor torque into the target control force that matches the vibration direction of the vibration system applied to the vibration system to achieve real-time frequency-domain adaptive vibration control.

8. The variable impedance vibration control system based on vibration main frequency estimation according to claim 7, characterized in that: The sensor includes an acceleration sensor and a displacement sensor. The acceleration sensor is used to collect acceleration signals of the vibration system, and the displacement sensor is used to collect displacement signals of the vibration system.

9. The variable impedance vibration control system based on vibration main frequency estimation according to claim 7, characterized in that: The processor includes a signal conditioning module, a frequency domain estimation module, an impedance mapping module, a force generation module, and a current generation module; the signal conditioning module is used to receive acceleration sensor and displacement sensor signals, perform filtering and smoothing conditioning operations on them, and output the conditioned sensor signals; the frequency domain estimation module is used to output a real-time vibration main frequency estimation value The impedance mapping module is used to output impedance parameters according to a preset frequency band parameter mapping table; the force generation module calculates the target control force based on the selected impedance parameters And output; the current generating module is used to receive the target control force , calculate the target current instruction .

10. The variable impedance vibration control system based on vibration main frequency estimation according to claim 9, characterized in that: The frequency domain estimation module also includes an extended Kalman filter module and an adaptive noise matrix adjustment module. The adaptive noise matrix adjustment module is used to receive the estimated state at the previous moment and the measurement signal at the current moment, and output the estimated noise matrix at the current moment. The extended Kalman filter module is used to receive the measurement signal at the current moment and the estimated noise matrix, and output the estimated value of the vibration main frequency at the current moment. .

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