Piezoelectric MEMS planar traveling wave resonator driving method based on embedded feedback electrode

Abstract

A piezoelectric MEMS planar traveling wave resonator driving method based on an embedded feedback electrode relates to the technical field of traveling wave microactuators, and comprises the following steps: applying a preset input driving signal to a resonant device; collecting the output signals of the driving electrodes and the output signals of the isolated electrodes for multiple times, and calculating the phase difference between the two signals in sequence; taking an average value of the phase differences and comparing the average value with the initial phase difference; if the average phase difference is equal to the initial phase difference, the frequency of the input driving signal is kept unchanged; if the average phase difference is smaller than the initial phase difference, the frequency of the input driving signal is adjusted until the output phase difference is equal to the initial phase difference, and the frequency of the input driving signal is kept; if the average phase difference is larger than the initial phase difference, the frequency of the input driving signal is adjusted until the output phase difference is equal to the initial phase difference, and the frequency of the input driving signal is kept, and the problems that in a traditional resonator driving method, the precision of monitoring the resonance state is low, and the device structure is complex are solved.

Description

Technical Field

[0001] This invention relates to the field of traveling wave micro-actuator technology, and more specifically to a driving method for a piezoelectric MEMS planar traveling wave resonator based on an embedded feedback electrode. Background Technology

[0002] Piezoelectric MEMS planar traveling wave resonators are key actuators fabricated using microelectromechanical systems (MEMS) technology. They generate two standing waves by arranging periodic driving electrodes on a planar piezoelectric material and inputting multiple AC signals with a specific phase difference, which then superimpose to form a traveling wave. This traveling wave drives "particles" on the material surface to undergo elliptical motion, thereby outputting torque through friction. It is widely used in cutting-edge fields such as precision actuation, microrobotics, and optical calibration.

[0003] To ensure driving performance, the frequency of the input driving signal must always remain consistent with the mechanical resonant frequency of the device structure. In this resonant state, the traveling wave amplitude is at its maximum, the modes are most complete, and thus the maximum driving torque is output. However, in practical applications, factors such as load variations, ambient temperature fluctuations, or device aging can all alter the equivalent stiffness of the resonator structure, causing its resonant frequency to drift. If the driving frequency is not adjusted in real time, it will lead to attenuation of the traveling wave amplitude and mode distortion, ultimately resulting in a decrease in output torque and a deterioration in operational stability and reliability.

[0004] Therefore, achieving real-time tracking of the resonant frequency and adaptive adjustment of the driving frequency is the key to improving the performance of piezoelectric planar traveling wave resonators. Currently, those skilled in the art are mainly committed to solving this problem by integrating monitoring structures and feedback control circuits.

[0005] In the prior art, a mainstream approach is to use an isolated electrode (lone pole) embedded in the device to monitor vibration status. For example, Chinese patent CN111952433A discloses an isolated pole structure for a piezoelectric traveling wave micro actuator. This structure proposes to place an isolated pole between the driving electrode and the fixed support beam for in-situ detection of the traveling wave state. However, the deformation amplitude of the piezoelectric material at this location is much smaller than that in the central region of the driving electrode, resulting in a weak output signal from the isolated pole, a low signal-to-noise ratio, and difficulty in accurately extracting the frequency and phase characteristics of the signal, thus limiting the accuracy of subsequent feedback control.

[0006] Another publication, CN117460390A, discloses a monitoring structure and design method for a piezoelectric planar driver based on embedded solitaires. This method achieves feedback control by arranging multiple solitaires within the intervals of multiple driving electrodes and comprehensively comparing the amplitude and phase difference of their output signals. Although this method can improve the integrity of traveling waves, it also brings significant drawbacks: First, the multiple solitaire structure increases the design complexity and process difficulty of MEMS devices, thereby increasing manufacturing costs. Second, the increased number of solitaires encroaches on the effective area of ​​the driving electrodes in a limited plane, which may lead to a decrease in the driver's output capability. Finally, the back-end processing circuit needs to process multiple signals and perform complex calculations simultaneously, which greatly increases the complexity and cost of the system.

[0007] In addition, there are external monitoring methods such as laser vibration measurement, which can accurately measure the amplitude, but require the integration of additional optical components, resulting in a large system size and increased power consumption, which contradicts the original intention of miniaturization and integration of MEMS devices.

[0008] Therefore, we propose a resonator driving method that can achieve high-precision resonant state monitoring while maintaining the simplicity of the device structure and low cost. Summary of the Invention

[0009] The purpose of this invention is to provide a driving method for a piezoelectric MEMS planar traveling wave resonator based on an embedded feedback electrode, which solves the problems of low accuracy in monitoring the resonance state and complex device structure in traditional resonator driving methods.

[0010] This invention is achieved through the following technical solution: A driving method for a piezoelectric MEMS planar traveling wave resonator based on an embedded feedback electrode, specifically including: The isolated electrodes are sequentially distributed inside or between the driving electrode region, and the isolated electrodes and the driving electrode have a fixed phase difference. A preset input drive signal is applied to the piezoelectric MEMS planar traveling wave resonator; The output signals of the driving electrode and the lone electrode are acquired multiple times, and their phase difference is calculated sequentially. Take the average of the phase differences calculated multiple times and compare it with the initial phase difference; If the average phase difference is equal to the initial phase difference, the frequency of the input drive signal remains unchanged. If the average phase difference is less than the initial phase difference, an adaptive PID feedback automatic adjustment algorithm is used to increase the frequency of the input drive signal until the phase difference between the output signal of the drive electrode and the output signal of the lone electrode is equal to the initial phase difference, and the frequency of the drive input signal is maintained. If the average phase difference is greater than the initial phase difference, an adaptive PID feedback automatic adjustment algorithm is used to reduce the frequency of the input drive signal until the phase difference between the output signal of the drive electrode and the output signal of the lone electrode is equal to the initial phase difference, and the frequency of the drive input signal is maintained.

[0011] Furthermore, the initial phase difference is .

[0012] Furthermore, the adaptive PID feedback automatic adjustment algorithm specifically includes: When the phase difference between the lone electrode output signal and the drive electrode output signal is equal to the initial phase difference, the corresponding frequency information is written into the PID controller; The circuit controller receives the output of the PID controller, then changes the frequency of the drive input signal, and uses an AD acquisition circuit to acquire the phase difference between the lone pole output signal and the drive electrode output signal in real time. Determine the magnitude of the acquired phase difference compared to the initial phase difference; If the acquired phase difference is greater than the initial phase difference, the frequency increases; if the acquired phase difference is less than the initial phase difference, the frequency decreases. The least squares method is used to estimate the parameters of the acquired phase difference to obtain the estimated phase difference value; The difference between the estimated phase difference and the initial phase difference is used as a measure of the error. The internal parameters of the PID controller are adjusted using the error metric and frequency direction. The adjusted internal parameters of the PID controller are returned to the circuit controller for iterative processing until the phase difference between the real-time acquired lone pole output signal and the drive electrode output signal equals the initial phase difference.

[0013] Furthermore, the step of using the least squares method to estimate the parameters of the acquired phase difference to obtain the estimated phase difference value specifically includes: The resonator system is modeled as a dynamic model in discrete time. Rewrite the dynamic model in vector form; By collecting observation data from the most recent N time points, a data matrix and observation vector are constructed. The parameter vector is estimated by minimizing the sum of squared errors.

[0014] Furthermore, the resonator system is modeled as a dynamic model in discrete time, and the specific formula is as follows:

[0015] In the formula, It is in the The phase difference actually collected and calculated at each sampling time; It is in the The amount of drive frequency adjustment applied at each moment; and These are the system model parameters that need to be estimated; It is modeling noise.

[0016] Furthermore, the dynamic model is rewritten in vector form, specifically using the following formula:

[0017] In the formula, It is the parameter vector to be estimated. It is a data vector.

[0018] Furthermore, by collecting observation data from the most recent N time points, a data matrix and an observation vector are constructed, specifically using the following formula:

[0019]

[0020] In the formula, It is a data matrix. It is the observation vector.

[0021] Furthermore, the method of minimizing the sum of squared errors to obtain the estimated value of the parameter vector is specifically formulated as follows:

[0022] and This is an estimate of the parameter vector.

[0023] Furthermore, adjusting the internal parameters of the PID controller using the error metric and frequency direction specifically includes: Performance metrics are constructed based on the error measurement values; Use gradient descent to optimize performance metrics and obtain performance gradients; Define the direction constraint function based on the frequency direction; Calculate the gradient of the constraint function to obtain the constraint gradient; The PID parameters are updated by combining the performance gradient and the constraint gradient.

[0024] Furthermore, this driving method also includes: Detect whether the held drive input signal has changed; If a change occurs, the changed drive input signal is reapplied to the piezoelectric MEMS planar traveling wave resonator. Then repeat the steps of acquiring, calculating, and judging the input drive signal and the isolated output signal.

[0025] The technical solution of the present invention has at least the following advantages and beneficial effects: This invention discloses a driving method for a piezoelectric MEMS planar traveling wave resonator based on an embedded feedback electrode. By arranging the lone pole inside or in the gap of the driving electrode, making it closer to the region of maximum traveling wave amplitude, the amplitude and signal-to-noise ratio of the lone pole output signal are significantly improved. Closed-loop control can be achieved with only one or a few lone poles with a fixed phase difference. While ensuring performance, this greatly reduces the manufacturing cost of the MEMS resonator and the implementation cost of the control system.

[0026] By grouping the isolated electrodes within the drive electrodes and their gaps, an optimized layout of monitoring points was achieved, further ensuring signal quality. Simultaneously, the initial phase difference was explicitly set to... This provides a clear and stable frequency locking target for frequency locking control, ensuring that the driver can operate stably in the optimal resonant state and output maximum torque.

[0027] In addition, the introduced adaptive PID feedback automatic adjustment algorithm, combined with the least squares method for online estimation of system parameters, can dynamically optimize the controller parameters. This enables the system to not only quickly determine the direction of frequency adjustment, but also to adapt to changes in the dynamic characteristics of the resonator, achieving fast and stable frequency tracking. It also exhibits strong robustness to load changes and environmental interference, significantly improving the dynamic performance and long-term stability of the driver.

[0028] Furthermore, by continuously monitoring the drive status and restarting the adjustment process when lockout occurs, a closed-loop feedback mechanism is established throughout the entire working period, ensuring that the traveling wave resonator can always automatically maintain a high-performance operating state when facing continuously changing operating conditions. Attached Figure Description

[0029] Figure 1 This is a schematic diagram of the driving method for a piezoelectric MEMS planar traveling wave resonator based on an embedded feedback electrode according to the present invention. Figure 2 This is a schematic diagram of the driving electrode distribution structure in this invention; Figure 3 This is a schematic diagram of the isolated pole distribution structure in this invention. Detailed Implementation

[0030] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0031] Example 1 like Figure 1 The method shown is a driving method for a piezoelectric MEMS planar traveling wave resonator based on an embedded feedback electrode, which specifically includes: The isolated electrodes are sequentially distributed inside or between the driving electrode region, and the isolated electrodes and the driving electrode have a fixed phase difference. The arrangement of the driving electrode and the lone electrode is as follows: Figure 2 As shown, specifically: The driving electrodes are configured as multiple electrodes, which are evenly spaced along the center of the piezoelectric MEMS planar traveling wave resonator, and are arranged in groups of four. Each group of four driving electrodes has a 90° phase difference between them, and the adjustable parameters of the phase difference are frequency and amplitude; and by... and Applying an electrical signal can induce a standing wave, and simultaneously... and Applying an electrical signal can excite another standing wave. The two standing waves have the same amplitude and frequency, and when they are superimposed, they form a traveling wave with double the amplitude. The traveling wave drives the load to move and outputs an electrode driving signal. When the frequency of the driving electrical signal matches the resonant frequency of the driver structure, a resonance effect can be generated, the amplitude is greatly amplified, and a large output torque is generated. However, due to changes in the load characteristics of the driving electrodes or interference from the external environment, the stiffness and other parameters of the resonator structure will be affected, thereby changing the resonant frequency of the structure and causing the resonance effect to disappear. Under the same driving signal, the output torque of the driver will decrease. It is important to note that Figure 2 The color of the driving electrode is yellow. Figure 3 The color of the middle pole is green. Since the vibration deformation generated by the traveling wave is converted into an electrical signal through the piezoelectric effect and output through the solenoid, the magnitude of this output signal is directly related to the magnitude of the deformation (the amplitude of the traveling wave). Therefore, the output signal of the solenoid is a sinusoidal signal with the same frequency as the traveling wave; thus, different solenoid positions can be designed, such as... Figure 3 At points a, b, c, and d shown, the four solitary poles are located at... Inside the driving electrode and gap, Internal and and gap; When a traveling wave is excited, the wave crest reaches... At the driving electrode, lone electrode a is also at a peak, while lone electrode b is in a horizontal position, lone electrode c is at a trough, and lone electrode d is in a horizontal position; after a quarter wavelength, The driving electrode is in a horizontal position, while lone electrode a is in a horizontal position, lone electrode b is at a crest, lone electrode c is horizontal, and lone electrode d is at a trough; therefore, Figure 3 The output signals of the isolated poles a, b, c, and d at different distribution positions in the structure have fixed phase differences with the output signals of the driving electrodes, which are 0°, -45°, -90°, and -135°, respectively. Based on the phase difference relationship between the forced vibration input drive and the vibration at different frequencies, it can be concluded that when the input drive frequency is less than the resonant frequency of the structure, the phase differences between the driving signal and the isolated poles a, b, c, and d are 0°, -45°, -90°, and -135°, respectively; when the input drive frequency is greater than the resonant frequency of the structure, the phase differences between the driving signal and the isolated poles a, b, c, and d are 180°, 135°, 90°, and 45°, respectively; and when the input drive frequency is equal to the resonant frequency of the structure, the phase differences between the driving signal and the isolated poles a, b, c, and d are 90°, 45°, 0°, and -45°, respectively.

[0032] Based on the above principle, the phase difference between the isolated output signal and the input drive signal at a specific position can be calculated to determine whether the frequency of the input drive signal is less than, greater than, or equal to the resonant frequency of the resonator. Adjusting the input drive signal frequency based on the calculation result, then recalculating the phase difference, and adjusting the input drive signal frequency again, repeating this process, will gradually bring the frequency of the input drive signal closer to the resonant frequency, causing the output torque of the traveling wave resonator to gradually reach its maximum value.

[0033] A preset input drive signal is applied to the piezoelectric MEMS planar traveling wave resonator; The output signals of the driving electrode and the lone electrode are acquired multiple times, and their phase difference is calculated sequentially. ; Take the average of the phase differences calculated multiple times and compare it with the initial phase difference; Specifically, the initial phase difference is ; If the average phase difference is equal to the initial phase difference, the frequency of the input drive signal remains unchanged. If the average phase difference is less than the initial phase difference, an adaptive PID feedback automatic adjustment algorithm is used to increase the frequency of the input drive signal until the phase difference between the output signal of the drive electrode and the output signal of the lone electrode is equal to the initial phase difference, and the frequency of the drive input signal is maintained. If the average phase difference is greater than the initial phase difference, an adaptive PID feedback automatic adjustment algorithm is used to reduce the frequency of the input drive signal until the phase difference between the output signal of the drive electrode and the output signal of the lone electrode is equal to the initial phase difference, and the frequency of the drive input signal is maintained.

[0034] Example 2 As one embodiment, the adaptive PID feedback automatic adjustment algorithm specifically includes: When the phase difference between the lone electrode output signal and the drive electrode output signal is equal to the initial phase difference, the corresponding frequency information is written into the PID controller; The output of the PID controller is a "control quantity". This "control quantity" is used to directly set or generate a new drive signal frequency. That is, the subsequent frequency generation unit obtains the corresponding adjusted frequency value based on the control quantity, and the adjusted input drive signal can be obtained based on the adjusted frequency value. The circuit controller receives the output of the PID controller, then changes the frequency of the drive input signal, and uses an AD acquisition circuit to acquire the phase difference between the lone pole output signal and the drive electrode output signal in real time. Determine the magnitude of the acquired phase difference compared to the initial phase difference; If the acquired phase difference is greater than the initial phase difference, the frequency increases; if the acquired phase difference is less than the initial phase difference, the frequency decreases. The least squares method is used to estimate the parameters of the acquired phase difference to obtain the estimated phase difference value, specifically including: The resonator system is modeled as a dynamic model in discrete time, and the calculation formula is as follows:

[0035] In the formula, It is in the The phase difference actually collected and calculated at each sampling time, i.e. ; It is in the The amount of drive frequency adjustment applied at each moment; and These are the system model parameters that need to be estimated; It is modeling noise; The dynamic model is rewritten in vector form, and the calculation formula is as follows:

[0036] In the formula, It is the parameter vector to be estimated. It is a data vector, composed of historical observation data; By collecting observation data from the most recent N time points Construct the data matrix and observation vector, and calculate them using the following formula:

[0037]

[0038] In the formula, It is a data matrix. It is the observation vector; The estimated values ​​of the parameter vector are obtained by minimizing the sum of squared errors. The calculation formula is as follows:

[0039] and These are estimates of the parameter vector; The difference between the estimated phase difference and the initial phase difference is used as a measure of the error. By utilizing the error metric and frequency direction, the internal parameters of the PID controller are adjusted, specifically including: Build performance metrics:

[0040] In the formula, , and These are the weighting coefficients. This is the squared error term; minimizing this term allows the system to quickly eliminate errors. Minimizing the squared term of the control quantity can prevent excessive control energy and thus have a smoothing effect. The square term of the rate of change of the control quantity can be minimized to make the control output smoother and reduce oscillations. Gradient descent is used to optimize performance metrics and obtain performance gradients. ; Define the direction constraint function based on the frequency direction:

[0041] In the formula, For the PID controller based on the current parameters The calculated frequency adjustment amount, This is the maximum permissible frequency adjustment, a safety limit; and the significance of this constraint function is that when the frequency adjustment direction is consistent with the direction of the control quantity, and When the value is less than the maximum value, the function value is positive, indicating encouragement; otherwise, it is negative, indicating punishment. This ensures that parameter adjustments do not cause the frequency to change drastically in the wrong direction. Calculate the constraint function with respect to parameters The gradient, i.e., the constraint gradient. ; The PID parameters are updated by combining the performance gradient and the constraint gradient:

[0042] In the formula, The new PID parameters for the next time step; These are the PID parameters at the current moment; The learning rate is an important hyperparameter that determines the step size for parameter updates. A step size that is too small will result in slow convergence, while a step size that is too large will lead to instability. The constraint weights are used to balance the importance of "pursuing optimal performance" and "obeying directional constraints".

[0043] The adjusted internal parameters of the PID controller are returned to the circuit controller for iterative processing until the phase difference between the real-time acquired lone electrode output signal and the drive electrode output signal equals the initial phase difference; that is, the updated PID parameters. The output is sent to the circuit controller, which then changes the frequency of the drive input signal. This alters the relationship between the lone pole output signal and the drive electrode output signal, causing their phase difference to change until the phase difference between the acquired lone pole output signal and the drive electrode output signal equals the initial phase difference. This indicates that the adjustment is complete, and the adjustment of the PID controller is finished.

[0044] Example 3 As one embodiment, this driving method further includes: Detect whether the held drive input signal has changed; If a change occurs, the changed drive input signal is reapplied to the M piezoelectric MEMS planar traveling wave resonator. Then repeat the steps of acquiring, calculating, and judging the input drive signal and the isolated output signal.

[0045] This step is a feedback step because, according to the scheme in Example 1, the output frequency of the resonator has been ensured to be such that the phase difference between the lone electrode output signal and the drive electrode output signal is equal to... The frequency of the resonator is constant, but when the resonant frequency changes due to load variations or environmental interference, the phase difference between the lone electrode output signal and the drive electrode output signal will no longer be constant. At this point, it is necessary to readjust the driving signal input to the MEMS piezoelectric plane resonator. The adjustment process involves repeatedly acquiring the output signals of the driving electrode and the lone electrode, and calculating their phase difference in turn. Take the average of the phase differences calculated multiple times and compare it with the initial phase difference; If the average phase difference is equal to the initial phase difference, the frequency of the input drive signal remains unchanged. If the average phase difference is less than the initial phase difference, an adaptive PID feedback automatic adjustment algorithm is used to increase the frequency of the input drive signal until the phase difference between the output signal of the drive electrode and the output signal of the lone electrode is equal to the initial phase difference, and the frequency of the drive input signal is maintained. If the average phase difference is greater than the initial phase difference, an adaptive PID feedback automatic adjustment algorithm is used to reduce the frequency of the input drive signal until the phase difference between the output signal of the drive electrode and the output signal of the lone electrode equals the initial phase difference, and the frequency of the drive input signal is maintained. These processes are described.

[0046] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A driving method for a piezoelectric MEMS planar traveling wave resonator based on an embedded feedback electrode, characterized in that, Specifically, it includes: The isolated electrodes are sequentially distributed inside or between the driving electrode region, and the isolated electrodes and the driving electrode have a fixed phase difference. A preset input drive signal is applied to the piezoelectric MEMS planar traveling wave resonator; The output signals of the driving electrode and the lone electrode are acquired multiple times, and their phase difference is calculated sequentially. Take the average of the phase differences calculated multiple times and compare it with the initial phase difference; If the average phase difference is equal to the initial phase difference, the frequency of the input drive signal remains unchanged. If the average phase difference is less than the initial phase difference, an adaptive PID feedback automatic adjustment algorithm is used to increase the frequency of the input drive signal until the phase difference between the output signal of the drive electrode and the output signal of the lone electrode is equal to the initial phase difference, and the frequency of the drive input signal is maintained. If the average phase difference is greater than the initial phase difference, an adaptive PID feedback automatic adjustment algorithm is used to reduce the frequency of the input drive signal until the phase difference between the output signal of the drive electrode and the output signal of the lone electrode is equal to the initial phase difference, and the frequency of the drive input signal is maintained.

2. The driving method for a piezoelectric MEMS planar traveling wave resonator based on an embedded feedback electrode according to claim 1, characterized in that: The initial phase difference is .

3. The driving method for a piezoelectric MEMS planar traveling wave resonator based on an embedded feedback electrode according to claim 1, characterized in that: The adaptive PID feedback automatic adjustment algorithm specifically includes: When the phase difference between the lone electrode output signal and the drive electrode output signal is equal to the initial phase difference, the corresponding frequency information is written into the PID controller; The circuit controller receives the output of the PID controller, then changes the frequency of the drive input signal, and uses an AD acquisition circuit to acquire the phase difference between the lone pole output signal and the drive electrode output signal in real time. Determine the magnitude of the acquired phase difference compared to the initial phase difference; If the acquired phase difference is greater than the initial phase difference, the frequency increases; if the acquired phase difference is less than the initial phase difference, the frequency decreases. The least squares method is used to estimate the parameters of the acquired phase difference to obtain the estimated phase difference value; The difference between the estimated phase difference and the initial phase difference is used as a measure of the error. The internal parameters of the PID controller are adjusted using the error metric and frequency direction. The adjusted internal parameters of the PID controller are returned to the circuit controller for iterative processing until the phase difference between the real-time acquired lone pole output signal and the drive electrode output signal equals the initial phase difference.

4. The driving method for a piezoelectric MEMS planar traveling wave resonator based on an embedded feedback electrode according to claim 3, characterized in that: The step of using the least squares method to estimate the parameters of the acquired phase difference to obtain the estimated phase difference value specifically includes: The resonator system is modeled as a dynamic model in discrete time. Rewrite the dynamic model in vector form; By collecting observation data from the most recent N time points, a data matrix and observation vector are constructed. The parameter vector is estimated by minimizing the sum of squared errors.

5. The driving method for a piezoelectric MEMS planar traveling wave resonator based on an embedded feedback electrode according to claim 4, characterized in that: The resonator system is modeled as a dynamic model in discrete time, and the specific formula is as follows: In the formula, It is in the The phase difference actually collected and calculated at each sampling time; It is in the The amount of drive frequency adjustment applied at each moment; and These are the system model parameters that need to be estimated; It is modeling noise.

6. The driving method for a piezoelectric MEMS planar traveling wave resonator based on an embedded feedback electrode according to claim 5, characterized in that: The specific formula for rewriting the dynamic model in vector form is as follows: In the formula, It is the parameter vector to be estimated. It is a data vector.

7. The driving method for a piezoelectric MEMS planar traveling wave resonator based on an embedded feedback electrode according to claim 6, characterized in that: The process involves collecting observation data from the most recent N time points to construct a data matrix and an observation vector, using the following formula: In the formula, It is a data matrix. It is the observation vector.

8. The driving method for a piezoelectric MEMS planar traveling wave resonator based on an embedded feedback electrode according to claim 7, characterized in that: The method of minimizing the sum of squared errors to obtain the estimated value of the parameter vector is specifically formulated as follows: and This is an estimate of the parameter vector.

9. The driving method for a piezoelectric MEMS planar traveling wave resonator based on an embedded feedback electrode according to claim 3, characterized in that: The method of adjusting the internal parameters of the PID controller using the error metric and frequency direction specifically includes: Performance metrics are constructed based on the error measurement values; Use gradient descent to optimize performance metrics and obtain performance gradients; Define the direction constraint function based on the frequency direction; Calculate the gradient of the constraint function to obtain the constraint gradient; The PID parameters are updated by combining the performance gradient and the constraint gradient.

10. The driving method for a piezoelectric MEMS planar traveling wave resonator based on an embedded feedback electrode according to claim 1, characterized in that: This driving method also includes: Detect whether the held drive input signal has changed; If a change occurs, the changed drive input signal is reapplied to the piezoelectric MEMS planar traveling wave resonator. Then repeat the steps of acquiring, calculating, and judging the input drive signal and the isolated output signal.

Images