High-voltage servo driver control method and system based on intelligent efficient control algorithm

Abstract

The invention belongs to the technical field of servo drivers, and particularly relates to a high-voltage servo driver control method and system based on an intelligent efficient control algorithm, and the method comprises the steps: collecting a DC bus voltage value and power grid voltage fluctuation data in real time, and predicting the influence quantity of the power grid voltage fluctuation on the DC bus voltage in a future preset time interval; and dynamically adjusting a proportion coefficient of PID control, calculating an integral value and a differential value of an error signal, and finally generating an optimized control signal to adjust the output current of the driver, thereby realizing closed-loop control. The method not only can effectively compensate the adverse effect of the power grid voltage fluctuation on the servo driver and improve the position control precision, but also simplifies the system design and reduces the cost. Therefore, the invention provides a solution which is more stable, accurate, economical and efficient, and is particularly suitable for industrial application environments with higher requirements on position control.

Description

Technical Field

[0001] The present invention belongs to the technical field of servo drivers, and particularly relates to a control method and system for a high-voltage servo driver based on an intelligent and efficient control algorithm. Background Art

[0002] In the field of industrial automation, high-voltage DC servo drivers are widely used in application scenarios of precise position control. Traditionally, these drivers rely on the PID (Proportional-Integral-Derivative) control algorithm to achieve precise control of the motor. However, with the increasing complexity of application scenarios, especially in an environment with frequent grid voltage fluctuations, the traditional PID control method has exposed some deficiencies. The main problem is that when the AC grid voltage fluctuates, it will cause the instability of the DC bus voltage, which in turn affects the position control accuracy of the servo driver. Since it is difficult to completely avoid the grid voltage fluctuations, how to effectively compensate for the impact of such fluctuations on the servo driver has become an urgent technical problem to be solved.

[0003] The prior art usually uses fixed PID parameters for control, which cannot adapt to the dynamic changes brought by grid voltage fluctuations in real time, resulting in a decrease in position control accuracy. In addition, the existing improvement schemes often increase the complexity and cost of the system, and at the same time fail to fully consider the impact of grid voltage fluctuations on the performance of the control system in the future for a period of time. Summary of the Invention

[0004] The purpose of the present invention is to provide a control method and system for a high-voltage servo driver based on an intelligent and efficient control algorithm, which can not only effectively compensate for the adverse effects of grid voltage fluctuations on the servo driver, improve the position control accuracy, but also simplify the system design and reduce the cost, so as to solve the problems proposed in the above background art.

[0005] To achieve the above purpose, the present invention adopts the following technical solutions: A control method for a high-voltage servo driver based on an intelligent and efficient control algorithm, comprising the following steps: Real-time collect the DC bus voltage value of the high-voltage servo driver and the grid voltage fluctuation data to obtain real-time data, and based on the real-time data, calculate the deviation value between the DC bus voltage at the current moment and the target value as the error signal; According to the grid voltage fluctuation data, predict the influence amount of the grid voltage fluctuation on the DC bus voltage within a preset time interval in the future; Based on the error signal and the influence amount, dynamically adjust the proportional coefficient of the PID control, and use the error signal to calculate the integral value of the error signal, and the calculation coefficient of the integral value is associated with the proportional coefficient; Calculate the differential value of the error signal based on the current change rate of the error signal; Add the proportional coefficient, integral value, and differential value to generate the control signal of the driver, and adjust the output current of the driver according to the control signal to complete the closed-loop control.

[0006] Preferably, the method for real-time collecting the DC bus voltage value and grid voltage fluctuation data of the high-voltage servo driver to obtain real-time data includes: Synchronously collect the DC bus voltage value V_m and the grid voltage fluctuation amplitude ΔV through a voltage sensor, and set the sampling frequency to f_s; Perform a sliding window filtering process on the V_m and ΔV, and the calculation formula is: V_filtered=(V_m1+V_m2+...+V_mk) / k, where k is the number of sampling points within the sliding window; Based on the V_filtered and ΔV, calculate the weighted fusion value V_fuse=V_filtered*(1-α)+ΔV*α, where α is a preset weight coefficient; Combine the V_fuse with the grid voltage fluctuation data ΔV to form the real-time data.

[0007] Preferably, based on the real-time data, calculating the deviation value between the current DC bus voltage and the target value as the error signal includes: Extract the current DC bus voltage value V_now and the preset target voltage value V_target from the real-time data; According to the V_now and V_target, calculate the initial error E_initial=V_target-V_now; Apply the proportional adjustment factor K_p to the E_initial, and calculate the corrected error signal E_corrected=E_initial*K_p; Combine the E_corrected and the grid voltage fluctuation amplitude ΔV in the real-time data, and calculate the final error signal E_final=E_corrected+ΔV*K_p.

[0008] Preferably, according to the grid voltage fluctuation data, predicting the influence amount of the grid voltage fluctuation on the DC bus voltage within a preset future time interval includes: Extract the grid voltage fluctuation amplitude ΔV and the change rate R_ΔV from the real-time data; Based on the change rate R_ΔV, calculate the predicted value of the grid voltage fluctuation within the next t seconds ΔV_future=ΔV+R_ΔV*t, where t is the preset time interval; Calculate the impact on the DC bus voltage Impact = ΔV_future * K_conv by combining the ΔV_future and the DC bus voltage conversion coefficient K_conv; Add the Impact to the current value of the DC bus voltage V_now to obtain the predicted value of the adjusted DC bus voltage V_predict = V_now + Impact.

[0009] Preferably, based on the error signal and the impact, dynamically adjust the proportional coefficient of the PID control, including: Obtain data from the final error signal E_final and the impact, and calculate the comprehensive adjustment factor F_adj = E_final + Impact to reflect the influence of the error signal and the grid voltage fluctuation on the system; Adjust the initial proportional coefficient K_p0 according to the F_adj, and the new proportional coefficient K_p_new = K_p0 + F_adj * C_adj, where C_adj is an adjustment constant; Apply the K_p_new to the PID control link, update the control parameters, and calculate the output control signal U_out = K_p_new * E_final using the updated parameters.

[0010] Preferably, use the error signal to calculate the integral value of the error signal, and the calculation coefficient of the integral value is associated with the proportional coefficient, including: Obtain the error signal values {E_1, E_2,..., E_n} of consecutive n sampling points from the final error signal E_final; Based on the error signal values, calculate the cumulative error E_sum = E_1 + E_2 +... + E_n; According to the new proportional coefficient K_p_new, determine the integral adjustment coefficient I_adj = K_p_new * I_coef, where I_coef is a preset integral coefficient; Use the E_sum and I_adj to calculate the integral value of the error signal I_value = E_sum * I_adj.

[0011] Preferably, calculate the differential value of the error signal based on the current change rate of the error signal, including: Select the error signal values {E_t1, E_t2,..., E_tm} of consecutive m sampling points from the final error signal E_final; According to the error signal values, calculate the error change amount ΔE_i = E_ti - E_t(i - 1) between adjacent sampling points, where i is an integer from 2 to m; Based on the error change amount ΔE_i and the sampling time interval Δt, calculate the average change rate of the error signal R_avg = (ΔE_2 + ΔE_3 +... + ΔE_m) / ((m - 1)*Δt); Using the average change rate R_avg and the preset differential adjustment coefficient D_coef, calculate the differential value of the error signal D_value = R_avg*D_coef.

[0012] Preferably, add the proportional coefficient, the integral value, and the differential value to generate the control signal of the driver, including: Obtain values from the new proportional coefficient K_p_new, the integral value of the error signal I_value, and the differential value of the error signal D_value; Based on the K_p_new, I_value, and D_value, calculate the preliminary control signal U_prelim = K_p_new*E_final + I_value + D_value; Adjust the amplitude of the preliminary control signal U_prelim according to the system requirements, and apply the gain adjustment factor G_adj to obtain the adjusted control signal U_adjusted = U_prelim*G_adj; Send the U_adjusted as the final control signal to the high-voltage servo driver to adjust the output to achieve position control.

[0013] Preferably, adjust the output current of the driver according to the control signal to complete the closed-loop control, including: Obtain values from the final control signal U_adjusted; Based on the U_adjusted, calculate the change amount of the output current to be adjusted ΔI = U_adjusted / R_sense, where R_sense is the resistance value of the current detection resistor; Add the ΔI to the current output current I_current to obtain the target output current I_target = I_current + ΔI; Adjust the output current of the high-voltage servo driver according to the I_target, monitor the deviation between the actual position and the target position through the feedback loop, and update E_final using the deviation to achieve closed-loop control.

[0014] On the other hand, the present invention proposes a high-voltage servo driver control system based on an intelligent and efficient control algorithm, including: An error signal calculation module, configured to collect the DC bus voltage value of the high-voltage servo driver and the grid voltage fluctuation data in real time to obtain real-time data, and based on the real-time data, calculate the deviation value between the current DC bus voltage and the target value as the error signal; A future impact prediction module for predicting the impact of grid voltage fluctuations on the DC bus voltage within a preset future time interval based on the grid voltage fluctuation data; An integral calculation module for dynamically adjusting the proportional coefficient of PID control based on the error signal and the impact amount, calculating the integral value of the error signal using the error signal, and the calculation coefficient of the integral value being associated with the proportional coefficient; A differential value calculation module for calculating the differential value of the error signal based on the current change rate of the error signal; A closed-loop control module for adding the proportional coefficient, integral value, and differential value to generate a control signal for the driver, and adjusting the driver output current according to the control signal to complete closed-loop control.

[0015] Technical effects and advantages of the present invention: The control method and system of a high-voltage servo driver based on an intelligent and efficient control algorithm proposed by the present invention have the following advantages compared with the prior art: The present invention realizes closed-loop control by collecting the DC bus voltage value and grid voltage fluctuation data in real time, combining with predicting the impact of grid voltage fluctuations on the DC bus voltage within a preset future time interval, dynamically adjusting the proportional coefficient of PID control, calculating the integral value and differential value of the error signal, and finally generating an optimized control signal to adjust the driver output current. This method can not only effectively compensate for the adverse effects of grid voltage fluctuations on the servo driver, improve the position control accuracy, but also simplify the system design and reduce the cost. Therefore, the present invention provides a more stable, accurate, and cost-effective solution, which is particularly suitable for industrial application environments with high requirements for position control. Brief Description of the Drawings

[0016] Figure 1 It is a flowchart of the control method of a high-voltage servo driver based on an intelligent and efficient control algorithm of the present invention; Figure 2 It is a block diagram of the control system of a high-voltage servo driver based on an intelligent and efficient control algorithm of the present invention. Detailed Embodiments

[0017] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. The specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0018] The present invention provides as Figure 1A control method for a high-voltage servo driver based on an intelligent and efficient control algorithm is shown. It can not only effectively compensate for the adverse effects of grid voltage fluctuations on the servo driver, improve the position control accuracy, but also simplify the system design and reduce the cost, as follows: In this embodiment, the control method for a high-voltage servo driver based on an intelligent and efficient control algorithm includes the following steps: Step 1: Real-time collect the DC bus voltage value and grid voltage fluctuation data of the high-voltage servo driver to obtain real-time data; specifically including: Synchronously collect the DC bus voltage value V_m and the grid voltage fluctuation amplitude ΔV through a voltage sensor, and set a fixed sampling frequency f_s to ensure the continuity and reliability of the data; this synchronous collection method ensures that the instantaneous changes of the DC bus voltage and the grid voltage fluctuation can be accurately captured, providing high-quality basic data for subsequent data processing.

[0019] Perform a sliding window filtering process on the V_m and ΔV, and the calculation formula is: V_filtered=(V_m1+V_m2+...+V_mk) / k, where k is the number of sampling points within the sliding window; this formula is used to calculate the average value of all sampling points within a period of time (i.e., the sliding window) to smooth the noise in the original signal and reduce the influence of high-frequency interference on subsequent analysis.

[0020] Based on the V_filtered and ΔV, calculate the weighted fusion value V_fuse=V_filtered*(1-α)+ΔV*α, where α is a preset weight coefficient between 0 and 1, used to adjust the proportion between the filtering result of the DC bus voltage and the influence of the grid voltage fluctuation. This formula is used to reasonably combine the information from two sources to form a more comprehensive voltage evaluation value; Combine the V_fuse with the grid voltage fluctuation data ΔV to form the real-time data. The finally formed real-time data set not only contains the processed DC bus voltage information, but also includes the directly measured grid voltage fluctuation data.

[0021] Embodiment 1 Suppose there is a high-voltage servo drive system, whose normal operating range of the DC bus voltage is between 300V and 400V, and the grid voltage fluctuates frequently. To achieve stable control, the sampling frequency f_s=1000Hz is set, the sliding window size k=5 is selected, and the weight coefficient α=0.2.

[0022] First, obtain a set of sample data through a voltage sensor, such as: $V_{m1} = 310V$, $V_{m2} = 308V$, $V_{m3} = 312V$, $V_{m4} = 315V$, $V_{m5} = 313V$. At the same time, the measured amplitude of the grid voltage fluctuation $\Delta V = 5V$.

[0023] Next, calculate using the sliding window filtering formula: $V_{filtered}=(310 + 308 + 312 + 315 + 313) / 5 = 311.6V$.

[0024] Then, calculate using the weighted fusion formula: $V_{fuse}=311.6*0.8 + 5*0.2 = 249.28 + 1 = 250.28V$.

[0025] Finally, combine $V_{fuse}$ with the original grid voltage fluctuation data $\Delta V$ to form a complete real - time data set for the control system to use.

[0026] Step 2: Based on the real - time data, calculate the deviation value between the current DC bus voltage and the target value as the error signal; specifically including: Extract the current DC bus voltage value $V_{now}$ and the preset target voltage value $V_{target}$ from the real - time data; according to $V_{now}$ and $V_{target}$, calculate the initial error $E_{initial}=V_{target}-V_{now}$; this formula is used to calculate the difference between the current DC bus voltage and the desired voltage. This difference represents the immediate error of the system and is an important basis for adjusting the control strategy.

[0027] Apply the proportional regulation factor $K_p$ to $E_{initial}$ to amplify or reduce the influence degree of the error signal, and calculate the corrected error signal $E_{corrected}=E_{initial}*K_p$; this step enhances the response speed and strength of the system to the error by proportional regulation of the initial error.

[0028] Combine $E_{corrected}$ and the amplitude of the grid voltage fluctuation $\Delta V$ in the real - time data, and calculate the final error signal $E_{final}=E_{corrected}+\Delta V*K_p$. Incorporating the grid voltage fluctuation factor into the calculation of the error signal improves the adaptability and robustness of the system to external interference, and helps to achieve more accurate position control.

[0029] Example 2 Suppose a high - voltage servo drive system, and its target DC bus voltage $V_{target}$ is set to 350V. At a certain moment, the measured DC bus voltage value $V_{now}$ is 345V, the amplitude of the grid voltage fluctuation $\Delta V$ is 3V, and the proportional regulation factor $K_p$ is set to 2.

[0030] First, extract V_now = 345V and V_target = 350V from the real-time data.

[0031] Next, calculate the initial error E_initial = V_target - V_now = 350 - 345 = 5V.

[0032] Then, apply the proportional regulation factor K_p to calculate the corrected error signal E_corrected = E_initial * K_p = 5 * 2 = 10.

[0033] Finally, combine the grid voltage fluctuation amplitude ΔV to calculate the final error signal E_final = E_corrected + ΔV * K_p = 10 + 3 * 2 = 16.

[0034] Through the above steps, not only the initial error of the system is obtained, but also the influence of the grid voltage fluctuation on the system is considered, thus generating a comprehensive error signal.

[0035] Step 3: According to the grid voltage fluctuation data, predict the influence amount of the grid voltage fluctuation on the DC bus voltage within a preset future time interval; specifically including: Extract the grid voltage fluctuation amplitude ΔV and the change rate R_ΔV from the real-time data; based on the change rate R_ΔV, calculate the predicted value of the grid voltage fluctuation within the next t seconds ΔV_future = ΔV + R_ΔV * t, where t is the preset time interval; this formula is used to predict the grid voltage fluctuation situation within the next t seconds. By adding the current fluctuation amplitude ΔV and the change rate R_ΔV multiplied by the time interval t, the voltage fluctuation trend within a certain future period can be estimated.

[0036] Combine the ΔV_future and the DC bus voltage conversion coefficient K_conv to quantify the specific influence of the grid voltage fluctuation on the future DC bus voltage, and calculate the influence amount Impact = ΔV_future * K_conv; by multiplying the predicted fluctuation value ΔV_future by the conversion coefficient K_conv, the specific influence amount on the DC bus voltage can be obtained.

[0037] Add the Impact to the current value V_now of the DC bus voltage to obtain the predicted value V_predict of the adjusted DC bus voltage = V_now + Impact. This formula is used to calculate the predicted value of the adjusted DC bus voltage. By adding the current DC bus voltage value V_now and the predicted influence amount Impact, the predicted value of the DC bus voltage at a certain future moment can be obtained.

[0038] Example 3 Suppose a high-voltage servo drive system with the current DC bus voltage V_now being 350V. At a certain moment, the amplitude of the grid voltage fluctuation ΔV collected in real time is 3V, the change rate of the grid voltage fluctuation R_ΔV is 0.5V / s, the set preset time interval t is 10 seconds, and the DC bus voltage conversion coefficient K_conv is 0.8.

[0039] First, extract the amplitude of the grid voltage fluctuation ΔV = 3V and the change rate R_ΔV = 0.5V / s from the real-time data.

[0040] Next, calculate the predicted value of the grid voltage fluctuation within the next 10 seconds: ΔV_future = ΔV + R_ΔV * t = 3 + 0.5 * 10 = 8V.

[0041] Then, use the conversion coefficient K_conv to calculate the impact on the DC bus voltage: Impact = ΔV_future * K_conv = 8 * 0.8 = 6.4V.

[0042] Finally, add the impact to the current DC bus voltage value to obtain the predicted value of the adjusted DC bus voltage: V_predict = V_now + Impact = 350 + 6.4 = 356.4V.

[0043] Through the above steps, not only the predicted value of the grid voltage fluctuation within a future period of time is obtained, but also the specific impact of this fluctuation on the DC bus voltage is calculated, and based on this, the future DC bus voltage value is predicted.

[0044] Step 4: Dynamically adjust the proportional coefficient of the PID control based on the error signal and the impact; specifically including: Obtain data from the final error signal E_final and the impact Impact, and calculate the comprehensive adjustment factor F_adj = E_final + Impact. This formula combines the error signal and the impact of the grid voltage fluctuation to form a comprehensive adjustment factor for subsequent adjustment of the PID control parameters, in order to reflect the impact of the error signal and the grid voltage fluctuation on the system; this factor is used to quantify the combined impact of the current error signal and the grid voltage fluctuation on the system.

[0045] Adjust the initial proportional coefficient K_p0 according to the F_adj. The new proportional coefficient K_p_new = K_p0 + F_adj * C_adj, where C_adj is an adjustment constant used to adjust the influence degree of the adjustment factor on the proportional coefficient; by combining the comprehensive adjustment factor F_adj and the adjustment constant C_adj, the new proportional coefficient K_p_new suitable for the current state can be calculated.

[0046] Apply the K_p_new to the PID control loop, update the control parameters, and calculate the output control signal U_out = K_p_new * E_final using the updated parameters to drive the servo motor for position adjustment. This formula is used to calculate the output control signal. The new proportionality coefficient K_p_new is multiplied by the final error signal E_final to generate a control signal for adjusting the output current of the servo driver.

[0047] Embodiment 4 Suppose a high-voltage servo drive system with an initial proportionality coefficient K_p0 set to 1.5. At a certain moment, the calculated final error signal E_final is 8V, the impact of grid voltage fluctuation on the DC bus voltage Impact is 6.4V, and the adjustment constant C_adj is set to 0.3.

[0048] First, extract data from the final error signal E_final and the impact Impact, and calculate the comprehensive adjustment factor F_adj = E_final + Impact = 8 + 6.4 = 14.4.

[0049] Next, use the comprehensive adjustment factor F_adj to adjust the initial proportionality coefficient K_p0, and calculate the new proportionality coefficient K_p_new = K_p0 + F_adj * C_adj = 1.5 + 14.4 * 0.3 = 1.5 + 4.32 = 5.82.

[0050] Finally, apply the new proportionality coefficient K_p_new to the PID control loop, update the control parameters, and calculate the output control signal U_out = K_p_new * E_final = 5.82 * 8 = 46.56.

[0051] Through the above steps, not only the comprehensive adjustment factor of the system is obtained, but also the proportionality coefficient of the PID control is dynamically adjusted according to this factor, and then an output control signal suitable for the current state is generated.

[0052] Step Five: Use the error signal to calculate the integral value of the error signal, and the calculation coefficient of the integral value is associated with the proportionality coefficient; specifically including: Obtain the error signal values {E_1, E_2,..., E_n} of consecutive n sampling points from the final error signal E_final; these values represent the change of the system error over a period of time. For example, if the sampling frequency is once per second, then n samples represent the error changes in the past n seconds.

[0053] Based on the error signal values, calculate the cumulative error E_sum = E_1 + E_2 +... + E_n; this formula is used to calculate the sum of the error signal values at all sampling points, that is, the cumulative error. It reflects the overall error accumulation of the system over a period of time.

[0054] According to the new proportionality coefficient K_p_new, determine the integral adjustment coefficient I_adj = K_p_new * I_coef, where I_coef is a preset integral coefficient used to adjust the influence degree of the proportionality coefficient on the integral part. By multiplying the new proportionality coefficient K_p_new by I_coef, the integral adjustment coefficient I_adj is obtained.

[0055] Using the E_sum and I_adj, calculate the integral value of the error signal I_value = E_sum * I_adj; this formula is used to calculate the integral value of the error signal. By multiplying the cumulative error E_sum by the integral adjustment coefficient I_adj, the integral value of the error signal can be obtained, which reflects the cumulative effect of the system error over time.

[0056] Example 5 Suppose a high-voltage servo drive system. At a certain moment, the new proportionality coefficient K_p_new has been obtained as 5.82 (refer to the previous step), and the preset integral coefficient I_coef is set to 0.2. Now it is necessary to calculate the integral value of the error signal at the last 5 sampling points.

[0057] First, obtain the error signal values at 5 consecutive sampling points from the final error signal E_final. Suppose these values are E_1 = 8V, E_2 = 7.5V, E_3 = 7V, E_4 = 6.5V, and E_5 = 6V respectively.

[0058] Next, based on these error signal values, calculate the cumulative error E_sum = E_1 + E_2 + E_3 + E_4 + E_5 = 8 + 7.5 + 7 + 6.5 + 6 = 35V.

[0059] Then, according to the new proportionality coefficient K_p_new, determine the integral adjustment coefficient I_adj = K_p_new * I_coef = 5.82 * 0.2 = 1.164.

[0060] Finally, using the cumulative error E_sum and the integral adjustment coefficient I_adj, calculate the integral value of the error signal I_value = E_sum * I_adj = 35 * 1.164 = 40.74.

[0061] Through the above steps, not only the cumulative error of the system over a period of time is obtained, but also the weight of the integral part is dynamically adjusted according to the current proportionality coefficient, and then the integral value of the error signal is calculated.

[0062] Step Six: Calculate the differential value of the error signal based on the current change rate of the error signal; specifically including: Select the error signal values {E_t1, E_t2,..., E_tm} of m consecutive sampling points from the final error signal E_final. These values represent the change of the system error over a period of time. For example, if the sampling frequency is once per second, then m samples represent the error changes in the past m seconds.

[0063] According to the error signal values, calculate the error change amount ΔE_i = E_ti - E_t(i - 1) between adjacent sampling points, where i is an integer from 2 to m; this formula is used to calculate the error change amount between adjacent sampling points. By comparing the error differences between each sampling point and its previous sampling point, the change rate of the error signal over time can be quantified.

[0064] Based on the error change amount ΔE_i and the sampling time interval Δt, calculate the average change rate of the error signal R_avg = (ΔE_2 + ΔE_3 +... + ΔE_m) / ((m - 1) * Δt); this formula is used to calculate the average change rate of the error signal. By adding up the error change amounts between all adjacent sampling points and dividing by the total sampling interval (i.e., (m - 1) * Δt), the average rate of change of the error signal over time can be obtained.

[0065] Use the average change rate R_avg and the preset differential adjustment coefficient D_coef, which is used to adjust the influence degree of the average change rate on the differential part, to calculate the differential value of the error signal D_value = R_avg * D_coef. The differential value helps the system predict the future error trend, make adjustments in advance, reduce overshoot and oscillation, thereby improving the control accuracy and stability.

[0066] Example 6 Suppose a high-voltage servo drive system. At a certain moment, a series of values of the final error signal E_final have been obtained. Now it is necessary to calculate the differential value of the error signal for the nearest 5 sampling points (m = 5), the sampling time interval Δt is 0.1 second, and the preset differential adjustment coefficient D_coef is set to 0.5.

[0067] First, select the error signal values of 5 consecutive sampling points from the final error signal E_final. Suppose these values are E_t1 = 8V, E_t2 = 7.5V, E_t3 = 7V, E_t4 = 6.5V, E_t5 = 6V respectively.

[0068] Next, according to these error signal values, calculate the error change amount between adjacent sampling points: ΔE_2 = E_t2 - E_t1 = 7.5 - 8 = -0.5V, ΔE_3 = E_t3 - E_t2 = 7 - 7.5 = -0.5V, ΔE_4 = E_t4 - E_t3 = 6.5 - 7 = -0.5V, ΔE_5 = E_t5 - E_t4 = 6 - 6.5 = -0.5V。

[0069] Then, based on the error change ΔE_i and the sampling time interval Δt, calculate the average change rate of the error signal: R_avg = (-0.5 + -0.5 + -0.5 + -0.5) / ((5 - 1)*0.1) = -2 / 0.4 = -5V / s.

[0070] Finally, use the average change rate R_avg and the differential adjustment coefficient D_coef to calculate the differential value of the error signal: D_value = R_avg * D_coef = -5 * 0.5 = -2.5.

[0071] Through the above steps, not only the error change trend of the system in the past period of time is obtained, but also the differential value of the error signal is dynamically calculated according to the current average change rate.

[0072] Step 7: Add the proportional coefficient, integral value, and differential value to generate the control signal of the driver; specifically including: Obtain values from the new proportional coefficient K_p_new, the integral value I_value of the error signal, and the differential value D_value of the error signal; these parameters are the basis for generating the final control signal.

[0073] Based on the K_p_new, I_value, and D_value, calculate the preliminary control signal U_prelim = K_p_new * E_final + I_value + D_value; this formula is used to calculate the preliminary control signal U_prelim. By multiplying the new proportional coefficient K_p_new by the final error signal E_final and adding the integral value I_value and the differential value D_value, a preliminary control signal can be obtained.

[0074] Adjust the amplitude of the preliminary control signal U_prelim according to the system requirements, apply the gain adjustment factor G_adj, which is used to adjust the amplitude of the preliminary control signal, to obtain the adjusted control signal U_adjusted = U_prelim * G_adj; by multiplying the preliminary control signal U_prelim by G_adj, the adjusted control signal U_adjusted can be obtained to meet the control requirements of a specific system.

[0075] Send the U_adjusted as the final control signal to the high-voltage servo driver to adjust the output to achieve position control. The driver adjusts its output current or voltage according to this signal, thereby controlling the position of the motor.

[0076] Embodiment 7 Suppose a high-voltage servo drive system. At a certain moment, the following parameters have been obtained: The new proportional coefficient K_p_new = 5.82; The final error signal E_final = 8V; The integral value of the error signal I_value = 40.74; The differential value of the error signal D_value = -2.5; The gain adjustment factor G_adj is set to 1.2.

[0077] First, obtain the values from the new proportional coefficient K_p_new, the integral value of the error signal I_value, and the differential value of the error signal D_value.

[0078] Next, based on K_p_new, I_value, and D_value, calculate the preliminary control signal: U_prelim = K_p_new * E_final + I_value + D_value = 5.82 * 8 + 40.74 + (-2.5) = 46.56 + 40.74 - 2.5 = 84.8.

[0079] Then, adjust the amplitude of the preliminary control signal U_prelim according to the system requirements, and apply the gain adjustment factor G_adj to obtain the adjusted control signal: U_adjusted = U_prelim * G_adj = 84.8 * 1.2 = 101.76.

[0080] Finally, send U_adjusted as the final control signal to the high-voltage servo driver to adjust the output to achieve position control.

[0081] Through the above steps, not only the preliminary control signal U_prelim is calculated, but also further adjustment is made according to the system requirements to generate the final control signal U_adjusted.

[0082] Step 8: Adjust the output current of the driver according to the control signal to complete the closed-loop control; specifically including: Obtain the value from the final control signal U_adjusted; this signal is comprehensively calculated based on proportional, integral, and differential values and is used to guide the servo driver to perform precise position control.

[0083] Based on the U_adjusted, calculate the required adjusted output current change ΔI = U_adjusted / R_sense, where R_sense is the resistance value of the current detection resistor; this formula is used to calculate the required adjusted output current change ΔI. By dividing the final control signal U_adjusted by the resistance value of the current detection resistor R_sense, the current change that needs to be increased or decreased can be obtained.

[0084] Add the ΔI to the current output current I_current to obtain the target output current I_target = I_current + ΔI; this formula is used to calculate the target output current I_target. By adding the current output current I_current and the required adjusted current change ΔI, the target output current value that the driver should reach can be obtained.

[0085] Adjust the actual output current of the high-voltage servo driver according to the calculated target output current I_target. At the same time, monitor the deviation between the actual position and the target position of the system in real time through the feedback loop, and use this deviation to update the error signal E_final, thereby forming a closed-loop control.

[0086] Embodiment 8 Suppose a high-voltage servo drive system, at a certain moment, the following parameters have been obtained: The final control signal U_adjusted = 101.76; The resistance value of the current detection resistor R_sense = 0.5 ohm; The current output current I_current = 20A.

[0087] First, obtain the value from the final control signal U_adjusted.

[0088] Next, calculate the required adjusted output current change based on U_adjusted: ΔI = U_adjusted / R_sense = 101.76 / 0.5 = 203.52A.

[0089] Then, add ΔI to the current output current I_current to obtain the target output current: I_target = I_current + ΔI = 20 + 203.52 = 223.52A.

[0090] Finally, adjust the output current of the high-voltage servo driver according to I_target. Suppose there is a deviation between the actual position and the target position, for example, the deviation is 2V, then update the final error signal E_final: E_final = Deviation = 2V.

[0091] In this example, not only the change in the output current ΔI that needs to be adjusted is calculated, and the target output current I_target is determined accordingly, but also the deviation between the actual position and the target position is monitored through a feedback loop, and the final error signal E_final is updated. This closed-loop control method ensures that the system can continuously monitor and correct its own behavior, maintaining high precision and stability.

[0092] On the other hand, the present invention proposes a high-voltage servo drive control system based on an intelligent and efficient control algorithm, as Figure 2 shown, including: An error signal calculation module, configured to collect in real time the DC bus voltage value of the high-voltage servo drive and the grid voltage fluctuation data to obtain real-time data, and based on the real-time data, calculate the deviation value between the current DC bus voltage and the target value as the error signal; A future impact prediction module, configured to predict the impact of grid voltage fluctuations on the DC bus voltage within a preset future time interval according to the grid voltage fluctuation data; An integral calculation module, configured to dynamically adjust the proportional coefficient of the PID control based on the error signal and the impact amount, and use the error signal to calculate the integral value of the error signal, and the calculation coefficient of the integral value is associated with the proportional coefficient; A differential value calculation module, configured to calculate the differential value of the error signal based on the current change rate of the error signal; A closed-loop control module, configured to add the proportional coefficient, the integral value, and the differential value to generate the control signal of the drive, and adjust the output current of the drive according to the control signal to complete the closed-loop control.

[0093] In addition, each of the above modules is also used to implement other steps of a high-voltage servo drive control method based on an intelligent and efficient control algorithm when executed, which will not be elaborated here one by one.

[0094] In summary, the present invention realizes closed-loop control by collecting in real time the DC bus voltage value and the grid voltage fluctuation data, and combining the predicted impact of grid voltage fluctuations on the DC bus voltage within a preset future time interval, dynamically adjusting the proportional coefficient of the PID control, calculating the integral value and the differential value of the error signal, and finally generating an optimized control signal to adjust the output current of the drive.

[0095] This method can not only effectively compensate for the adverse effects of grid voltage fluctuations on the servo drive, improve the position control accuracy, but also simplify the system design and reduce the cost. Therefore, the present invention provides a more stable, accurate and cost-effective solution, which is particularly suitable for industrial application environments with high requirements for position control.

[0096] Finally, it should be noted that the above are only preferred embodiments of the present invention and are not used to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A control method for a high-voltage servo driver based on an intelligent and efficient control algorithm, characterized in that, Including the following steps: Collect the DC bus voltage value of the high-voltage servo driver and the grid voltage fluctuation data in real time to obtain real-time data. Based on the real-time data, calculate the deviation value between the current DC bus voltage and the target value as the error signal; According to the grid voltage fluctuation data, predict the influence amount of the grid voltage fluctuation on the DC bus voltage within a preset time interval in the future; Based on the error signal and the influence amount, dynamically adjust the proportional coefficient of the PID control. Use the error signal to calculate the integral value of the error signal, and the calculation coefficient of the integral value is associated with the proportional coefficient; Calculate the differential value of the error signal based on the current change rate of the error signal; Add the proportional coefficient, integral value and differential value to generate the control signal of the driver, and adjust the output current of the driver according to the control signal to complete the closed-loop control.

2. The control method of the high-voltage servo driver based on the intelligent and efficient control algorithm according to claim 1, characterized in that, The real-time collection of the DC bus voltage value of the high-voltage servo driver and the grid voltage fluctuation data to obtain real-time data includes: Synchronously collect the DC bus voltage value V_m and the grid voltage fluctuation amplitude ΔV through a voltage sensor, and set the sampling frequency to f_s; Perform sliding window filtering processing on the V_m and ΔV, and the calculation formula is: V_filtered=(V_m1+V_m2+...+V_mk) / k, where k is the number of sampling points within the sliding window; Based on the V_filtered and ΔV, calculate the weighted fusion value V_fuse=V_filtered*(1-α)+ΔV*α, where α is a preset weight coefficient; Combine the V_fuse and the grid voltage fluctuation data ΔV to form the real-time data.

3. The control method of the high-voltage servo driver based on the intelligent and efficient control algorithm according to claim 2, characterized in that, The calculation of the deviation value between the current DC bus voltage and the target value as the error signal based on the real-time data includes: Extract the current DC bus voltage value V_now and the preset target voltage value V_target from the real-time data; According to the V_now and V_target, calculate the initial error E_initial=V_target-V_now; Apply the proportional adjustment factor K_p to the E_initial, and calculate the corrected error signal E_corrected=E_initial*K_p; Combine the E_corrected and the grid voltage fluctuation amplitude ΔV in the real-time data, and calculate the final error signal E_final=E_corrected+ΔV*K_p.

4. The control method of the high-voltage servo driver based on the intelligent and efficient control algorithm according to claim 3, characterized in that, According to the grid voltage fluctuation data, predicting the influence amount of the grid voltage fluctuation on the DC bus voltage within a preset time interval in the future includes: Extract the grid voltage fluctuation amplitude ΔV and the change rate R_ΔV from the real-time data; Based on the change rate R_ΔV, calculate the predicted value of the grid voltage fluctuation within the next t seconds ΔV_future=ΔV+R_ΔV*t, where t is the preset time interval; Combine the ΔV_future and the DC bus voltage conversion coefficient K_conv to calculate the influence amount Impact=ΔV_future*K_conv; Add the said Impact to the current value V_now of the DC bus voltage to obtain the predicted value V_predict of the adjusted DC bus voltage, where V_predict = V_now + Impact.

5. The control method of the high-voltage servo driver based on the intelligent and efficient control algorithm according to claim 4, wherein, Based on the error signal and the impact quantity, dynamically adjust the proportional coefficient of the PID control, including: Obtain data from the final error signal E_final and the impact quantity Impact, and calculate the comprehensive adjustment factor F_adj = E_final + Impact to reflect the influence of the error signal and the grid voltage fluctuation on the system; Adjust the initial proportional coefficient K_p0 according to the F_adj, and the new proportional coefficient K_p_new = K_p0 + F_adj * C_adj, where C_adj is the adjustment constant; Apply the K_p_new to the PID control link, update the control parameters, and calculate the output control signal U_out = K_p_new * E_final using the updated parameters.

6. The control method of the high-voltage servo driver based on the intelligent and efficient control algorithm according to claim 5, wherein, Calculate the integral value of the error signal using the error signal, where the calculation coefficient of the integral value is associated with the proportional coefficient, including: Obtain the error signal values {E_1, E_2,..., E_n} of consecutive n sampling points from the final error signal E_final; Based on the error signal values, calculate the cumulative error E_sum = E_1 + E_2 +... + E_n; Determine the integral adjustment coefficient I_adj = K_p_new * I_coef according to the new proportional coefficient K_p_new, where I_coef is the preset integral coefficient; Calculate the integral value I_value of the error signal using the E_sum and I_adj, where I_value = E_sum * I_adj.

7. The control method of a high-voltage servo driver based on an intelligent and efficient control algorithm according to claim 6, characterized in that, Calculate the differential value of the error signal based on the current change rate of the error signal, including: Select the error signal values {E_t1, E_t2,..., E_tm} of consecutive m sampling points from the final error signal E_final; According to the error signal values, calculate the error change amount ΔE_i = E_ti - E_t(i - 1) between adjacent sampling points, where i is an integer from 2 to m; Based on the error change amount ΔE_i and the sampling time interval Δt, calculate the average change rate R_avg = (ΔE_2 + ΔE_3 +... + ΔE_m) / ((m - 1) * Δt) of the error signal; Calculate the differential value D_value of the error signal using the average change rate R_avg and the preset differential adjustment coefficient D_coef, where D_value = R_avg * D_coef.

8. The control method of the high-voltage servo driver based on the intelligent and efficient control algorithm according to claim 7, characterized in that, Add the proportional coefficient, the integral value, and the differential value to generate the control signal of the driver, including: Obtain the numerical values from the new proportional coefficient K_p_new, the integral value I_value of the error signal, and the differential value D_value of the error signal; Based on the K_p_new, I_value, and D_value, calculate the preliminary control signal U_prelim = K_p_new * E_final + I_value + D_value; Adjust the amplitude of the preliminary control signal U_prelim according to the system requirements, and apply the gain adjustment factor G_adj to obtain the adjusted control signal U_adjusted = U_prelim * G_adj; Send the U_adjusted as the final control signal to the high-voltage servo driver to adjust the output to achieve position control.

9. The control method of the high-voltage servo driver based on the intelligent and efficient control algorithm according to claim 8, wherein Adjust the drive output current according to the control signal to complete the closed-loop control, including: Obtain the value from the final control signal U_adjusted; Calculate the change in the output current ΔI = U_adjusted / R_sense required to be adjusted based on the U_adjusted, where R_sense is the resistance value of the current detection resistor; Add the ΔI to the current output current I_current to obtain the target output current I_target = I_current + ΔI; Adjust the output current of the high-voltage servo driver according to the I_target, monitor the deviation between the actual position and the target position through the feedback loop, and update E_final using the deviation to achieve closed-loop control.

10. A high-voltage servo driver control system based on an intelligent and efficient control algorithm for implementing the method according to any one of claims 1-9, characterized in that, Including: An error signal calculation module for collecting the DC bus voltage value of the high-voltage servo driver and the grid voltage fluctuation data in real time to obtain real-time data, and calculating the deviation value between the current DC bus voltage and the target value as the error signal based on the real-time data; A future impact prediction module for predicting the impact of the grid voltage fluctuation on the DC bus voltage within a preset future time interval according to the grid voltage fluctuation data; An integral calculation module for dynamically adjusting the proportional coefficient of the PID control based on the error signal and the impact, calculating the integral value of the error signal using the error signal, and the calculation coefficient of the integral value is associated with the proportional coefficient; A differential value calculation module for calculating the differential value of the error signal based on the current change rate of the error signal; A closed-loop control module for adding the proportional coefficient, the integral value, and the differential value to generate the control signal of the driver, adjusting the drive output current according to the control signal, and completing the closed-loop control.

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