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

Abstract

The present invention belongs to the technical field of servo drives, and specifically relates to a high-voltage servo drive control method and system based on an intelligent and efficient control algorithm. By collecting DC bus voltage values ​​and grid voltage fluctuation data in real time, and combining the predicted impact of grid voltage fluctuations on the DC bus voltage within a preset time interval in the future, the proportional coefficient of the PID control is dynamically adjusted, the integral value and differential value of the error signal are calculated, and finally an optimized control signal is generated to adjust the output current of the drive, thereby realizing closed-loop control. This method can not only effectively compensate for the adverse effects of grid voltage fluctuations on the servo drive and improve position control accuracy, but also simplify system design and reduce costs. Therefore, the present invention provides a more stable, accurate, and cost-effective solution, which is particularly suitable for industrial application environments with high position control requirements.

Description

Technical Field

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

[0002] In industrial automation, high-voltage DC servo drives are widely used in precision position control applications. Traditionally, these drives rely on the PID (Proportional-Integral-Derivative) control algorithm to achieve precise motor control. However, with the increasing complexity of these applications, particularly in environments with frequent grid voltage fluctuations, traditional PID control methods have exposed some shortcomings. The primary issue is that AC grid voltage fluctuations lead to DC bus voltage instability, which in turn affects the position control accuracy of the servo drive. Since grid voltage fluctuations are difficult to completely avoid, effectively compensating for the impact of these fluctuations on the servo drive has become a pressing technical challenge.

[0003] Existing technologies typically use fixed PID parameters for control, which cannot adapt to the dynamic changes caused by grid voltage fluctuations in real time, resulting in reduced position control accuracy. Furthermore, existing improvement solutions often increase system complexity and cost, while failing to fully consider the impact of grid voltage fluctuations on control system performance over a period of time. Summary of the Invention

[0004] The purpose of the present invention is to provide a high-voltage servo drive control method and system 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 drive and improve position control accuracy, but also simplify system design and reduce costs, so as to solve the problems raised in the above background technology.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: a high-voltage servo drive control method based on an intelligent and efficient control algorithm, comprising the following steps:

[0006] Real-time acquisition of 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, calculating the deviation between the DC bus voltage at the current moment and the target value as an error signal;

[0007] Predicting the impact of grid voltage fluctuations on the DC bus voltage within a future preset time interval based on the grid voltage fluctuation data;

[0008] Dynamically adjust the proportional coefficient of PID control based on the error signal and the influence amount, and calculate the integral value of the error signal using the error signal, wherein the calculation coefficient of the integral value is associated with the proportional coefficient;

[0009] calculating a derivative value of the error signal based on a current rate of change of the error signal;

[0010] The proportional coefficient, integral value and differential value are added together to generate a control signal for the driver, and the driver output current is adjusted according to the control signal to complete closed-loop control.

[0011] Preferably, the real-time acquisition of the high-voltage servo driver DC bus voltage value and grid voltage fluctuation data to obtain real-time data includes:

[0012] The DC bus voltage value V_m and the grid voltage fluctuation amplitude ΔV are synchronously collected through the voltage sensor, and the sampling frequency is set to f_s;

[0013] The sliding window filtering process is performed on the V_m and ΔV, and the calculation formula is:

[0014] V_filtered=(V_m1+V_m2+...+V_mk) / k, where k is the number of sampling points in the sliding window;

[0015] Based on V_filtered and ΔV, a weighted fusion value V_fuse=V_filtered*(1-α)+ΔV*α is calculated, where α is a preset weight coefficient;

[0016] The V_fuse is combined with the grid voltage fluctuation data ΔV to form the real-time data.

[0017] Preferably, the step of calculating the deviation between the DC bus voltage at the current moment and the target value as the error signal based on the real-time data includes:

[0018] Extracting the current DC bus voltage value V_now and the preset target voltage value V_target from the real-time data;

[0019] According to V_now and V_target, calculate the initial error E_initial = V_target - V_now;

[0020] Applying a proportional adjustment factor K_p to the E_initial to calculate a corrected error signal E_corrected = E_initial*K_p;

[0021] Combining E_corrected and the grid voltage fluctuation amplitude ΔV in the real-time data, the final error signal E_final=E_corrected+ΔV*K_p is calculated.

[0022] Preferably, predicting the impact of grid voltage fluctuations on the DC bus voltage within a future preset time interval based on the grid voltage fluctuation data includes:

[0023] Extracting the grid voltage fluctuation amplitude ΔV and the change rate R_ΔV from the real-time data;

[0024] Based on the change rate R_ΔV, a predicted value of grid voltage fluctuation in the next t seconds is calculated as ΔV_future=ΔV+R_ΔV*t, where t is a preset time interval;

[0025] Combined with the ΔV_future and the DC bus voltage conversion coefficient K_conv, the impact on the DC bus voltage is calculated as Impact = ΔV_future * K_conv;

[0026] The Impact is added to the current value of the DC bus voltage V_now to obtain an adjusted DC bus voltage prediction value V_predict=V_now+Impact.

[0027] Preferably, dynamically adjusting the proportional coefficient of the PID control based on the error signal and the influence amount includes:

[0028] 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 impact of the error signal and grid voltage fluctuation on the system;

[0029] 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;

[0030] The K_p_new is applied to the PID control link to update the control parameters, and the updated parameters are used to calculate the output control signal U_out = K_p_new * E_final.

[0031] Preferably, the error signal is used to calculate the integral value of the error signal, and the calculation coefficient of the integral value is associated with the proportional coefficient, including:

[0032] Obtain error signal values ​​{E_1, E_2, ..., E_n} of n consecutive sampling points from the final error signal E_final;

[0033] Based on the error signal value, calculate the cumulative error E_sum=E_1+E_2+...+E_n;

[0034] According to the new proportional coefficient K_p_new, the integral adjustment coefficient I_adj=K_p_new*I_coef is determined, where I_coef is the preset integral coefficient;

[0035] Using E_sum and I_adj, the integrated value of the error signal I_value=E_sum*I_adj is calculated.

[0036] Preferably, calculating the differential value of the error signal based on the current rate of change of the error signal comprises:

[0037] Select error signal values ​​{E_t1, E_t2, ..., E_tm} of m consecutive sampling points from the final error signal E_final;

[0038] Calculate the error variation between adjacent sampling points ΔE_i=E_ti-E_t(i-1) according to the error signal value, where i is an integer from 2 to m;

[0039] Based on the error variation ΔE_i and the sampling time interval Δt, the average rate of change of the error signal R_avg=(ΔE_2+ΔE_3+...+ΔE_m) / ((m-1)*Δt) is calculated;

[0040] The average change rate R_avg and the preset differential adjustment coefficient D_coef are used to calculate the differential value D_value of the error signal = R_avg*D_coef.

[0041] Preferably, adding the proportional coefficient, the integral value and the differential value to generate the control signal of the driver includes:

[0042] Get the value from the new proportional coefficient K_p_new, the error signal integral value I_value and the error signal differential value D_value;

[0043] 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;

[0044] Adjust the amplitude of the preliminary control signal U_prelim according to system requirements, apply the gain adjustment factor G_adj, and obtain the adjusted control signal U_adjusted=U_prelim*G_adj;

[0045] The U_adjusted is sent as a final control signal to the high-voltage servo driver for adjusting the output to achieve position control.

[0046] Preferably, adjusting the driver output current according to the control signal to complete closed-loop control includes:

[0047] Obtaining a value from the final control signal U_adjusted;

[0048] Based on U_adjusted, the output current change amount ΔI=U_adjusted / R_sense required for adjustment is calculated, where R_sense is the resistance value of the current detection resistor;

[0049] Add the ΔI to the current output current I_current to obtain the target output current I_target=I_current+ΔI;

[0050] The output current of the high-voltage servo driver is adjusted according to the I_target, the deviation between the actual position and the target position is monitored through a feedback loop, and the deviation is used to update E_final to achieve closed-loop control.

[0051] On the other hand, the present invention proposes a high-voltage servo drive control system based on an intelligent and efficient control algorithm, comprising:

[0052] An error signal calculation module is used to collect the DC bus voltage value of the high-voltage servo drive and the grid voltage fluctuation data in real time to obtain real-time data, and based on the real-time data, calculate the deviation between the DC bus voltage at the current moment and the target value as the error signal;

[0053] A future impact prediction module is used to predict the impact of grid voltage fluctuations on the DC bus voltage within a future preset time interval based on the grid voltage fluctuation data;

[0054] an integral calculation module, configured to dynamically adjust a proportional coefficient of PID control based on the error signal and the influence amount, and calculate an integral value of the error signal using the error signal, wherein the calculation coefficient of the integral value is associated with the proportional coefficient;

[0055] a differential value calculation module, configured to calculate a differential value of the error signal based on a current rate of change of the error signal;

[0056] The closed-loop control module is used to add the proportional coefficient, integral value and differential value to generate a control signal for the driver, and adjust the driver output current according to the control signal to complete closed-loop control.

[0057] Technical effects and advantages of the present invention: The high-voltage servo drive control method and system based on the intelligent and efficient control algorithm proposed in the present invention have the following advantages over the prior art:

[0058] The present invention achieves closed-loop control by collecting DC bus voltage and grid voltage fluctuation data in real time, and by predicting the impact of grid voltage fluctuations on the DC bus voltage within a preset future time interval. The method dynamically adjusts the proportional coefficient of the PID control, calculates the integral and differential values ​​of the error signal, and ultimately generates an optimized control signal to adjust the driver output current. This method not only effectively compensates for the adverse effects of grid voltage fluctuations on the servo driver and improves position control accuracy, but also simplifies system design and reduces costs. Therefore, the present invention provides a more stable, precise, and cost-effective solution, particularly suitable for industrial applications with high position control requirements. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 This is a flow chart of a high-voltage servo drive control method based on an intelligent and efficient control algorithm of the present invention;

[0060] Figure 2 This is a block diagram of the high-voltage servo drive control system based on the intelligent and efficient control algorithm of the present invention. DETAILED DESCRIPTION

[0061] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of 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 ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0062] The present invention provides Figure 1 The high-voltage servo drive control method shown here, based on an intelligent and efficient control algorithm, can not only effectively compensate for the adverse effects of grid voltage fluctuations on the servo drive and improve position control accuracy, but also simplify system design and reduce costs. The details are as follows:

[0063] In this embodiment, a high-voltage servo drive control method based on an intelligent and efficient control algorithm includes the following steps:

[0064] Step 1: Real-time acquisition of the DC bus voltage value of the high-voltage servo drive and the grid voltage fluctuation data to obtain real-time data; specifically including:

[0065] The DC bus voltage value V_m and the grid voltage fluctuation amplitude ΔV are synchronously collected through voltage sensors, and a fixed sampling frequency f_s is set to ensure data continuity and reliability. This synchronous collection method ensures that the instantaneous changes of the DC bus voltage and grid voltage fluctuations can be accurately captured, providing high-quality basic data for subsequent data processing.

[0066] The sliding window filtering process is performed on the V_m and ΔV, and the calculation formula is:

[0067] V_filtered = (V_m1 + V_m2 + ... + V_mk) / k, where k is the number of sampling points in the sliding window. This formula is used to calculate the average of all sampling points over a period of time (i.e., the sliding window) to smooth noise in the original signal and reduce the impact of high-frequency interference on subsequent analysis.

[0068] Based on V_filtered and ΔV, a weighted fusion value V_fuse = V_filtered*(1-α)+ΔV*α is calculated, where α is a preset weight coefficient between 0 and 1, which is used to adjust the ratio between the filtered DC bus voltage and the influence of grid voltage fluctuations. This formula is used to rationally combine information from the two sources to form a more comprehensive voltage assessment value;

[0069] The V_fuse is combined with the grid voltage fluctuation data ΔV to form the real-time data. The final real-time data set includes not only the processed DC bus voltage information but also the directly measured grid voltage fluctuation data.

[0070] Example 1

[0071] Consider a high-voltage servo drive system with a DC bus voltage operating between 300V and 400V and frequent grid voltage fluctuations. To achieve stable control, a sampling frequency of f_s = 1000Hz is set, a sliding window size of k = 5, and a weighting factor of α = 0.2 are selected.

[0072] First, obtain a set of sample data through the voltage sensor, such as:

[0073] V_m1=310V,V_m2=308V,V_m3=312V,V_m4=315V,V_m5=313V, and the grid voltage fluctuation amplitude ΔV=5V is measured at the same time.

[0074] Then, the sliding window filter formula is applied to calculate:

[0075] V_filtered=(310+308+312+315+313) / 5=311.6V.

[0076] Then, use the weighted fusion formula to calculate:

[0077] V_fuse=311.6*0.8+5*0.2=249.28+1=250.28V.

[0078] Finally, V_fuse is combined with the original grid voltage fluctuation data ΔV to form a complete real-time data set for use by the control system.

[0079] Step 2: Based on the real-time data, calculate the deviation between the DC bus voltage at the current moment and the target value as an error signal; specifically including:

[0080] The current DC bus voltage V_now and the preset target voltage V_target are extracted from the real-time data. Based on V_now and V_target, an initial error, E_initial = V_target - V_now, is calculated. This formula is used to calculate the difference between the current DC bus voltage and the desired voltage. This difference represents the system's immediate error and is an important basis for adjusting the control strategy.

[0081] A proportional adjustment factor K_p is applied to E_initial to amplify or reduce the influence of the error signal, and the corrected error signal E_corrected = E_initial*K_p is calculated. This step enhances the system's response speed and strength to the error by proportionally adjusting the initial error.

[0082] Combining E_corrected with the grid voltage fluctuation amplitude ΔV in real-time data, the final error signal E_final = E_corrected + ΔV * K_p is calculated. Incorporating grid voltage fluctuations into the error signal calculation improves the system's adaptability and robustness to external interference, helping to achieve more precise position control.

[0083] Example 2

[0084] Consider a high-voltage servo drive system with a target DC bus voltage V_target set to 350 V. At a certain moment, the real-time acquired DC bus voltage V_now is 345 V, the grid voltage fluctuation amplitude ΔV is 3 V, and the proportional adjustment factor K_p is set to 2.

[0085] First, extract V_now=345V and V_target=350V from the real-time data.

[0086] Next, calculate the initial error E_initial = V_target - V_now = 350 - 345 = 5V.

[0087] Then, the proportional adjustment factor K_p is applied to calculate the corrected error signal E_corrected = E_initial*K_p=5*2=10.

[0088] Finally, the final error signal E_final = E_corrected + ΔV*K_p = 10 + 3*2 = 16 is calculated based on the grid voltage fluctuation amplitude ΔV.

[0089] Through the above steps, not only the initial error of the system is obtained, but also the impact of grid voltage fluctuation on the system is taken into account, thereby generating a comprehensive error signal.

[0090] Step 3: predicting the impact of grid voltage fluctuations on the DC bus voltage within a future preset time interval based on the grid voltage fluctuation data; specifically including:

[0091] The grid voltage fluctuation amplitude ΔV and rate of change R_ΔV are extracted from the real-time data. Based on the rate of change R_ΔV, a predicted grid voltage fluctuation value ΔV_future = ΔV + R_ΔV * t is calculated for the next t seconds, where t is a preset time interval. This formula is used to predict grid voltage fluctuations for the next t seconds. By multiplying the current fluctuation amplitude ΔV and the rate of change R_ΔV by the time interval t, the voltage fluctuation trend for the next period of time can be estimated.

[0092] The ΔV_future and the DC bus voltage conversion coefficient K_conv are combined to quantify the specific impact of grid voltage fluctuations on the future DC bus voltage, and the impact on the DC bus voltage is calculated as Impact = ΔV_future * K_conv. The specific impact on the DC bus voltage can be obtained by multiplying the predicted fluctuation value ΔV_future by the conversion coefficient K_conv.

[0093] Adding Impact to the current DC bus voltage value V_now yields the adjusted DC bus voltage prediction value V_predict = V_now + Impact. This formula is used to calculate the adjusted DC bus voltage prediction value. By adding the current DC bus voltage value V_now to the predicted impact value Impact, the predicted DC bus voltage value at a future time can be obtained.

[0094] Example 3

[0095] Consider a high-voltage servo drive system with a current DC bus voltage V_now of 350 V. At a specific moment, the real-time collected grid voltage fluctuation amplitude ΔV is 3 V, the grid voltage fluctuation rate R_ΔV is 0.5 V / s, the preset time interval t is 10 seconds, and the DC bus voltage conversion coefficient K_conv is 0.8.

[0096] First, the grid voltage fluctuation amplitude ΔV=3V and change rate R_ΔV=0.5V / s are extracted from the real-time data.

[0097] Next, the predicted value of the grid voltage fluctuation in the next 10 seconds is calculated as ΔV_future=ΔV+R_ΔV*t=3+0.5*10=8V.

[0098] Then, the conversion coefficient K_conv is used to calculate the impact on the DC bus voltage: Impact = ΔV_future*K_conv = 8*0.8 = 6.4V.

[0099] Finally, the impact value is added to the current DC bus voltage value to obtain the adjusted DC bus voltage prediction value V_predict=V_now+Impact=350+6.4=356.4V.

[0100] Through the above steps, not only the predicted value of the grid voltage fluctuation in the future period is obtained, but also the specific impact of this fluctuation on the DC bus voltage is calculated, and the future DC bus voltage value is predicted accordingly.

[0101] Step 4: Dynamically adjust the proportional coefficient of PID control based on the error signal and the influence quantity; specifically including:

[0102] Data is obtained from the final error signal E_final and the impact variable Impact to calculate the comprehensive adjustment factor F_adj = E_final + Impact. This formula combines the error signal and the impact of grid voltage fluctuations to form a comprehensive adjustment factor to facilitate subsequent adjustment of PID control parameters. This factor reflects the impact of the error signal and grid voltage fluctuations on the system; this factor is used to quantify the combined impact of the current error signal and grid voltage fluctuations on the system.

[0103] The initial proportional coefficient K_p0 is adjusted 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 used to adjust the influence of the adjustment factor on the proportional coefficient; by combining the comprehensive adjustment factor F_adj and the adjustment constant C_adj, a new proportional coefficient K_p_new suitable for the current state can be calculated.

[0104] K_p_new is applied to the PID control process to update the control parameters. The updated parameters are used to calculate the output control signal U_out = K_p_new * E_final, which is used to drive the servo motor for position adjustment. This formula is used to calculate the output control signal. The new proportional coefficient K_p_new is multiplied by the final error signal E_final to generate the control signal used to adjust the servo drive's output current.

[0105] Example 4

[0106] Consider a high-voltage servo drive system with an initial proportional 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 fluctuations on the DC bus voltage is 6.4V, and the adjustment constant C_adj is set to 0.3.

[0107] First, extract data from the final error signal E_final and the impact value Impact, and calculate the comprehensive adjustment factor F_adj = E_final + Impact = 8 + 6.4 = 14.4.

[0108] Next, the comprehensive adjustment factor F_adj is used to adjust the initial proportional coefficient K_p0, and the new proportional coefficient K_p_new = K_p0 + F_adj*C_adj = 1.5 + 14.4*0.3 = 1.5 + 4.32 = 5.82 is calculated.

[0109] Finally, the new proportional coefficient K_p_new is applied to the PID control link, the control parameters are updated, and the output control signal U_out = K_p_new*E_final = 5.82*8 = 46.56 is calculated using the updated parameters.

[0110] Through the above steps, not only the comprehensive adjustment factor of the system is obtained, but also the proportional coefficient of the PID control is dynamically adjusted according to this factor, thereby generating an output control signal suitable for the current state.

[0111] Step 5: 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; specifically including:

[0112] Obtain error signal values ​​{E_1, E_2, ..., E_n} for n consecutive sampling points from the final error signal E_final; these values ​​represent the change in system error over a period of time. For example, if the sampling frequency is once per second, then n samples represent the error change over the past n seconds.

[0113] Based on the error signal values, the cumulative error E_sum = E_1 + E_2 + ... + E_n is calculated. This formula is used to calculate the sum of the error signal values ​​at all sampling points, i.e., the cumulative error. It reflects the overall error accumulation of the system over a period of time.

[0114] Based on the new proportional coefficient K_p_new, the integral adjustment coefficient I_adj = K_p_new * I_coef is determined, where I_coef is the preset integral coefficient used to adjust the degree of influence of the proportional coefficient on the integral part. The integral adjustment coefficient I_adj is obtained by multiplying the new proportional coefficient K_p_new by I_coef.

[0115] Using E_sum and I_adj, the integral value of the error signal is calculated as I_value = E_sum * I_adj. This formula is used to calculate the integral value of the error signal. By multiplying the accumulated error E_sum by the integral adjustment coefficient I_adj, the integral value of the error signal can be obtained. This value reflects the cumulative effect of system error over time.

[0116] Example 5

[0117] Assume a high-voltage servo drive system. At a certain moment, the new proportional coefficient K_p_new has been determined to be 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 for the most recent five sampling points.

[0118] First, obtain the error signal values ​​of five consecutive sampling points from the final error signal E_final. Assume that these values ​​are E_1=8V, E_2=7.5V, E_3=7V, E_4=6.5V, and E_5=6V.

[0119] Next, based on these error signal values, the cumulative error E_sum=E_1+E_2+E_3+E_4+E_5=8+7.5+7+6.5+6=35V is calculated.

[0120] Then, based on the new proportional coefficient K_p_new, the integral adjustment coefficient I_adj=K_p_new*I_coef=5.82*0.2=1.164 is determined.

[0121] Finally, using the accumulated error E_sum and the integral adjustment coefficient I_adj, the integral value of the error signal is calculated as I_value = E_sum*I_adj = 35*1.164 = 40.74.

[0122] Through the above steps, not only the accumulated error of the system in the past period of time is obtained, but also the weight of the integral part is dynamically adjusted according to the current proportional coefficient, and then the integral value of the error signal is calculated.

[0123] Step 6: Calculate the differential value of the error signal based on the current rate of change of the error signal; specifically including:

[0124] From the final error signal E_final, select the error signal values ​​{E_t1, E_t2, ..., E_tm} at m consecutive sampling points. These values ​​represent the change in system error over a period of time. For example, if the sampling frequency is once per second, then m samples represent the error change over the past m seconds.

[0125] Based on the error signal value, the error change between adjacent sampling points is calculated as ΔE_i = E_ti - E_t(i-1), where i is an integer from 2 to m. This formula is used to calculate the error change between adjacent sampling points. By comparing the error difference between each sampling point and the previous sampling point, the rate of change of the error signal over time can be quantified.

[0126] Based on the error change ΔE_i and the sampling interval Δt, the average rate of change of the error signal, R_avg, is calculated as (ΔE_2 + ΔE_3 + ... + ΔE_m) / ((m-1) * Δt). This formula is used to calculate the average rate of change of the error signal. By summing the error changes 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.

[0127] The average rate of change, R_avg, and the preset differential adjustment coefficient, D_coef, are used to adjust the influence of the average rate of change on the differential component. The differential value of the error signal, D_value = R_avg * D_coef, is calculated. The differential value helps the system predict future error trends and make adjustments in advance, reducing overshoot and oscillation, thereby improving control accuracy and stability.

[0128] Example 6

[0129] Consider a high-voltage servo drive system. At a specific moment in time, a series of values ​​of the final error signal, E_final, are obtained. The differential values ​​of the error signal at the five most recent sampling points (m = 5) need to be calculated. The sampling interval Δt is 0.1 seconds, and the differential adjustment coefficient D_coef is set to 0.5.

[0130] First, select the error signal values ​​of five consecutive sampling points from the final error signal E_final. Assume that these values ​​are E_t1=8V, E_t2=7.5V, E_t3=7V, E_t4=6.5V, and E_t5=6V.

[0131] Then, based on these error signal values, calculate the error change between adjacent sampling points:

[0132] ΔE_2=E_t2-E_t1=7.5-8=-0.5V,

[0133] ΔE_3=E_t3-E_t2=7-7.5=-0.5V,

[0134] ΔE_4=E_t4-E_t3=6.5-7=-0.5V,

[0135] ΔE_5=E_t5-E_t4=6-6.5=-0.5V.

[0136] Then, based on the error change ΔE_i and the sampling time interval Δt, the average change rate of the error signal is calculated: R_avg=(-0.5+-0.5+-0.5+-0.5) / ((5-1)*0.1)=-2 / 0.4=-5V / s.

[0137] Finally, the differential value of the error signal is calculated using the average rate of change R_avg and the differential adjustment coefficient D_coef: D_value = R_avg*D_coef = -5*0.5 = -2.5.

[0138] 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.

[0139] Step 7: Add the proportional coefficient, integral value, and differential value to generate a control signal for the driver; specifically, the steps include:

[0140] The values ​​are obtained from the new proportional coefficient K_p_new, the error signal integral value I_value, and the error signal differential value D_value; these parameters are the basis for generating the final control signal.

[0141] Based on K_p_new, I_value, and D_value, a preliminary control signal U_prelim is calculated as: K_p_new*E_final+I_value+D_value. This formula is used to calculate the preliminary control signal U_prelim. A preliminary control signal is obtained 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.

[0142] The amplitude of the preliminary control signal U_prelim is adjusted according to the system requirements, and the gain adjustment factor G_adj is applied 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 the specific system.

[0143] This U_adjusted is sent as the final control signal to the high-voltage servo driver to adjust the output for position control. The driver adjusts its output current or voltage based on this signal to control the position of the motor.

[0144] Example 7

[0145] Assume that a high-voltage servo drive system has the following parameters at a certain moment:

[0146] New proportional coefficient K_p_new=5.82;

[0147] Final error signal E_final = 8V;

[0148] Error signal integral value I_value=40.74;

[0149] Error signal differential value D_value=-2.5;

[0150] The gain adjustment factor G_adj is set to 1.2.

[0151] First, obtain numerical values ​​from the new proportional coefficient K_p_new, the error signal integral value I_value, and the error signal differential value D_value.

[0152] Next, based on K_p_new, I_value and D_value, the preliminary control signal is calculated:

[0153] 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.

[0154] 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:

[0155] U_adjusted=U_prelim*G_adj=84.8*1.2=101.76.

[0156] Finally, U_adjusted is sent as the final control signal to the high-voltage servo drive to adjust the output to achieve position control.

[0157] Through the above steps, not only the preliminary control signal U_prelim is calculated, but also further adjusted according to system requirements to generate the final control signal U_adjusted.

[0158] Step 8: Adjust the driver output current according to the control signal to complete closed-loop control; specifically including:

[0159] A numerical value is obtained from the final control signal U_adjusted; this signal is calculated based on proportional, integral and differential values ​​and is used to guide the servo drive to perform precise position control.

[0160] Based on U_adjusted, the required output current change ΔI is calculated as U_adjusted / R_sense, where R_sense is the resistance of the current sensing resistor. This formula is used to calculate the required output current change ΔI. The required current change can be calculated by dividing the final control signal U_adjusted by the resistance of the current sensing resistor R_sense.

[0161] Adding ΔI to the current output current I_current yields the target output current I_target = I_current + ΔI. This formula is used to calculate the target output current I_target. Adding the current output current I_current to the desired current change ΔI yields the target output current the driver should achieve.

[0162] The actual output current of the high-voltage servo driver is adjusted based on the calculated target output current I_target. Simultaneously, the deviation between the system's actual position and the target position is monitored in real time through a feedback loop, and this deviation is used to update the error signal E_final, thus forming a closed-loop control.

[0163] Example 8

[0164] Assume that a high-voltage servo drive system has the following parameters at a certain moment:

[0165] The final control signal U_adjusted=101.76;

[0166] Current detection resistor value R_sense = 0.5 ohm;

[0167] The current output current I_current=20A.

[0168] First, the value of the final control signal U_adjusted is obtained.

[0169] Next, the output current change that needs to be adjusted is calculated based on U_adjusted:

[0170] ΔI=U_adjusted / R_sense=101.76 / 0.5=203.52A.

[0171] Then, add ΔI to the current output current I_current to get the target output current:

[0172] I_target=I_current+ΔI=20+203.52=223.52A.

[0173] Finally, the output current of the high-voltage servo driver is adjusted according to I_target. Assuming that there is a deviation between the actual position and the target position, for example, the deviation is 2V, the final error signal E_final is updated:

[0174] E_final = deviation = 2V.

[0175] In this example, not only is the required output current change, ΔI, calculated and used to determine the target output current, I_target, but a feedback loop also monitors the deviation between the actual and target positions and updates the final error signal, E_final. This closed-loop control approach ensures that the system continuously monitors and corrects its behavior, maintaining high accuracy and stability.

[0176] On the other hand, the present invention proposes a high-voltage servo drive control system based on an intelligent and efficient control algorithm, such as Figure 2 Shown, including:

[0177] An error signal calculation module is used to collect the DC bus voltage value of the high-voltage servo drive and the grid voltage fluctuation data in real time to obtain real-time data, and based on the real-time data, calculate the deviation between the DC bus voltage at the current moment and the target value as the error signal;

[0178] A future impact prediction module is used to predict the impact of grid voltage fluctuations on the DC bus voltage within a future preset time interval based on the grid voltage fluctuation data;

[0179] an integral calculation module, configured to dynamically adjust a proportional coefficient of PID control based on the error signal and the influence amount, and calculate an integral value of the error signal using the error signal, wherein the calculation coefficient of the integral value is associated with the proportional coefficient;

[0180] a differential value calculation module, configured to calculate a differential value of the error signal based on a current rate of change of the error signal;

[0181] The closed-loop control module is used to add the proportional coefficient, integral value and differential value to generate a control signal for the driver, and adjust the driver output current according to the control signal to complete closed-loop control.

[0182] In addition, when executed, the above modules are also used to implement other steps of the above-mentioned high-voltage servo drive control method based on an intelligent and efficient control algorithm, which will not be described one by one here.

[0183] In summary, the present invention realizes closed-loop control by collecting the DC bus voltage value and grid voltage fluctuation data in real time, and combining the predicted impact of grid voltage fluctuation on the DC bus voltage within a preset time interval in the future, 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.

[0184] This approach not only effectively compensates for the adverse effects of grid voltage fluctuations on the servo drive and improves position control accuracy, but also simplifies system design and reduces costs. Therefore, the present invention provides a more stable, accurate, and cost-effective solution, particularly suitable for industrial applications with demanding position control requirements.

[0185] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A high-voltage servo drive control method based on an intelligent and efficient control algorithm, characterized in that: The following steps are involved: Real-time acquisition of the DC bus voltage value of the high-voltage servo drive and the grid voltage fluctuation data to obtain real-time data, specifically including: synchronously acquiring the DC bus voltage value V_m and the grid voltage fluctuation amplitude ΔV through a voltage sensor, with the sampling frequency set to f_s; performing sliding window filtering on V_m and ΔV, using the calculation formula: V_filtered=(V_m1+V_m2+...+V_mk) / k, where k is the number of sampling points in the sliding window; based on V_filtered and ΔV, calculating the weighted fusion value V_fuse=V_filtered*(1-α)+ΔV*α, where α is a preset weight coefficient; and combining V_fuse with the grid voltage fluctuation data ΔV to form real-time data; Calculating a deviation between a DC bus voltage at a current moment and a target value as an error signal based on the real-time data, specifically comprising: extracting a current DC bus voltage value V_now and a preset target voltage value V_target from the real-time data; calculating an initial error E_initial = V_target - V_now based on V_now and V_target; applying a proportional adjustment factor K_p to E_initial to calculate a corrected error signal E_corrected = E_initial*K_p; and calculating a final error signal E_final = E_corrected + ΔV*K_p based on E_corrected and a grid voltage fluctuation amplitude ΔV in the real-time data; Predicting the impact of grid voltage fluctuations on the DC bus voltage within a future preset time interval based on the grid voltage fluctuation data; Dynamically adjust the proportional coefficient of PID control based on the error signal and the influence amount, and calculate the integral value of the error signal using the error signal, wherein the calculation coefficient of the integral value is associated with the proportional coefficient; calculating a derivative value of the error signal based on a current rate of change of the error signal; Adding the proportional coefficient, integral value, and differential value to generate a control signal for the driver specifically includes: obtaining a numerical value from a new proportional coefficient K_p_new, an integral value I_value of the error signal, and a differential value D_value of the error signal; calculating a preliminary control signal U_prelim = K_p_new*E_final+I_value+D_value based on K_p_new, I_value, and D_value; adjusting the amplitude of the preliminary control signal U_prelim according to system requirements and applying a gain adjustment factor G_adj to obtain an adjusted control signal U_adjusted = U_prelim*G_adj; and sending U_adjusted as a final control signal to the high-voltage servo driver for adjusting the output to achieve position control; The output current of the driver is adjusted according to the control signal to complete closed-loop control.

2. The high-voltage servo drive control method based on intelligent and efficient control algorithm according to claim 1 is characterized in that: Predicting, based on the grid voltage fluctuation data, the impact of the grid voltage fluctuation on the DC bus voltage within a future preset time interval, including: Extracting the grid voltage fluctuation amplitude ΔV and the change rate R_ΔV from the real-time data; Based on the change rate R_ΔV, a predicted value of grid voltage fluctuation in the next t seconds is calculated as ΔV_future=ΔV+R_ΔV*t, where t is a preset time interval; Combined with the ΔV_future and the DC bus voltage conversion coefficient K_conv, the impact on the DC bus voltage is calculated as Impact = ΔV_future * K_conv; The Impact is added to the current value of the DC bus voltage V_now to obtain an adjusted DC bus voltage prediction value V_predict=V_now+Impact.

3. The high-voltage servo drive control method based on intelligent and efficient control algorithm according to claim 2 is characterized in that: Dynamically adjusting the proportional coefficient of PID control based on the error signal and the influence quantity includes: 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 impact of the error signal and 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; The K_p_new is applied to the PID control link to update the control parameters, and the updated parameters are used to calculate the output control signal U_out = K_p_new * E_final.

4. The high-voltage servo drive control method based on intelligent and efficient control algorithm according to claim 3 is characterized in that: Utilizing the error signal, calculating an integral value of the error signal, wherein a calculation coefficient of the integral value is associated with a proportional coefficient, including: Obtain error signal values ​​{E_1, E_2, ..., E_n} of n consecutive sampling points from the final error signal E_final; Based on the error signal value, calculate the cumulative error E_sum=E_1+E_2+...+E_n; According to the new proportional coefficient K_p_new, the integral adjustment coefficient I_adj=K_p_new*I_coef is determined, where I_coef is the preset integral coefficient; Using E_sum and I_adj, the integrated value of the error signal I_value=E_sum*I_adj is calculated.

5. The high-voltage servo drive control method based on intelligent and efficient control algorithm according to claim 4 is characterized in that: Calculate the derivative of the error signal based on the current rate of change of the error signal, including: Select error signal values ​​{E_t1, E_t2, ..., E_tm} of m consecutive sampling points from the final error signal E_final; Calculate the error variation between adjacent sampling points ΔE_i=E_ti-E_t(i-1) according to the error signal value, where i is an integer from 2 to m; Based on the error variation ΔE_i and the sampling time interval Δt, the average rate of change of the error signal R_avg=(ΔE_2+ΔE_3+...+ΔE_m) / ((m-1)*Δt) is calculated; The average change rate R_avg and the preset differential adjustment coefficient D_coef are used to calculate the differential value D_value of the error signal = R_avg*D_coef.

6. The high-voltage servo drive control method based on intelligent and efficient control algorithm according to claim 5 is characterized in that: Adjusting the driver output current according to the control signal to complete closed-loop control includes: Obtaining a value from the final control signal U_adjusted; Based on U_adjusted, the output current change amount ΔI=U_adjusted / R_sense required for adjustment is calculated, 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; The output current of the high-voltage servo driver is adjusted according to the I_target, the deviation between the actual position and the target position is monitored through a feedback loop, and the deviation is used to update E_final to achieve closed-loop control.

7. A high-voltage servo drive control system based on an intelligent and efficient control algorithm for implementing the method according to any one of claims 1 to 6, characterized in that: include: The error signal calculation module is used to collect the DC bus voltage value of the high-voltage servo drive and the grid voltage fluctuation data in real time to obtain real-time data. Specifically, it includes: synchronously collecting the DC bus voltage value V_m and the grid voltage fluctuation amplitude ΔV through the voltage sensor, and the sampling frequency is set to f_s; performing sliding window filtering on 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 in the sliding window; based on V_filtered and ΔV, calculating the weighted fusion value V_fuse=V_filtered*(1-α)+ΔV*α, where α is the preset weight coefficient; combining V_fuse with the grid voltage fluctuation data ΔV to form a real-time data; based on the real-time data, calculating the deviation between the DC bus voltage at the current moment and the target value as an error signal, specifically comprising: extracting the current DC bus voltage value V_now and the preset target voltage value V_target from the real-time data; calculating the initial error E_initial = V_target - V_now according to V_now and V_target; applying the proportional adjustment factor K_p to E_initial to calculate the corrected error signal E_corrected = E_initial * K_p; combining E_corrected and the grid voltage fluctuation amplitude ΔV in the real-time data to calculate the final error signal E_final = E_corrected + ΔV * K_p; A future impact prediction module is used to predict the impact of grid voltage fluctuations on the DC bus voltage within a future preset time interval based on the grid voltage fluctuation data; an integral calculation module, configured to dynamically adjust a proportional coefficient of PID control based on the error signal and the influence amount, and calculate an integral value of the error signal using the error signal, wherein the calculation coefficient of the integral value is associated with the proportional coefficient; a differential value calculation module, configured to calculate a differential value of the error signal based on a current rate of change of the error signal; The closed-loop control module is used to add the proportional coefficient, integral value and differential value to generate the control signal of the driver, specifically including: obtaining numerical values ​​from the new proportional coefficient K_p_new, the error signal integral value I_value and the error signal differential value D_value; based on K_p_new, I_value and D_value, calculating the preliminary control signal U_prelim=K_p_new*E_final+I_value+D_value; adjusting the amplitude of the preliminary control signal U_prelim according to system requirements, applying the gain adjustment factor G_adj, and obtaining the adjusted control signal U_adjusted=U_prelim*G_adj; sending U_adjusted as the final control signal to the high-voltage servo driver for adjusting the output to achieve position control; adjusting the driver output current according to the control signal to complete closed-loop control.

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