A control method and system for a servo motor in a servo system

Abstract

The present invention discloses a control method and system for a servo motor in a servo system, which relates to the technical field of servo motor control, including: a control system sets a target value that the motor needs to achieve; real-time acquisition of motor operation data; based on the set target and real-time data, a control instruction is calculated and converted into an output control signal; real-time monitoring of the motor operation state, and a real-time parameter optimization model is established based on real-time operation parameters and historical operation parameters; based on the real-time parameter optimization model, the parameters are dynamically adjusted so that the motor reaches the target range. The present invention analyzes and predicts the motor operation parameters, and based on the prediction results, the motor parameters are dynamically adjusted in real time, which makes it less likely for the parameters to make mistakes during the adjustment process, makes the data adjustment more accurate, more flexible, brings better prospects for use, prolongs the service life of the motor, and makes the motor more intelligent.

Description

Technical Field

[0001] The present invention relates to the technical field of servo motor control, and in particular to a control method and system for a servo motor in a servo system. Background Art

[0002] A servo system is a closed-loop control system used to precisely control parameters such as position, speed or force. It usually includes components such as servo motors, sensors, controllers and actuators. The servo system usually uses position sensors and speed sensors to obtain the real-time status of the motor. These feedback signals are used for closed-loop control to ensure that the system can achieve the desired motion accuracy and stability.

[0003] The existing control methods for servo motors are too limited and cannot be adjusted dynamically in real time, which leads to easy errors in parameter adjustment, low accuracy of data adjustment, and low flexibility. Summary of the invention

[0004] In order to solve the above technical problems, a control method and system for a servo motor in a servo system are provided. This technical solution solves the above problems.

[0005] In order to achieve the above purpose, the technical solution adopted by the present invention is:

[0006] A control method and system for a servo motor in a servo system, comprising:

[0007] The control system sets the target value that the motor needs to achieve;

[0008] Get motor operation data in real time;

[0009] Based on the set target and real-time data, the control instructions are calculated and converted into output control signals;

[0010] Monitor the motor operating status in real time and establish a real-time parameter optimization model based on real-time operating parameters and historical operating parameters;

[0011] Based on the real-time parameter optimization model, the parameters are dynamically adjusted to make the motor reach the target range.

[0012] Preferably, the control system sets the motor to achieve the target specifically including:

[0013] Determining target parameters, wherein the target parameters include a target speed, a target torque, a target position, and a target power;

[0014] Setting a control strategy, wherein the control strategy includes open-loop control, closed-loop control and adaptive control;

[0015] Input the target parameters into the control system as reference signals;

[0016] Select a control mode, which includes speed control, position control and torque control;

[0017] Enter the set value in the controller and configure the relevant parameters;

[0018] Confirm the final goal setting and enter the formal operation stage of the system.

[0019] Preferably, the real-time acquisition of motor operation data specifically includes:

[0020] Collect data from motor sensors;

[0021] Perform edge node data processing at edge nodes and use the cloud to store large amounts of data;

[0022] The edge node data processing formula is: in, For the current moment The output value of Current moment The input value of For the previous moment The output value of are the coefficients of the filter.

[0023] Preferably, the step of calculating the control instruction based on the set target and the real-time data and converting it into an output control signal specifically includes:

[0024] Calculate the error between the set target value and the real-time data;

[0025] Calculating control instructions according to the error value, wherein the control instructions include proportional, integral and differential;

[0026] Perform PID control calculation based on control instructions;

[0027] Based on PID control calculation, the control command is converted into the input voltage of the motor to adjust its operating state.

[0028] Preferably, the performing PID control calculation based on the control instruction specifically includes:

[0029] Among them, the PID control calculation formula is: In the formula, For The output signal at the time, For Always set the difference between the target and the real-time measurement value. is the proportional gain, is the integral gain, is the differential gain, From time 0 to time The cumulative sum of the error values ​​is is the rate of change of error over time.

[0030] The calculation of the error between the set target value and the real-time data specifically includes:

[0031] The error calculation formula is: In the formula, For The error in time, For The target value set at any time, is The actual measured value at the moment .

[0032] Preferably, the real-time monitoring of the motor operating state and establishing a real-time parameter optimization model based on the real-time operating parameters and historical operating parameters specifically include:

[0033] Obtain the motor's operating parameters in real time;

[0034] Convert the vibration signal in the time domain into a signal in the frequency domain;

[0035] Based on the frequency domain signal, the features in the vibration signal are extracted and the vibration root mean square is calculated as the vibration feature;

[0036] Calculate the heat of the motor;

[0037] Evaluate overall load status based on vibration and heating data;

[0038] Build analytical and predictive models and use historical data to perform trend analysis and forecasts on motors.

[0039] The establishment of the analysis and prediction model and the use of historical data to perform trend analysis and prediction of the motor specifically include:

[0040] The analysis and prediction model formula is: In the formula, is the frequency domain signal, is the time domain signal, is the time variable, is a frequency variable, is an imaginary unit, is the angular frequency portion of the frequency, Represents the integral variable The differential elements of is the root mean square of vibration, It is The sampling value of the vibration signal, is the sample size, It's heat. is the heating coefficient, is the power of the motor, For the comprehensive load rating, and . is the weight coefficient, is The load forecast value at the time, and is the regression coefficient, is The actual value at the moment;

[0041] Set warning thresholds based on load status and forecast results;

[0042] The threshold calculation formula is: In the formula, is the threshold value, is the mean, is the standard deviation, is a constant term;

[0043] When the predicted value exceeds the threshold, a warning is issued.

[0044] Preferably, the dynamically adjusting the parameters based on the real-time parameter optimization model so that the motor reaches the target range specifically includes:

[0045] Adjust the motor parameters based on the prediction results of the analysis and prediction model;

[0046] Introducing a dynamic adjustment mechanism to dynamically update model parameters based on real-time data and forecast data;

[0047] The dynamic adjustment formula is: In the formula, For in time The parameter estimates at time , For in time The parameter estimates at time , is the gain factor, For in time The target value at the moment, For in time The feature vector at time, is the predicted value of the current feature and the previous parameter, The actual observed value With the predicted value The difference between.

[0048] A control system for a servo motor in a servo system, the control system comprising:

[0049] Target setting module: used to control the control system to set the target value that the motor needs to achieve;

[0050] Data acquisition module: The data acquisition module is electrically connected to the target setting module, and the data acquisition module is used to acquire the motor operation data in real time;

[0051] Control instruction output module: The control instruction output module is electrically connected to the data acquisition module and the target setting module, and is used to calculate the control instruction based on the set target and real-time data, and convert it into an output control signal;

[0052] Parameter analysis and optimization module: The parameter analysis and optimization module is electrically connected to the control instruction output module, the data acquisition module and the target setting module. The parameter analysis and optimization module is used to monitor the motor operation status in real time and establish a real-time parameter optimization model based on the real-time operation parameters and the historical operation parameters;

[0053] Real-time parameter adjustment module: The real-time parameter adjustment module is electrically connected to the parameter analysis and optimization module, the control instruction output module, the data acquisition module and the target setting module. The real-time parameter adjustment module is used to dynamically adjust the parameters based on the real-time parameter optimization model so that the motor reaches the target range.

[0054] Compared with the prior art, the present invention has the following beneficial effects:

[0055] The present invention proposes to analyze and predict the operating parameters of the motor, and based on the prediction results, to dynamically adjust the motor parameters in real time, so that the parameters are less prone to errors during the adjustment process, making the data adjustment more accurate and more flexible, bringing better usage prospects, extending the service life of the motor, and making the motor more intelligent. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 It is a step flow framework diagram of the present invention;

[0057] Figure 2 A detailed flow chart of the steps for setting the target value that the motor needs to achieve in the control system of the present invention;

[0058] Figure 3 A flowchart of the detailed steps for obtaining motor operation data in real time in the present invention;

[0059] Figure 4 It is a detailed step flow chart of calculating control instructions based on set targets and real-time data and converting them into output control signals in the present invention;

[0060] Figure 5 A detailed flow chart of the steps for real-time monitoring of the motor operating status and establishing a real-time parameter optimization model based on real-time operating parameters and historical operating parameters in the present invention

[0061] Figure 6 It is a detailed step flow chart of dynamically adjusting parameters based on the real-time parameter optimization model in the present invention so that the motor reaches the target range;

[0062] Figure 7 It is a system framework diagram of the present invention. DETAILED DESCRIPTION

[0063] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art may think of other obvious variations.

[0064] Reference Figure 1 As shown, a control method and system for a servo motor in a servo system, comprising:

[0065] The control system sets the target value that the motor needs to achieve;

[0066] Get motor operation data in real time;

[0067] Based on the set target and real-time data, the control instructions are calculated and converted into output control signals;

[0068] Monitor the motor operating status in real time and establish a real-time parameter optimization model based on real-time operating parameters and historical operating parameters;

[0069] Based on the real-time parameter optimization model, the parameters are dynamically adjusted to make the motor reach the target range.

[0070] Reference Figure 2 As shown, the control system sets the motor to achieve the target specifically including:

[0071] Determining target parameters, wherein the target parameters include a target speed, a target torque, a target position, and a target power;

[0072] Setting a control strategy, wherein the control strategy includes open-loop control, closed-loop control and adaptive control;

[0073] Input the target parameters into the control system as reference signals;

[0074] Select a control mode, which includes speed control, position control and torque control;

[0075] Enter the set value in the controller and configure the relevant parameters;

[0076] Confirm the final goal setting and enter the formal operation stage of the system.

[0077] Reference Figure 3 As shown, the real-time acquisition of motor operation data specifically includes:

[0078] Collect data from motor sensors;

[0079] Perform edge node data processing at edge nodes and use the cloud to store large amounts of data;

[0080] The edge node data processing formula is: in, For the current moment The output value of Current moment The input value of For the previous moment The output value of are the coefficients of the filter.

[0081] Reference Figure 4 As shown, the calculation of control instructions based on the set target and real-time data and conversion into output control signals specifically includes:

[0082] Calculate the error between the set target value and the real-time data;

[0083] Calculating control instructions according to the error value, wherein the control instructions include proportional, integral and differential;

[0084] Perform PID control calculation based on control instructions;

[0085] Based on PID control calculation, the control command is converted into the input voltage of the motor to adjust its operating state.

[0086] The PID control calculation based on the control instruction specifically includes:

[0087] Among them, the PID control calculation formula is: In the formula, For The output signal at the time, For Always set the difference between the target and the real-time measurement value. is the proportional gain, is the integral gain, is the differential gain, From time 0 to time The cumulative sum of the error values ​​is is the rate of change of error over time.

[0088] The calculation of the error between the set target value and the real-time data specifically includes:

[0089] The error calculation formula is: In the formula, For The error in time, For The target value set at any time, is The actual measured value at the moment .

[0090] Reference Figure 5 As shown, the real-time monitoring of the motor operating state and the establishment of a real-time parameter optimization model based on the real-time operating parameters and the historical operating parameters specifically include:

[0091] Obtain the motor's operating parameters in real time;

[0092] Convert the vibration signal in the time domain into a signal in the frequency domain;

[0093] Based on the frequency domain signal, the features in the vibration signal are extracted and the vibration root mean square is calculated as the vibration feature;

[0094] Calculate the heat of the motor;

[0095] Evaluate overall load status based on vibration and heating data;

[0096] Build analytical and predictive models and use historical data to perform trend analysis and forecasts on motors.

[0097] The establishment of the analysis and prediction model and the use of historical data to perform trend analysis and prediction of the motor specifically include:

[0098] The analysis and prediction model formula is: In the formula, is the frequency domain signal, is the time domain signal, is the time variable, is a frequency variable, is an imaginary unit, is the angular frequency portion of the frequency, Represents the integral variable The differential elements of is the root mean square of vibration, It is The sampling value of the vibration signal, is the sample size, It's heat. is the heating coefficient, is the power of the motor, For the comprehensive load rating, and is the weight coefficient, is The load forecast value at the time, and is the regression coefficient, is The actual value at the moment;

[0099] Set warning thresholds based on load status and forecast results;

[0100] The threshold calculation formula is: In the formula, is the threshold value, is the mean, is the standard deviation, is a constant term;

[0101] When the predicted value exceeds the threshold, a warning is issued.

[0102] Reference Figure 6 As shown, the real-time parameter optimization model is used to dynamically adjust the parameters so that the motor reaches the target range, specifically including:

[0103] Adjust the motor parameters based on the prediction results of the analysis and prediction model;

[0104] Introducing a dynamic adjustment mechanism to dynamically update model parameters based on real-time data and forecast data;

[0105] The dynamic adjustment formula is: In the formula, For in time The parameter estimates at time , For in time The parameter estimates at time , is the gain factor, For in time The target value at the moment, For in time The feature vector at time, is the predicted value of the current feature and the previous parameter, The actual observed value With the predicted value The difference between.

[0106] Reference Figure 7 As shown, a control system of a servo motor in a servo system, the control system comprises:

[0107] Target setting module: used to control the control system to set the target value that the motor needs to achieve;

[0108] Data acquisition module: The data acquisition module is electrically connected to the target setting module, and the data acquisition module is used to acquire the motor operation data in real time;

[0109] Control instruction output module: The control instruction output module is electrically connected to the data acquisition module and the target setting module, and is used to calculate the control instruction based on the set target and real-time data, and convert it into an output control signal;

[0110] Parameter analysis and optimization module: The parameter analysis and optimization module is electrically connected to the control instruction output module, the data acquisition module and the target setting module. The parameter analysis and optimization module is used to monitor the motor operation status in real time and establish a real-time parameter optimization model based on the real-time operation parameters and the historical operation parameters;

[0111] Real-time parameter adjustment module: The real-time parameter adjustment module is electrically connected to the parameter analysis and optimization module, the control instruction output module, the data acquisition module and the target setting module. The real-time parameter adjustment module is used to dynamically adjust the parameters based on the real-time parameter optimization model so that the motor reaches the target range.

[0112] The use process of the present invention is:

[0113] Step 1: Determine target parameters, which include target speed, target torque, target position and target power;

[0114] Step 2: Setting a control strategy, which includes open-loop control, closed-loop control, and adaptive control;

[0115] Step 3: Input the target parameters into the control system as a reference signal;

[0116] Step 4: Select a control mode, which includes speed control, position control and torque control;

[0117] Step 5: Enter the set value in the controller and configure the relevant parameters;

[0118] Step 6: Confirm the final goal setting and enter the system formal operation stage;

[0119] Step 7: Collect data from the motor sensor;

[0120] Step 8: Analyze and predict the health status of the equipment based on the vibration data of the motor and the heating coefficient of the motor;

[0121] Step 9: Perform edge node data processing at the edge node and use the cloud to store large-capacity data;

[0122] Step 10: Calculate the error between the set target value and the real-time data;

[0123] Step 11: Calculate control instructions according to the error value, wherein the control instructions include proportional, integral and differential;

[0124] Step 12: Perform PID control calculation based on the control instruction;

[0125] Step 13: Based on PID control calculation, the control command is converted into the input voltage of the motor to adjust its operating state;

[0126] Step 14: Obtain the operating parameters of the motor in real time;

[0127] Step 15: Convert the vibration signal in the time domain into a frequency domain signal;

[0128] Step 16: Based on the frequency domain signal, extract the features in the vibration signal and calculate the vibration root mean square as the vibration feature;

[0129] Step 17: Calculate the heat of the motor;

[0130] Step 18: Evaluate the overall load status based on the vibration data and the heating data;

[0131] Step 19: Establish an analysis and prediction model and use historical data to perform trend analysis and prediction of the motor;

[0132] Step 20: Adjust the motor parameters based on the prediction results of the analysis and prediction model;

[0133] Step 21: Introduce a dynamic adjustment mechanism to dynamically update model parameters based on real-time data and predicted data.

[0134] To sum up, the advantages of the present invention are: the present invention proposes to analyze and predict the operating parameters of the motor, and based on the prediction results, the motor parameters are adjusted in real time and dynamically, which makes it less prone to errors in the parameter adjustment process, makes the data adjustment more accurate and more flexible, brings better usage prospects, extends the service life of the motor, and makes the motor more intelligent.

[0135] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the attached claims and their equivalents.

Claims

1. A method for controlling a servo motor in a servo system, It is characterized in that Control methods include: The control system sets the target value that the motor needs to achieve; Obtain motor operation data in real time; Based on the set target and real-time data, the control instructions are calculated and converted into output control signals; Monitor the motor operating status in real time and establish a real-time parameter optimization model based on real-time operating parameters and historical operating parameters; Based on the real-time parameter optimization model, the parameters are dynamically adjusted to make the motor reach the target range; The control system sets the motor to achieve the target including: Determining target parameters, wherein the target parameters include a target speed, a target torque, a target position, and a target power; Setting a control strategy, wherein the control strategy includes open-loop control, closed-loop control and adaptive control; Input the target parameters into the control system as reference signals; Select a control mode, which includes speed control, position control and torque control; Enter the set value in the controller and configure the relevant parameters; Confirm the final goal setting and enter the formal operation stage of the system; The real-time acquisition of motor operation data specifically includes: Collect data from motor sensors; Perform edge node data processing at edge nodes and use the cloud to store large amounts of data; The edge node data processing formula is: in, For the current moment The output value of Current moment The input value of For the previous moment The output value of are the coefficients of the filter; The real-time monitoring of the motor operating state and establishing a real-time parameter optimization model based on the real-time operating parameters and the historical operating parameters specifically include: Obtain the motor's operating parameters in real time; Convert the vibration signal in the time domain into a signal in the frequency domain; Based on the frequency domain signal, the features in the vibration signal are extracted and the vibration root mean square is calculated as the vibration feature; Calculate the heat of the motor; Evaluate overall load status based on vibration and heating data; Establish an analytical prediction model and use historical data to perform trend analysis and prediction of motors, including: The analysis and prediction model formula is: In the formula, is the frequency domain signal, is the time domain signal, is the time variable, is a frequency variable, is an imaginary unit, is the angular frequency portion of the frequency, Represents the integral variable The differential elements of Vibration RMS, It is The sampling value of the vibration signal, is the sample size, It's heat. is the heating coefficient, is the power of the motor, For the comprehensive load rating, and is the weight coefficient, is The load forecast value at the time, and is the regression coefficient, is The actual value at the moment; Set warning thresholds based on load status and forecast results; The threshold calculation formula is: In the formula, is the threshold value, is the mean, is the standard deviation, is a constant term; when the predicted value exceeds the threshold, a warning is issued.

2. A method for controlling a servo motor in a servo system according to claim 1, It is characterized in that The calculation of control instructions based on the set target and real-time data and conversion into output control signals specifically includes: Calculate the error between the set target value and the real-time data; Calculating control instructions according to the error value, wherein the control instructions include proportional, integral and differential; Perform PID control calculation based on control instructions; Based on PID control calculation, the control command is converted into the input voltage of the motor to adjust its operating state.

3. The method for controlling a servo motor in a servo system according to claim 2, It is characterized in that The PID control calculation is performed based on the control instruction. include: Among them, the PID control calculation formula is: In the formula, For The output signal at the time, For Always set the difference between the target and the real-time measurement value. is the proportional gain, is the integral gain, is the differential gain, From time 0 to time The cumulative sum of the error values ​​is is the rate of change of error over time.

4. A method for controlling a servo motor in a servo system according to claim 3, It is characterized in that Calculate the error between the set target value and the real-time data include: The error calculation formula is: In the formula, For The error in time, For The target value set at any time, is The actual measured value at the moment .

5. The method for controlling a servo motor in a servo system according to claim 1, It is characterized in that The method of dynamically adjusting the parameters based on the real-time parameter optimization model so that the motor reaches the target range specifically includes: Adjust the motor parameters based on the prediction results of the analysis and prediction model; Introducing a dynamic adjustment mechanism to dynamically update model parameters based on real-time data and forecast data; The dynamic adjustment formula is: In the formula, For in time The parameter estimates at time , For in time The parameter estimates at time , is the gain factor, For in time The target value at the moment, For in time The feature vector at time, is the predicted value of the current feature and the previous parameter, The actual observed value With the predicted value The difference between.

6. A control system for a servo motor in a servo system, used to implement the control method for a servo motor in a servo system as claimed in claim 1, It is characterized in that The control system includes: Target setting module: used to control the control system to set the target value that the motor needs to achieve; Data acquisition module: The data acquisition module is electrically connected to the target setting module, and the data acquisition module is used to acquire the motor operation data in real time; Control instruction output module: The control instruction output module is electrically connected to the data acquisition module and the target setting module, and is used to calculate the control instruction based on the set target and real-time data, and convert it into an output control signal; Parameter analysis and optimization module: The parameter analysis and optimization module is electrically connected to the control instruction output module, the data acquisition module and the target setting module. The parameter analysis and optimization module is used to monitor the motor operation status in real time and establish a real-time parameter optimization model based on the real-time operation parameters and the historical operation parameters; Parameter real-time adjustment module: The parameter real-time adjustment module is electrically connected to the parameter analysis and optimization module, the control instruction output module, the data acquisition module and the target setting module. The parameter real-time adjustment module is used to dynamically adjust the parameters based on the real-time parameter optimization model so that the motor reaches the target range; The real-time monitoring of the motor operating state and establishing a real-time parameter optimization model based on the real-time operating parameters and the historical operating parameters specifically include: Obtain the motor's operating parameters in real time; Convert the vibration signal in the time domain into a signal in the frequency domain; Based on the frequency domain signal, the features in the vibration signal are extracted and the vibration root mean square is calculated as the vibration feature; Calculate the heat of the motor; Evaluate overall load status based on vibration and heating data; Establish an analytical prediction model and use historical data to perform trend analysis and prediction of motors, including: The analysis and prediction model formula is: In the formula, is the frequency domain signal, is the time domain signal, is the time variable, is a frequency variable, is an imaginary unit, is the angular frequency portion of the frequency, Represents the integral variable The differential elements of is the root mean square of vibration, It is The sampling value of the vibration signal, is the sample size, It's heat. is the heating coefficient, is the power of the motor, For the comprehensive load rating, and is the weight coefficient, is The load forecast value at the time, and is the regression coefficient, is The actual value at the moment; Set warning thresholds based on load status and forecast results; The threshold calculation formula is: In the formula, is the threshold value, is the mean, is the standard deviation, is a constant term; When the predicted value exceeds the threshold, a warning is issued.

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