Rotary table PID (Proportion Integration Differentiation) controller parameter self-tuning method and system based on multi-algorithm fusion

Abstract

The invention discloses a turntable PID (Proportion Integration Differentiation) controller parameter self-tuning method and system based on multi-algorithm fusion, mainly relates to the technical field of turntable control, and comprises a plurality of specific tuning steps of data acquisition and preprocessing, model identification, PID controller parameter automatic calculation and parameter adjustment and verification, and is also matched with an automatic tuning system for specific implementation. The automatic setting system comprises a DSP board card upper computer software module and a PID self-setting software module, the DSP board card upper computer software module is used for setting communication parameters, sending and receiving data and generating a model identification file, and the PID self-setting software module comprises a plurality of program units and is used for further verifying the PID controller parameter self-setting method. The control precision and stability of the rotary table control system can be improved.

Description

Technical Field

[0001] The present invention mainly relates to the field of turntable control technology, and in particular to a turntable PID controller parameter self-tuning method and system based on multi-algorithm fusion. Background Art

[0002] In modern industrial automation and precision control systems, turntables are key rotary actuators whose control accuracy and stability have a crucial impact on the performance of the entire system. As one of the most commonly used controllers in industrial control, the proper tuning of the PID controller's parameters plays a decisive role in the control of turntables.

[0003] Traditional turntable PID controller parameter tuning methods mainly rely on manual experience trial and error or some classic methods such as the Ziegler-Nichols method. However, these methods have many drawbacks: 1. The operator’s experience is required to be high, and the parameters adjusted by different operators may vary greatly, resulting in unstable control effects.

[0004] 2. The tuning process is cumbersome and time-consuming, especially when facing different turntable loads, working environments and control requirements. It requires repeated trials and adjustments, which is inefficient.

[0005] 3. It is difficult to accurately meet the complex control performance index requirements, such as overshoot, rise time, steady-state error, etc., and the performance potential of the turntable cannot be fully utilized.

[0006] With the development of control theory and computer technology, although some PID parameter tuning methods based on advanced technologies such as optimization algorithms and intelligent control have emerged, these methods often have problems such as high computational complexity, poor real-time performance, and strong dependence on models, making them difficult to be widely used in actual turntable control systems.

[0007] Therefore, there is an urgent need for an efficient, accurate, easy-to-use and adaptable turntable PID controller parameter self-tuning method and system to overcome the shortcomings of the existing technology, improve the performance and reliability of the turntable control system, and meet the strict requirements of turntable control accuracy and stability in industrial production. Summary of the Invention

[0008] (1) Technical issues to be resolved In view of the above problems, the present invention needs to provide a turntable PID controller parameter self-tuning method and system based on multi-algorithm fusion, which can improve the performance and reliability of the turntable control system.

[0009] (2) Technical solution In response to the above technical problems, the present invention provides a turntable PID controller parameter self-tuning method based on multi-algorithm fusion, comprising the following steps: Step 1: Use the DSP board to send a single-point sinusoidal excitation signal to the turntable driver and communicate through the RS422 interface at a baud rate of 921600 and a transmission period of 1ms. Record the turntable's response signal and save the collected data as a model identification .TXT file. Step 2: Based on the collected excitation signal and response signal, the Fourier transform algorithm is used to pre-process the data to extract the frequency component and amplitude and phase information. Then, the system identification algorithm is used to identify the mathematical model of the turntable, determine the model order and generate the model numerator and denominator. At the same time, the model is evaluated to determine whether it is usable; Step 3: Manually input the turntable's control objectives: crossover frequency, phase margin, and the system's internal parameter h. Based on the identified mathematical model, an optimization algorithm based on the phase margin method and internal model control principle is used to automatically calculate the PID controller's parameter values ​​and simulation results. Step 4: Determine whether the control requirements are met based on the simulation results. If not, readjust the control target or manually adjust the PID controller parameters and perform simulation calculations again until satisfactory parameter values ​​are obtained. Finally, input the determined PID controller parameter values ​​into the DSP board host computer software for actual verification.

[0010] Furthermore, the system identification algorithm adopted in step 2 is the least squares method.

[0011] Furthermore, the automatic calculation of the parameter values ​​of the PID controller in step 3 includes the following process: S1. Calculate the controller gain that meets the phase margin requirement based on the input crossover frequency and phase margin, combined with the frequency response characteristics of the turntable model. S2. Using the internal model control principle, design the structure of the PID controller, distribute the controller gain to the proportional, integral and differential links, and obtain preliminary Kp, Ki and Kd values; S3. Further adjust and optimize the PID parameters according to the h value to meet the dynamic performance requirements of the system.

[0012] Furthermore, in step three, the parameter value Kp of the PID controller is the proportional coefficient, which determines the degree of correction made by the PID controller to the error in the feedback signal. Ki is the integral coefficient, which is used to eliminate the steady-state error of the system. Kd is the differential coefficient, which is used to suppress overshoot and oscillation of the system.

[0013] Furthermore, the simulation results in step 3 include six indicators: phase margin, bandwidth, overshoot, rise time, error 1s, and error 10s.

[0014] The turntable PID controller parameter self-tuning system based on multi-algorithm fusion adopts the turntable PID controller parameter self-tuning method based on multi-algorithm fusion described above. The system includes: a DSP board host computer software module and a PID self-tuning software module; The DSP board host computer software module includes a communication setting unit: used to set communication parameters with the DSP board; Excitation signal sending and control unit: responsible for sending excitation signals to the turntable driver and controlling the excitation signals; Response signal acquisition and storage unit: collects the response signal of the turntable under the action of the excitation signal and saves the collected data as a model identification .TXT file; PID self-tuning software modules include: Data loading unit: used to load the model identification .TXT file generated by the DSP board host computer software; Model generation unit: uses Fourier transform algorithm to pre-process data, and uses system identification algorithm to identify the mathematical model of the turntable, generates the frequency response curve of the turntable model, and displays the fitting effect of the test data and the identification model; Target input unit: used to input the crossover frequency, phase margin and system internal parameter h value control target; Automatic calculation unit: Automatically calculate PID controller parameters and simulation results using an optimization algorithm based on the phase margin method and internal model control principle; Manual update unit: allows users to manually adjust PID parameters and perform simulation; Controller parameter display unit: used to display PID controller parameter values; Simulation result display unit: displays simulation results in graphical and numerical form, including turntable excitation signal, response signal, frequency response Bode diagram, crossover angular frequency and phase margin maximum, unit step response curve, system open-loop frequency response Bode diagram and closed-loop frequency response Bode diagram.

[0015] Furthermore, the PID self-tuning software module also includes an evaluation unit, which can automatically determine whether the model is usable based on the model numerator and denominator generated by the estimated model order, thereby providing a basis for subsequent PID parameter tuning.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention can quickly and accurately adjust the PID controller parameters that meet different control requirements through the steps of data acquisition, model identification, automatic calculation of PID parameters, and parameter adjustment and verification, combined with the collaborative work of DSP board host computer software and PID self-tuning software module, effectively improving the control accuracy, stability and dynamic performance of the turntable control system, reducing dependence on manual experience, meeting the turntable control accuracy and stability requirements in industrial production, and having broad application prospects and practical engineering value. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is a flow chart of the turntable PID controller parameter self-tuning method of the present invention.

[0018] Figure 2 This is the architecture diagram of the turntable PID controller parameter self-tuning system of the present invention.

[0019] Figure 3 It is a schematic diagram showing the parameters of the self-tuning system. DETAILED DESCRIPTION

[0020] The present invention will be further described below with reference to specific embodiments. The present invention is explained through the exemplary embodiments and descriptions of the present invention, but is not intended to limit the present invention.

[0021] Example 1: A turntable PID controller parameter self-tuning method based on multi-algorithm fusion, comprising the following steps: Step 1: Use the DSP board to send a single-point sinusoidal excitation signal to the turntable driver. Communicate through the RS422 interface at a baud rate of 921600 and a transmission period of 1ms to ensure accurate signal transmission and sampling. Record the turntable's response signal to the excitation signal, including information such as position, speed, and current. Save the collected data as a model identification .TXT file for subsequent data processing and analysis.

[0022] Step 2: Based on the collected excitation signal and response signal, the Fourier transform algorithm is used to preprocess the data to extract the frequency component and amplitude phase information. Then, the system identification algorithm, such as the least squares method, is used to identify the mathematical model of the turntable, estimate the model order, which is generally 1st, 2nd or 3rd order, calculate the model parameters, obtain the transfer function model of the turntable, determine the model order and generate the model numerator and denominator, and evaluate the identified model. By comparing the fit of the model output with the actual response signal, residual analysis and other indicators, the model is evaluated to determine whether it is usable.

[0023] Step 3. Manually enter the turntable's control objectives: crossover frequency, phase margin, and the system's internal parameter h. The crossover frequency is related to the system's closed-loop bandwidth. The phase margin determines the system's stability and dynamic performance. The h value is used to adjust the system's dynamic process.

[0024] According to the mathematical model obtained by identification, the parameter values ​​of the PID controller and the simulation results are automatically calculated using an optimization algorithm based on the phase margin method and internal model control principle.

[0025] Automatic calculation of PID controller parameter values ​​includes the following process: S1. Calculate the controller gain that meets the phase margin requirement based on the input crossover frequency and phase margin, combined with the frequency response characteristics of the turntable model. S2. Using the internal model control principle, design the structure of the PID controller, distribute the controller gain to the proportional, integral and differential links, and obtain preliminary Kp, Ki and Kd values; S3. Further adjust and optimize the PID parameters according to the h value to meet the dynamic performance requirements of the system.

[0026] After calculating the PID parameters, simulation calculations are performed to obtain simulation results such as the system's phase margin, bandwidth, overshoot, rise time, error 1s, and error 10s to evaluate the rationality of the PID parameters and the performance of the control system.

[0027] The simulation results in step 3 include phase margin, bandwidth, overshoot, rise time, error 1s and error 10s indicators.

[0028] In step three, the parameter value Kp of the PID controller is the proportional coefficient, which determines the degree of correction made by the PID controller to the error in the feedback signal. Ki is the integral coefficient, which is used to eliminate the steady-state error of the system. Kd is the differential coefficient, which is used to suppress overshoot and oscillation of the system.

[0029] Step 4: Determine whether the control requirements are met based on the simulation results. If not, readjust the control target or manually adjust the PID controller parameters and perform simulation calculations again until satisfactory parameter values ​​are obtained. Finally, input the determined PID controller parameter values ​​into the DSP board host computer software for actual verification.

[0030] By actually running the turntable control system, verify the effectiveness of the PID parameters in actual control. If the actual control effect is consistent with the simulation results and meets the control requirements, the PID controller parameter self-tuning is complete; otherwise, repeat the above steps to further optimize the PID parameters.

[0031] Attachment Figure 3The figure shows the turntable excitation signal, response signal, frequency response Bode diagram, maximum crossover angular frequency and phase margin, unit step response, system open-loop frequency response Bode diagram and closed-loop frequency response Bode diagram, etc.; the frequency response curve of turntable model identification shows the fitting effect of test data and identification model; the unit step response curve reflects the dynamic performance of the turntable control system under the tuned PID parameters, including overshoot, rise time and steady-state error; the system open-loop frequency response Bode diagram and closed-loop frequency response Bode diagram respectively show the open-loop frequency characteristics and closed-loop frequency characteristics of the system, as well as the corresponding stability indicators such as amplitude margin and phase margin.

[0032] The specific operation process of the turntable PID controller parameter self-tuning method based on multi-algorithm fusion of the present invention is as follows: Data acquisition: Open the DSP board host computer software, enter the "Model Identification" tab, and set the communication parameters to RS422 interface, baud rate 921600, and transmission period 1ms.

[0033] Select axis number 1, excitation mode as "single-point sine", gain percentage as 50%, start frequency as 1Hz, end frequency as 100Hz, step value as 1Hz, and number of cycles as 5.

[0034] Click the "Set" button, confirm that the parameter settings are correct, click the "Start Saving" button, and then click the "Start Excitation" button. The DSP board will start sending a single-point sinusoidal excitation signal to the turntable driver, while simultaneously collecting the turntable's position, speed, and current response signals in real time.

[0035] When the excitation frequency reaches the termination frequency (100 Hz), the excitation signal and response signal automatically return to zero. Click the "End Excitation" and "End Save" buttons to complete data acquisition. Check whether the "Model Identification.TXT" file is generated in the C:\temp\ directory to confirm that the data has been saved successfully.

[0036] Model identification: Open the PID auto-tuning software, click the "Load Data" button, select the "Model Identification.TXT" file in the C:\temp\ directory, and the graphic display area on the right side of the software will display the time domain waveforms of the turntable excitation signal and response signal.

[0037] Enter the estimated model order as 2 in the "Model Order" text box and click the "Generate Model" button. The software uses the FFT algorithm to convert the data into the frequency domain and uses the least squares method to estimate the model parameters. The Bode plot of the turntable model frequency response on the right shows the frequency response curves of the test data and the identification model. At the same time, the software displays the model numerator as [0.5, 1.2] and the model denominator as [1, 0.8, 0.2]. The model evaluation result is "Model Available."

[0038] Automatically calculate the PID controller parameters: Enter the target crossover frequency as 20 Hz in the "Crossover Frequency" text box, enter the phase margin as 60 degrees in the "Phase Margin" text box, and enter the h value as 10000 in the "h" text box.

[0039] Click the "Automatic Calculation" button, and the software will automatically calculate the parameter values ​​of the PID controller: Kp=1.5, Ki=0.8, Kd=0.2 using an optimization algorithm based on the phase margin method and internal model control principle, and perform simulation calculations.

[0040] The simulation results show that the phase margin is 62 degrees, the bandwidth (-3dB) is 30Hz, the overshoot is 5%, the rise time is 0.8 seconds, the error (1s) is 0.01°, and the error (10s) is 0.005°. All indicators meet the control requirements.

[0041] Parameter adjustment and verification: Since the simulation results meet the control requirements, the PID controller parameter values ​​(Kp=1.5, Ki=0.8, Kd=0.2) are directly input into the corresponding PID parameter setting area in the DSP board host computer software.

[0042] The system was run in an actual turntable control system, and the control effect of the turntable was observed through actual operation and testing. The response characteristics of the turntable in actual operation were highly consistent with the simulation results, with a position control accuracy of ±0.01°, stable speed, no obvious overshoot and oscillation, small steady-state error, and a stable and reliable system. The self-tuning of the turntable PID controller parameters was successfully achieved, significantly improving the performance of the turntable control system.

[0043] Example 2: In this example, assuming that the initial model identification result is "model unavailable", it is necessary to readjust the model order for model identification. The specific steps are as follows: Data collection: The steps are the same as in Example 1.

[0044] Model identification: After loading the "Model Identification.TXT" file into the PID self-tuning software, enter the estimated model order as 1 in the "Model Order" text box and click the "Generate Model" button. The results show that the fitting effect between the test data and the identification model is poor, and the model evaluation is "Model Unusable".

[0045] Adjust the model order to 3 and click the "Generate Model" button again. At this time, the test data and the identification model fit well, and the model evaluation result is "Model Available". The model numerator is [0.3, 1.8, 0.5] and the model denominator is [1, 1.2, 0.5, 0.1].

[0046] Automatic calculation of PID controller parameters and subsequent steps: As in Example 1, according to the new model order and parameters, the corresponding PID parameters are automatically calculated and simulated and verified in practice, and finally the self-tuning of the PID controller parameters is completed.

[0047] Example 3: In this example, it is assumed that the initial automatically calculated PID parameter simulation results do not meet the control requirements, and it is necessary to optimize the PID parameters by manually adjusting them. The specific steps are as follows: Data acquisition, model identification, and automatic calculation of PID parameters: The steps are the same as in Example 1. The automatically calculated PID parameters are Kp=1.2, Ki=0.5, and Kd=0.1. The simulation results show that the overshoot is 15%, which exceeds the expected control requirement (the overshoot should be less than or equal to 10%).

[0048] Parameter adjustment and verification: Click the "Manual Update" button, manually adjust the Ki parameter from 0.5 to 0.6, keep Kp and Kd unchanged, and perform simulation calculations again.

[0049] New simulation results show that overshoot is reduced to 8%, meeting the control requirements. At the same time, other performance indicators such as bandwidth, rise time, and steady-state error remain within reasonable ranges.

[0050] The adjusted PID parameters (Kp=1.2, Ki=0.6, Kd=0.1) were input into the DSP board host computer software for actual verification. The actual operation results showed that the control performance of the turntable was significantly improved, and the overshoot was controlled within 8%, meeting the strict control requirements and verifying the effectiveness and practicality of the manual adjustment of PID parameters.

[0051] Example 4: A turntable PID controller parameter self-tuning system based on multi-algorithm fusion adopts a turntable PID controller parameter self-tuning method based on multi-algorithm fusion. The system includes: DSP board host computer software module, PID self-tuning software module; The DSP board host computer software module includes a communication setting unit: used to set the communication parameters with the DSP board, including selecting the RS422 communication interface, setting the baud rate to 921600, and the sending period to 1ms, etc., to ensure reliable communication between the host computer and the DSP board; Excitation signal sending and control unit: responsible for sending excitation signals to the turntable driver and controlling the excitation signals; controlling the amplitude, frequency and other parameters of the excitation signal, and performing frequency sweep operations according to the set starting frequency, ending frequency, step value and number of cycles. Response signal acquisition and storage unit: collects the response signal of the turntable under the action of the excitation signal in real time, including information such as position, speed and current, and saves the collected data as a model identification .TXT file.

[0052] PID self-tuning software modules include: Data loading unit: used to load the model identification .TXT file generated by the DSP board host computer software, read the excitation signal and response signal data into the software system, and provide data support for subsequent model identification and PID parameter tuning; Model generation unit: Uses Fourier transform algorithm to pre-process data, adopts phase unwrapping technology to solve FFT phase jump problem, extracts frequency components and amplitude phase information, and uses system identification algorithm to identify the mathematical model of the turntable, calculates model parameters and generates the frequency response curve of the turntable model. At the same time, the identified model is evaluated and the fitting effect of the test data and the identification model is displayed. The model evaluation result "model is available" or "model is not available" is displayed to determine whether the model can be used for subsequent PID parameter tuning; Target input unit: provides a user interface for users to manually input the crossover frequency, phase margin and system internal parameter h value, providing a basis for the automatic calculation of PID controller parameters; Automatic calculation unit: Based on the identified turntable mathematical model and the control target input by the user, the optimization algorithm based on the phase margin method and internal model control principle is used to automatically calculate the PID controller parameters and simulation results; Manual update unit: allows users to manually adjust PID parameters and trigger re-simulation calculation, so that users can fine-tune PID parameters according to actual needs and experience to further optimize the performance of the control system; Controller parameter display unit: used to display the PID controller parameter values, showing the PID controller parameter values ​​(Kp, Ki and Kd) in a clear and intuitive way, making it convenient for users to view and record; Simulation result display unit: displays simulation results in graphical and numerical form, including turntable excitation signal, response signal, frequency response Bode plot, crossover angular frequency and phase margin maximum, unit step response curve, system open-loop frequency response Bode plot and closed-loop frequency response Bode plot, etc., providing users with comprehensive and accurate information for evaluating and analyzing the performance of the control system; The PID self-tuning software module also includes an evaluation unit, which can automatically determine whether the model is usable based on the model numerator and denominator generated by the estimated model order, providing a basis for subsequent PID parameter tuning.

[0053] Any matters not described in the present invention are applicable to the prior art.

Claims

1. A turntable PID controller parameter self-tuning method based on multi-algorithm fusion, characterized by: The following steps are involved: Step 1: Use the DSP board to send a single-point sinusoidal excitation signal to the turntable driver and communicate through the RS422 interface at a baud rate of 921600 and a transmission period of 1ms. Record the turntable's response signal and save the collected data as a model identification .TXT file. Step 2: Based on the collected excitation signal and response signal, the Fourier transform algorithm is used to pre-process the data to extract the frequency component and amplitude and phase information. Then, the system identification algorithm is used to identify the mathematical model of the turntable, determine the model order and generate the model numerator and denominator. At the same time, the model is evaluated to determine whether it is usable; Step 3: Manually input the turntable's control objectives: crossover frequency, phase margin, and the system's internal parameter h. Based on the identified mathematical model, an optimization algorithm based on the phase margin method and internal model control principle is used to automatically calculate the PID controller's parameter values ​​and simulation results. Step 4: Determine whether the control requirements are met based on the simulation results. If not, readjust the control target or manually adjust the PID controller parameters and perform simulation calculations again until satisfactory parameter values ​​are obtained. Finally, input the determined PID controller parameter values ​​into the DSP board host computer software for actual verification.

2. The method for self-tuning parameters of a turntable PID controller based on multi-algorithm fusion according to claim 1 is characterized in that: The system identification algorithm used in step 2 is the least squares method.

3. The turntable PID controller parameter self-tuning method based on multi-algorithm fusion according to claim 1 is characterized in that: The automatic calculation of the PID controller parameter values ​​in step 3 includes the following process: S1. Calculate the controller gain that meets the phase margin requirement based on the input crossover frequency and phase margin, combined with the frequency response characteristics of the turntable model. S2. Using the internal model control principle, design the structure of the PID controller, distribute the controller gain to the proportional, integral and differential links, and obtain preliminary Kp, Ki and Kd values; S3. Further adjust and optimize the PID parameters according to the h value to meet the dynamic performance requirements of the system.

4. The method for self-tuning parameters of a turntable PID controller based on multi-algorithm fusion according to claim 3 is characterized in that: In step three, the parameter value Kp of the PID controller is the proportional coefficient, which determines the degree of correction made by the PID controller to the error in the feedback signal. Ki is the integral coefficient, which is used to eliminate the steady-state error of the system. Kd is the differential coefficient, which is used to suppress overshoot and oscillation of the system.

5. The turntable PID controller parameter self-tuning method based on multi-algorithm fusion according to claim 1 is characterized in that: The simulation results in step 3 include six indicators: phase margin, bandwidth, overshoot, rise time, error 1s, and error 10s.

6. A turntable PID controller parameter self-tuning system based on multi-algorithm fusion, which adopts the turntable PID controller parameter self-tuning method based on multi-algorithm fusion as described in any one of claims 1 to 5, characterized in that: The system includes: a DSP board host computer software module and a PID self-tuning software module; The DSP board host computer software module includes a communication setting unit: used to set communication parameters with the DSP board; Excitation signal sending and control unit: responsible for sending excitation signals to the turntable driver and controlling the excitation signals; Response signal acquisition and storage unit: collects the response signal of the turntable under the action of the excitation signal and saves the collected data as a model identification .TXT file; PID self-tuning software modules include: Data loading unit: used to load the model identification .TXT file generated by the DSP board host computer software; Model generation unit: uses Fourier transform algorithm to pre-process data, and uses system identification algorithm to identify the mathematical model of the turntable, generates the frequency response curve of the turntable model, and displays the fitting effect of the test data and the identification model; Target input unit: used to input the crossover frequency, phase margin and system internal parameter h value control target; Automatic calculation unit: Automatically calculate PID controller parameters and simulation results using an optimization algorithm based on the phase margin method and internal model control principle; Manual update unit: allows users to manually adjust PID parameters and perform simulation; Controller parameter display unit: used to display PID controller parameter values; Simulation result display unit: displays simulation results in graphical and numerical form, including turntable excitation signal, response signal, frequency response Bode diagram, crossover angular frequency and phase margin maximum, unit step response curve, system open-loop frequency response Bode diagram and closed-loop frequency response Bode diagram.

7. The turntable PID controller parameter self-tuning system based on multi-algorithm fusion according to claim 6 is characterized in that: The PID self-tuning software module also includes an evaluation unit, which can automatically determine whether the model is usable based on the model numerator and denominator generated by the estimated model order, providing a basis for subsequent PID parameter tuning.

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