Motor control parameter frequency domain setting method based on electromechanical coupling parameter identification

Abstract

An electromechanical coupling parameter identification and motor control parameter frequency domain setting method comprises the following steps: establishing a permanent magnet synchronous motor electrical parameter identification mathematical model, setting a robot excitation experiment, collecting joint permanent magnet synchronous motor data in the experiment process, and identifying joint permanent magnet synchronous motor electrical parameters from the joint permanent magnet synchronous motor data; and a control system model comprising a permanent magnet synchronous motor current loop, a speed loop and a position loop is established, optimized three-loop control PI parameters are obtained according to joint permanent magnet synchronous motor electrical parameters, a robot controller is arranged, and the position tracking precision of each joint motor is improved. According to the method, single off-line setting of the motor by adopting nominal electromechanical coupling parameters can be avoided, accurate setting of three-loop control parameters of the motor is realized, the position tracking error of the permanent magnet synchronous motor of each joint of the industrial robot is reduced, and the positioning precision of an end effector of the industrial robot is improved.

Description

Technical Field

[0001] This invention relates to a technology in the field of robot control, specifically a method for identifying electromechanical coupling parameters and frequency domain tuning of motor control parameters. Background Technology

[0002] Existing methods for tuning the three-loop control parameters of permanent magnet synchronous motors mainly rely on empirical or rule-based methods. Model-based methods use nominal electromechanical parameters, ignore the time-varying drift of electrical parameters and the deviation of torque gain from actual operating conditions, and do not consider the dynamic coupling effect of multi-axis, making it difficult to directly apply the parameters to the whole machine. Summary of the Invention

[0003] This invention addresses the shortcomings of existing technologies, such as complex tuning operations, poor generalization, failure to reveal the mathematical mapping relationship between motor electrical parameters and three-loop control parameters, and lack of consideration for the motor model when tuning the three-loop control parameters. It proposes a method for electromechanical coupling parameter identification and frequency domain tuning of motor control parameters. This method avoids using nominal electromechanical coupling parameters for single offline tuning of the motor, achieving accurate tuning of the motor's three-loop control parameters, reducing the position tracking error of the permanent magnet synchronous motors at each joint of the industrial robot, and improving the positioning accuracy of the industrial robot's end effector.

[0004] This invention is achieved through the following technical solution:

[0005] This invention relates to a method for electromechanical coupling parameter identification and motor control parameter frequency domain tuning. After establishing a mathematical model for identifying the electrical parameters of a permanent magnet synchronous motor (PMSM), a robot excitation experiment is set up, and data from the joint PMSMs during the experiment is collected to identify the electrical parameters of the joint PMSMs. Then, a control system model including the current loop, speed loop, and position loop of the PMSM is established. Based on the electrical parameters of the joint PMSMs, optimized three-loop control PI parameters are obtained, and the robot controller is set up to improve the position tracking accuracy of each joint motor.

[0006] This invention relates to a system for implementing the above-mentioned method, comprising: a data acquisition unit, an electrical parameter identification unit, and a motor three-loop control parameter frequency domain tuning unit, wherein: the data acquisition unit acquires the three-phase current, dq-axis current, and dq-axis voltage of the joint permanent magnet synchronous motor through a robot trajectory excitation experiment, generating a dataset for electrical parameter identification of the robot joint permanent magnet synchronous motor; the motor electrical parameter identification unit calculates the motor electrical parameters based on the acquired motor three-phase current, dq-axis current, and dq-axis voltage data through inverse Park transform. The current and voltage in the coordinate system are used to identify the motor resistance, inductance, and flux linkage parameters using a recursive least squares algorithm. The motor three-loop control parameter tuning frequency domain analysis unit calculates the transfer functions of the current loop, speed loop, and position loop based on the motor three-loop control block diagram. Using cutoff frequency and phase margin as indicators, a three-loop control system is established. The mathematical mapping relationship between parameters and motor electromechanical coupling parameters is established. Using the identified actual electromechanical coupling parameters of the motor, the optimal parameters for each control loop are calculated. The parameters were then used to verify the improved motor position tracking accuracy through trajectory tracking experiments.

[0007] Technical effect

[0008] This invention establishes a coupled mathematical model of the electromechanical coupling parameters of robot joint motors and the three-loop control transfer function. Excitation experiments are then conducted on each joint of the robot sequentially. Current and voltage data from each joint motor are collected to identify the motor's electrical parameters. The PI parameters of the three-loop control after tuning are solved using the frequency domain method and input into the robot controller via software. Compared with existing technologies, this invention improves the position tracking accuracy of the robot joint permanent magnet synchronous motors. For straight lines and great circles, the average position tracking error of the tuned robot joint motors is reduced by 38.84% and 31.20% respectively compared to before tuning. Attached Figure Description

[0009] Figure 1 This is a flowchart of the present invention;

[0010] Figure 2 This is a hardware architecture diagram for an example embodiment;

[0011] Figure 3 This is a schematic diagram of the tuning framework of the present invention;

[0012] Figure 4 The following is a graph showing the resistance, inductance, and flux linkage of the motors at each joint of the robot in this embodiment.

[0013] Figure 5 The example shows the position tracking error curves of each joint motor when the robot tracks a straight trajectory.

[0014] Figure 6 The example shows the position tracking error curves of the joint motors when the robot tracks a large circular trajectory. Detailed Implementation

[0015] like Figure 1 As shown, this embodiment relates to a method for electromechanical coupling parameter identification and motor control parameter frequency domain tuning, including:

[0016] Step 1, Establish Mathematical model for identifying electrical parameters of permanent magnet synchronous motors in a coordinate system, specifically including:

[0017] 1.1) Establish The voltage equation for a permanent magnet synchronous motor in the coordinate system is as follows: For a surface-mounted permanent magnet synchronous motor The voltage equation in the coordinate system is: ,in: and For permanent magnet synchronous motors and Under-axis voltage, and They are respectively and Current under the shaft, and These are the resistance and flux linkage of a permanent magnet synchronous motor, respectively. and These are the electrical angular velocity and electrical angle of the permanent magnet synchronous motor, respectively. For time, shaft and The axial inductances are equal, that is .

[0018] The permanent magnet synchronous motor Current and voltage in a coordinate system generally cannot be directly acquired, but are obtained through the acquisition of... The current and voltage in the coordinate system are obtained by inverse Park transformation, and the transformation formula is: , , , ,in: and For permanent magnet synchronous motors and Under-axis voltage, and They are respectively and Current under the shaft.

[0019] 1.2) Reorganize the voltage equation from step 1.1 to solve the problem caused by... The lack of rank in the axis voltage equation makes it impossible to... The problem of identifying all electrical parameters in a coordinate system is as follows: ,in: A matrix composed of electrical parameters to be identified. , , , .

[0020] Step two involves conducting robot stimulation experiments and collecting data from the joint permanent magnet synchronous motors, specifically including:

[0021] 2.1) Based on the limitations of the robot's joint angles, angular velocities, and angular accelerations, design the robot joint trajectories for identifying the electrical parameters of the permanent magnet synchronous motor. Specifically, design the angular accelerations of each robot joint. ,in: These represent the maximum angle, maximum angular velocity, and maximum angular acceleration of the joint, respectively. By taking the intermediate time variable of the trajectory as the basis and performing a second integral on the designed angular acceleration, the robot joint excitation trajectory used to identify the electrical parameters of the permanent magnet synchronous motor can be obtained.

[0022] The joint excitation trajectory needs to be independently excited by each joint under the robot's rated load conditions. The design enables the motor to output a torque close to the rated torque and fully excite the motion trajectory within the rated speed range, while avoiding frequent acceleration and deceleration and maintaining a uniform speed operation phase. This ensures that the motor current and voltage data collected under steady-state conditions can effectively improve the identification accuracy of the electrical parameters of the permanent magnet synchronous motor.

[0023] 2.2) Perform trajectory excitation experiments for each joint of the robot in sequence according to the designed joint trajectory. Use the motor driver of each joint to collect voltage and current data, and use the encoder to collect the angle data of each joint motor. The collected data is used for electrical parameter identification of the permanent magnet synchronous motor of each joint.

[0024] like Figure 2 As shown, the hardware facilities corresponding to the robot stimulation experiment include: a six-axis serial industrial robot, a robot control cabinet, a Beckhoff industrial computer based on TwinCAT3, and an EtherCAT communication bus module.

[0025] Step 3: Identify the electrical parameters of the joint permanent magnet synchronous motor from the data collected in Step 2, specifically including:

[0026] 3.1) Establish the basic model of the recursive least squares algorithm, that is, to minimize the L2 norm of the system output vector error, specifically: The estimated model parameters are updated in each iteration using the gradient descent principle. , where: system model , For the number of iterations, For the system output vector, Input matrix to the system, Given the parameter matrix of the model to be identified, The system's output vector is the identified value of the model parameters. , This is the forgetting factor, typically taken as 0.9 to 1. Here is the gain matrix. Covariance matrix.

[0027] 3.2) Based on the voltage equation reconstructed in step 1.2, the electrical parameters of the joint permanent magnet synchronous motor are identified using the recursive least squares algorithm in step 3.1. Specifically, the forgetting factor is initialized. Initial value of the resistor to be identified Initial value of inductor to be identified Initial value of magnetic flux to be identified Initial value of covariance matrix ,for Axis voltage equation, calculate output vector Calculate the input matrix Calculate the gain matrix Update the parameter matrix to be identified Update the covariance matrix ,for Axis voltage equation, calculate output vector Calculate the input matrix Calculate the gain matrix Update the parameter matrix to be identified Update the covariance matrix Then, the parameters to be identified are updated by the first recursive least squares algorithm. Used to calculate the second recursive least squares algorithm The parameters to be identified are updated by the second recursive least squares algorithm. Used to calculate the second recursive least squares algorithm until the resistance identification value Inductance identification value Magnetic link identification value The identification curves of the resistance, inductance, and flux linkage of the permanent magnet synchronous motors at each joint of the robot converge to near their respective nominal values, as shown below. Figure 4 As shown.

[0028] Step four involves establishing a control system model that includes the permanent magnet synchronous motor's current loop, speed loop, and position loop. Based on the electrical parameters of the joint permanent magnet synchronous motor identified in step three, optimized three-loop control PI parameters are obtained, and the robot controller is configured. Specifically, this includes:

[0029] 4.1) Establish the control system model, specifically: the open-loop transfer function of the current loop. Open-loop transfer function of the velocity loop Open-loop transfer function of the position loop Among them: the current loop PI controller stage Power inverter stage Electrical model section Dead zone delay First-order filter stage for current command , For the inverter switching cycle, Delay time for dead zone The current command first-order filter frequency, For the proportional gain of the current loop controller, For the integral gain of the current loop controller; for the speed loop PI controller stage. Torque gain stage Motor dynamics model First-order command filtering stage of the speed loop First-order feedback filter stage of the speed loop , The moment of inertia of the motor rotor. This is the motor torque gain coefficient. The first-order command filter frequency for the speed loop. The first-order feedback filter frequency of the speed loop, For the proportional gain of the speed loop controller, For the integral gain of the speed loop controller; for the position loop PI controller stage. Points system , For the proportional gain of the position loop controller, This is the integral gain of the position loop controller.

[0030] The motor torque gain It is calculated in the following way: based on the electromagnetic torque of the motor. For adopting For a surface-mounted permanent magnet synchronous motor using a vector control strategy, the electromagnetic torque simplifies to: , That is, the motor torque gain coefficient is obtained through the identified motor flux linkage. Calibration is performed, including: This represents the number of pole pairs of the motor.

[0031] 4.2) Based on the open-loop transfer functions of the current loop, velocity loop, and position loop established in step 4.1, using the cutoff frequency and phase margin as indices of the dynamic performance and stability of each control loop, solve for the optimized PI control parameters of each control loop. Specifically, for the open-loop transfer function of the current loop, the phase margin... ,in: Let be the cutoff frequency of the open-loop transfer function of the current loop. From the fact that the open-loop transfer amplitude of the current loop at the cutoff frequency is 1, we can obtain: The optimized PI control parameters of the current loop are obtained. , ,in: , For the open-loop transfer function of the velocity loop, the phase margin ,in: Let be the cutoff frequency of the open-loop transfer function of the velocity loop. From the fact that the open-loop transfer amplitude of the velocity loop at the cutoff frequency is 1, we can obtain: The optimized PI control parameters of the speed loop are obtained. , ,in: , For the open-loop transfer function of the position loop, the phase margin ,in: Let be the cutoff frequency of the open-loop transfer function of the position loop. From the fact that the open-loop transfer amplitude of the position loop at the cutoff frequency is 1, we can obtain: The optimized PI control parameters of the position loop are obtained. , .

[0032] 4.3) Based on the electrical parameters of the permanent magnet synchronous motor for each joint identified in step three, i.e., resistance... ,inductance and magnetic chain Calculate the optimized PI control parameters for the current loop, speed loop, and position loop: .

[0033] 4.4) The PI control parameters optimized in step 4.3 are set in the robot controller.

[0034] The settings described herein are modified, but not limited to, through the controller software of the driver manufacturer. The driver manufacturer is Qingneng Dechuang Company, and all controller software is DriverMaster. The driver model used is CDRD-6A08. The PI regulator parameters in the online servo parameters of the controller can be modified through the DriverMaster software.

[0035] Step 5: Based on the optimized robot controller from Step 4, conduct a robot trajectory tracking experiment to verify the improvement in the position tracking accuracy of each joint motor. This includes:

[0036] 5.1) Select the straight line trajectory and great circle trajectory used in the experiment according to the performance specifications and test methods of industrial robots (GB / T 12642—2013 / ISO9283:1998).

[0037] 5.2) Under the factory-set three-loop control parameters of the permanent magnet synchronous motor at each joint, and the motor three-loop control parameters optimized according to step four, as follows: Figure 2Under the hardware environment settings shown, the linear and great circle trajectories in step 5.1 are run in Cyclic Synchronous Position Mode (CSP). The tracking errors of each joint motor are collected using Beckhoff TwinCAT. The position tracking error curves before and after motor tuning for the linear trajectory are shown below. Figure 5 As shown, the position tracking error curves of the large circular trajectory motor before and after calibration are as follows: Figure 6 As shown, the maximum value (Max), average value (Mean), and standard deviation (STD) of the motor position tracking error are calculated and compared with those before tuning.

[0038] Through specific practical experiments, under the above hardware environment settings, for a straight trajectory, the maximum value of the robot's joint motor position tracking error was 14.7 (from before tuning). rad), 15.4 ( rad), 20.9 ( rad), 70.9 ( rad), 14.6 ( rad), 17.3 ( (rad) decreased to 6.6 ( rad), 6.2 ( rad), 11.3 ( rad), 38.7 ( rad), 5.4 ( rad), 6.1 ( (rad). The results show that for straight-line trajectories and great-circle trajectories, the average position tracking error of the robot joint motors after tuning is reduced by 38.84% and 31.20% respectively compared with that before tuning. This invention can achieve a significant improvement in the position tracking accuracy of the joint motors of industrial robots. The comparison results of other indicators for straight-line trajectories are shown in Table 1, and the comparison results of various indicators for great-circle trajectories are shown in Table 2.

[0039] Table 1 Comparison of Position Tracking Errors of Linear Trajectory Motors ( rad)

[0040] Table 2 Comparison of Position Tracking Errors of Large Circular Track Motors ( rad)

[0041] Compared with existing technologies, this invention optimizes the three-loop control PI parameters of the joint motor of an industrial robot by identifying the electromechanical coupling parameters, thereby improving its position tracking accuracy. Specifically, by establishing a coupling model between the motor's electromechanical coupling parameters and the three-loop control transfer function, and analytically solving the mathematical mapping relationship between the PI parameters and the motor's electromechanical coupling parameters using the frequency domain method, the control parameter tuning method designed in this invention can obtain better three-loop control parameters than empirical methods, thus significantly improving the motion control performance of the permanent magnet synchronous motor of the industrial robot joint.

[0042] The above-described specific implementations can be partially adjusted by those skilled in the art in different ways without departing from the principles and purpose of the present invention. The scope of protection of the present invention is defined by the claims and is not limited to the above-described specific implementations. All implementation schemes within the scope of the claims are bound by the present invention.

Claims

1. A method for identifying electromechanical coupling parameters and tuning motor control parameters in the frequency domain, characterized in that, After establishing a mathematical model for identifying the electrical parameters of the permanent magnet synchronous motor, a robot excitation experiment was set up. Data of the joint permanent magnet synchronous motors was collected during the experiment, and the electrical parameters of the joint permanent magnet synchronous motors were identified from them. Then, a control system model including the current loop, speed loop and position loop of the permanent magnet synchronous motor was established. Based on the electrical parameters of the joint permanent magnet synchronous motors, the optimized three-loop control PI parameters were obtained and the robot controller was set up to improve the position tracking accuracy of each joint motor.

2. The method for electromechanical coupling parameter identification and motor control parameter frequency domain tuning according to claim 1, characterized in that, The aforementioned establishment of a mathematical model for identifying the electrical parameters of a permanent magnet synchronous motor, namely, establishing... Mathematical model for identifying electrical parameters of permanent magnet synchronous motors in a coordinate system, specifically including: 1.1) Establish The voltage equation for a permanent magnet synchronous motor in the coordinate system is as follows: For a surface-mounted permanent magnet synchronous motor The voltage equation in the coordinate system is: ,in: and For permanent magnet synchronous motors and Under-axis voltage, and They are respectively and Current under the shaft, and These are the resistance and flux linkage of a permanent magnet synchronous motor, respectively. and These are the electrical angular velocity and electrical angle of the permanent magnet synchronous motor, respectively. For time, shaft and The axial inductances are equal, that is ; 1.2) Reorganize the voltage equation from step 1.1 to solve the problem caused by... The lack of rank in the axis voltage equation makes it impossible to... The problem of identifying all electrical parameters in a coordinate system is as follows: ,in: A matrix composed of electrical parameters to be identified. , , , .

3. The method for electromechanical coupling parameter identification and motor control parameter frequency domain tuning according to claim 2, characterized in that, The permanent magnet synchronous motor The current and voltage in the coordinate system are obtained by collecting data. The current and voltage in the coordinate system are obtained by inverse Park transformation, and the transformation formula is: , , , ,in: and For permanent magnet synchronous motors and Under-axis voltage, and They are respectively and Current under the shaft.

4. The method for electromechanical coupling parameter identification and motor control parameter frequency domain tuning according to claim 1, characterized in that, The acquisition of joint permanent magnet synchronous motor data specifically includes: 2.1) Based on the limitations of the robot's joint angles, angular velocities, and angular accelerations, design the robot joint trajectories for identifying the electrical parameters of the permanent magnet synchronous motor. Specifically, design the angular accelerations of each robot joint. ,in: These represent the maximum angle, maximum angular velocity, and maximum angular acceleration of the joint, respectively. By taking the intermediate time variable of the trajectory and performing a second integral on the designed angular acceleration, the robot joint excitation trajectory used to identify the electrical parameters of the permanent magnet synchronous motor can be obtained. 2.2) Perform trajectory excitation experiments for each joint of the robot in sequence according to the designed joint trajectory. Use the motor driver of each joint to collect voltage and current data, and use the encoder to collect the angle data of each joint motor. The collected data is used for electrical parameter identification of the permanent magnet synchronous motor of each joint.

5. The method for electromechanical coupling parameter identification and motor control parameter frequency domain tuning according to claim 1, characterized in that, The identification specifically includes: 3.1) Establish the basic model of the recursive least squares algorithm, that is, to minimize the L2 norm of the system output vector error, specifically: The estimated model parameters are updated in each iteration using the gradient descent principle. , where: system model , For the number of iterations, For the system output vector, Input matrix to the system, Given the parameter matrix of the model to be identified, The system's output vector is the identified value of the model parameters. , This is the forgetting factor, typically taken as 0.9 to 1. Here is the gain matrix. Covariance matrix; 3.2) Based on the voltage equation reconstructed in step 1.2, a recursive least squares algorithm is constructed to identify the electrical parameter equations. Specifically, the forgetting factor is initialized. Initial value of the resistor to be identified Initial value of inductor to be identified Initial value of magnetic flux to be identified Initial value of covariance matrix ,for Axis voltage equation, calculate output vector Calculate the input matrix Calculate the gain matrix Update the parameter matrix to be identified Update the covariance matrix ,for Axis voltage equation, calculate output vector Calculate the input matrix Calculate the gain matrix Update the parameter matrix to be identified Update the covariance matrix Then, the parameters to be identified are updated by the first recursive least squares algorithm. Used to calculate the second recursive least squares algorithm The parameters to be identified are updated by the second recursive least squares algorithm. Used to calculate the second recursive least squares algorithm until the resistance identification value Inductance identification value Magnetic link identification value They converge to near their respective nominal values.

6. The method for electromechanical coupling parameter identification and motor control parameter frequency domain tuning according to claim 1, characterized in that, The optimized three-loop control PI parameters and robot controller settings specifically include: 4.1) Establish the control system model, specifically: the open-loop transfer function of the current loop. Open-loop transfer function of the velocity loop Open-loop transfer function of the position loop Among them: the current loop PI controller stage Power inverter stage Electrical model section Dead zone delay First-order filter stage for current command , For the inverter switching cycle, Delay time for dead zone The current command first-order filter frequency, For the proportional gain of the current loop controller, For the integral gain of the current loop controller; for the speed loop PI controller stage. Torque gain stage Motor dynamics model First-order command filtering stage of the speed loop First-order feedback filter stage of the speed loop , The moment of inertia of the motor rotor. This is the motor torque gain coefficient. The first-order command filter frequency for the speed loop. The first-order feedback filter frequency of the speed loop, For the proportional gain of the speed loop controller, For the integral gain of the speed loop controller; for the position loop PI controller stage. Points system , For the proportional gain of the position loop controller, The integral gain of the position loop controller; 4.2) Based on the open-loop transfer functions of the current loop, velocity loop, and position loop established in step 4.1, using the cutoff frequency and phase margin as indices of the dynamic performance and stability of each control loop, solve for the optimized PI control parameters of each control loop. Specifically, for the open-loop transfer function of the current loop, the phase margin... ,in: Let be the cutoff frequency of the open-loop transfer function of the current loop. From the fact that the open-loop transfer amplitude of the current loop at the cutoff frequency is 1, we can obtain: The optimized PI control parameters of the current loop are obtained. , ,in: , For the open-loop transfer function of the velocity loop, the phase margin ,in: Let be the cutoff frequency of the open-loop transfer function of the velocity loop. From the fact that the open-loop transfer amplitude of the velocity loop at the cutoff frequency is 1, we can obtain: The optimized PI control parameters of the speed loop are obtained. , ,in: , For the open-loop transfer function of the position loop, the phase margin ,in: Let be the cutoff frequency of the open-loop transfer function of the position loop. From the fact that the open-loop transfer amplitude of the position loop at the cutoff frequency is 1, we can obtain: The optimized PI control parameters of the position loop are obtained. , ; 4.3) Based on the electrical parameters of the permanent magnet synchronous motor for each joint identified in step three, i.e., resistance... ,inductance and magnetic chain Calculate the optimized PI control parameters for the current loop, speed loop, and position loop: .

7. The method for electromechanical coupling parameter identification and motor control parameter frequency domain tuning according to claim 6, characterized in that, The motor torque gain It is calculated in the following way: based on the electromagnetic torque of the motor. For adopting For a surface-mounted permanent magnet synchronous motor using a vector control strategy, the electromagnetic torque simplifies to: , That is, the motor torque gain coefficient is obtained through the identified motor flux linkage. Calibration is performed, including: This represents the number of pole pairs of the motor.

8. The method for electromechanical coupling parameter identification and motor control parameter frequency domain tuning according to any one of claims 1-7, characterized in that, The robot includes: a six-axis serial industrial robot, a robot control cabinet, a Beckhoff industrial computer based on TwinCAT3, and an EtherCAT communication bus module; The joint excitation trajectory needs to be independently excited by each joint under the robot's rated load conditions. The design enables the motor to output a torque close to the rated torque and fully excite the motion trajectory within the rated speed range, while avoiding frequent acceleration and deceleration and maintaining a uniform speed operation phase. This ensures that the motor current and voltage data collected under steady-state conditions can effectively improve the identification accuracy of the electrical parameters of the permanent magnet synchronous motor.

9. A system for electromechanical coupling parameter identification and motor control parameter frequency domain tuning that implements the method of any one of claims 1-8, characterized in that, include: The system comprises a data acquisition unit, an electrical parameter identification unit, and a motor three-loop control parameter frequency domain tuning unit. Specifically: the data acquisition unit collects the three-phase current, dq-axis current, and dq-axis voltage of the joint permanent magnet synchronous motor through robot trajectory excitation experiments, generating a dataset for electrical parameter identification of the robot joint permanent magnet synchronous motor; the motor electrical parameter identification unit calculates the motor's electrical parameters based on the collected three-phase current, dq-axis current, and dq-axis voltage data through inverse Park transform. The current and voltage in the coordinate system are used to identify the motor resistance, inductance, and flux linkage parameters using a recursive least squares algorithm. The motor three-loop control parameter tuning frequency domain analysis unit calculates the transfer functions of the current loop, speed loop, and position loop based on the motor three-loop control block diagram. Using cutoff frequency and phase margin as indicators, a three-loop control system is established. The mathematical mapping relationship between parameters and motor electromechanical coupling parameters is established. Using the identified actual electromechanical coupling parameters of the motor, the optimal parameters for each control loop are calculated. The parameters were then used to verify the improved motor position tracking accuracy through trajectory tracking experiments.

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