A method of controlling a winding and unwinding motor
Patent Information
- Application Number
- CN202611273323.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-08-20
- Publication Date
- 2026-10-27
AI Technical Summary
[0004]然而，伺服驱动系统在整个卷绕过程中通常采用固定的速度环比例增益和积分增益，不能随负载惯量的变化自动调整
Smart Images
Figure CN122993570A_ABST
Abstract
Description
Technical Field
[0001] This application belongs to the technical field of winding and unwinding equipment, and in particular relates to a method for controlling winding and unwinding motors. Background Technology
[0002] Unwinding and rewinding equipment is used to complete the tasks of unwinding, conveying, and rewinding roll materials. When the equipment is running, the roll material needs to be wound onto the take-up shaft at a set linear speed.
[0003] In practical applications, existing technologies typically calculate the servo motor's rotational speed command in real time based on the current roll diameter. Since the roll diameter continuously changes during winding or unwinding, the rotational speed needs to be automatically adjusted according to the roll diameter to maintain a constant outer linear velocity—reducing the speed when the roll diameter increases and increasing it when the roll diameter decreases. Simultaneously, the roll mass and moment of inertia also change significantly with the roll diameter: it is light when empty and heavy when fully wound, with a large range of load inertia.
[0004] However, servo drive systems typically employ fixed proportional and integral gains in the speed loop throughout the winding process, failing to automatically adjust to changes in load inertia. High gain during empty winding can easily lead to vibration or overshoot; low gain during full winding results in sluggish response and increased speed tracking error. Therefore, in existing technologies, it is difficult for equipment to maintain consistent speed control performance across different winding diameter stages, ultimately impacting product quality. Summary of the Invention
[0005] In view of the above-mentioned defects or deficiencies in the prior art, it is desirable to provide a winding and unwinding motor control method that can obtain the predicted value of electromagnetic torque based on the parameter vector to be estimated at the previous moment, determine the prediction error between the current measured electromagnetic torque and the predicted value, and simultaneously obtain the gain vector recursively based on the covariance matrix at the previous moment and the current angular acceleration. The gain vector and the prediction error are used to correct the parameter vector to be estimated at the previous moment to obtain the total moment of inertia at the current moment and determine the current winding diameter. This allows the total moment of inertia to track the slow changes in winding diameter and load inertia during the winding and unwinding process in real time, improving the accuracy of winding diameter estimation and the adaptability to load changes.
[0006] This application provides a method for controlling a winding / unwinding motor, the method comprising: Obtain the estimated parameter vector and motor angular acceleration of the take-up and unwind motor at the previous moment. The estimated parameter vector includes the total moment of inertia and the load torque. The total moment of inertia includes the motor inertia and the load inertia of the motor shaft. When the previous moment is the initial moment, the corresponding estimated parameter vector and motor angular acceleration are preset values. Obtain the measured value of the electromagnetic torque of the take-up and unwind motor at the current moment; The predicted value of the electromagnetic torque at the current moment is determined based on the parameter vector to be estimated at the previous moment and the motor angular acceleration at the current moment. The prediction error at the current moment is determined based on the measured and predicted values of the electromagnetic torque at the current moment. The gain vector of the prediction error is derived by recursively calculating the covariance matrix of the previous time step and the motor angular acceleration of the current time step. The covariance matrix is used to characterize the estimation error of the parameter vector to be estimated. When the previous time step is the initial time step, the corresponding covariance matrix is a preset value. The estimated parameter vector at the previous time step is updated based on the prediction error at the current time step and the gain vector of the prediction error at the current time step to obtain the estimated parameter vector at the current time step. Extract the total moment of inertia of the take-up and unwind motors at the current moment from the parameter vector to be estimated at the current moment; Determine the current roll diameter corresponding to the total moment of inertia at the current moment; The take-up and unwind motors are controlled based on the total moment of inertia and the current roll diameter at the current moment.
[0007] In conjunction with the first aspect, in one possible implementation, the current roll diameter corresponding to the total moment of inertia at the current moment is determined as follows: Obtain multiple preset boundary values, including the maximum value of the total moment of inertia, the minimum value of the total moment of inertia, the maximum roll diameter corresponding to the maximum value, and the minimum roll diameter corresponding to the minimum value; Based on multiple boundary values, linear interpolation is performed to obtain a mapping table. The mapping table is used to define the total moment of inertia corresponding to multiple different roll diameters. The current volume diameter is obtained by querying the mapping table based on the total moment of inertia at the current moment.
[0008] In conjunction with the first aspect, in one possible implementation, the take-up and unwinding motors are controlled based on the total moment of inertia and the current roll diameter at the current moment, specifically as follows: The velocity loop proportional gain is determined based on the total moment of inertia at the current moment, the preset desired velocity loop target bandwidth, and the preset velocity loop damping coefficient. The velocity loop integral gain is determined based on the total moment of inertia at the current moment and the desired velocity loop target bandwidth. The target angular velocity of the take-up and unwinding motors is determined based on the current roll diameter and the preset direction coefficient. The direction coefficient is used to represent the rotation direction of the take-up and unwinding motors. The take-up and unwind motors are controlled based on the current speed loop proportional gain, speed loop integral gain, and target angular velocity.
[0009] In conjunction with the first aspect, one possible implementation method also includes: The formula for determining a first-order low-pass filter is as follows:
[0010] In the formula, It is a first-order low-pass filter. is the preset low-pass filter cutoff frequency, and s is the Laplace operator; Obtain the motor torque current at the current moment, and perform first-order low-pass filtering on the motor torque current and angular acceleration at the current moment based on a first-order low-pass filter. The electromagnetic torque at the current moment is determined based on the motor torque current after first-order low-pass filtering.
[0011] In conjunction with the first aspect, one possible implementation involves querying a mapping table based on the total moment of inertia at the current moment to obtain the corresponding current volume diameter, specifically as follows: If the total moment of inertia at the current moment is greater than the maximum value, then the current roll diameter is the maximum roll diameter; If the total moment of inertia at the current moment is less than the minimum value, then the current roll diameter is the minimum roll diameter; If the total moment of inertia at the current moment is between the maximum and minimum values, then interpolation calculation is performed based on the mapping table to obtain the current roll diameter.
[0012] In conjunction with the first aspect, in one possible implementation, the prediction error at the current moment is determined based on the measured and predicted values of the electromagnetic torque at the current moment, specifically as follows:
[0013] In the formula, k represents the current time. Let be the prediction error at time k; Let k be the measured value of the electromagnetic torque at time k. Let be the vector of parameters to be estimated at time k-1; Let k be the predicted value of the electromagnetic torque at time k. Let k be the data vector at time k; The vector of parameters to be estimated is determined based on the following formula:
[0014] In the formula, The total moment of inertia at time K-1, The load torque at time k-1; The data vector is determined based on the following formula:
[0015] In the formula, Let k be the motor angular acceleration after first-order low-pass filtering.
[0016] In conjunction with the first aspect, in one possible implementation, the gain vector of the prediction error is recursively derived based on the covariance matrix of the previous time step and the motor angular acceleration of the current time step, specifically as follows:
[0017] In the formula, Let be the gain vector at time k; Let be the covariance matrix at time k-1; λ is the preset forgetting factor, 0 < λ ≤ 1.
[0018] In conjunction with the first aspect, in one possible implementation, the estimated parameter vector from the previous time step is updated based on the prediction error at the current time step and the gain vector of the prediction error at the current time step to obtain the estimated parameter vector at the current time step, specifically as follows:
[0019] In the formula, Let be the vector of parameters to be estimated at time k; Let be the vector of parameters to be estimated at time k-1.
[0020] In conjunction with the first aspect, one possible implementation method also includes: Update the covariance matrix of the previous time step to obtain the covariance matrix of the current time step; The update process of the covariance matrix at the previous time step is as follows:
[0021] In the formula: Let be the covariance matrix at time k; Let I be the covariance matrix at time k-1; I is the 2×2 identity matrix.
[0022] In conjunction with the first aspect, in one possible implementation, the total moment of inertia of the winding and unwinding motors at the current moment is extracted from the parameter vector to be estimated at the current moment, specifically as follows:
[0023] In the formula, Let k be the total moment of inertia at time k. Attached Figure Description
[0024] Other features, objects, and advantages of this application will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings: Figure 1 This is a schematic diagram of the winding and unwinding structure provided in this application, as one embodiment. Figure 2 This is a flowchart illustrating the unwinding and take-up motor control method of this application in one embodiment; Figure 3 This is a structural diagram of the computer device provided in this application, as one embodiment. Detailed Implementation
[0025] The present application will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings.
[0026] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. The present application will now be described in detail with reference to the accompanying drawings and embodiments. Furthermore, the term "and / or" in this document is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. The terms "first" and "second," etc., in the specification and claims of the embodiments of this application are used to distinguish different objects, not to describe a specific order of objects.
[0027] Unwinding and winding equipment is mainly used to complete the tasks of unwinding, conveying, and winding roll materials. During operation, the roll material needs to continuously pass through guide rollers, traction rollers, and processing mechanisms at a set linear speed, and finally be wound onto the take-up shaft. Since the roll diameter changes continuously during the winding or unwinding process, the shaft speed needs to be automatically adjusted according to the roll diameter, provided that the target linear speed remains constant.
[0028] To address the issue of roll diameter acquisition, existing technologies mainly employ three types of methods. The first type is the direct measurement method, which involves measuring the roll radius by installing laser displacement sensors, ultrasonic sensors, or other roll diameter detection devices. This method is the most intuitive in principle, but it requires additional sensors and other equipment, and the sensors are susceptible to interference from factors such as mechanical vibration and installation position errors. If mechanical contact measurement is used, it may also wear or scratch the soft roll material.
[0029] The second type is the indirect calculation method, which calculates the roll diameter based on the ratio of the roll rotation speed to the roll material linear speed. However, this method is prone to large calculation fluctuations at low speeds and during start-stop phases due to the small speed signal. It is also affected by speed measurement noise, servo following error, and roll material slippage.
[0030] The third type is cumulative estimation, which estimates the current roll diameter based on the material thickness and cumulative conveying length. Its accuracy depends on the thickness parameter, the initial roll diameter, and the degree of winding compaction, and it is prone to cumulative errors as the running time increases.
[0031] However, the existing methods mentioned above mainly focus on acquiring the roll diameter and correcting the rotational speed command, and usually fail to reflect the actual situation of load inertia changing with the roll diameter in real time, and are also difficult to automatically adjust the control parameters of the servo drive system accordingly. In fact, the load inertia is small when the roll is empty and increases significantly when the roll is full. Because the existing methods lack real-time perception of inertia changes, the servo drive system generally still uses fixed speed loop proportional gain and integral gain throughout the entire winding process. This leads to the system responding too quickly under low inertia conditions, which is prone to vibration or overshoot; while under high inertia conditions, the system responds slowly, and the speed following error increases significantly. This results in large differences in the dynamic response and stability of the equipment at different roll diameter stages, making it difficult to maintain relatively consistent control quality throughout the entire process.
[0032] This application provides a method for controlling take-up and unwinding motors, applied to... Figure 1 The winding and unwinding equipment shown, such as Figure 2 As shown, the method includes: S1. Obtain the estimated parameter vector and motor angular acceleration of the winding and unwinding motor at the previous moment. The estimated parameter vector includes the total moment of inertia and the load torque. The total moment of inertia includes the motor inertia and the load inertia of the motor shaft. When the previous moment is the initial moment, the corresponding estimated parameter vector and motor angular acceleration are preset values. The vector of parameters to be estimated is determined based on the following formula:
[0033] In the formula, The total moment of inertia at time K-1, The load torque at time k-1; S2. Obtain the measured value of the electromagnetic torque of the winding and unwinding motor at the current moment; S3. Based on the parameter vector to be estimated at the previous moment and the motor angular acceleration at the current moment, determine the predicted value of the electromagnetic torque at the current moment. S4. Determine the prediction error at the current moment based on the measured and predicted values of the electromagnetic torque at the current moment; One possible implementation, S4, is as follows:
[0034] In the formula, k represents the current time. Let be the prediction error at time k; Let k be the measured value of the electromagnetic torque at time k. Let be the vector of parameters to be estimated at time k-1; Let k be the predicted value of the electromagnetic torque at time k. Let k be the data vector at time k.
[0035] The data vector is determined based on the following formula:
[0036] In the formula, Let k be the motor angular acceleration after first-order low-pass filtering.
[0037] As can be seen from the above prediction error formula, in order to enable the recursive result to track the slow changes in roll diameter and load inertia during the winding and unwinding process in real time, this application calculates the prediction error at each sampling moment. That is, using the parameter vector to be estimated updated at the previous moment and the input data such as angular acceleration at the current moment, the predicted value of the electromagnetic torque at the current moment is calculated. Then, the predicted value is compared with the electromagnetic torque actually measured at the current moment, and the difference between the two is the prediction error.
[0038] S5. Based on the covariance matrix of the previous moment and the motor angular acceleration of the current moment, the gain vector of the prediction error is recursively calculated for the current moment. The covariance matrix is used to characterize the estimation error of the parameter vector to be estimated. When the previous moment is the initial moment, the corresponding covariance matrix is a preset value. One possible implementation, S5, is as follows:
[0039] In the formula, Let be the gain vector at time k; λ is the covariance matrix at time k-1; λ is the preset forgetting factor, 0<λ≤1. The smaller the value, the greater the influence of the recursive process on the parameter vector to be estimated; the closer λ is to 1, the less emphasis is placed on the electromagnetic torque and angular acceleration at the current time, and the smoother the change of the recursive result.
[0040] S6. Update the parameter vector to be estimated at the previous time step based on the prediction error at the current time step and the gain vector of the prediction error at the current time step to obtain the parameter vector to be estimated at the current time step. One possible implementation, S6, is as follows:
[0041] In the formula, Let be the vector of parameters to be estimated at time k; Let be the vector of parameters to be estimated at time k-1.
[0042] It is worth mentioning that the covariance matrix is used to characterize the estimation error of the parameter vector to be estimated, that is, to reflect the confidence level of the guessed value of the parameter vector θ[k] at the current time. The value of this matrix directly reflects the confidence level of the current estimation result of the parameter vector to be estimated: the larger the value, the lower the confidence of the current estimation result, and the larger the subsequent correction step size; the smaller the value, the higher the confidence of the current estimation result, and the smaller the subsequent correction step size.
[0043] S7. Extract the total moment of inertia of the winding and unwinding motors at the current moment from the parameter vector to be estimated at the current moment. In one possible implementation, S7 is specifically as follows:
[0044] In the formula, Let k be the total moment of inertia at time k.
[0045] S8. Determine the current roll diameter corresponding to the total moment of inertia at the current moment; In one possible implementation, S8 is specifically: Obtain multiple preset boundary values, including the maximum value of the total moment of inertia, the minimum value of the total moment of inertia, the maximum roll diameter corresponding to the maximum value, and the minimum roll diameter corresponding to the minimum value; Based on multiple boundary values, linear interpolation is performed to obtain a mapping table. The mapping table is used to define the total moment of inertia corresponding to multiple different roll diameters. The current volume diameter is obtained by querying the mapping table based on the total moment of inertia at the current moment.
[0046] The mathematical expression for the mapping table is:
[0047] In the formula, Indicates the calibrated inertia; Indicates the current volume diameter.
[0048] Specifically, when looking up the mapping table, the total moment of inertia is used as input and the roll diameter is used as output. The endpoints corresponding to the optical axis state and the full roll state are the physical boundaries of the total moment of inertia, that is:
[0049] In the formula, The total moment of inertia corresponding to the optical axis of the unwinding or rewinding shaft; This is the total moment of inertia corresponding to a fully loaded unwinding or rewinding shaft.
[0050] One possible implementation is to consider the current total moment of inertia value. ,like Located between two adjacent calibration inertia and Between, that is:
[0051] Based on the predefined linear interpolation slope of the interval containing the current total moment of inertia:
[0052] The current roll diameter can then be calculated using linear interpolation based on two adjacent calibration points:
[0053] In the formula, The diameter is estimated based on the current moment of inertia.
[0054] S9. Control the take-up and unwind motors based on the total moment of inertia and the current roll diameter at the current moment.
[0055] In one possible implementation, S9 is specifically as follows: S91. Determine the velocity loop proportional gain based on the total moment of inertia at the current moment, the preset desired velocity loop target bandwidth, and the preset velocity loop damping coefficient. S92. Determine the velocity loop integral gain based on the total moment of inertia at the current moment and the desired velocity loop target bandwidth;
[0056] In the formula, For the target bandwidth of the desired speed loop, Let be the damping coefficient of the velocity loop. Therefore, it can be seen that when the roll diameter increases, leading to an increase in load inertia, the proportional gain and integral gain of the velocity loop increase accordingly; conversely, when the roll diameter decreases, leading to a decrease in load inertia, the proportional gain and integral gain of the velocity loop decrease accordingly.
[0057] This application calculates the proportional and integral gains of the speed loop in real time based on the current total moment of inertia, enabling the servo system to maintain similar dynamic response characteristics under different roll diameters and load inertia conditions. Specifically, when the roll diameter and load inertia increase, the controller automatically increases the proportional and integral gains proportionally to provide sufficient driving torque and maintain system response speed; when the roll diameter and load inertia decrease, the controller automatically reduces the gain to prevent vibration or overshoot caused by excessive gain. Because the gain value always maintains a matching relationship with the current actual inertia, the closed-loop bandwidth and damping ratio of the speed loop remain basically consistent under different operating conditions, thereby enabling the equipment to obtain smooth, fast, and stable speed regulation performance across the entire roll diameter range, improving the control quality and product consistency of the winding and unwinding process.
[0058] The derivation process of the formulas for determining the velocity loop proportional gain and velocity loop integral gain is explained below: Ignoring elastic deformation and high-frequency oscillation components in the mechanical transmission system, and considering only the rigid overall motion behavior of the system in the low-frequency range, the dynamic relationship between the electromagnetic torque and the motor angular velocity can be approximated as a pure integral element, i.e., the rate of change of the angular velocity is proportional to the electromagnetic torque and inversely proportional to the total moment of inertia at the current moment.
[0059] If the speed loop uses a parallel PI controller, the controller can be represented as:
[0060] In the formula: For the velocity loop proportional gain, This is the integral gain of the velocity loop.
[0061] By combining the two formulas above to form a velocity closed loop and comparing the coefficients of a standard second-order system, we can obtain the formula in S92.
[0062] This application automatically updates the speed loop proportional gain and integral gain based on the total moment of inertia, so that the servo control parameters match the current load state, avoiding the problems of vibration or overshoot caused by fixed gain under small inertia state, and slow response and increased following error under large inertia state.
[0063] S93. Determine the target angular velocity of the take-up and unwinding motors based on the current roll diameter and the preset direction coefficient. The direction coefficient is used to represent the rotation direction of the take-up and unwinding motors. Obtain the current volume size Then, the target angular velocity of the take-up and unwinding motors can be calculated based on the target linear velocity. Let... Let be the target linear velocity, and i be the transmission ratio, representing the ratio of the motor angular velocity to the reel angular velocity. Let be the direction coefficient, then the target angular velocity of the motor is:
[0064] In the formula, Used to distinguish between the winding direction and the unwinding direction; when the target linear speed... When the current roll diameter remains constant, the larger the current roll diameter, the higher the target angular velocity of the motor. The lower the current roll diameter, the smaller the target angular velocity of the motor. The higher. Therefore, through real-time updates And calculate the target angular velocity This can maintain a constant linear speed on the outer edge of the roll material.
[0065] S94. Control the take-up and unwind motors based on the current speed loop proportional gain, speed loop integral gain, and target angular velocity.
[0066] In S94, this application can further ensure the stable operation of the winding and unwinding equipment under different states such as optical axis, half roll and full roll by smoothly updating the roll diameter, speed command and servo gain.
[0067] This application calculates the target speed of the servo motor based on the target linear speed and the current roll diameter, so that the motor speed decreases accordingly when the winding roll diameter increases and increases accordingly when the unwinding roll diameter decreases, thereby maintaining a constant output linear speed of the roll material.
[0068] It is worth mentioning that in actual winding and unwinding servo systems, there are usually elastic components such as couplings, synchronous belts, reduction gears, and reel shafts between the motor and the load. Therefore, the system will have resonant and anti-resonant frequencies. Near these frequencies, the amplitude and phase of the servo system will change drastically, and the equivalent moment of inertia, as represented by electromagnetic torque and angular acceleration, will no longer be a stable constant but will exhibit obvious frequency-dependent characteristics. Without low-pass filtering, the dynamic components of the resonant or anti-resonant frequency bands will enter the least-squares recursive data during the subsequent calculation of the total moment of inertia, causing the calculated equivalent total moment of inertia to be affected by the resonant point, resulting in fluctuations, abrupt changes, or deviations from the low-frequency rigid body inertia. Based on the above reasons, one possible implementation is that this application performs the same low-pass filtering on the motor torque current and angular acceleration at the current moment, specifically: The formula for determining a first-order low-pass filter is as follows:
[0069] In the formula, It is a first-order low-pass filter. is the preset low-pass filter cutoff frequency, and s is the Laplace operator; Obtain the motor torque current at the current moment, and perform first-order low-pass filtering on the motor torque current and angular acceleration at the current moment based on a first-order low-pass filter. The electromagnetic torque at the current moment is determined based on the motor torque current after first-order low-pass filtering.
[0070] In this application, the first-order low-pass filter not only suppresses current sampling noise and speed feedback noise, but also reduces the influence of mechanical resonance and anti-resonance frequency bands on the total moment of inertia recursion. Through low-pass filtering, this application ensures that the data participating in the total moment of inertia recursion primarily reflects the low-frequency rigid body characteristics of the overall motion of the motor and load, while filtering out high-frequency dynamic components near the resonance and anti-resonance frequencies. This processing reduces the impact of mechanical resonance on the total moment of inertia recursion results, improving the stability and reliability of subsequent roll diameter estimation, speed command calculation, and servo gain tuning.
[0071] In one possible implementation, the current volume diameter is obtained by querying a mapping table based on the total moment of inertia at the current moment, specifically as follows: If the total moment of inertia at the current moment is greater than the maximum value, then the current roll diameter is the maximum roll diameter; If the total moment of inertia at the current moment is less than the minimum value, then the current roll diameter is the minimum roll diameter; If the total moment of inertia at the current moment is between the maximum and minimum values, then interpolation calculation is performed based on the mapping table to obtain the current roll diameter.
[0072] In other words, this application relates to the total moment of inertia at the current moment. use and By limiting the time to obtain the final value of the total moment of inertia. :
[0073] This application measures the total moment of inertia under optical axis, full roll, and several intermediate roll diameter conditions, and establishes a mapping table between the total moment of inertia and the roll diameter through offline fitting. The total moment of inertia corresponding to the optical axis condition is set as the lower limit, and the total moment of inertia corresponding to the full roll condition is set as the upper limit, to constrain the recursive results of the online total moment of inertia. When the recursive results exceed a reasonable range or lack sufficient reliability, the previous valid value is maintained to avoid abrupt changes in roll diameter, rotational speed, and control gain caused by abnormal results.
[0074] One possible implementation method also includes: Update the covariance matrix of the previous time step to obtain the covariance matrix of the current time step; The update process of the covariance matrix at the previous time step is as follows:
[0075] In the formula: Let be the covariance matrix at time k; Let be the covariance matrix at time k-1; λ be the preset forgetting factor; and I be the 2×2 identity matrix.
[0076] The process of determining the mapping relationship table will be explained next through Example 1: Specifically, during the offline calibration phase, N known volume diameter states are selected as calibration points.
[0077]
[0078] Let the first The actual roll diameter of each calibration point is The calibration points are arranged in ascending order of roll diameter, and can be represented as follows:
[0079] It should be noted that the calibration points should cover the entire working range of the equipment, including the optical axis state, the full roll state, and several intermediate roll diameter states. In actual implementation, both calibration accuracy and operational complexity should be considered.
[0080] At each roll diameter calibration point The following steps utilize the aforementioned method with a forgetting factor to obtain the corresponding moment of inertia. Specifically: during the calibration stage, a laser or ultrasonic distance sensor is installed to measure the distance between the outer surface of the roll material and the fixed point in real time, converting it into the current roll diameter value; when the sensor reading equals the preset calibration point, the corresponding total moment of inertia is automatically recorded. .
[0081] To reduce the total moment of inertia obtained in a single operation The random error can be repeated M times under the same roll diameter condition, and the results obtained from multiple tests can be analyzed. Take the average value as the calibration inertia corresponding to that calibration point. .
[0082]
[0083] in, Indicates the first The moment of inertia used is obtained by recursively calculating the total moment of inertia at each roll diameter calibration point for the mth rotation. Because... The upper and lower bound constraints have already been completed in the recursive phase, therefore each of the formulas... All are effective inertia values.
[0084] Based on the actual roll diameter at each calibration point and its corresponding calibrated inertia This yields a set of discrete inertia-roll diameter calibration data:
[0085] This calibration data is used to construct an inertia-volume diameter mapping table.
[0086] The aforementioned offline calibration method, based on actual equipment and roll material testing, can incorporate factors that are difficult to model precisely, such as material properties, winding tightness, transmission mechanism inertia, and equipment assembly errors, into the calibration relationship. Compared to directly calculating the roll diameter based on theoretical parameters such as material density, thickness, width, and compaction degree, it can reduce the impact of parameter errors on the accuracy of roll diameter calculation and reduce the amount of online calculation by using a lookup table.
[0087] Furthermore, the conversion from inertia to roll diameter is achieved using lookup tables and linear interpolation, which reduces computational complexity, provides good real-time performance, and facilitates implementation in servo drives or motion controllers. When the number of calibration points is sufficient, piecewise linear interpolation can approximate the nonlinear relationship between rotational inertia and roll diameter well, and provide a stable and continuous roll diameter input for subsequent target speed calculation and automatic servo gain tuning.
[0088] The derivation of the prediction error formula is explained below: The equations of motion for the winding and unwinding motors are:
[0089] In the formula, This represents the motor speed, measured in rad / s. Let be the angular acceleration of the motor, and let The unit is rad / s 2 ; The electromagnetic torque output by the motor, in N. m. Load torque, in N. m.
[0090] It is worth mentioning that, :in, This is the sum of the motor's inertia and the load inertia referred to the motor shaft. This refers to the motor's inertia. The load inertia is calculated for the motor shaft, and the unit is kg. m 2 .
[0091] In the formula, the electromagnetic torque output by the motor is... It can be expressed by torque current as:
[0092] In the formula, The torque constant of the motor is expressed in N. m / A; This represents the motor torque current, measured in amperes (A). The equation of motion for the motor can then be further expressed as:
[0093] As can be seen from the above formula, during the operation of the motor, if the motor torque current can be collected... and motor angular velocity And calculate angular acceleration Then, the current total moment of inertia can be determined based on the relationship between electromagnetic torque and angular acceleration. Perform the calculation.
[0094] To suppress current sampling noise, encoder quantization error, and high-frequency mechanical vibration, this embodiment uses the same first-order low-pass filter for both current and rotational speed:
[0095] In the formula, This is the cutoff frequency of the low-pass filter, measured in rad / s. The filtered torque current, motor speed, and motor acceleration can be expressed as follows:
[0096] In the formula, ( s ( ) represents the filtered current in the frequency domain; ( s () represents the filtered rotational speed in the frequency domain; ( s () represents the filtered angular acceleration of the motor in the frequency domain.
[0097] Due to the first-order low-pass filter For a linear time-invariant system, the filtered equations of motion for the motor can be obtained:
[0098] As can be seen from the above equation, after the same first-order low-pass filtering, the electromagnetic torque and angular velocity still satisfy the motor's motion equations, and therefore will not change the current total moment of inertia. The physical meaning of .
[0099] Within a short recursive window, the load torque can be treated as a constant or slowly changing quantity. Based on the filtered equations of motion, the following discrete model can be established:
[0100] In the formula, K represents the sampling point at time k. Let be the electromagnetic torque of the motor at time k; Let k be the total moment of inertia at time k, and k be the quantity that needs to be recursively calculated. Let k be the angular acceleration of the motor at time k; Let be the load torque at time k, which is an unknown quantity.
[0101] To facilitate computer processing, this application rewrites the discrete model into a linear regression form:
[0102] In the formula, ; ; ; : represents measurement noise and modeling error, and is an unknown quantity.
[0103] The prediction error is then:
[0104] It is worth mentioning that the magnitude of this prediction error directly reflects the applicability of the parameter vector to be estimated at the previous moment under the current new operating conditions—the larger the error, the more significant the change in load state, and the more necessary it is to use this error to make a larger correction to the parameter estimate; conversely, it indicates that the current parameter estimate only needs a small adjustment. By continuously calculating the prediction error and using it to drive the recursive update of the parameter vector to be estimated, the algorithm can maintain effective tracking of the current moment of inertia and load torque throughout the entire winding and unwinding process, thus providing an accurate basis for subsequent automatic tuning of the speed loop gain and winding diameter estimation.
[0105] It should be noted that although the operations of the method of the present invention are described in a specific order in the accompanying drawings, this does not require or imply that these operations must be performed in that specific order, or that all of the operations shown must be performed to achieve the desired result. On the contrary, the steps depicted in the flowchart may be performed in a different order. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps.
[0106] On the other hand, this application also provides a computer-readable storage medium, which may be included in a computer device or exist independently without being assembled into the computer device. The aforementioned computer-readable storage medium stores one or more programs that, when used by one or more processors, execute the methods described in this application. For example, it may execute... Figure 2 The steps of the method shown.
[0107] In another aspect, this application also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements... Figure 2 The steps of the method shown.
[0108] On the other hand, this application also provides a computer-readable storage medium, which may be included in a computer device or exist independently without being assembled into the computer device. The aforementioned computer-readable storage medium stores one or more programs that, when used by one or more processors, execute the methods described in this application. For example, it may execute... Figure 2 The steps of the method shown.
[0109] This application provides a computer program product including instructions that, when executed, cause the method described in this application to be performed. For example, it can execute... Figure 2 The steps of the method shown.
[0110] The following is for reference. Figure 3 , Figure 3 A schematic diagram of the structure of a computer device suitable for implementing the embodiments of this application is shown. like Figure 3 As shown, the computer system includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes based on programs stored in read-only memory (ROM) 302 or programs loaded from storage section 308 into random access memory (RAM) 303. RAM 303 also stores various programs and data required for the system's operating instructions. CPU 301, ROM 302, and RAM 303 are interconnected via bus 304. Input / output (I / O) interface 305 is also connected to bus 304.
[0111] The following components are connected to I / O interface 305: an input section 306 including a keyboard, mouse, etc.; an output section 307 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN card, modem, etc. The communication section 309 performs communication processing via a network such as the Internet. Drive 310 is also connected to I / O interface 305 as needed. Removable media 311, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 310 as needed so that computer programs read from them can be installed into storage section 308 as needed.
[0112] Specifically, according to embodiments of this application, Figure 2 The described process can be implemented as a computer software program. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowchart. In such an embodiment, the computer program contains program code for performing the methods shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via communication section 309, and / or installed from removable medium 311. When the computer program is executed by central processing unit (CPU) 301, it performs the functions defined in the system of this application.
[0113] On another front, this application also provides a computer-readable storage medium, which may be included in an electronic device or exist independently without being assembled into the electronic device. The aforementioned computer-readable storage medium stores one or more programs that, when used by one or more processors, execute the methods of this application. For example, it may execute... Figure 2 The steps of the method shown.
[0114] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.
[0115] The above description is merely a preferred embodiment of this application and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in this application is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the inventive concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features with similar functions disclosed in this application.
Claims
1. A method for controlling a take-up and unwinding motor, characterized in that, The method includes: Obtain the estimated parameter vector and motor angular acceleration of the take-up and unwind motor at the previous moment. The estimated parameter vector includes the total moment of inertia and the load torque. The total moment of inertia includes the motor inertia and the load inertia of the motor shaft. When the previous moment is the initial moment, the corresponding estimated parameter vector and motor angular acceleration are preset values. Obtain the measured value of the electromagnetic torque of the take-up and unwind motor at the current moment; The predicted value of the electromagnetic torque at the current moment is determined based on the parameter vector to be estimated at the previous moment and the motor angular acceleration at the current moment. The prediction error at the current moment is determined based on the measured value and the predicted value of the electromagnetic torque at the current moment; The gain vector of the prediction error is derived by recursively calculating the current time based on the covariance matrix of the previous time and the motor angular acceleration at the current time; the covariance matrix is used to characterize the estimation error of the parameter vector to be estimated, and when the previous time is the initial time, the corresponding covariance matrix is a preset value. Based on the prediction error at the current time and the gain vector of the prediction error at the current time, update the parameter vector to be estimated at the previous time to obtain the parameter vector to be estimated at the current time. Extract the total moment of inertia of the take-up and unwind motors at the current moment from the parameter vector to be estimated at the current moment; Determine the current roll diameter corresponding to the total moment of inertia at the current moment; The take-up and unwind motors are controlled based on the total moment of inertia and the current roll diameter at the current moment.
2. The method according to claim 1, characterized in that, Specifically, the current roll diameter corresponding to the total moment of inertia at the current moment is determined as follows: Obtain multiple preset boundary values, including the maximum value of the total moment of inertia, the minimum value of the total moment of inertia, the maximum roll diameter corresponding to the maximum value, and the minimum roll diameter corresponding to the minimum value; Based on the multiple boundary values, linear interpolation is performed to obtain a mapping table, which is used to define the total moment of inertia corresponding to multiple different roll diameters. The current volume diameter is obtained by querying the mapping table based on the total moment of inertia at the current moment.
3. The method according to claim 2, characterized in that, Based on the total moment of inertia at the current moment and the current roll diameter, the take-up and unwinding motors are controlled as follows: The velocity loop proportional gain is determined based on the total moment of inertia at the current moment, the preset desired velocity loop target bandwidth, and the preset velocity loop damping coefficient. The velocity loop integral gain is determined based on the total moment of inertia at the current moment and the desired velocity loop target bandwidth. The target angular velocity of the take-up and unwinding motor is determined based on the current roll diameter and a preset direction coefficient, wherein the direction coefficient is used to characterize the rotation direction of the take-up and unwinding motor. The take-up and unwind motors are controlled based on the current speed loop proportional gain, speed loop integral gain, and target angular velocity.
4. The method according to claim 1, characterized in that, The method further includes: A first-order low-pass filter is determined, and the formula for determining the first-order low-pass filter is as follows: In the formula, It is a first-order low-pass filter. is the preset low-pass filter cutoff frequency, and s is the Laplace operator; Obtain the motor torque current at the current moment, and perform first-order low-pass filtering on the motor torque current and angular acceleration at the current moment based on the first-order low-pass filter. The electromagnetic torque at the current moment is determined based on the motor torque current after first-order low-pass filtering.
5. The method according to claim 2, characterized in that, Based on the total moment of inertia at the current moment, the mapping table is consulted to obtain the corresponding current volume diameter, specifically: If the total moment of inertia at the current moment is greater than the maximum value, then the current roll diameter is the maximum roll diameter; If the total moment of inertia at the current moment is less than the minimum value, then the current roll diameter is the minimum roll diameter; If the total moment of inertia at the current moment is between the maximum and minimum values, then interpolation calculation is performed based on the mapping table to obtain the current roll diameter.
6. The method according to claim 4, characterized in that, The prediction error at the current moment is determined based on the measured value and the predicted value of the electromagnetic torque at the current moment, specifically as follows: In the formula, k represents the current time. Let be the prediction error at time k; Let k be the measured value of the electromagnetic torque at time k. Let be the vector of parameters to be estimated at time k-1; Let k be the predicted value of the electromagnetic torque at time k; Let k be the data vector at time k; The vector of parameters to be estimated is determined based on the following formula: In the formula, The total moment of inertia at time K-1, The load torque at time k-1; The data vector is determined based on the following formula: In the formula, Let k be the motor angular acceleration after first-order low-pass filtering.
7. The method according to claim 6, characterized in that, Based on the covariance matrix of the previous moment and the motor angular acceleration of the current moment, the gain vector of the prediction error for the current moment is recursively derived as follows: In the formula, Let be the gain vector at time k; Let be the covariance matrix at time k-1; λ is the preset forgetting factor, 0 < λ ≤ 1.
8. The method according to claim 7, characterized in that, The estimated parameter vector from the previous time step is updated based on the prediction error at the current time step and the gain vector of the prediction error at the current time step, to obtain the estimated parameter vector at the current time step, specifically as follows: In the formula, Let be the vector of parameters to be estimated at time k; Let be the vector of parameters to be estimated at time k-1.
9. The method according to claim 8, characterized in that, The method further includes: Update the covariance matrix of the previous time step to obtain the covariance matrix of the current time step; The update process of the covariance matrix at the previous time step is as follows: In the formula: Let be the covariance matrix at time k; Let I be the covariance matrix at time k-1; I is the 2×2 identity matrix.
10. The method according to claim 9, characterized in that, From the parameter vector to be estimated at the current moment, extract the total moment of inertia of the take-up and unwinding motors at the current moment, specifically: In the formula, Let k be the total moment of inertia at time k.