Sparse synchronous copper calendering profile control method, system, device, product, and medium

Abstract

The present application relates to the field of production line control, and provides a sparse synchronous copper calendering distribution control method, system, device, product and medium, comprising: collecting initial production line data; obtaining a virtual clock phase correction amount according to sparse correction data, performing data synchronization on the initial production line data through the virtual clock phase correction amount, and obtaining aligned production line data; selecting a data iteration strategy, performing control parameter calculation on the data iteration strategy and the aligned production line data, and obtaining initial control parameters; calculating a loss parameter drop rate of the initial control parameters, determining a loss parameter drop rate threshold, updating the initial control parameters and calculating the loss parameter drop rate until the loss parameter drop rate is less than the loss parameter drop rate threshold, and obtaining updated control parameters; obtaining target control parameters through an edge control period, a working condition disturbance index and the updated control parameters, and performing copper calendering distribution control through the target control parameters.

Description

Technical Field

[0001] This invention relates to the field of production line control technology, and in particular to a method, system, equipment, product, and medium for controlling the distribution of sparse synchronous copper rolling. Background Technology

[0002] A continuous rolling production line for copper billets typically consists of multiple continuous stands. There is a coupling relationship between the roll gap, roll speed, tension, and roll temperature of each stand. Fluctuations in the hardness of the incoming material, roll surface wear, and roll temperature drift are transmitted along the speed chain and tension chain.

[0003] Existing multi-rack distributed control solutions typically rely on high-frequency communication, hardware timestamps, or dedicated time-sensitive networks to maintain synchronization between nodes. For low-cost edge controllers, continuously exchanging high-frequency synchronization messages or full status data consumes communication bandwidth and increases the communication processing burden.

[0004] Existing adaptive model predictive control typically performs rolling optimization with fixed complexity in each control cycle. In the steady-state phase, the computation of the full nonlinear model and the fully coupled matrix generates unnecessary edge computing load; in the transient phase, the reduced-order model or fixed sparse matrix may fail to reflect the strong coupling, and for the processor, the fixed iteration frequency also leads to a waste of computing power. Summary of the Invention

[0005] This invention aims to at least solve one of the technical problems existing in related technologies. To this end, this invention provides a method, system, equipment, product, and medium for controlling the distribution of sparse synchronous copper rolling, thereby enabling control of copper rolling production lines.

[0006] This invention provides a method for controlling the sparse synchronous copper rolling distribution, comprising: S1: Set up a data acquisition unit, which collects data to obtain initial production line data; S2: Receive sparse correction data, obtain virtual clock phase correction amount based on sparse correction data, and synchronize the initial production line data with the virtual clock phase correction amount to obtain aligned production line data. S3: Obtain the operating status, select a data iteration strategy based on the operating status, and calculate the control parameters using the data iteration strategy and aligned production line data to obtain the initial control parameters; S4: Calculate the loss parameter decrease rate of the initial control parameters, determine the loss parameter decrease rate threshold, update the initial control parameters and calculate the loss parameter decrease rate until the loss parameter decrease rate is less than the loss parameter decrease rate threshold, and obtain the updated control parameters; S5: Calculate the edge control cycle for updating control parameters, calculate the operating condition disturbance index, obtain the target control parameters through the edge control cycle, operating condition disturbance index and updated control parameters, and perform copper rolling distribution control through the target control parameters.

[0007] According to the sparse synchronous copper rolling distribution control method provided by the present invention, in step S1, the data acquisition unit includes an inlet thickness measurement unit, an outlet thickness measurement unit, a roll gap position sensor, a roll speed encoder, a tension sensor, a roll surface temperature sensor, and a rolling force sensor. The initial production line data includes inlet copper plate thickness, outlet copper plate thickness, roll gap position, roll speed, copper plate tension, roll surface temperature, and rolling force.

[0008] According to the sparse synchronous copper rolling distribution control method provided by the present invention, step S2 further includes: S21: Receive sparse correction data, obtain a phase deviation estimate based on the sparse correction data, and obtain a drift compensation term based on the initial production line data; S22: Obtain historical drift error, determine drift compensation term coefficients based on the historical drift error, statistically analyze the synchronization convergence parameters of the sparse correction data, and obtain deviation estimate coefficients based on the synchronization convergence parameters; S23: The virtual clock phase correction amount is obtained through the drift compensation term, phase deviation estimate, drift compensation term coefficient, and deviation estimate coefficient. The initial production line data is synchronized using the virtual clock phase correction amount to obtain aligned production line data.

[0009] According to the sparse synchronous copper rolling distribution control method provided by the present invention, step S3 further includes: S31: Obtain production line control parameters, obtain the operating condition state based on the production line control parameters, construct a candidate iterative strategy including reduced-order linear quadratic adjustment and nonlinear model prediction, and select a data iteration strategy from the candidate iterative strategies based on the operating condition state. S32: Decouple the aligned production line data to obtain decoupled production line data, and calculate the control parameters using the decoupled production line data and the data iteration strategy to obtain the initial control parameters.

[0010] According to the sparse synchronous copper rolling distribution control method provided by the present invention, in step S4, a production data prediction model is constructed, the initial control parameters are input into the production data prediction model to obtain predicted production parameters, the control loss is calculated through the predicted production parameters, and the decrease rate of the loss parameter is calculated based on the control loss.

[0011] According to the sparse synchronous copper rolling distribution control method provided by the present invention, in step S5, a threshold for operating condition disturbance index and a threshold for edge control period are set, and a conservative control parameter is determined. When the operating condition disturbance index is greater than the threshold for operating condition disturbance index or the edge control period is greater than the threshold for edge control period, the conservative control parameter is used as the target control parameter; otherwise, the updated control parameter is used as the target control parameter.

[0012] This invention also provides a sparse synchronous copper rolling distribution control system, comprising: Initial production line data module: Used to set up the data acquisition unit, which collects data to obtain the initial production line data; Data synchronization module: used to receive sparse correction data, obtain virtual clock phase correction amount based on sparse correction data, and synchronize the initial production line data with the virtual clock phase correction amount to obtain aligned production line data; Initial control parameter module: used to obtain the operating condition status, select a data iteration strategy based on the operating condition status, and calculate the control parameters by using the data iteration strategy and aligned production line data to obtain the initial control parameters; Parameter iteration module: used to calculate the rate of decrease of the loss parameter of the initial control parameters, determine the threshold of the rate of decrease of the loss parameter, update the initial control parameters and calculate the rate of decrease of the loss parameter until the rate of decrease of the loss parameter is less than the threshold of the rate of decrease of the loss parameter, and obtain the updated control parameters; Target control parameter module: used to calculate the edge control cycle for updating control parameters, calculate the operating condition disturbance index, obtain the target control parameters through the edge control cycle, operating condition disturbance index and updated control parameters, and perform copper rolling distribution control through the target control parameters.

[0013] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of any of the above-described sparse synchronous copper rolling distribution control methods.

[0014] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the sparse synchronous copper rolling distribution control method described above.

[0015] The present invention also provides a computer program product, the computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, which, when executed by a computer, enable the computer to perform the steps of any of the sparse synchronous copper rolling distribution control methods described above.

[0016] The above-described one or more technical solutions in the embodiments of the present invention have at least one of the following technical effects: The sparse synchronous copper rolling distribution control method, system, equipment, product, and medium provided by this invention can achieve data alignment with relatively low computing power through virtual clock phase correction, without consuming excessive computing power for data alignment. The data iteration strategy can be selected according to the working conditions, which can reduce the demand for computing power. The loss parameter decay rate can effectively control the number of iterations of the control parameters, avoiding the waste of computing power caused by excessive iterations.

[0017] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0019] Figure 1 This is a flowchart illustrating the sparse synchronous copper rolling distribution control method provided by the present invention.

[0020] Figure 2 This is a schematic diagram of the sparse synchronous copper rolling distribution control system provided by the present invention.

[0021] Figure 3 This is a schematic diagram of the sparse synchronous copper rolling distribution control device provided by the present invention.

[0022] Figure label: 100. Initial production line data module; 200. Data synchronization module; 300. Initial control parameter module; 400. Parameter iteration module; 500. Target control parameter module; 810. Processor; 820. Communication interface; 830. Memory; 840. Communication bus. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention. The following embodiments are used to illustrate this invention but cannot be used to limit the scope of this invention.

[0024] In the description of the embodiments of the present invention, it should be noted that the terms "first", "second" and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0025] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0026] The following is combined with Figures 1 to 3 Specific embodiments of the present invention are described below. Figure 1 This is a flowchart illustrating the sparse synchronous copper rolling distribution control method provided by the present invention, including: S1: Set up a data acquisition unit, which collects data to obtain initial production line data; Furthermore, the purpose of this stage is to collect data to obtain initial production line data. Specifically, in step S1, the data acquisition unit includes an inlet thickness measurement unit, an outlet thickness measurement unit, a roll gap position sensor, a roll speed encoder, a tension sensor, a roll surface temperature sensor, and a rolling force sensor. The initial production line data includes the inlet copper plate thickness, the outlet copper plate thickness, the roll gap position, the roll speed, the copper plate tension, the roll surface temperature, and the rolling force.

[0027] The specific implementation method for the above steps in this embodiment is as follows: First, a data acquisition unit needs to be set up, including an inlet thickness measurement unit, an outlet thickness measurement unit, a roll gap position sensor, a roll speed encoder, a tension sensor, a roll surface temperature sensor, and a rolling force sensor. The inlet thickness measurement unit measures the thickness of the copper plate at the production line inlet; the outlet thickness measurement unit measures the thickness of the copper plate at the production line outlet; the roll gap position sensor measures the roll gap position; the roll speed encoder measures the roll speed; the tension sensor measures the copper plate tension; the roll surface temperature sensor measures the roll surface temperature; and the rolling force sensor measures the rolling force applied to the copper plate. When these parameters are measured, the time of measurement is used as a time stamp to obtain the initial production line data.

[0028] S2: Receive sparse correction data, obtain virtual clock phase correction amount based on sparse correction data, and synchronize the initial production line data with the virtual clock phase correction amount to obtain aligned production line data. Furthermore, the objective of this stage is to obtain the virtual clock phase correction value, thereby performing data synchronization and obtaining aligned production line data. Specifically, step S2 further includes: S21: Receive sparse correction data, obtain a phase deviation estimate based on the sparse correction data, and obtain a drift compensation term based on the initial production line data; S22: Obtain historical drift error, determine drift compensation term coefficients based on the historical drift error, statistically analyze the synchronization convergence parameters of the sparse correction data, and obtain deviation estimate coefficients based on the synchronization convergence parameters; S23: The virtual clock phase correction amount is obtained through the drift compensation term, phase deviation estimate, drift compensation term coefficient, and deviation estimate coefficient. The initial production line data is synchronized using the virtual clock phase correction amount to obtain aligned production line data.

[0029] The specific implementation method for the above steps in this embodiment is as follows: In actual production, due to the different temperature sensitivities and data acquisition principles of various data acquisition units, the sampling intervals of the data collected by each data acquisition unit will drift and experience occasional errors as production progresses, leading to misalignment. This drift and occasional error trend is usually relatively fixed. To address this issue and overcome the aforementioned problems, this invention proposes a method for aligning production line data using virtual clock phase correction. First, sparse correction data needs to be received. This sparse correction data consists of the data collected by each data acquisition unit, transmitted every 10ms to 50ms within a 100ms to 500ms time window. After receiving the sparse correction data, the control unit calculates the estimated phase deviation of the i-th data acquisition unit at time k based on the average deviation of the transmission time of each sparse correction data point within the time window relative to the time stamp of the sparse correction data in the previous time window. On a continuous copper billet rolling production line, due to the high temperature, the measurement results of each data acquisition unit will drift. The drift compensation term for the i-th data acquisition unit at time k can be estimated based on the roll surface temperature. .

[0030] Subsequently, the historical drift compensation terms are obtained and used as historical drift errors. The coefficients of the drift compensation terms can then be determined based on these historical drift errors. Its value ranges from 0 to 1, with a default initial value of 0.2. Additionally, it is necessary to estimate the synchronization convergence parameter of the sparse correction data. The synchronization convergence parameter is the absolute value of the average deviation of the sparse correction data relative to the standard data acquisition time point. The deviation estimate coefficient can be estimated based on the synchronization convergence parameter. Its value ranges from 0 to 1, with a default initial value of 0.5.

[0031] Subsequently, the virtual clock phase correction of the i-th data acquisition unit at time k is obtained through the drift compensation term, phase deviation estimate, drift compensation term coefficient, and deviation estimate coefficient. : in, This represents the virtual clock phase correction value for the i-th data acquisition unit at time k-1, which is the previous time. If there was no previous virtual clock phase correction value, the value is 0. By directly correcting the time stamps of each data point in the initial production line data based on this virtual clock phase correction value, aligned production line data can be obtained. This ensures that the production line data obtained by each data acquisition unit is roughly aligned, avoiding misalignment that could prevent control parameter calculation. Furthermore, compared to aligning each production line data point sequentially, this method can effectively save computing resources within acceptable error limits, adapting to the lower-performance processors typically equipped in production equipment and meeting timeliness requirements.

[0032] S3: Obtain the operating status, select a data iteration strategy based on the operating status, and calculate the control parameters using the data iteration strategy and aligned production line data to obtain the initial control parameters; Furthermore, the objective of this stage is to select a data iteration strategy to calculate the control parameters and obtain the initial control parameters. Specifically, step S3 further includes: S31: Obtain production line control parameters, obtain the operating condition state based on the production line control parameters, construct a candidate iterative strategy including reduced-order linear quadratic adjustment and nonlinear model prediction, and select a data iteration strategy from the candidate iterative strategies based on the operating condition state. S32: Decouple the aligned production line data to obtain decoupled production line data, and calculate the control parameters using the decoupled production line data and the data iteration strategy to obtain the initial control parameters.

[0033] The specific implementation method for the above steps in this embodiment is as follows: First, production line control parameters are needed; these are the parameters output by the production line to control various parts of the line. The operating state is determined based on these parameters, including critical and stable operating states. A critical operating state occurs when the production line control parameters are close to their limits; otherwise, a stable operating state is considered. Subsequently, an iterative strategy is constructed, including reduced-order linear quadratic adjustment and nonlinear model prediction. Here, nonlinear model prediction is used under critical operating conditions, while reduced-order linear quadratic adjustment is used under stable operating conditions.

[0034] Subsequently, the alignment production line data is decoupled, which means that some less important parameters are hidden, and only the parameters that are more important for regulating the production line are retained, thus obtaining decoupled production line data. This decoupled production line data is then input into the selected data iteration strategy for control parameter calculation, in order to calculate the control parameters for regulating the equipment in the production line, thereby ensuring the quality of the copper plates produced by the production line. This yields the initial control parameters.

[0035] S4: Calculate the loss parameter decrease rate of the initial control parameters, determine the loss parameter decrease rate threshold, update the initial control parameters and calculate the loss parameter decrease rate until the loss parameter decrease rate is less than the loss parameter decrease rate threshold, and obtain the updated control parameters; Furthermore, the objective of this stage is to calculate the rate of decrease of the loss parameter, thereby updating the initial control parameters to obtain updated control parameters. Specifically, in step S4, a production data prediction model is constructed, the initial control parameters are input into the production data prediction model to obtain predicted production parameters, the control loss is calculated using the predicted production parameters, and the rate of decrease of the loss parameter is calculated based on the control loss.

[0036] The specific implementation method for the above steps in this embodiment is as follows: First, a production data prediction model needs to be constructed. Initial control parameters are input into this model, which then predicts the production line data obtained after adjusting the production line according to these initial parameters, thus yielding the predicted production parameters. Next, an ideal production line data point is determined as the ideal production line data. Finally, the control loss at time k can be assessed based on the deviation between the predicted production parameters and the ideal production line data. Then calculate the rate of decrease of the loss parameter at time k. : in, The control loss at time k-1, To prevent constants with a denominator of 0, the initial control parameters are then updated further with the goal of minimizing the control loss. This involves continuously adjusting the initial control parameters to minimize the control loss and calculating the rate of decrease in the loss parameter after adjustment. The process continues until the rate of decrease in the loss parameter falls below a preset threshold. At this point, further updates to the initial control parameters are considered pointless and a waste of computational resources, and the updates are stopped, yielding the updated control parameters. Here, the threshold for the rate of decrease in the loss parameter is calculated based on the mean and standard deviation of historical loss parameter decrease rates.

[0037] S5: Calculate the edge control cycle for updating control parameters, calculate the operating condition disturbance index, obtain the target control parameters through the edge control cycle, operating condition disturbance index and updated control parameters, and perform copper rolling distribution control through the target control parameters.

[0038] Furthermore, the purpose of this stage is to calculate the edge control cycle and operating condition disturbance index to obtain the target control parameter, and then to control the copper rolling distribution using the target control parameter. Specifically, in step S5, a threshold for the operating condition disturbance index and a threshold for the edge control cycle are set, and a conservative control parameter is determined. When the operating condition disturbance index is greater than the threshold for the operating condition disturbance index or the edge control cycle is greater than the threshold for the edge control cycle, the conservative control parameter is used as the target control parameter; otherwise, the updated control parameter is used as the target control parameter.

[0039] The specific implementation method for the above steps in this embodiment is as follows: First, it's necessary to set the operating condition disturbance index threshold and the edge control cycle threshold. It's also necessary to determine conservative control parameters that can ensure the production line operates smoothly and without failures to the greatest extent possible. Then, the edge control cycle is obtained by adding up the times required to execute steps S1 to S4. Additionally, the operating condition disturbance index needs to be calculated. : in, Weighting for copper plate hardness deviation; Normalized copper plate hardness deviation; Weighting of roller surface wear; This represents the normalized roller surface wear amount; Weighted by the roll temperature drift rate; This represents the normalized roller temperature drift rate.

[0040] When the operating condition disturbance index exceeds the operating condition disturbance index threshold or the edge control cycle exceeds the edge control cycle threshold, it indicates that the disturbance to the production line is too large or the solution of the control parameters is too slow to keep up with the production speed. In this case, the conservative control parameters should be directly used as the target control parameters to ensure the smooth and safe operation of the production line. Otherwise, the updated control parameters should be used as the target control parameters to control the production line.

[0041] The sparse synchronous copper rolling distribution control device provided by the present invention is described below. The sparse synchronous copper rolling distribution control device described below can be referred to in correspondence with the sparse synchronous copper rolling distribution control method described above.

[0042] Figure 2 A schematic diagram of a sparse synchronous copper rolling distribution control system is shown, such as... Figure 2 As shown, the method for implementing the sparse synchronous copper rolling distribution control method described above includes: Initial production line data module 100: Used to set up the data acquisition unit, which collects data to obtain initial production line data; Data synchronization module 200: used to receive sparse correction data, obtain virtual clock phase correction amount based on sparse correction data, and synchronize the initial production line data with the virtual clock phase correction amount to obtain aligned production line data; Initial control parameter module 300: used to obtain the operating condition status, select a data iteration strategy based on the operating condition status, and calculate the control parameters through the data iteration strategy and aligned production line data to obtain the initial control parameters; Parameter Iteration Module 400: Used to calculate the loss parameter decrease rate of the initial control parameters, determine the loss parameter decrease rate threshold, update the initial control parameters and calculate the loss parameter decrease rate until the loss parameter decrease rate is less than the loss parameter decrease rate threshold, and obtain the updated control parameters; Target control parameter module 500: used to calculate the edge control cycle of the updated control parameters, calculate the operating condition disturbance index, obtain the target control parameters through the edge control cycle, operating condition disturbance index and updated control parameters, and perform copper rolling distribution control through the target control parameters.

[0043] Figure 3 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 3 As shown, the electronic device may include: a processor 810, a communication interface 820, a memory 830, and a communication bus 840, wherein the processor 810, the communication interface 820, and the memory 830 communicate with each other via the communication bus 840. The processor 810 can call a computer program in the memory 830 to execute a sparse synchronous copper rolling distribution control method, which includes: S1: Set up a data acquisition unit, which collects data to obtain initial production line data; S2: Receive sparse correction data, obtain virtual clock phase correction amount based on sparse correction data, and synchronize the initial production line data with the virtual clock phase correction amount to obtain aligned production line data. S3: Obtain the operating status, select a data iteration strategy based on the operating status, and calculate the control parameters using the data iteration strategy and aligned production line data to obtain the initial control parameters; S4: Calculate the loss parameter decrease rate of the initial control parameters, determine the loss parameter decrease rate threshold, update the initial control parameters and calculate the loss parameter decrease rate until the loss parameter decrease rate is less than the loss parameter decrease rate threshold, and obtain the updated control parameters; S5: Calculate the edge control cycle for updating control parameters, calculate the operating condition disturbance index, obtain the target control parameters through the edge control cycle, operating condition disturbance index and updated control parameters, and perform copper rolling distribution control through the target control parameters.

[0044] Furthermore, when the computer program in the aforementioned memory 830 can be implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0045] On the other hand, the present invention also provides a computer program product, the computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, wherein when the program instructions are executed by a computer, the computer is able to execute the sparse synchronous copper rolling distribution control method provided by the above methods, the method comprising: S1: Set up a data acquisition unit, which collects data to obtain initial production line data; S2: Receive sparse correction data, obtain virtual clock phase correction amount based on sparse correction data, and synchronize the initial production line data with the virtual clock phase correction amount to obtain aligned production line data. S3: Obtain the operating status, select a data iteration strategy based on the operating status, and calculate the control parameters using the data iteration strategy and aligned production line data to obtain the initial control parameters; S4: Calculate the loss parameter decrease rate of the initial control parameters, determine the loss parameter decrease rate threshold, update the initial control parameters and calculate the loss parameter decrease rate until the loss parameter decrease rate is less than the loss parameter decrease rate threshold, and obtain the updated control parameters; S5: Calculate the edge control cycle for updating control parameters, calculate the operating condition disturbance index, obtain the target control parameters through the edge control cycle, operating condition disturbance index and updated control parameters, and perform copper rolling distribution control through the target control parameters.

[0046] In another aspect, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to perform the aforementioned methods for controlling the sparse synchronous copper rolling distribution, the method comprising: S1: Set up a data acquisition unit, which collects data to obtain initial production line data; S2: Receive sparse correction data, obtain virtual clock phase correction amount based on sparse correction data, and synchronize the initial production line data with the virtual clock phase correction amount to obtain aligned production line data. S3: Obtain the operating status, select a data iteration strategy based on the operating status, and calculate the control parameters using the data iteration strategy and aligned production line data to obtain the initial control parameters; S4: Calculate the loss parameter decrease rate of the initial control parameters, determine the loss parameter decrease rate threshold, update the initial control parameters and calculate the loss parameter decrease rate until the loss parameter decrease rate is less than the loss parameter decrease rate threshold, and obtain the updated control parameters; S5: Calculate the edge control cycle for updating control parameters, calculate the operating condition disturbance index, obtain the target control parameters through the edge control cycle, operating condition disturbance index and updated control parameters, and perform copper rolling distribution control through the target control parameters.

[0047] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0048] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0049] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for controlling the distribution of sparse synchronous copper rolling, characterized in that, include: S1: Set up a data acquisition unit, which collects data to obtain initial production line data; S2: Receive sparse correction data, obtain virtual clock phase correction amount based on sparse correction data, and synchronize the initial production line data with the virtual clock phase correction amount to obtain aligned production line data. Step S2 further includes: S21: Receive sparse correction data, obtain a phase deviation estimate based on the sparse correction data, and obtain a drift compensation term based on the initial production line data; S22: Obtain historical drift error, determine drift compensation term coefficients based on the historical drift error, statistically analyze the synchronization convergence parameters of the sparse correction data, and obtain deviation estimate coefficients based on the synchronization convergence parameters; S23: The virtual clock phase correction amount is obtained through the drift compensation term, phase deviation estimate, drift compensation term coefficient, and deviation estimate coefficient. The initial production line data is synchronized using the virtual clock phase correction amount to obtain aligned production line data. S3: Obtain the operating status, select a data iteration strategy based on the operating status, and calculate the control parameters using the data iteration strategy and aligned production line data to obtain the initial control parameters; Step S3 further includes: S31: Obtain production line control parameters, obtain the operating condition state based on the production line control parameters, construct a candidate iterative strategy including reduced-order linear quadratic adjustment and nonlinear model prediction, and select a data iteration strategy from the candidate iterative strategies based on the operating condition state. S32: Decouple the aligned production line data to obtain decoupled production line data, and calculate the control parameters using the decoupled production line data and the data iteration strategy to obtain the initial control parameters; S4: Calculate the loss parameter decrease rate of the initial control parameters, determine the loss parameter decrease rate threshold, update the initial control parameters and calculate the loss parameter decrease rate until the loss parameter decrease rate is less than the loss parameter decrease rate threshold, and obtain the updated control parameters; S5: Calculate the edge control cycle for updating control parameters, calculate the operating condition disturbance index, obtain the target control parameters through the edge control cycle, operating condition disturbance index and updated control parameters, and perform copper rolling distribution control through the target control parameters.

2. The sparse synchronous copper rolling distribution control method according to claim 1, characterized in that, In step S1, the data acquisition unit includes an inlet thickness measurement unit, an outlet thickness measurement unit, a roll gap position sensor, a roll speed encoder, a tension sensor, a roll surface temperature sensor, and a rolling force sensor. The initial production line data includes the inlet copper plate thickness, the outlet copper plate thickness, the roll gap position, the roll speed, the copper plate tension, the roll surface temperature, and the rolling force.

3. The sparse synchronous copper rolling distribution control method according to claim 1, characterized in that, In step S4, a production data prediction model is constructed. The initial control parameters are input into the production data prediction model to obtain predicted production parameters. The control loss is calculated using the predicted production parameters, and the decrease rate of the loss parameters is calculated based on the control loss.

4. The sparse synchronous copper rolling distribution control method according to claim 1, characterized in that, In step S5, the operating condition disturbance index threshold and the edge control cycle threshold are set, and the conservative control parameter is determined. When the operating condition disturbance index is greater than the operating condition disturbance index threshold or the edge control cycle is greater than the edge control cycle threshold, the conservative control parameter is used as the target control parameter; otherwise, the updated control parameter is used as the target control parameter.

5. A sparse synchronous copper rolling distribution control system, used to execute the sparse synchronous copper rolling distribution control method as described in any one of claims 1 to 4, characterized in that, include: Initial production line data module: Used to set up the data acquisition unit, which collects data to obtain the initial production line data; Data synchronization module: used to receive sparse correction data, obtain virtual clock phase correction amount based on sparse correction data, and synchronize the initial production line data with the virtual clock phase correction amount to obtain aligned production line data; Initial control parameter module: used to obtain the operating condition status, select a data iteration strategy based on the operating condition status, and calculate the control parameters by using the data iteration strategy and aligned production line data to obtain the initial control parameters; Parameter iteration module: used to calculate the rate of decrease of the loss parameter of the initial control parameters, determine the threshold of the rate of decrease of the loss parameter, update the initial control parameters and calculate the rate of decrease of the loss parameter until the rate of decrease of the loss parameter is less than the threshold of the rate of decrease of the loss parameter, and obtain the updated control parameters; Target control parameter module: used to calculate the edge control cycle for updating control parameters, calculate the operating condition disturbance index, obtain the target control parameters through the edge control cycle, operating condition disturbance index and updated control parameters, and perform copper rolling distribution control through the target control parameters.

6. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the sparse synchronous copper rolling distribution control method as described in any one of claims 1 to 4.

7. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the sparse synchronous copper rolling distribution control method as described in any one of claims 1 to 4.

8. A computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, characterized in that, When the program instructions are executed by the computer, the computer is able to perform the sparse synchronous copper rolling distribution control method as described in any one of claims 1 to 4.

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