A steel plate tension dynamic optimization method and system based on model predictive control

Abstract

The present invention provides a method and system for dynamic optimization of steel plate tension based on model predictive control, which obtains material characteristic parameters of high-strength steel plates; uses model predictive control to predict the tension change of the high-strength steel plates according to the material characteristic parameters and defines the voltage adjustment parameter range of the electric control valve to generate a voltage adjustment instruction that matches the material characteristic parameters; uses pulse modulation technology to generate an optimized pulse sequence according to the speed adjustment requirements and real-time load status of the drive motor; determines the duty cycle adjustment direction and duty cycle adjustment ratio according to the voltage adjustment instruction to obtain a pulse sequence with adjusted duty cycle; uses the voltage adjustment instruction to correct the trigger phase of the pulse sequence with adjusted duty cycle so that the speed of the drive motor is synchronously matched with the tension adjustment amount. The technical solution provided by the present invention realizes the synchronous adaptive optimization of the tension control response speed and material characteristic change of high-strength steel plates during the production process.

Description

Technical Field

[0001] The present invention relates to the technical field of rolling process optimization, and in particular to a steel plate tension dynamic optimization method and system based on model predictive control. Background Art

[0002] During the continuous production of high-strength steel plates, the stability of tension control directly impacts plate forming quality and production efficiency. The material properties of high-strength steel plates (such as hardness and thickness) can dynamically change during rolling due to factors such as temperature gradients and roll wear, leading to increased tension fluctuations. Existing technologies struggle to simultaneously meet the requirements of dynamic parameter adaptation, multivariable collaborative optimization, and control signal timing synchronization. Consequently, an adaptive control solution is urgently needed that can integrate material characteristic parameters with actuator status in real time.

[0003] The typical solution currently used to address these production needs is a collaborative control method based on feedback proportional-integral-derivative control (PID) and fixed-rule pulse modulation. This method uses a tension sensor to collect real-time production line tension data. The PID controller then calculates the reference voltage adjustment for the electronically controlled valve. Simultaneously, a pulse train with a fixed duty cycle is generated based on a preset speed-tension mapping table to control the drive motor. The electronically controlled valve voltage regulation and pulse train generation utilize separate control logic, which are roughly synchronized via a timing alignment module. This approach has significant drawbacks in practice: For example, the PID controller relies on fixed parameters, resulting in response lag or overshoot in sudden tension changes. Furthermore, the pulse train's duty cycle and trigger phase are generated based on static rules, resulting in inaccurate synchronization between the motor speed and tension adjustment. This can lead to control signal conflicts, especially when material properties fluctuate frequently, exacerbating system instability. Summary of the Invention

[0004] The present invention provides a method and system for dynamic optimization of steel plate tension based on model predictive control, which is used to solve the problems in the prior art that rely on fixed parameters, resulting in response lag or overshoot in tension mutation scenarios; the synchronization accuracy of motor speed and tension adjustment amount is insufficient, especially when material properties fluctuate frequently, which easily causes control signal conflicts and aggravates system instability.

[0005] In a first aspect, the present invention provides a method for dynamic optimization of steel plate tension based on model predictive control, comprising:

[0006] Obtaining material characteristic parameters of the high-strength steel plate, wherein the material characteristic parameters include hardness parameters and thickness parameters;

[0007] Based on the material characteristic parameters, using model predictive control, the tension change of the high-strength steel plate is predicted and a voltage adjustment parameter range of the electric control valve is defined to generate a voltage adjustment instruction that matches the material characteristic parameters;

[0008] According to the speed regulation requirements and real-time load status of the drive motor, pulse modulation technology is used to generate an optimized pulse sequence;

[0009] Determining a duty cycle adjustment direction and a duty cycle adjustment ratio according to the voltage regulation instruction to adjust the optimized pulse sequence to obtain a pulse sequence with adjusted duty cycle;

[0010] The voltage regulation instruction is used to correct the trigger phase of the pulse sequence after adjusting the duty cycle, so that the speed of the drive motor is synchronously matched with the tension adjustment amount, thereby achieving synchronous adaptive optimization of the tension control response speed and material property changes of the high-strength steel plate during the production process.

[0011] Optionally, based on the material characteristic parameters, model predictive control is used to predict the tension change of the high-strength steel plate and define a voltage adjustment parameter range of the electric control valve to generate a voltage adjustment instruction matching the material characteristic parameters, including:

[0012] Based on the hardness parameter and thickness parameter in the material characteristic parameters, a dynamic relationship model between deformation rate and tension value is constructed by using model predictive control;

[0013] Within the prediction window of the model predictive control, the rising rate, peak range and decay rate of the tension fluctuation are calculated using the dynamic relationship model to divide the tension fluctuation threshold range;

[0014] Based on the tension fluctuation threshold interval and the optimization objective of the model predictive control, defining a voltage adjustment parameter range of the electronically controlled valve, wherein the voltage adjustment parameter range includes a voltage increment upper limit, a voltage attenuation lower limit, and an adjustment step constraint;

[0015] Based on the voltage adjustment parameter range and in combination with the dynamic correlation between the deformation rate and the tension fluctuation threshold interval, a candidate voltage adjustment parameter sequence is generated through model predictive control optimization;

[0016] Performing continuity check on the candidate voltage regulation parameter sequence to generate a target voltage regulation parameter combination that meets the voltage mutation amplitude limit and the adjacent parameter timing interval constraint;

[0017] A final target voltage adjustment parameter with the shortest adjacent parameter time interval and the smallest voltage mutation amplitude is extracted from the target voltage adjustment parameter combination, and the final target voltage adjustment parameter is converted into a voltage adjustment instruction matching the material characteristic parameter.

[0018] Optionally, based on the voltage adjustment parameter range and in combination with the dynamic correlation between the deformation rate and the tension fluctuation threshold interval, a candidate voltage adjustment parameter sequence is generated through model predictive control optimization, including:

[0019] According to the numerical range of the deformation rate, the tension fluctuation threshold interval is divided into multiple subintervals, each subinterval corresponding to a specific variation range of the deformation rate;

[0020] generating an initial voltage regulation parameter set matching the deformation rate of each subinterval based on the voltage increment upper limit and the voltage attenuation lower limit of the voltage regulation parameter range;

[0021] Performing parameter expansion on the initial voltage adjustment parameter set to generate an expanded voltage adjustment parameter set;

[0022] According to the adjustment step size constraint, the voltage adjustment parameters in the expanded voltage adjustment parameter set are discretized and segmented to generate a discretized voltage adjustment parameter set;

[0023] Within the prediction window of the model predictive control, according to the dynamic correlation between the deformation rate and the tension fluctuation threshold range, the target voltage regulation parameter that meets the multi-stage tension fluctuation suppression requirements is selected from the discretized voltage regulation parameter set to generate a candidate voltage regulation parameter sequence.

[0024] Optionally, pulse modulation technology is used to generate an optimized pulse sequence based on the speed regulation requirements and real-time load status of the drive motor, including:

[0025] According to the speed regulation requirements of the drive motor, the reference waveform parameters of the pulse modulation technology are set, wherein the reference waveform parameters include the initial pulse width and the initial pulse interval;

[0026] Based on the initial pulse width and the initial pulse interval, generating an initial control signal waveform according to a periodic arrangement rule, wherein the initial control signal waveform is composed of a plurality of pulse units;

[0027] Calculating a width adjustment amount of each pulse unit in the initial control signal waveform according to the real-time load state of the drive motor, wherein the width adjustment amount is proportional to the change in the real-time load state;

[0028] Superimposing the width adjustment amount of each pulse unit in the initial control signal waveform and the corresponding initial pulse width to generate a first adjusted pulse unit, and recombining the first adjusted pulse units to generate a transition pulse sequence;

[0029] The intervals between adjacent first adjusted pulse units in the transition pulse sequence are smoothed to eliminate the sudden changes in the intervals between adjacent first adjusted pulse units, thereby generating an optimized pulse sequence.

[0030] Optionally, determining a duty cycle adjustment direction and a duty cycle adjustment ratio according to the voltage regulation instruction to adjust the optimized pulse sequence to obtain a pulse sequence with adjusted duty cycle includes:

[0031] The absolute value of the numerical change of the voltage regulation instruction is used as the duty cycle adjustment ratio, and the numerical change is divided into a positive change and a negative change according to a preset positive threshold and a preset negative threshold, and the positive change is used as the direction of increasing the duty cycle, and the negative change is used as the direction of decreasing the duty cycle;

[0032] Based on the duty cycle adjustment direction and the duty cycle adjustment ratio, establishing a high-level duration correction rule corresponding to each pulse unit in the optimized pulse sequence, wherein the duty cycle adjustment direction includes a duty cycle increasing direction and a duty cycle decreasing direction;

[0033] According to the high-level duration correction rule, correcting the high-level duration of the pulse unit in the optimized pulse sequence to generate a second adjusted pulse unit;

[0034] Verifying the second adjusted pulse units, and if the mutation amplitude of the high level duration of adjacent second adjusted pulse units exceeds a preset mutation threshold, smoothing the mutation amplitude to finally generate a verified pulse unit sequence;

[0035] The verified pulse unit sequence is reorganized to obtain a pulse sequence with adjusted duty cycle.

[0036] Optionally, the trigger phase of the pulse sequence after the duty cycle is adjusted is corrected by using the voltage adjustment instruction so that the rotation speed of the drive motor is synchronously matched with the tension adjustment amount, including:

[0037] According to the waveform data of the voltage value changing with time in the voltage regulation instruction, identifying the starting time point of the voltage value changing from low to high as the rising edge time point, and the starting time point of the voltage value changing from high to low as the falling edge time point;

[0038] Calculating a trigger phase correction amount for each pulse unit in the duty cycle-adjusted pulse sequence according to the rising edge time point and the falling edge time point;

[0039] Superimposing the trigger phase correction amount of each pulse unit in the pulse sequence after adjusting the duty cycle with the corresponding initial trigger time point to generate a third adjusted pulse unit;

[0040] Testing the third adjusted pulse unit, if the triggering time interval between adjacent third adjusted pulse units is less than a preset minimum interval threshold, shifting the triggering time point of the next third adjusted pulse unit backward until the preset minimum interval threshold is met, thereby obtaining a fourth adjusted pulse unit;

[0041] The fourth adjusted pulse unit is reorganized to generate a pulse sequence after the trigger phase is corrected, and the trigger time point of the pulse sequence after the trigger phase is synchronized with the waveform change of the voltage regulation instruction, so that the speed of the drive motor is synchronously matched with the tension adjustment amount.

[0042] In a second aspect, the present invention provides a steel plate tension dynamic optimization system based on model predictive control, comprising:

[0043] An acquisition module, configured to acquire material characteristic parameters of the high-strength steel plate, wherein the material characteristic parameters include hardness parameters and thickness parameters;

[0044] a prediction module, configured to predict the tension change of the high-strength steel plate and define a voltage adjustment parameter range of the electric control valve based on the material characteristic parameters using model predictive control, so as to generate a voltage adjustment instruction that matches the material characteristic parameters;

[0045] The generation module is used to generate an optimized pulse sequence using pulse modulation technology according to the speed adjustment requirements and real-time load status of the drive motor;

[0046] An adjustment module is used to determine the duty cycle adjustment direction and duty cycle adjustment ratio according to the voltage adjustment instruction, so as to adjust the optimized pulse sequence to obtain a pulse sequence with adjusted duty cycle.

[0047] A correction module is used to use the voltage regulation instruction to correct the trigger phase of the pulse sequence after adjusting the duty cycle, so that the speed of the drive motor is synchronously matched with the tension adjustment amount, thereby realizing synchronous adaptive optimization of the tension control response speed and material property changes of the high-strength steel plate during the production process.

[0048] In a third aspect, the present invention provides a computing device comprising a processor and a memory, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute a dynamic optimization method for steel plate tension based on model predictive control as described in any one of the first aspects.

[0049] In a fourth aspect, the present invention provides a computer storage medium having computer program instructions stored thereon, wherein the computer program instructions, when executed by a processor, implement a method for dynamic optimization of steel plate tension based on model predictive control as described in any one of the first aspects.

[0050] In the present invention, material characteristic parameters of a high-strength steel plate are obtained, wherein the material characteristic parameters include a hardness parameter and a thickness parameter; based on the material characteristic parameters, model predictive control is used to predict the tension change of the high-strength steel plate and define the voltage adjustment parameter range of the electric control valve to generate a voltage adjustment instruction that matches the material characteristic parameters; based on the speed adjustment requirements and real-time load status of the drive motor, pulse modulation technology is used to generate an optimized pulse sequence; based on the voltage adjustment instruction, the duty cycle adjustment direction and the duty cycle adjustment ratio are determined to adjust the optimized pulse sequence to obtain a pulse sequence with adjusted duty cycle; using the voltage adjustment instruction, the trigger phase of the pulse sequence with adjusted duty cycle is corrected so that the speed of the drive motor is synchronously matched with the tension adjustment amount, thereby realizing synchronous adaptive optimization of the tension control response speed and material characteristic change of the high-strength steel plate during the production process. The technical solution provided by the present invention provides accurate input basis for dynamic control by real-time collection of hardness and thickness parameters of high-strength steel plates, thereby solving the control lag problem caused by the failure to perceive changes in material properties in real time in traditional methods; dynamically predicts tension fluctuations based on material properties and optimizes the voltage adjustment parameters of the electric control valve, thereby overcoming the response lag defect of the fixed parameter controller and improving the adaptability to sudden changes in material properties; dynamically adjusts the pulse waveform in combination with the load state of the drive motor to avoid the mismatch between the control signal and the working condition caused by static rules, thereby enhancing the adaptability of the system to complex production environments; dynamically adjusts the pulse duty cycle according to the voltage instruction to achieve rapid matching of the motor speed and tension requirements, eliminating the overshoot or undershoot problem caused by the fixed duty cycle in the traditional solution; synchronously corrects the pulse trigger time point through the voltage adjustment instruction to resolve the control conflict caused by the timing deviation of the electric control valve and the motor action, thereby ensuring the coordinated accuracy of multiple actuators. Furthermore, based on the waveform data of the voltage regulation instruction, the rising and falling edge time points of the voltage change are identified, the trigger phase correction amount of each pulse unit is calculated, the initial trigger time point is adjusted by superimposing the correction amount, and the trigger intervals of adjacent pulse units are conflict detected and translated. Finally, a pulse sequence after the corrected trigger phase is generated that is strictly synchronized with the voltage instruction, eliminating the timing deviation between the electric control valve and the drive motor action, solving the speed and tension adjustment inaccuracy problem caused by signal asynchrony in traditional discrete control, improving the stability and response consistency of the system collaborative control, and adapting to the complex working conditions of rapid voltage jumps and frequent load fluctuations in high-strength steel plate production.

[0051] These and other aspects of the present invention will become more readily apparent from the following description of the embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following is a brief introduction to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0053] Figure 1 A flow chart of a method for dynamic optimization of steel plate tension based on model predictive control provided by an embodiment of the present invention;

[0054] Figure 2 A schematic structural diagram of a steel plate tension dynamic optimization system based on model predictive control provided by an embodiment of the present invention;

[0055] Figure 3 A schematic diagram of the structure of a computing device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0056] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0057] In some of the processes described in the specification and claims of the present invention and the above-mentioned figures, multiple operations that appear in a specific order are included, but it should be clearly understood that these operations may not be executed in the order in which they appear in this article or may be executed in parallel. The serial numbers of the operations, such as 101, 102, etc., are only used to distinguish between different operations, and the serial numbers themselves do not represent any execution order. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel. It should be noted that the descriptions of "first", "second", etc. in this article are used to distinguish different messages, devices, modules, etc., and do not represent the order of precedence, nor do they limit "first" and "second" to be different types.

[0058] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making any creative efforts shall fall within the scope of protection of the present invention.

[0059] Figure 1 The present invention provides a flow chart of a method for dynamic optimization of steel plate tension based on model predictive control, such as Figure 1 As shown, the method includes:

[0060] In order to solve the problem of tension fluctuation control caused by dynamic changes in material properties in the production of continuous high-strength steel plates, the existing technology relies on fixed-parameter PID controllers and static pulse modulation strategies, which makes it difficult to achieve precise coordination between the voltage of the electric control valve and the speed of the drive motor, resulting in response lag, insufficient synchronization accuracy and poor system stability. The present invention predicts tension changes by integrating the real-time detection of material characteristic parameters (such as hardness and thickness) with the dynamic optimization capability of model predictive control, and then generates voltage regulation instructions that match the material characteristics; at the same time, it dynamically generates an optimized pulse sequence based on the load state of the drive motor, and adjusts the pulse duty cycle and trigger phase in real time based on the voltage instruction, so that the action of the electric control valve is strictly synchronized with the motor speed, solving the defects of parameter solidification, timing mismatch and discrete control logic in traditional solutions, and finally achieving deep adaptation of tension control response speed and material property changes, ensuring the stability and efficiency of continuous production of high-strength steel plates. Based on this, the present invention provides a dynamic optimization method for steel plate tension based on model predictive control, such as Figure 1 ,include:

[0061] Step 101: Obtaining material characteristic parameters of a high-strength steel plate, wherein the material characteristic parameters include a hardness parameter and a thickness parameter;

[0062] In this step, high-strength steel refers to a metal material with higher tensile strength than conventional steel. It is commonly used in the automotive, construction, and other fields. Variations in its hardness and thickness significantly influence rolling tension control. Material characteristic parameters, including hardness and thickness, reflect the physical properties of the steel. The hardness parameter indicates the steel's resistance to plastic deformation and is calculated based on indentation depth or springback. The thickness parameter represents the cross-sectional dimensions of the steel and is acquired in real time using non-contact distance measurement equipment.

[0063] In this embodiment of the present invention, hardness and thickness sensors installed on the production line collect real-time hardness and thickness parameters of high-strength steel plates. The hardness parameter is obtained by measuring the steel plate's surface deformation resistance using an indentation method, while the thickness parameter is obtained by measuring the steel plate's cross-sectional dimensions using a laser rangefinder or ultrasonic thickness gauge. These material property parameters serve as input data for subsequent model predictive control, dynamically reflecting the physical properties of the steel plate during the rolling process.

[0064] Step 102: Based on the material characteristic parameters, using model predictive control, predict the tension change of the high-strength steel plate and define the voltage adjustment parameter range of the electronically controlled valve to generate a voltage adjustment instruction that matches the material characteristic parameters;

[0065] In this step, tension variation refers to the dynamic fluctuations in the tensile force applied to high-strength steel sheets during rolling, resulting from the interaction of material properties and rolling parameters. The electronically controlled valve is the actuator used to regulate hydraulic system pressure, and its voltage parameters determine the output pressure. Voltage regulation parameters, including the upper limit of voltage increment, the lower limit of voltage attenuation, and the regulation step size constraints, are generated through model predictive control optimization. The voltage regulation command, a control signal containing the target voltage value and its timing information, is output by model predictive control.

[0066] In an embodiment of the present invention, model predictive control is utilized in combination with the mechanical parameters of the rolling equipment (such as roll pressure and speed) to predict the fluctuation trend of high-strength steel plates in the future time domain (such as the rising rate, peak range, and attenuation stage). Based on the prediction results, the voltage regulation parameter range of the electric control valve (such as the upper limit of the voltage increment, the lower limit of the voltage attenuation, and the adjustment step constraint) is defined through a multi-objective optimization algorithm to generate a voltage regulation instruction that matches the current material properties.

[0067] Step 103: Generate an optimized pulse sequence using pulse modulation technology according to the speed regulation requirement of the drive motor and the real-time load status;

[0068] In this step, the drive motor refers to the actuator that controls the roll speed, and its speed is directly related to the tension adjustment. The speed adjustment demand refers to the motor speed setpoint calculated based on the target tension. The real-time load state refers to the current workload of the drive motor, obtained through a current or torque sensor. The optimized pulse train is a periodic pulse signal that has been smoothed and adjusted for the load state and is used to control the motor speed.

[0069] In this embodiment of the present invention, the initial pulse width and initial pulse interval are set based on the speed regulation requirements of the drive motor. Combined with the real-time load status of the drive motor, which is obtained through a current sensor or torque sensor, the pulse width is dynamically adjusted to generate an initial control signal waveform consisting of multiple pulse units. The intervals between adjacent pulses in the initial control signal waveform are smoothed to eliminate sudden changes in the intervals, generating an optimized pulse sequence to ensure dynamic matching of motor speed and load changes.

[0070] Step 104: determining a duty cycle adjustment direction and a duty cycle adjustment ratio according to the voltage regulation instruction, so as to adjust the optimized pulse sequence to obtain a pulse sequence with adjusted duty cycle;

[0071] In this step, the duty cycle adjustment direction refers to the tendency to increase or decrease the duration of the pulse high level. The duty cycle adjustment ratio refers to the ratio of the adjustment amplitude to the change in the voltage regulation command. The duty cycle-adjusted pulse sequence refers to the pulse signal generated by dynamically adjusting the duty cycle to meet the voltage regulation requirements.

[0072] In this embodiment of the present invention, the duty cycle adjustment direction (e.g., increase or decrease) and the duty cycle adjustment ratio (the ratio of the absolute value of the numerical change to a preset threshold) are determined by analyzing the numerical change in the voltage regulation command (e.g., the magnitude of the voltage increase or decrease). Based on the duty cycle adjustment direction and ratio, the high-level duration of each pulse unit in the optimized pulse sequence is corrected and verified to generate a pulse sequence with adjusted duty cycle, precisely matching the motor speed to the voltage regulation requirements.

[0073] Step 105: Using the voltage regulation instruction, the trigger phase of the pulse sequence after the duty cycle is adjusted is corrected so that the rotation speed of the drive motor is synchronously matched with the tension adjustment amount, thereby achieving synchronous adaptive optimization of the tension control response speed and the change of material properties of the high-strength steel plate during the production process;

[0074] In this step, the trigger phase refers to the starting time of the pulse signal, which determines the timing of the motor's operation. The tension adjustment refers to the required tension adjustment value, calculated by the difference between the current tension and the target tension. The tension control response speed refers to the time it takes for the system to detect tension deviation and complete the adjustment, reflecting control efficiency. Material property changes refer to the dynamic fluctuations in the hardness or thickness of high-strength steel plates during the rolling process, caused by factors such as temperature and wear.

[0075] In an embodiment of the present invention, the trigger phase correction amount of each pulse unit is calculated by analyzing the waveform data of the voltage regulation instruction (such as the rising edge and falling edge time points); the trigger phase correction amount of each pulse unit is superimposed with the corresponding initial trigger time point, and the trigger intervals of adjacent pulse units are conflict checked and translated to generate a pulse sequence after the corrected trigger phase that is strictly synchronized with the voltage instruction, thereby ensuring real-time synchronization of the drive motor speed and the tension adjustment amount.

[0076] The embodiments of the present invention solve the defects of parameter solidification, timing mismatch and discrete control logic in traditional solutions, improve the response speed and synchronization accuracy of tension control, adapt to the sudden changes in material properties and complex working conditions in the production of high-strength steel plates, and ensure production stability and efficiency.

[0077] For example, in a continuous high-strength steel plate rolling production line, the hardness parameters (such as 450HB) and thickness parameters (such as 2.5mm) of the steel plate are first collected in real time through hardness sensors and laser thickness gauges; the parameters are input into the model predictive control to predict the tension change in the next 10 seconds and generate a voltage adjustment instruction for the electronic control valve (such as from 5V to 8V); at the same time, according to the target speed of the drive motor (2000rpm) and the real-time load current (15A), pulse modulation technology is used to generate an optimized pulse sequence (duty cycle 50%), in which the pulse width is adjusted to 55% through load feedback; the duty cycle increase direction and duty cycle are determined based on the numerical change of the voltage instruction (+3V). The duty cycle of the optimized pulse sequence is adjusted to 65% by comparing the adjustment ratio (30%) to obtain the pulse sequence after duty cycle adjustment; the rising edge time point of the voltage regulation instruction (t=2s) is analyzed, and the trigger phase correction amount (such as +0.1ms) of each pulse unit in the pulse sequence after duty cycle adjustment is calculated to adjust the pulse sequence. After verification, it is detected that the trigger time interval of adjacent pulse units is too small (0.5ms<1ms threshold), and the pulse trigger time of the latter pulse unit is shifted to 1.2ms. Finally, the pulse sequence after trigger phase correction is generated, and the driving motor speed is strictly matched with the tension adjustment amount to achieve tension fluctuation suppression and improve production efficiency.

[0078] The present invention provides a specific embodiment, step 102, constructing a dynamic data fusion framework, wherein the dynamic data fusion framework adjusts the association rules between the structured data and the unstructured data according to real-time analysis requirements, specifically comprising the following steps:

[0079] Step 201: Based on the hardness parameter and thickness parameter in the material characteristic parameters, a dynamic relationship model between deformation rate and tension value is constructed using model predictive control;

[0080] In this step, the deformation rate refers to the deformation amplitude of the high-strength steel plate per unit time during the rolling process. It is calculated by dividing the roll pressure by (hardness parameter × thickness parameter) and reflects the material's plastic deformation capacity. The tension value refers to the tensile force exerted on the high-strength steel plate during rolling. It is calculated by multiplying the deformation rate by the material's elastic modulus and is used to evaluate the stability of tension control. The dynamic relationship model is a mathematical model constructed based on model predictive control that describes the real-time correlation between the deformation rate, material characteristic parameters, and tension value.

[0081] In an embodiment of the present invention, hardness parameters and thickness parameters are used as input variables through model predictive control, and combined with the mechanical parameters of the rolling equipment (such as roll pressure and line speed) to establish a dynamic relationship model between deformation rate and tension value. The model is obtained by training historical rolling data and can predict tension changes.

[0082] Step 202: within the prediction window of the model predictive control, using the dynamic relationship model to calculate the rising rate, peak range, and decay rate of the tension fluctuation to divide the tension fluctuation threshold range;

[0083] In this step, the prediction window refers to the time range (e.g., 10 seconds) used in model predictive control to simulate future operating conditions, within which the optimization strategy is calculated. Tension fluctuation refers to the dynamic change in tension during the rolling process. The rise rate refers to the average rate of increase in tension from baseline to peak value, calculated by dividing the change in tension by the time difference. The peak interval refers to the time period during which the tension value remains above 90% of the peak value, reflecting the duration of the high tension state. The decay rate refers to the average deceleration in tension from peak value to baseline, calculated by dividing the change in tension by the time difference. The tension fluctuation threshold interval refers to the level of tension fluctuation (e.g., high, medium, low) classified by the rise rate, peak interval, and decay rate, and is used to dynamically adjust the control strategy.

[0084] In this embodiment of the present invention, within the prediction window (e.g., 10 seconds) of a model predictive control simulation, a dynamic relationship model is used to extract the slope of the rising phase of the tension variation curve as the rise rate, peak interval, and decay rate. Based on these parameters, tension fluctuations are divided into three threshold ranges: high, medium, and low. For example, the high fluctuation range is defined as a rise rate greater than 5 N / s and a peak interval exceeding 3 seconds.

[0085] Step 203: Based on the tension fluctuation threshold range and the optimization objective of the model predictive control, defining a voltage adjustment parameter range of the electronically controlled valve, wherein the voltage adjustment parameter range includes a voltage increment upper limit, a voltage attenuation lower limit, and an adjustment step constraint;

[0086] In this step, the optimization objective refers to the comprehensive indicators to be minimized in model predictive control (such as tension fluctuation amplitude and electric control valve energy consumption). Multi-objective balancing is achieved through weight allocation. The voltage increment upper limit refers to the maximum voltage increase allowed in a single adjustment and is dynamically set based on the tension fluctuation threshold range. The voltage attenuation lower limit refers to the maximum voltage drop allowed in a single adjustment and is used to prevent overshoot. The adjustment step size constraint is the minimum time interval between adjacent voltage adjustment actions to ensure the stability of the electric control valve response.

[0087] In an embodiment of the present invention, based on the tension fluctuation threshold interval and the optimization objective of model predictive control, a voltage regulation parameter range is set by a multi-objective optimization algorithm (such as linear programming), which includes an upper limit on voltage increment (such as +2V), a lower limit on voltage attenuation (such as -1.5V) and an adjustment step constraint (such as 0.5 seconds), and is dynamically adjusted according to the threshold interval (such as a high fluctuation interval corresponds to a looser upper limit on increment), wherein the optimization objectives include minimizing the tension fluctuation amplitude and the energy consumption of the electronically controlled valve.

[0088] Step 204: Based on the voltage adjustment parameter range and in combination with the dynamic correlation between the deformation rate and the tension fluctuation threshold range, a candidate voltage adjustment parameter sequence is generated through model predictive control optimization;

[0089] In this step, the dynamic association refers to a regular mapping between deformation rate and tension fluctuation threshold range (e.g., high deformation rate corresponds to high fluctuation range). The candidate voltage regulation parameter sequence refers to multiple voltage regulation schemes generated by model predictive control, each set containing voltage parameters that are continuous in time sequence.

[0090] In an embodiment of the present invention, the tension fluctuation threshold interval is divided into multiple sub-intervals according to the deformation rate, and an initial voltage adjustment parameter set matching the deformation rate of each sub-interval is generated according to the voltage adjustment parameter range. The parameters are expanded and segmented to generate a discretized voltage adjustment parameter set, from which the target voltage adjustment parameters that meet the multi-stage tension fluctuation suppression requirements are selected to generate a candidate voltage adjustment parameter sequence.

[0091] Step 205: performing continuity check on the candidate voltage regulation parameter sequence to generate a target voltage regulation parameter combination that meets the voltage mutation amplitude limit and the adjacent parameter timing interval constraint;

[0092] In this step, the voltage mutation amplitude limit refers to the maximum allowable change in adjacent voltage parameters (e.g., ±3V) to prevent overload of the electronically controlled valve. The adjacent parameter timing interval constraint refers to the minimum time interval between voltage adjustment actions (e.g., 0.5 seconds) to avoid frequent adjustments.

[0093] In this embodiment of the present invention, candidate sequences are screened using validation rules: if the magnitude of the sudden change in adjacent parameters exceeds a preset limit (e.g., a single-step change exceeding 3V) or the timing interval is less than a constraint (e.g., 0.3 seconds), the sequence is discarded. By traversing all candidate sequences, only target parameter combinations that meet the criteria (e.g., [+1.5V, +0.8V, -0.3V]) are retained, ensuring smooth and executable adjustments.

[0094] Step 206: extracting a final target voltage adjustment parameter with the shortest adjacent parameter time interval and the smallest voltage mutation amplitude from the target voltage adjustment parameter combination, and converting the final target voltage adjustment parameter into a voltage adjustment instruction matching the material characteristic parameter;

[0095] In an embodiment of the present invention, a priority sorting algorithm is used to select the final target voltage regulation parameter with the shortest adjacent parameter timing interval (e.g., intervals greater than 0.5 seconds) and the smallest voltage mutation amplitude (e.g., single-step changes less than 2V), and the parameter is mapped into a time-voltage value sequence (e.g., t=0s→5V, t=0.5s→6.5V) to convert it into a voltage regulation instruction that matches the material characteristic parameters and can be directly sent to the electronically controlled valve.

[0096] The embodiments of the present invention solve the problems of voltage regulation strategy solidification, response lag and sudden overshoot in traditional solutions, improve the adaptability and stability of tension control, and are particularly suitable for complex working conditions where material properties frequently fluctuate in the production of high-strength steel plates.

[0097] The present invention provides a specific embodiment, step 204, based on the voltage adjustment parameter range, combined with the dynamic correlation between the deformation rate and the tension fluctuation threshold range, generating a candidate voltage adjustment parameter sequence through model predictive control optimization, specifically comprising the following steps:

[0098] Step 211: Divide the tension fluctuation threshold interval into multiple subintervals according to the numerical range of the deformation rate, each subinterval corresponding to a specific variation range of the deformation rate;

[0099] In this step, the specific variation range refers to the numerical interval into which the deformation rate is divided (eg, 0.05-0.1 mm / s), which is used to associate control strategies with different tension fluctuation threshold intervals.

[0100] In an embodiment of the present invention, the tension fluctuation threshold interval (such as high, medium, and low fluctuation intervals) is further refined into multiple sub-intervals through predefined deformation rate segmentation rules (such as 0-0.05mm / s as a low rate zone, 0.05-0.1mm / s as a medium rate zone, and 0.1mm / s and above as a high rate zone), where each sub-interval corresponds to a specific variation range of the deformation rate (such as the high rate zone corresponds to a deformation rate ≥0.1mm / s), which is used to dynamically adapt to the voltage regulation strategy under different deformation rates.

[0101] Step 212: generating an initial voltage regulation parameter set matching the deformation rate of each subinterval based on the voltage increment upper limit and the voltage attenuation lower limit of the voltage regulation parameter range;

[0102] In this step, the initial voltage adjustment parameter set refers to a preliminary voltage adjustment parameter group generated based on the deformation rate of the sub-interval, and is generated between the voltage increment upper limit and the attenuation lower limit by linear interpolation.

[0103] In an embodiment of the present invention, based on the deformation rate corresponding to the sub-interval (such as the high-rate zone), a set of initial voltage adjustment parameters (such as +2V, +1.5V, +1V) are generated by linear interpolation between the upper limit of the voltage increment (such as +2V) and the lower limit of the voltage attenuation (such as -1.5V), forming an initial voltage adjustment parameter set that matches the current deformation rate. This set is used to cover possible voltage adjustment requirements within the sub-interval.

[0104] Step 213: performing parameter expansion on the initial voltage adjustment parameter set to generate an expanded voltage adjustment parameter set;

[0105] In this step, the expanded voltage regulation parameter set refers to a parameter set obtained by dynamically adjusting the initial voltage regulation parameters by superimposing or attenuating the deformation rate variation, reflecting the impact of the real-time deformation rate on voltage regulation.

[0106] In an embodiment of the present invention, the initial voltage adjustment parameters in the initial voltage adjustment parameter set are dynamically adjusted by superimposing or attenuating deformation rate changes to generate an expanded voltage adjustment parameter set. For example, in a high-rate region, if the deformation rate increase (the difference between the current deformation rate and the baseline deformation rate) is 0.02 mm / s, the initial voltage adjustment parameter (e.g., +2V) is superimposed with the product of this deformation rate increase and a preset scaling factor (e.g., 0.1 V / mm / s) (+0.2V) to generate an expanded voltage adjustment parameter (e.g., +2.2V). Similarly, the deformation rate attenuation is calculated using the same rules, ultimately forming the expanded voltage adjustment parameter set (e.g., [+2.2V, +1.7V, +1.2V]).

[0107] Step 214: Discretize and segment the voltage regulation parameters in the expanded voltage regulation parameter set according to the regulation step size constraint to generate a discretized voltage regulation parameter set;

[0108] In this step, the discretized voltage regulation parameter set refers to a parameter set obtained by segmenting the continuous voltage regulation parameters in the expanded voltage regulation parameter set according to the regulation step constraint, which is adapted to the minimum regulation accuracy of the electronically controlled valve (such as 0.5V step).

[0109] In an embodiment of the present invention, the expanded voltage regulation parameter is discretized and segmented according to the regulation step constraint (such as 0.5V). For example, the expanded voltage regulation parameter is +2.2V, which is discretized into +2.0V and +2.5V in a step of 0.5V, and finally a set of discrete voltage regulation parameters (such as [+2.0V, +1.5V, +1.0V]) is generated to ensure that the discretized voltage regulation parameters meet the minimum regulation accuracy requirements of the electronically controlled valve.

[0110] Step 215: Within the prediction window of the model predictive control, based on the dynamic correlation between the deformation rate and the tension fluctuation threshold range, select a target voltage adjustment parameter that meets the multi-stage tension fluctuation suppression requirement from the discretized voltage adjustment parameter set to generate a candidate voltage adjustment parameter sequence;

[0111] In this step, the multi-stage tension fluctuation suppression requirement refers to the need to simultaneously meet the different control requirements of the tension rise, peak maintenance and attenuation stages within the prediction window of the model predictive control (for example, a high voltage increment is required in the rise stage and a moderate voltage reduction is required in the attenuation stage).

[0112] In an embodiment of the present invention, the rolling optimization mechanism of model predictive control is used to evaluate the inhibitory effect of the discrete voltage regulation parameters on the multi-stage tension fluctuation suppression requirements within a prediction window (e.g., 10 seconds), and the target voltage regulation parameters that can simultaneously meet the threshold intervals of each stage (e.g., the voltage increment in the high fluctuation area ≥ 1.5V) are selected to generate a candidate voltage regulation parameter sequence (e.g., [+2.0V, +1.5V, -0.5V]).

[0113] The embodiments of the present invention solve the problem that the traditional solution has a single voltage regulation strategy and cannot adapt to multi-stage tension fluctuations, improves the ability to suppress complex tension changes during the rolling process of high-strength steel plates, and ensures the accuracy and stability of the electric control valve action.

[0114] The present invention provides a specific embodiment, step 103, using pulse modulation technology to generate an optimized pulse sequence according to the speed regulation requirement and real-time load status of the drive motor, specifically including the following steps:

[0115] Step 301: setting reference waveform parameters of the pulse modulation technology according to the speed regulation requirement of the drive motor, wherein the reference waveform parameters include an initial pulse width and an initial pulse interval;

[0116] In this step, the reference waveform parameters refer to the basic set values of the initial pulse waveform in pulse modulation technology, including the initial pulse width and initial pulse interval. The initial pulse width refers to the high-level duration of a single pulse and is determined by dividing the target speed by the preset frequency coefficient. For example, 2000 rpm corresponds to 0.5 ms. The initial pulse interval refers to the time difference between the starting points of adjacent pulses and is used to control the periodic arrangement of the pulse signal. For example, a 1 ms interval generates a 1000 Hz pulse frequency.

[0117] In an embodiment of the present invention, the reference waveform parameters of the pulse modulation technology are set according to the speed regulation requirements of the drive motor to generate a basic control signal that matches the speed requirements, wherein the initial pulse width and initial pulse interval are calculated by the target speed (such as 2000 rpm) and the preset frequency coefficient (such as the number of pulses per revolution).

[0118] Step 302: Based on the initial pulse width and initial pulse interval, generate an initial control signal waveform according to a periodic arrangement rule, wherein the initial control signal waveform is composed of a plurality of pulse units;

[0119] In this step, the periodic arrangement rule refers to the rule in which pulse units are arranged in a fixed time cycle, for example, a 0.5ms high-level + 1ms low-level cycle. The initial control signal waveform refers to the original pulse signal generated by the reference waveform parameters, consisting of multiple periodically repeating pulse units. A pulse unit is the basic component of a pulse signal, consisting of a high-level phase and a low-level phase.

[0120] In this embodiment of the present invention, pulse modulation technology is used to cyclically arrange the initial pulse width and interval at a fixed period, generating an initial control signal waveform composed of multiple pulse units (each pulse unit contains high-level and low-level phases). For example, a waveform with an initial pulse width of 0.5ms and an initial pulse interval of 1ms consists of periodically repeating pulse units with a high level of 0.5ms and a low level of 1ms.

[0121] Step 303: Calculating a width adjustment amount of each pulse unit in the initial control signal waveform according to the real-time load state of the drive motor, wherein the width adjustment amount is proportional to a change in the real-time load state;

[0122] In this step, the width adjustment amount refers to the pulse width change value calculated based on the real-time load state of the drive motor, and is proportional to the change in the real-time load state (such as the current increment). For example, every 1A current change corresponds to a 0.1ms width adjustment.

[0123] In an embodiment of the present invention, the real-time load state of the drive motor is obtained through a current sensor or a torque sensor (for example, the load current increases from 10A to 15A), the load change (for example, +5A) is calculated, and a width adjustment amount (for example, +0.5ms) is generated according to a preset ratio (for example, every 1A load change corresponds to a 0.1ms pulse width adjustment). The width adjustment amount is proportional to the change in the real-time load state to ensure that the pulse width dynamically adapts to load fluctuations.

[0124] Step 304: superimposing the width adjustment amount of each pulse unit in the initial control signal waveform and the corresponding initial pulse width to generate a first adjusted pulse unit, and recombining the first adjusted pulse units to generate a transition pulse sequence;

[0125] In this step, the first adjusted pulse unit refers to the pulse unit after the initial pulse width is superimposed with the adjustment amount. The transition pulse sequence refers to the intermediate pulse signal generated by reorganizing the first adjusted pulse unit according to the initial pulse interval, and the interval continuity needs to be further optimized.

[0126] In an embodiment of the present invention, the initial pulse width (e.g., 0.5 ms) of each pulse unit is added to the width adjustment amount (e.g., +0.5 ms) to generate a first adjusted pulse unit (e.g., 1.0 ms high level), and the unit is reorganized into a transition pulse sequence according to the original periodic arrangement rule (e.g., 1 ms interval). The reorganized transition pulse sequence retains the initial pulse interval, but the pulse width has been adjusted according to the load state.

[0127] Step 305: smoothing the intervals between adjacent first adjusted pulse units in the transition pulse sequence to eliminate the sudden changes in the intervals between adjacent first adjusted pulse units, thereby generating an optimized pulse sequence;

[0128] In this step, the sudden change interval refers to an abnormal time difference between adjacent first adjusted pulse units in the transition pulse sequence that does not meet the minimum interval setting value, for example, the interval between the end of the front pulse and the start of the rear pulse is less than 0.3ms.

[0129] In this embodiment of the present invention, an interpolation algorithm is used to detect sudden changes in the intervals between adjacent first-adjusted pulse units (e.g., the time interval between the end of a previous pulse and the start of a subsequent pulse is less than 0.3 ms). The intervals are then extended to a value above a preset threshold (e.g., 1 ms). For example, the start time of the subsequent pulse is shifted from 2.5 ms to 3.0 ms. This eliminates the sudden changes in intervals and generates a time-continuous, optimized pulse sequence.

[0130] The embodiments of the present invention solve the problems of motor speed inaccuracy and signal mutation caused by load fluctuations in traditional pulse modulation technology, improve the stability and response accuracy of drive motor control, and adapt to the complex working conditions of frequent load fluctuations in high-strength steel plate production.

[0131] The present invention provides a specific embodiment, step 104, determining a duty cycle adjustment direction and a duty cycle adjustment ratio according to the voltage regulation instruction to adjust the optimized pulse sequence to obtain a pulse sequence with adjusted duty cycle, specifically comprising the following steps:

[0132] Step 401: Using the absolute value of the numerical variation of the voltage regulation instruction as the duty cycle adjustment ratio, and dividing the numerical variation into a positive variation and a negative variation according to a preset positive threshold and a preset negative threshold, using the positive variation as the duty cycle increasing direction and the negative variation as the duty cycle decreasing direction;

[0133] In this step, the numerical change refers to the difference between the current value of the voltage regulation instruction and the previous value, and is used to quantify the dynamic magnitude of the voltage regulation demand. The preset positive threshold is the minimum change (e.g., +1V) required to determine a positive increase in the voltage regulation demand. Values below this threshold do not trigger a duty cycle increase. The preset negative threshold is the maximum change (e.g., -0.5V) required to determine a negative decrease in the voltage regulation demand. Values above this threshold do not trigger a duty cycle decrease. The portion of the positive change index value that exceeds the preset positive threshold reflects a voltage increase. The portion of the negative change index value that falls below the preset negative threshold reflects a voltage decrease. The duty cycle increase direction refers to an adjustment trend toward an increase in the pulse high-level duration, corresponding to a positive voltage regulation demand. The duty cycle decrease direction refers to an adjustment trend toward a decrease in the pulse high-level duration, corresponding to a negative voltage regulation demand.

[0134] In this embodiment of the present invention, the numerical change is calculated by analyzing the difference between the current voltage value of the voltage regulation command and the previous time point. For example, if the current voltage is 8V and the previous voltage was 5V, the numerical change is +3V. If the numerical change is greater than a preset positive threshold (e.g., +1V), it is determined to be a positive change, corresponding to an increase in the duty cycle; if it is less than a preset negative threshold (e.g., -0.5V), it is determined to be a negative change, corresponding to a decrease in the duty cycle. The duty cycle adjustment ratio is determined by the ratio of the absolute value of the numerical change to a preset reference value (e.g., 10% for every 1V).

[0135] Step 402: establishing a high-level duration correction rule corresponding to each pulse unit in the optimized pulse sequence based on a duty cycle adjustment direction and the duty cycle adjustment ratio, wherein the duty cycle adjustment direction includes a duty cycle increase direction and a duty cycle decrease direction;

[0136] In this step, the high-level duration correction rule refers to a mathematical relationship (such as linear superposition or attenuation) that defines how the duty cycle adjustment direction and the duty cycle adjustment ratio affect the high-level duration.

[0137] In an embodiment of the present invention, when defining the direction of increasing the duty cycle, the high-level duration correction value is the product of the initial high-level duration and the duty cycle adjustment ratio. For example, if the initial high-level duration is 1ms and the duty cycle adjustment ratio is 30%, the high-level duration correction value is 0.3ms. When defining the direction of decreasing the duty cycle, the high-level duration correction value is the attenuation product of the initial high-level duration and the duty cycle adjustment ratio. For example, if the initial high-level duration is 1ms and the duty cycle adjustment ratio is 20%, the high-level duration correction value is 0.8ms. This high-level duration correction rule ensures that the duty cycle adjustment amount strictly matches the voltage change requirement.

[0138] Step 403: correcting the high-level duration of the pulse unit in the optimized pulse sequence according to the high-level duration correction rule to generate a second adjusted pulse unit;

[0139] In this step, the high-level duration refers to the duration of the high-level signal in a single pulse unit, which determines the duty cycle. The second adjusted pulse unit refers to the pulse unit after the high-level duration is adjusted according to the high-level duration correction rule, for example, from 1ms to 1.3ms.

[0140] In this embodiment of the present invention, according to the high-level duration correction rule, the initial high-level duration of each pulse unit (e.g., 1ms) is superimposed with the high-level duration correction value (e.g., +0.3ms) to generate a second adjusted pulse unit, while maintaining the initial pulse interval. For example, a pulse unit in the original optimized pulse sequence with a high-level duration of 1ms and a low-level duration of 2ms is adjusted to a high-level duration of 1.3ms and a low-level duration of 2ms.

[0141] Step 404: Verify the second adjusted pulse units. If the mutation amplitude of the high level duration of adjacent second adjusted pulse units exceeds a preset mutation threshold, smooth the mutation amplitude to finally generate a verified pulse unit sequence.

[0142] In this step, the mutation amplitude refers to the difference in high-level durations between adjacent second-adjusted pulse units, used to detect whether the signal jump exceeds the allowable range. The preset mutation threshold refers to the maximum allowable high-level duration difference (e.g., 0.3ms), exceeding which smoothing is required. The verified pulse unit sequence refers to the smoothed set of second-adjusted pulse units, ensuring that adjacent high-level durations vary smoothly.

[0143] In an embodiment of the present invention, the difference in high-level duration between adjacent second adjusted pulse units is detected. For example, if the high-level duration of the previous adjusted pulse unit is 1.3ms and that of the latter is 0.8ms, the difference in high-level duration is 0.5ms. If the value exceeds a preset mutation threshold (such as 0.3ms), the difference is distributed to multiple pulse units through an interpolation algorithm (such as linear interpolation) to generate a verified pulse unit sequence.

[0144] Step 405: reorganize the verified pulse unit sequence to obtain a pulse sequence with adjusted duty cycle;

[0145] In this embodiment of the present invention, the verified pulse units are reassembled according to the original periodic arrangement rule (e.g., 2ms intervals) to ensure timing continuity and stability of the motor control signal. For example, the verified pulse unit sequence is 1.1ms high level followed by 2ms low level, which is reassembled into a continuous signal output.

[0146] The embodiments of the present invention solve the problems in traditional solutions where duty cycle adjustment is disconnected from voltage changes and signal mutations cause control jitter, improve the synchronization accuracy of motor speed and tension adjustment, and adapt to the complex working conditions of rapid voltage jumps in high-strength steel plate production.

[0147] The present invention provides a specific embodiment, step 105, using the voltage adjustment instruction to correct the trigger phase of the pulse sequence after the duty cycle is adjusted so that the speed of the drive motor is synchronously matched with the tension adjustment amount, specifically comprising the following steps:

[0148] Step 501: Based on the waveform data of the voltage value changing with time in the voltage regulation instruction, identify the starting time point of the voltage value changing from low to high as the rising edge time point, and the starting time point of the voltage value changing from high to low as the falling edge time point;

[0149] In this step, waveform data refers to the time-varying numerical sequence of the voltage values of the voltage regulation instructions. This data reflects the timing characteristics of the electronically controlled valve's operation and is acquired through real-time voltage signal acquisition. The rising edge time point refers to the moment when the voltage value transitions from a low level to a high level, marking the start of the voltage regulation action. The falling edge time point refers to the moment when the voltage value transitions from a high level to a low level, marking the end of the voltage regulation action.

[0150] In this embodiment of the present invention, the voltage turning point is detected by analyzing the waveform data of the voltage regulation instruction. When the voltage value jumps from a state lower than the previous value to a value higher than the next value, the time point is recorded as the rising edge time point; when the voltage value jumps from a state higher than the previous value to a value lower than the next value, the time point is recorded as the falling edge time point. For example, the starting time t = 2s when the voltage value rises from 5V to 7V is the rising edge time point.

[0151] Step 502: Calculating a trigger phase correction value of each pulse unit in the duty cycle-adjusted pulse sequence according to the rising edge time point and the falling edge time point;

[0152] In this step, the trigger phase correction amount refers to the time offset that needs to be adjusted for the trigger time point of the pulse unit in the pulse sequence after adjusting the duty cycle. It is calculated by multiplying the timing distance by the correction coefficient, reflecting the synchronization requirement of the voltage regulation instruction on the motor action timing.

[0153] In an embodiment of the present invention, the timing distance is calculated by measuring the time difference between the initial trigger time point of a pulse unit and the time point of the nearest rising or falling edge. This timing distance is then multiplied by a defined trigger phase correction factor, e.g., each millisecond of time difference corresponds to a 0.1 ms phase correction, to obtain the trigger phase correction amount. For example, if the distance between the initial trigger time point of a pulse unit and the time point of the nearest rising edge in a pulse sequence after duty cycle adjustment is 3 ms, and the preset correction factor is 0.1, the trigger phase correction amount is 0.3 ms.

[0154] Step 503: superimposing the trigger phase correction value of each pulse unit in the pulse sequence after the duty cycle is adjusted with the corresponding initial trigger time point to generate a third adjusted pulse unit;

[0155] In this step, the third adjusted pulse unit refers to the pulse unit after the initial trigger time point is superimposed with the trigger phase correction amount, which is used to preliminarily align the action timings of the electronically controlled valve and the motor.

[0156] In this embodiment of the present invention, the initial trigger time of each pulse unit (e.g., t = 5ms) is added to the trigger phase correction (e.g., +0.3ms) to generate an adjusted pulse unit with a trigger time of t = 5.3ms. The adjusted pulse unit retains the original high-level duration and interval; only the trigger time is modified. For example, a pulse sequence with a high level of 1ms at t = 5ms after duty cycle adjustment is adjusted to a high level of 1ms at t = 5.3ms.

[0157] Step 504: testing the third adjusted pulse unit. If the triggering time interval between adjacent third adjusted pulse units is less than a preset minimum interval threshold, shifting the triggering time point of the next third adjusted pulse unit backward until it meets the preset minimum interval threshold, thereby obtaining a fourth adjusted pulse unit.

[0158] In this step, the trigger interval refers to the time difference between the triggering time points of adjacent third-adjusted pulse units and is used to detect timing conflicts. The preset minimum interval threshold refers to the minimum allowed triggering time interval to prevent control conflicts caused by pulse signal overlap. The fourth-adjusted pulse unit refers to the pulse unit generated by shifting the out-of-limit triggering time point to ensure that the timing interval meets the constraints.

[0159] In an embodiment of the present invention, the trigger time intervals of adjacent pulse units are detected, such as the previous trigger time t=5.3ms, the next trigger time t=5.5ms, and the interval is 0.2ms. If it is less than the preset minimum interval threshold, such as 0.5ms, the trigger time point of the next pulse unit is shifted backward to meet the preset minimum interval threshold, such as t=5.8ms, to generate a fourth adjusted pulse unit. The shift operation ensures the timing continuity of the pulse sequence through an interpolation algorithm.

[0160] Step 505: Reorganize the fourth adjusted pulse unit to generate a pulse sequence with a modified trigger phase, wherein the triggering time point of the pulse sequence with the modified trigger phase is synchronized with the waveform change of the voltage adjustment instruction, so that the speed of the drive motor is synchronously matched with the tension adjustment amount;

[0161] In this step, the pulse sequence after the trigger phase is corrected refers to the pulse signal finally generated, and its triggering time point is strictly synchronized with the waveform change of the voltage regulation instruction.

[0162] In this embodiment of the present invention, the shifted fourth adjusted pulse unit is reassembled according to the original periodic arrangement rule (e.g., one pulse unit every 2ms), ultimately generating a pulse sequence with a modified trigger phase. For example, the pulse sequence with modified trigger phases is a high level for 1ms at t=5.3ms and a high level for 1ms at t=5.8ms, ensuring that the trigger timing is strictly synchronized with the waveform changes of the voltage regulation command.

[0163] The embodiment of the present invention achieves precise synchronization between the voltage regulation of the electric control valve and the speed of the drive motor by correcting the pulse trigger phase and resolving timing conflicts, solves the control signal conflicts and speed and tension misalignment problems caused by timing deviations in traditional solutions, improves the stability of system collaborative control, and adapts to the complex working conditions of rapid voltage jumps and frequent load fluctuations in high-strength steel plate production.

[0164] The present invention provides a specific embodiment, step 502, calculating the trigger phase correction amount of each pulse unit in the pulse sequence after the duty cycle is adjusted according to the rising edge time point and the falling edge time point, specifically includes the following steps:

[0165] Step 511: Calculate the absolute values of voltage changes corresponding to the rising edge time point and the falling edge time point respectively;

[0166] In this step, the absolute value of the voltage change refers to the voltage change amplitude at the rising edge or falling edge time point of the voltage regulation instruction, which is calculated by subtracting the absolute value of the voltage value at the previous moment from the current voltage value.

[0167] In this embodiment of the present invention, the voltage values of the voltage regulation instruction at the rising edge (e.g., when the voltage rises from 5V to 8V at t = 2s) and the falling edge (e.g., when the voltage drops from 8V to 6V at t = 4s) are obtained and their absolute values are calculated. For example, the absolute value of the rising edge change is |8V - 5V| = 3V, and the absolute value of the falling edge change is |6V - 8V| = 2V. This absolute value of the voltage change is used to quantify the intensity of the voltage regulation action, reflecting the dynamic amplitude of the electronically controlled valve's regulation requirements.

[0168] Step 512: defining a trigger phase correction coefficient according to the absolute value of the voltage change;

[0169] In this step, the trigger phase correction coefficient refers to a proportional factor set according to the absolute value of the voltage change, which is used to map the voltage regulation requirement to a time correction value, for example, each 1V change corresponds to a 0.05ms coefficient.

[0170] In this embodiment of the present invention, the absolute value of the voltage change is mapped to the trigger phase correction factor using a preset proportional relationship, such as a 0.05ms correction factor for every 1V change. For example, a 3V absolute change on the rising edge corresponds to a 0.15ms trigger phase correction factor, while a 2V absolute change on the falling edge corresponds to a 0.10ms trigger phase correction factor. A larger trigger phase correction factor indicates a stronger voltage regulation requirement and a larger trigger phase correction amplitude.

[0171] Step 513: Calculating an initial trigger phase correction value for each pulse unit in the duty cycle-adjusted pulse sequence based on the trigger phase correction coefficient, the initial trigger time point corresponding to each pulse unit in the duty cycle-adjusted pulse sequence, a first timing distance between the initial trigger time point and the rising edge time point, and a second timing distance between the initial trigger time point and the falling edge time point;

[0172] In this step, the first timing distance refers to the time difference between the initial triggering time point of the pulse unit and the time point of the most recent rising edge, which is used to measure the timing correlation between the pulse and the voltage increase action. The second timing distance refers to the time difference between the initial triggering time point of the pulse unit and the time point of the most recent falling edge, which is used to measure the timing correlation between the pulse and the voltage decrease action. The initial trigger phase correction refers to the preliminary correction value calculated by the timing distance and the trigger phase correction coefficient, which requires further constraints to ensure compliance with the timing rules of the pulse sequence.

[0173] In an embodiment of the present invention, by measuring the first timing distance between the initial trigger time point and the nearest rising edge time point of each pulse unit in the pulse sequence after the duty cycle is adjusted, such as the first timing distance between the initial pulse trigger time t=2.3s and the rising edge time point t=2.0s is 0.3s, and measuring the second timing distance between the initial pulse trigger time t=2.3s and the nearest falling edge time point, such as the second timing distance between the initial pulse trigger time t=2.3s and the falling edge time point t=4.0s is 1.7s, the smaller first timing distance (0.3s) is selected and multiplied by the corresponding trigger phase correction coefficient (0.15ms) to obtain the initial trigger phase correction amount, that is, 0.3s×0.15ms / s=0.045ms.

[0174] Step 514: performing boundary constraint processing on the initial trigger phase correction value to obtain a trigger phase correction value;

[0175] In this embodiment of the present invention, the initial trigger phase correction is constrained within a preset allowable correction range (e.g., ±0.05ms). For example, if the initial trigger phase correction is +0.045ms, it is output directly; if the initial trigger phase correction is +0.06ms, it is scaled to +0.05ms. This constrained trigger phase correction ensures that the pulse triggering time does not exceed the periodic arrangement of the pulse sequence.

[0176] The embodiments of the present invention solve the problem of disconnection between the pulse trigger phase and the voltage regulation action in the traditional solution, improve the timing synchronization accuracy of the electric control valve and the drive motor, avoid the control signal conflict caused by phase deviation, and adapt to the complex requirements of rapid voltage jumps in the production of high-strength steel plates.

[0177] Figure 2 The present invention provides a structural diagram of a steel plate tension dynamic optimization system based on model predictive control, as shown in FIG. Figure 2 As shown, the system includes:

[0178] An acquisition module 21 is used to acquire material characteristic parameters of the high-strength steel plate, wherein the material characteristic parameters include hardness parameters and thickness parameters;

[0179] A prediction module 22 is configured to predict the tension change of the high-strength steel plate and define a voltage adjustment parameter range of the electric control valve based on the material characteristic parameters using model predictive control to generate a voltage adjustment instruction that matches the material characteristic parameters;

[0180] The generation module 23 is used to generate an optimized pulse sequence using pulse modulation technology according to the speed adjustment requirements and real-time load status of the drive motor;

[0181] The adjustment module 24 is used to determine the duty cycle adjustment direction and the duty cycle adjustment ratio according to the voltage adjustment instruction, so as to adjust the optimized pulse sequence to obtain a pulse sequence with adjusted duty cycle.

[0182] The correction module 25 is used to use the voltage regulation instruction to correct the trigger phase of the pulse sequence after adjusting the duty cycle, so that the speed of the drive motor is synchronously matched with the tension adjustment amount, thereby realizing the synchronous adaptive optimization of the tension control response speed and material property changes of the high-strength steel plate during the production process.

[0183] Figure 2 The steel plate tension dynamic optimization system based on model predictive control can be executed Figure 1The implementation principles and technical effects of the model predictive control-based steel plate tension dynamic optimization method described in the illustrated embodiment are not further elaborated. The specific manner in which each module and unit performs operations in the model predictive control-based steel plate tension dynamic optimization system described in the above embodiment has been described in detail in the relevant embodiments of the method and will not be further elaborated here.

[0184] In one possible design, Figure 2 The steel plate tension dynamic optimization system based on model predictive control of the embodiment shown can be implemented as a computing device, such as Figure 3 As shown, the computing device may include a storage component 31 and a processing component 32;

[0185] The storage component 31 stores one or more computer instructions, wherein the one or more computer instructions are called and executed by the processing component 32 .

[0186] The processing component 32 is used to: obtain material characteristic parameters of the high-strength steel plate, wherein the material characteristic parameters include hardness parameters and thickness parameters; based on the material characteristic parameters, use model predictive control to predict the tension change of the high-strength steel plate and define the voltage adjustment parameter range of the electric control valve to generate a voltage adjustment instruction that matches the material characteristic parameters; based on the speed adjustment requirements and real-time load status of the drive motor, use pulse modulation technology to generate an optimized pulse sequence; based on the voltage adjustment instruction, determine the duty cycle adjustment direction and duty cycle adjustment ratio to adjust the optimized pulse sequence to obtain a pulse sequence with adjusted duty cycle; use the voltage adjustment instruction to correct the trigger phase of the pulse sequence with adjusted duty cycle, so that the speed of the drive motor is synchronously matched with the tension adjustment amount, thereby realizing synchronous adaptive optimization of the tension control response speed and material characteristic changes of the high-strength steel plate during the production process.

[0187] The processing component 32 may include one or more processors to execute computer instructions to complete all or part of the steps in the above method. Of course, the processing component may also be implemented as one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above method.

[0188] The storage component 31 is configured to store various types of data to support operations at the terminal. The storage component can be implemented by any type of volatile or non-volatile memory device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disk.

[0189] Of course, a computing device may also include other components, such as input / output interfaces, display components, communication components, etc.

[0190] The input / output interface provides an interface between the processing component and the peripheral interface module, which can be an output device, an input device, etc.

[0191] The communication component is configured to facilitate, among other things, wired or wireless communications between the computing device and other devices.

[0192] Among them, the computing device can be a physical device or an elastic computing host provided by a cloud computing platform, etc. In this case, the computing device can refer to a cloud server, and the above-mentioned processing components, storage components, etc. can be basic server resources rented or purchased from the cloud computing platform.

[0193] The embodiment of the present invention further provides a computer storage medium storing a computer program, which can achieve the above-mentioned Figure 1 The embodiment shown is a method for dynamic optimization of steel plate tension based on model predictive control.

[0194] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0195] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0196] Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented using software plus a necessary general-purpose hardware platform, or of course, hardware. Based on this understanding, the essence of the above technical solution, or the portion 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, a magnetic disk, or an optical disk, and includes a number of instructions for causing a computer device (such as a personal computer, server, or network device) to execute the methods described in each embodiment or certain portions of the embodiments.

[0197] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for dynamic optimization of steel plate tension based on model predictive control, characterized in that: include: Obtaining material characteristic parameters of the high-strength steel plate, wherein the material characteristic parameters include hardness parameters and thickness parameters; Based on the material characteristic parameters, using model predictive control, the tension change of the high-strength steel plate is predicted and a voltage adjustment parameter range of the electric control valve is defined to generate a voltage adjustment instruction that matches the material characteristic parameters; According to the speed regulation requirements and real-time load status of the drive motor, pulse modulation technology is used to generate an optimized pulse sequence; Determining a duty cycle adjustment direction and a duty cycle adjustment ratio according to the voltage regulation instruction to adjust the optimized pulse sequence to obtain a pulse sequence with adjusted duty cycle; Using the voltage regulation instruction, the trigger phase of the pulse sequence after the duty cycle is adjusted is corrected so that the speed of the drive motor is synchronously matched with the tension adjustment amount, thereby achieving synchronous adaptive optimization of the tension control response speed and the change of material properties during the production process of the high-strength steel plate; Based on the material characteristic parameters, model predictive control is used to predict the tension change of the high-strength steel plate and define the voltage adjustment parameter range of the electric control valve to generate a voltage adjustment instruction that matches the material characteristic parameters, including: Based on the hardness parameter and thickness parameter in the material characteristic parameters, a dynamic relationship model between deformation rate and tension value is constructed by using model predictive control; Within the prediction window of the model predictive control, the rising rate, peak range and decay rate of the tension fluctuation are calculated using the dynamic relationship model to divide the tension fluctuation threshold range; Based on the tension fluctuation threshold interval and the optimization objective of the model predictive control, defining a voltage adjustment parameter range of the electronically controlled valve, wherein the voltage adjustment parameter range includes a voltage increment upper limit, a voltage attenuation lower limit, and an adjustment step constraint; Based on the voltage adjustment parameter range and in combination with the dynamic correlation between the deformation rate and the tension fluctuation threshold interval, a candidate voltage adjustment parameter sequence is generated through model predictive control optimization; Performing continuity check on the candidate voltage regulation parameter sequence to generate a target voltage regulation parameter combination that meets the voltage mutation amplitude limit and the adjacent parameter timing interval constraint; A final target voltage adjustment parameter with the shortest adjacent parameter time interval and the smallest voltage mutation amplitude is extracted from the target voltage adjustment parameter combination, and the final target voltage adjustment parameter is converted into a voltage adjustment instruction matching the material characteristic parameter.

2. The method according to claim 1, characterized in that Based on the voltage adjustment parameter range and in combination with the dynamic correlation between the deformation rate and the tension fluctuation threshold range, a candidate voltage adjustment parameter sequence is generated through model predictive control optimization, including: According to the numerical range of the deformation rate, the tension fluctuation threshold interval is divided into multiple subintervals, each subinterval corresponding to a specific variation range of the deformation rate; generating an initial voltage regulation parameter set matching the deformation rate of each subinterval based on the voltage increment upper limit and the voltage attenuation lower limit of the voltage regulation parameter range; Performing parameter expansion on the initial voltage adjustment parameter set to generate an expanded voltage adjustment parameter set; According to the adjustment step size constraint, the voltage adjustment parameters in the expanded voltage adjustment parameter set are discretized and segmented to generate a discretized voltage adjustment parameter set; Within the prediction window of the model predictive control, according to the dynamic correlation between the deformation rate and the tension fluctuation threshold range, the target voltage regulation parameter that meets the multi-stage tension fluctuation suppression requirements is selected from the discretized voltage regulation parameter set to generate a candidate voltage regulation parameter sequence.

3. The method according to claim 1, characterized in that According to the speed regulation requirements and real-time load status of the drive motor, pulse modulation technology is used to generate an optimized pulse sequence, including: According to the speed regulation requirements of the drive motor, the reference waveform parameters of the pulse modulation technology are set, wherein the reference waveform parameters include the initial pulse width and the initial pulse interval; Based on the initial pulse width and the initial pulse interval, generating an initial control signal waveform according to a periodic arrangement rule, wherein the initial control signal waveform is composed of a plurality of pulse units; Calculating a width adjustment amount of each pulse unit in the initial control signal waveform according to the real-time load state of the drive motor, wherein the width adjustment amount is proportional to the change in the real-time load state; Superimposing the width adjustment amount of each pulse unit in the initial control signal waveform and the corresponding initial pulse width to generate a first adjusted pulse unit, and recombining the first adjusted pulse units to generate a transition pulse sequence; The intervals between adjacent first adjusted pulse units in the transition pulse sequence are smoothed to eliminate the sudden changes in the intervals between adjacent first adjusted pulse units, thereby generating an optimized pulse sequence.

4. The method according to claim 1, wherein Determining a duty cycle adjustment direction and a duty cycle adjustment ratio according to the voltage regulation instruction to adjust the optimized pulse sequence to obtain a pulse sequence with adjusted duty cycle, including: The absolute value of the numerical change of the voltage regulation instruction is used as the duty cycle adjustment ratio, and the numerical change is divided into a positive change and a negative change according to a preset positive threshold and a preset negative threshold, and the positive change is used as the direction of increasing the duty cycle, and the negative change is used as the direction of decreasing the duty cycle; Based on the duty cycle adjustment direction and the duty cycle adjustment ratio, establishing a high-level duration correction rule corresponding to each pulse unit in the optimized pulse sequence, wherein the duty cycle adjustment direction includes a duty cycle increasing direction and a duty cycle decreasing direction; According to the high-level duration correction rule, correcting the high-level duration of the pulse unit in the optimized pulse sequence to generate a second adjusted pulse unit; Verifying the second adjusted pulse units, and if the mutation amplitude of the high level duration of adjacent second adjusted pulse units exceeds a preset mutation threshold, smoothing the mutation amplitude to finally generate a verified pulse unit sequence; The verified pulse unit sequence is reorganized to obtain a pulse sequence with adjusted duty cycle.

5. The method according to claim 1, wherein Using the voltage regulation instruction, the trigger phase of the pulse sequence after the duty cycle is adjusted is corrected so that the speed of the drive motor is synchronously matched with the tension adjustment amount, including: According to the waveform data of the voltage value changing with time in the voltage regulation instruction, identifying the starting time point of the voltage value changing from low to high as the rising edge time point, and the starting time point of the voltage value changing from high to low as the falling edge time point; Calculating a trigger phase correction amount for each pulse unit in the duty cycle-adjusted pulse sequence according to the rising edge time point and the falling edge time point; Superimposing the trigger phase correction amount of each pulse unit in the pulse sequence after adjusting the duty cycle with the corresponding initial trigger time point to generate a third adjusted pulse unit; Testing the third adjusted pulse unit, if the triggering time interval between adjacent third adjusted pulse units is less than a preset minimum interval threshold, shifting the triggering time point of the next third adjusted pulse unit backward until the preset minimum interval threshold is met, thereby obtaining a fourth adjusted pulse unit; The fourth adjusted pulse unit is reorganized to generate a pulse sequence after the trigger phase is corrected, and the trigger time point of the pulse sequence after the trigger phase is synchronized with the waveform change of the voltage regulation instruction, so that the speed of the drive motor is synchronously matched with the tension adjustment amount.

6. The method according to claim 5, characterized in that Calculating the trigger phase correction amount of each pulse unit in the pulse sequence after adjusting the duty cycle according to the rising edge time point and the falling edge time point, including: Calculate the absolute values of voltage changes corresponding to the rising edge time point and the falling edge time point respectively; Defining a trigger phase correction coefficient according to the absolute value of the voltage value change; Calculating an initial trigger phase correction amount for each pulse unit in the pulse sequence after the duty cycle is adjusted according to the trigger phase correction coefficient, an initial trigger time point corresponding to each pulse unit in the pulse sequence after the duty cycle is adjusted, a first timing distance between the initial trigger time point and the rising edge time point, and a second timing distance between the initial trigger time point and the falling edge time point; Boundary constraint processing is performed on the initial trigger phase correction amount to obtain a trigger phase correction amount.

7. A steel plate tension dynamic optimization system based on model predictive control, characterized in that: include: An acquisition module, configured to acquire material characteristic parameters of the high-strength steel plate, wherein the material characteristic parameters include hardness parameters and thickness parameters; a prediction module, configured to predict the tension change of the high-strength steel plate and define a voltage adjustment parameter range of the electric control valve based on the material characteristic parameters using model predictive control, so as to generate a voltage adjustment instruction that matches the material characteristic parameters; The generation module is used to generate an optimized pulse sequence using pulse modulation technology according to the speed adjustment requirements and real-time load status of the drive motor; an adjustment module, configured to determine a duty cycle adjustment direction and a duty cycle adjustment ratio according to the voltage adjustment instruction, so as to adjust the optimized pulse sequence to obtain a pulse sequence with adjusted duty cycle; a correction module, configured to use the voltage adjustment instruction to correct the trigger phase of the pulse sequence after the duty cycle is adjusted, so that the rotation speed of the drive motor is synchronously matched with the tension adjustment amount, thereby achieving synchronous adaptive optimization of the tension control response speed and the change of material properties of the high-strength steel plate during the production process; Based on the material characteristic parameters, model predictive control is used to predict the tension change of the high-strength steel plate and define the voltage adjustment parameter range of the electric control valve to generate a voltage adjustment instruction that matches the material characteristic parameters, including: Based on the hardness parameter and thickness parameter in the material characteristic parameters, a dynamic relationship model between deformation rate and tension value is constructed by using model predictive control; Within the prediction window of the model predictive control, the rising rate, peak range and decay rate of the tension fluctuation are calculated using the dynamic relationship model to divide the tension fluctuation threshold range; Based on the tension fluctuation threshold interval and the optimization objective of the model predictive control, defining a voltage adjustment parameter range of the electronically controlled valve, wherein the voltage adjustment parameter range includes a voltage increment upper limit, a voltage attenuation lower limit, and an adjustment step constraint; Based on the voltage adjustment parameter range and in combination with the dynamic correlation between the deformation rate and the tension fluctuation threshold interval, a candidate voltage adjustment parameter sequence is generated through model predictive control optimization; Performing continuity check on the candidate voltage regulation parameter sequence to generate a target voltage regulation parameter combination that meets the voltage mutation amplitude limit and the adjacent parameter timing interval constraint; A final target voltage adjustment parameter with the shortest adjacent parameter time interval and the smallest voltage mutation amplitude is extracted from the target voltage adjustment parameter combination, and the final target voltage adjustment parameter is converted into a voltage adjustment instruction matching the material characteristic parameter.

8. A computing device, characterized in that It comprises a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement a steel plate tension dynamic optimization method based on model predictive control as described in any one of claims 1 to 6.

9. A computer storage medium, characterized in that A computer program is stored, and when the computer program is executed by a computer, a steel plate tension dynamic optimization method based on model predictive control as described in any one of claims 1 to 6 is implemented.

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