Temperature control method and device for NMP rectification, electronic equipment and medium

Abstract

The invention relates to the technical field of NMP rectification, in particular to a temperature control method and device for NMP rectification, electronic equipment and a medium. The method comprises the following steps: based on a temperature set value of a current control period, predicting temperature prediction values of a plurality of future control periods by using a preset temperature dynamic prediction model; the deviation between the temperature predicted value of each future control period and the temperature set value of the corresponding future control period is calculated, and a preset optimization target is determined based on a deviation calculation result; and on the basis of a preset optimization target, determining an optimal control sequence for adjusting the reflux quantity in the current control period, and adjusting the reflux quantity in the current control period according to the optimal control sequence for adjusting the reflux quantity, so as to complete the control on the actual temperature of the rectifying section in the current control period. Therefore, the problems of insufficient temperature control precision and weak anti-interference capability in the NMP rectification process are solved, and efficient and stable NMP rectification production is realized.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of NMP rectification, and particularly relates to a temperature control method and device for NMP rectification, an electronic device and a medium. BACKGROUND

[0002] N-methyl-2-pyrrolidone (NMP) is a key solvent for preparation of lithium battery positive electrode materials, and the purity of NMP can directly affect the performance of the battery, and rectification is a core process for efficient recovery and purification of NMP. In the NMP rectification process, temperature is a key parameter for determining the separation efficiency of impurities, and accurate control of the temperature of each stage of the rectification tower is a core prerequisite for ensuring product quality. However, due to the high boiling point and strong polarity of NMP, the rectification process has significant inertia and nonlinearity, which puts high requirements on the accuracy and stability of the temperature control of the rectification process.

[0003] In related technologies, the temperature control of NMP rectification mainly relies on a traditional cascade PID (Proportional Integral Derivative) control method. The cascade PID control system includes a main loop and a secondary loop. The main loop takes the temperature of the rectification section as a controlled variable, and the set value is determined by process requirements. The secondary loop takes the heating power of the heater as a controlled variable, and the set value is determined by the output of the main PID controller. The secondary PID controller adjusts the output of the heater according to the heating power deviation to stabilize the temperature of the rectification section. However, this method cannot dynamically optimize the control parameters in real time, resulting in insufficient temperature control accuracy and weak anti-interference ability in the NMP rectification process, which needs to be solved urgently. SUMMARY

[0004] The application provides a temperature control method and device for NMP rectification, an electronic device and a medium to solve the problems of insufficient temperature control accuracy and weak anti-interference ability in the NMP rectification process, and realize efficient and stable NMP rectification production.

[0005] To achieve the above-mentioned purpose, the first aspect embodiment of the application provides a temperature control method for NMP rectification, comprising the following steps:

[0006] obtaining a temperature set value of a current control period, and predicting temperature prediction values of a plurality of future control periods based on the temperature set value of the current control period by using a preset temperature dynamic prediction model, wherein the preset temperature dynamic prediction model is obtained based on historical operation data of the rectification tower and a dynamic matrix control principle;

[0007] obtaining temperature set values of the plurality of future control periods, respectively calculating a deviation between a temperature prediction value of each future control period and a temperature set value of the corresponding future control period, and determining a preset optimization target based on the deviation calculation result;

[0008] Based on the preset optimization target, a reflux flow adjustment optimal control sequence of the current control period is determined, and the reflux flow of the current control period is adjusted according to the reflux flow adjustment optimal control sequence to complete the control of the actual temperature of the rectification section of the current control period.

[0009] According to an embodiment of the present application, before predicting the temperature prediction values of the plurality of future control periods based on the temperature set value of the current control period and using the preset temperature dynamic prediction model, the following steps are further included:

[0010] Obtaining historical operation data of the rectification tower, and dividing the historical operation data into a training set and a validation set;

[0011] Based on the training set and the dynamic matrix control principle, an initial temperature dynamic prediction model is constructed;

[0012] Obtaining step response data of the rectification tower control system, and based on the step response data, using the validation set to verify whether the initial temperature dynamic prediction model meets a preset standard;

[0013] In the case where the initial temperature dynamic prediction model meets the preset standard, the initial temperature dynamic prediction model is taken as the preset temperature dynamic prediction model.

[0014] According to an embodiment of the present application, the adjusting the reflux flow of the current control period according to the reflux flow adjustment optimal control sequence to complete the control of the actual temperature of the rectification section of the current control period includes:

[0015] Determining a reflux flow adjustment amount of the current control period according to the reflux flow adjustment optimal control sequence, and determining a target reflux flow value according to the reflux flow adjustment amount, and adjusting the current reflux flow of the rectification tower to meet the target reflux flow value;

[0016] Obtaining a current actual temperature of the rectification section corresponding to the target reflux flow value, and calculating a first deviation value between the temperature set value of the current control period and the current actual temperature of the rectification section;

[0017] Based on the first deviation value and a preset weight distribution strategy, correcting a temperature prediction value of a next control period adjacent to the current control period, and taking the corrected temperature prediction value of the next control period as a temperature set value of the next control period;

[0018] When the next control period is the current control period, re-performing the step of predicting the temperature prediction values of the multiple future control periods by using the preset temperature dynamic prediction model based on the temperature set value of the current control period.

[0019] According to an embodiment of the present application, the adjusting the current reflux flow of the rectification tower to meet the target reflux flow value comprises:

[0020] Obtaining an actual reflux flow of the current control period, calculating a target opening degree adjustment amount of the adjusting valve by using a PID controller based on a second deviation value between the target reflux flow value and the actual reflux flow;

[0021] Adjusting the current reflux flow of the rectification tower to meet the target reflux flow value based on the target opening degree adjustment amount.

[0022] According to the temperature control method for NMP rectification provided by the embodiments of the present application, by using the temperature set value of the current control period, the temperature prediction values of the multiple future control periods can be predicted by using the preset temperature dynamic prediction model; the deviations between the temperature prediction values of each future control period and the temperature set values of the corresponding future control periods are calculated respectively, and the preset optimization target can be determined based on the deviation calculation results; based on the preset optimization target, the optimal control sequence of the reflux flow adjustment of the current control period can be determined, and the reflux flow of the current control period is adjusted according to the optimal control sequence of the reflux flow adjustment, so as to complete the control of the actual temperature of the rectification section of the current control period. Therefore, the problems of insufficient temperature control precision and weak anti-interference ability in the NMP rectification process are solved, and efficient and stable NMP rectification production is realized.

[0023] To achieve the above object, the second aspect of the present application provides a temperature control device for NMP rectification, comprising:

[0024] A prediction module is configured to obtain a temperature set value of a current control period, and predict temperature prediction values of multiple future control periods based on the temperature set value of the current control period by using a preset temperature dynamic prediction model, wherein the preset temperature dynamic prediction model is obtained based on historical operation data of the rectification tower and dynamic matrix control principle;

[0025] A determination module is configured to obtain temperature set values of the multiple future control periods, calculate deviations between the temperature prediction values of each future control period and the temperature set values of the corresponding future control periods respectively, and determine a preset optimization target based on the deviation calculation results;

[0026] an adjusting module configured to determine a flow rate adjustment optimal control sequence of the current control period based on the preset optimization target, and adjust the flow rate of the current control period according to the flow rate adjustment optimal control sequence to complete the control of the actual temperature of the rectifying section of the current control period.

[0027] According to an embodiment of the present application, before predicting the temperature prediction values of the plurality of future control periods by using the preset temperature dynamic prediction model based on the temperature set value of the current control period, the prediction module is further configured to:

[0028] obtain historical operation data of the rectifying column, and divide the historical operation data into a training set and a verification set;

[0029] construct an initial temperature dynamic prediction model based on the training set and a dynamic matrix control principle;

[0030] obtain step response data of the rectifying column control system, and verify whether the initial temperature dynamic prediction model meets a preset standard by using the verification set based on the step response data;

[0031] in a case where the initial temperature dynamic prediction model meets the preset standard, taking the initial temperature dynamic prediction model as the preset temperature dynamic prediction model.

[0032] According to an embodiment of the present application, the adjusting module comprises:

[0033] an adjusting unit configured to determine a flow rate adjustment amount of the current control period according to the flow rate adjustment optimal control sequence, determine a target flow rate value according to the flow rate adjustment amount, and adjust the current flow rate of the rectifying column to meet the target flow rate value;

[0034] a calculation unit configured to obtain a current rectifying section actual temperature corresponding to the target flow rate value, and calculate a first deviation value between the temperature set value of the current control period and the current rectifying section actual temperature;

[0035] a correction unit configured to correct a temperature prediction value of a next control period adjacent to the current control period based on the first deviation value and a preset weight distribution strategy, and take the corrected temperature prediction value of the next control period as a temperature set value of the next control period;

[0036] an execution unit configured to re-execute the step of predicting the temperature prediction values of the plurality of future control periods by using the preset temperature dynamic prediction model based on the temperature set value of the current control period when the next control period is the current control period.

[0037] According to one embodiment of the present application, the adjusting unit is specifically used for:

[0038] The actual reflux flow of the current control period is obtained, a target opening degree adjustment amount of the adjusting valve is calculated by using a PID controller based on a second deviation value between the target reflux flow value and the actual reflux flow;

[0039] The current reflux flow of the rectifying tower is adjusted to meet the target reflux flow value based on the target opening degree adjustment amount.

[0040] According to the temperature control device for NMP rectification provided in the embodiments of the present application, by using the preset temperature dynamic prediction model, the temperature prediction values of multiple future control periods can be predicted based on the temperature set value of the current control period; the deviation between the temperature prediction value of each future control period and the temperature set value of the corresponding future control period is calculated respectively, and the preset optimization target can be determined based on the deviation calculation result; based on the preset optimization target, the reflux flow adjustment optimal control sequence of the current control period can be determined, and the reflux flow of the current control period is adjusted according to the reflux flow adjustment optimal control sequence, so as to complete the control of the actual temperature of the rectification section of the current control period. In this way, the problems of insufficient temperature control precision and weak anti-interference ability in the NMP rectification process are solved, and efficient and stable NMP rectification production is realized.

[0041] To achieve the above object, the third aspect of the present application provides an electronic device, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the temperature control method for NMP rectification as described in the above embodiments.

[0042] To achieve the above object, the fourth aspect of the present application provides a computer readable storage medium having a computer program stored thereon, wherein the program is executed by a processor to implement the temperature control method for NMP rectification as described in the above embodiments.

[0043] To achieve the above object, the fifth aspect of the present application provides a computer program product comprising a computer program, wherein the computer program is executed by a processor to implement the temperature control method for NMP rectification as described in the above embodiments.

[0044] The additional aspects and advantages of the present application will be partially given in the following description, partially become obvious from the following description, or be known by the practice of the present application. BRIEF DESCRIPTION OF DRAWINGS

[0045] The above and / or additional aspects and advantages of the present application will become apparent and more readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings, in which:

[0046] Figure 1 FIG. 1 is a flowchart of a temperature control method for NMP rectification according to an embodiment of the present application;

[0047] Figure 2 FIG. 4 is a sampling diagram of a unit step data according to an embodiment of the present application;

[0048] Figure 3 FIG. 6 is a block diagram of a temperature control system for NMP rectification according to an embodiment of the present application;

[0049] Figure 4 FIG. 7 is a block diagram of a temperature control device for NMP rectification according to an embodiment of the present application;

[0050] Figure 5 FIG. 8 is a structural diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0051] Embodiments of the present application are described in detail below with reference to the accompanying drawings. The embodiments described below are examples for explaining the present application and should not be understood as limiting the present application.

[0052] A temperature control method, device, electronic device and medium for NMP rectification according to embodiments of the present application are described below with reference to the accompanying drawings.

[0053] Figure 1 FIG. 1 is a flowchart of a temperature control method for NMP rectification according to an embodiment of the present application.

[0054] As shown in FIG. 1, the temperature control method for NMP rectification includes the following steps: Figure 1

[0055] In step S101, a temperature set value of a current control period is obtained, and a temperature prediction value of a plurality of future control periods is predicted based on the temperature set value of the current control period by using a preset temperature dynamic prediction model, wherein the preset temperature dynamic prediction model is obtained based on historical operation data of the rectification tower and a dynamic matrix control principle.

[0056] ​It can be understood that the temperature set value can be determined according to the requirements of the NMP rectification process. The control period can be combined with the temperature hysteresis time, the system dynamic response, the cooperation of the main and auxiliary circuits, and the real-time calculation capability, and through experiments or system identification, a suitable period length is determined to ensure that the main dynamic stage is covered while the control is timely. The multiple future control periods refer to a number of time units extending from the current control period to the future, which are used to predict and plan the long-term performance of the system, rather than just the state of the current control period. The preset temperature dynamic prediction model is a mathematical model, which is constructed based on the dynamic matrix control principle and the historical operation data of the rectification tower. The rectification tower is a chemical equipment used for separating different components in a liquid mixture. Through the process of heating and cooling, light components and heavy components can be gradually separated. Dynamic matrix control is an advanced control algorithm mainly applied to industrial process control. It can predict future outputs by analyzing the dynamic characteristics of the system and optimize control strategies to improve the stability and efficiency of the system. The historical operation data of the rectification tower refers to various parameters and state information recorded during the operation of the rectification tower in the past, which can include temperature-related data (such as temperature measurements of rectification and stripping sections), flow data (such as column top reflux flow, feed flow, etc.), control parameters (such as regulating valve opening, PID controller set value and output value, etc.), disturbance records (such as changes in feed composition, etc.), and environmental parameters (such as ambient temperature, pressure, etc.).

[0057] Specifically, in the current control period, based on the temperature set value of the current control period, the preset temperature dynamic prediction model (obtained based on the historical operation data of the rectification tower and the dynamic matrix control principle) can be used to predict the temperature change trend in the next multiple future control periods, and the temperature prediction value of each future control period can be obtained. In this way, the future temperature fluctuation can be understood in advance, which is convenient for better temperature control and management in the future.

[0058] In step S102, the temperature set value of the multiple future control periods is obtained, the deviation between the temperature prediction value of each future control period and the temperature set value of the corresponding future control period is calculated, and the preset optimization target is determined based on the deviation calculation result.

[0059] Specifically, after obtaining the temperature prediction values of the plurality of future control periods, the deviation between the temperature prediction value and the corresponding temperature set value of each future control period can be calculated based on the temperature set value and the temperature prediction value of each future control period, so as to obtain the deviation results of the plurality of future control periods. Through the deviation results, the degree of deviation between the temperature prediction value and the actual temperature set value can be analyzed, which provides key data support for further optimizing the temperature control strategy. Based on these deviation results, the preset optimization target can be further determined, which aims to minimize the temperature deviation and at the same time reduce the fluctuation of the control amount, so as to ensure that the temperature control of the entire system can reach the established performance standard.

[0060] In step S103, based on the preset optimization target, the flowback amount adjustment optimal control sequence of the current control period is determined, and the flowback amount of the current control period is adjusted according to the flowback amount adjustment optimal control sequence, so as to complete the control of the actual temperature of the rectifying section in the current control period.

[0061] Specifically, after obtaining the preset optimization target, in order to achieve this target, the embodiments of the present application can optimize the flowback amount adjustment strategy in the current control period and the plurality of future control periods based on the preset optimization target, and find a set of optimal flowback amount adjustment amounts (i.e., the flowback amount adjustment optimal control sequence). The sequence can clearly indicate how much material should be refluxed in each control period to achieve precise control of the temperature of the rectifying section.

[0062] In actual operation, the flowback amount optimization adjustment of the current control period can be performed first, that is, the flowback amount of the current control period is adjusted according to the flowback amount adjustment optimal control sequence of the current control period, so as to achieve the control of the actual temperature of the rectifying section in the current control period. After the current control period ends, the actual temperature of the rectifying section in the next control period is adjusted.

[0063] For ease of understanding, how to adjust the flowback amount of each control period according to the flowback amount adjustment optimal control sequence to complete the control of the actual temperature of the rectifying section in each control period is described in detail below.

[0064] As a possible implementation manner, in some embodiments, the reflux flow rate of the current control period is adjusted according to the reflux flow rate adjustment optimal control sequence to complete the control of the actual temperature of the rectification section of the current control period, comprising: determining the reflux flow rate adjustment amount of the current control period according to the reflux flow rate adjustment optimal control sequence, and determining the target reflux flow rate value according to the reflux flow rate adjustment amount, and adjusting the current reflux flow rate of the rectification column to meet the target reflux flow rate value; obtaining the current rectification section actual temperature corresponding to the target reflux flow rate value, calculating the first deviation value between the temperature set value of the current control period and the current rectification section actual temperature; based on the first deviation value and a preset weight distribution strategy, correcting the temperature prediction value of the next control period adjacent to the current control period, and taking the corrected temperature prediction value of the next control period as the temperature set value of the next control period; when the next control period is taken as the current control period, re-executing the step of predicting the temperature prediction value of a plurality of future control periods based on the temperature set value of the current control period using the preset temperature dynamic prediction model.

[0065] Specifically, first, according to the reflux flow rate adjustment optimal control sequence of the current control period, the reflux flow rate adjustment amount that should be adjusted in the current control period can be determined, and based on the adjustment amount, the target reflux flow rate value can be further determined, and the current reflux flow rate of the rectification column is adjusted to meet the target reflux flow rate value. After performing the current reflux flow rate adjustment, the rectification section actual temperature can be collected in real time, and the error between the temperature set value of the current control period and the rectification section actual temperature is calculated to obtain the first deviation value, which reflects the difference between the accuracy of the preset temperature dynamic prediction model and the actual control effect.

[0066] Based on the first deviation value, the temperature prediction value of the next control period adjacent to the current control period can be corrected by error weighting (i.e. preset weight distribution strategy), and the purpose of weighting can make the correction process more reasonable and effective. The corrected temperature prediction value of the next control period is taken as the temperature set value of the next control period (the corrected temperature prediction value is taken as the input of the next control period for control calculation), and then the above prediction, deviation calculation, optimization strategy and control sequence generation process are repeated in the next control period, forming a rolling optimization control mode, which continuously adjusts the control strategy according to the actual situation, ensures that the actual temperature of the rectification section of each control period can always be stable near the set value, thereby forming a closed loop feedback regulation.

[0067] It should be noted that the rolling optimization control balances the temperature tracking accuracy and the stability of the flow regulation in each control cycle by adjusting the weight of the temperature deviation and the control amount change in the optimization target, so as to avoid system oscillation caused by the drastic change of the control amount. That is, when the temperature deviation is large, the system can automatically increase the deviation weight to speed up the temperature convergence speed and ensure fast approach to the set value; when the deviation is small, the control amount weight is increased, so that the flow regulation tends to be smooth, thereby effectively reducing the system oscillation risk in the regulation process and achieving the balance between the control sequence stability and the response speed.

[0068] Specifically, each specific time point k can determine m increments (input change) Δu(k)... Δu(k+m-l) starting from this time point, and the purpose of these increments is to ensure that the output values ω(k+1)... ω(k+p) of the system at the future p time points can be as close as possible to the temperature set value ω(k). During the temperature control process, the change of the increment Δu generally cannot be too drastic, so as to avoid causing instability of the system performance. Therefore, in order to optimize the control effect, an embodiment of the present application can adopt a reasonable sampling point kT optimization index, which can be selected based on the following principles:

[0069]

[0070] Wherein, q i , r j are weight coefficients, representing the suppression of tracking error and the suppression of control amount change. At different time points, the optimization performance index of the model is different, but the relative form of optimization is basically the same, and the whole temperature control process is rolling in this transition.

[0071] In addition, in the process of closed-loop feedback regulation, the error correction weight of the current control is the highest, and the weight of the subsequent control cycle decreases over time, so that the influence of the current disturbance on the subsequent prediction is preferentially corrected. This real-time dynamic correction mechanism can quickly compensate for the deviation between the model prediction and the actual working condition, and improve the adaptability of the preset temperature dynamic prediction model to disturbances such as feed fluctuations and equipment working condition changes.

[0072] Specifically, at t=kT, the increment Δu(k) can be calculated by the following formula:

[0073] u(k) = u(k-1) + Δu(k);

[0074] Since Δu(k) has already taken effect, when predicting the future output of the system, the influence of the increment needs to be added. At the sampling time (k+1)T, the actual output value y(k+1) of the system can be detected first, and then compared with the first component , so as to obtain the first deviation value:​

[0075]

[0076] Then, on the basis of the first deviation value, the temperature prediction value of the future control period is corrected by the method of e(k+1) weighting:

[0077]

[0078] Wherein, The corrected temperature prediction value at (k+1)T, h is the error correction weight vector.

[0079] Optionally, in some embodiments, the current reflux flow of the rectifying tower is adjusted to meet the target reflux flow value, comprising: obtaining the actual reflux flow of the current control period, based on the second deviation value between the target reflux flow value and the actual reflux flow, using the PID controller to calculate the target opening adjustment amount of the regulating valve; based on the target opening adjustment amount, the current reflux flow of the rectifying tower is adjusted to meet the target reflux flow value.

[0080] Specifically, in order to ensure the accurate control of the temperature of the rectification process, first, the actual reflux flow data of the current control period can be obtained, and then the actual reflux flow data is compared with the target reflux flow value to determine the second deviation value between them. Based on the second deviation value, the PID controller can be used for calculation, so as to obtain the target opening adjustment amount of the regulating valve. As a key control parameter, the target opening adjustment amount can ensure that the current reflux flow can accurately reach or maintain the target reflux flow value, so as to realize the accurate control of the temperature of the rectification section.

[0081] Next, how to obtain the preset temperature dynamic prediction model is described in detail.

[0082] As a possible implementation, in some embodiments, before predicting the temperature prediction value of multiple future control periods based on the temperature set value of the current control period using the preset temperature dynamic prediction model, it further comprises: obtaining the historical operation data of the rectifying tower, and dividing the historical operation data into training set and validation set; based on the training set and the dynamic matrix control principle, an initial temperature dynamic prediction model is constructed; obtaining the step response data of the rectifying tower control system, based on the step response data, using the validation set to verify whether the initial temperature dynamic prediction model meets the preset standard; in the case that the initial temperature dynamic prediction model meets the preset standard, the initial temperature dynamic prediction model is used as the preset temperature dynamic prediction model.

[0083] The step response data is obtained by artificially applying a step change signal to the input end of the control system of the rectifying tower, for example, suddenly changing the reflux amount, and then collecting the response data of the output end rectifying section temperature. The data is mainly used to study the dynamic response characteristics of the system after being disturbed, including the temperature change speed, overshoot, and stabilization time, etc., and can clearly reflect the dynamic influence relationship of the reflux amount on the rectifying section temperature.

[0084] That is, the embodiment of the present application is theoretically supported by the dynamic matrix control principle, and a dynamic correlation model between the reflux amount at the top of the tower and the temperature of the rectifying section, that is, a preset temperature dynamic prediction model, is established by collecting relevant data (i.e., historical operation data of the rectifying tower) in the past operation process of the rectifying tower.

[0085] Specifically, the historical operation data of the rectifying tower can be divided into a training set and a validation set according to a certain proportion. Based on the training set, the dynamic correlation model between the reflux amount at the top of the tower and the temperature of the rectifying section, that is, the initial temperature dynamic prediction model, can be initially established by using the dynamic matrix control principle. In order to more accurately construct the prediction model, the step response data can be collected, that is, a step change signal (for example, suddenly changing the reflux amount) is applied to the input end of the control system of the rectifying tower, and then the response data (i.e., step response data) of the actual temperature of the output end rectifying section is continuously collected. In actual working conditions, the disturbance received by the rectifying tower can be complex and diverse, and the step response data can more directly reflect the dynamic response characteristics of the system after being disturbed by a specific disturbance (such as a step change in the reflux amount), thereby verifying the accuracy and reliability of the model under specific disturbance conditions, and supplementing and improving the missing or inaccurate parts of the model.

[0086] Further, the temperature change characteristics in the time domain of the model can be determined by using the collected step response data and the validation set, including key information such as the rate of temperature rise, the time to reach the peak value, and the steady-state value. Through these information, it can be verified whether the initial temperature dynamic prediction model meets the preset standard, and in the case that the initial temperature dynamic prediction model meets the preset standard, the initial temperature dynamic prediction model is taken as the preset temperature dynamic prediction model. With the help of the preset temperature dynamic prediction model, the subsequent trend of the temperature of the rectifying section can be predicted according to the change of the reflux amount, thereby providing a theoretical basis and quantitative support for subsequent accurate control.

[0087] The embodiment of the present application applies a step change signal to the input end of the control system of the rectifying tower, continuously collects the temperature response data of the output end, and selects the effective sampling data after the signal stabilizes as the input of the prediction model, so as to ensure that the model input can cover the complete dynamic stage of the temperature response, including the rising, peak value and steady-state process, thereby accurately capturing the large inertia and large lag characteristics of the NMP rectification.

[0088] For example, if Figure 2 As shown, the embodiment of the present application applies a step change signal to the input end of the control system of the distillation tower, and then a series of sequence sampling values ​​can be obtained at the output end at a series of predetermined sampling time points, such as T, 2T, 3T...nT. These sampling values ​​can be adjusted by dynamic coefficients a1, a2, a3...a n As time goes by, after a limited sampling period, the system will gradually tend to a stable state. At this time, by collecting and analyzing the set of sampled data {a1, a2, a3...a n} to accurately represent the system's dynamic characteristics and are used to construct the parameters of the preset temperature dynamic prediction model. Based on the superposition principle of linear systems, the system's total response can be viewed as the sum of the effects of individual input signal changes on the system. Therefore, using a given input signal (reflux flow) and the temperature object's unit step response model control increment (the response characteristics of the temperature object (distillation section temperature) when the input signal undergoes a unit step change), it is possible to predict the future output value of the temperature control system.

[0089] In order to facilitate those skilled in the art to further understand the temperature control method for NMP distillation proposed in the embodiment of the present application, the temperature control system for NMP distillation involved in the method is introduced below. In view of the fact that the inner loop of the traditional cascade PID control has a good effect on suppressing disturbances, while the outer loop has a poor effect on suppressing disturbances, this system is based on dynamic matrix control (DMC) and cascade PID control to predict temperature in a coordinated manner, that is, the inner loop still uses a PID controller to adjust the reflux flow, and the outer loop uses a DMC predictive controller, forming a cascade control device based on the DMC control algorithm, such as Figure 3 As shown, the system includes a DMC temperature controller, a flow controller, a regulating valve, a reflux pipeline, a flow transmitter, and a temperature transmitter. The DMC temperature controller uses the DMC algorithm to predict the temperature trend of the distillation section, generate a target reflux flow rate, and optimize the control sequence. The flow controller, also known as a PID controller, receives the target reflux flow rate and adjusts the valve opening in real time to precisely control the reflux flow rate. The regulating valve can adjust the valve opening based on the output signal of the flow controller to achieve physical regulation of the reflux flow rate. The reflux pipeline establishes a fluid channel between the top condenser and the distillation column to transport the regulated reflux flow rate. The flow transmitter detects the actual reflux flow rate in real time, converts the flow signal into a standard electrical signal, and feeds it back to the flow controller. The temperature transmitter collects the actual temperature value of the distillation section, converts the temperature signal into a standard electrical signal, and feeds it back to the DMC temperature controller for prediction and correction.

[0090] That is, the embodiment of the present application continues to use the main and auxiliary loop control architecture, the main loop outputs the target flow rate value through the DMC algorithm, the auxiliary loop takes the flow rate as the controlled variable and adjusts the valve opening through the PID controller in real time to realize the staged control of the rectifying section temperature, wherein the main loop prediction period and the auxiliary loop adjustment period are matched coordinately.

[0091] By measuring the rectifying section temperature lag time, the main dynamic stage of the temperature response can be reasonably covered by the main loop prediction period, so that the main loop focuses on temperature trend prediction and target flow rate value generation, the auxiliary loop can respond to the control instruction of the main loop in time and quickly adjust the flow rate valve opening, reduces the control lag, the main and auxiliary loop adjustment periods are matched coordinately, and finally the high-precision and high-stability control of the NMP rectification temperature is achieved.

[0092] In summary, the embodiment of the present application has at least the following advantages:

[0093] (1) The preset temperature dynamic prediction model is constructed by using the dynamic matrix control and the rolling optimization algorithm, which can improve the control precision of the NMP rectification temperature.

[0094] (2) By combining feedback correction with adaptive PID, the disturbance can be quickly responded.

[0095] (3) The main and auxiliary loop cascade control division of labor can reduce the control lag and shorten the temperature adjustment time.

[0096] According to the temperature control method for NMP rectification provided by the embodiment of the present application, based on the temperature set value of the current control period, the preset temperature dynamic prediction model can be used to predict the temperature prediction value of multiple future control periods; the deviation between the temperature prediction value of each future control period and the temperature set value of the corresponding future control period can be calculated respectively, and the preset optimization target can be determined based on the deviation calculation result; based on the preset optimization target, the optimal control sequence of the flow rate adjustment of the current control period can be determined, and the flow rate of the current control period is adjusted according to the optimal control sequence of the flow rate adjustment, so as to complete the control of the actual temperature of the rectifying section of the current control period. Thus, the problems of insufficient temperature control precision and weak anti-interference ability in the NMP rectification process are solved, and efficient and stable NMP rectification production is realized.

[0097] Secondly, the temperature control device for NMP rectification provided by the embodiment of the present application is described with reference to the accompanying drawings.

[0098] Figure 4 is the block schematic diagram of the temperature control device for NMP rectification of one embodiment of the present application.

[0099] As Figure 4As shown, the temperature control device 10 for NMP rectification includes a prediction module 100, a determination module 200, and an adjustment module 300.

[0100] The prediction module 100 is configured to obtain a temperature set value of a current control period, and predict temperature prediction values of multiple future control periods based on the temperature set value of the current control period by using a preset temperature dynamic prediction model, wherein the preset temperature dynamic prediction model is obtained based on historical operation data of the rectification column and a dynamic matrix control principle.

[0101] The determination module 200 is configured to obtain temperature set values of the multiple future control periods, calculate a deviation between the temperature prediction value of each future control period and the temperature set value of the corresponding future control period respectively, and determine a preset optimization target based on the deviation calculation results.

[0102] The adjustment module 300 is configured to determine a reflux flow adjustment optimal control sequence of the current control period based on the preset optimization target, and adjust the reflux flow of the current control period according to the reflux flow adjustment optimal control sequence, so as to complete the control of the actual temperature of the rectification section of the current control period.

[0103] Optionally, in some embodiments, before predicting the temperature prediction values of the multiple future control periods based on the temperature set value of the current control period by using the preset temperature dynamic prediction model, the prediction module 100 is further configured to:

[0104] obtain historical operation data of the rectification column, and divide the historical operation data into a training set and a verification set;

[0105] construct an initial temperature dynamic prediction model based on the training set and the dynamic matrix control principle;

[0106] obtain step response data of the rectification column control system, and verify whether the initial temperature dynamic prediction model meets a preset standard by using the verification set based on the step response data;

[0107] in a case where the initial temperature dynamic prediction model meets the preset standard, the initial temperature dynamic prediction model is taken as the preset temperature dynamic prediction model.

[0108] Optionally, in some embodiments, the adjustment module 300 includes:

[0109] an adjustment unit configured to determine a reflux flow adjustment amount of the current control period according to the reflux flow adjustment optimal control sequence, determine a target reflux flow value according to the reflux flow adjustment amount, and adjust the current reflux flow of the rectification column to meet the target reflux flow value;

[0110] The computing unit is configured to obtain a current rectification section actual temperature corresponding to the target reflux flow value, and calculate a first deviation value between the temperature set value of the current control period and the current rectification section actual temperature.

[0111] The correction unit is configured to correct the temperature prediction value of a next control period adjacent to the current control period based on the first deviation value and a preset weight distribution strategy, and take the corrected temperature prediction value of the next control period as the temperature set value of the next control period.

[0112] The execution unit is configured to re-execute the step of predicting the temperature prediction values of the plurality of future control periods based on the temperature set value of the current control period by using the preset temperature dynamic prediction model when the next control period is taken as the current control period.

[0113] Optionally, in some embodiments, the adjusting unit is specifically configured to:

[0114] The adjusting unit is configured to obtain an actual reflux flow of the current control period, calculate an opening degree adjustment amount of the adjusting valve by using a PID controller based on a second deviation value between the target reflux flow value and the actual reflux flow, and adjust the current reflux flow of the rectification tower to meet the target reflux flow value based on the opening degree adjustment amount.

[0115] The adjusting unit is configured to obtain an actual reflux flow of the current control period, calculate an opening degree adjustment amount of the adjusting valve by using a PID controller based on a second deviation value between the target reflux flow value and the actual reflux flow, and adjust the current reflux flow of the rectification tower to meet the target reflux flow value based on the opening degree adjustment amount.

[0116] It should be noted that the foregoing description of the embodiments of the temperature control method for NMP rectification also applies to the embodiments of the temperature control device for NMP rectification, which will not be described here again.

[0117] The temperature control device for NMP rectification provided by the embodiments of the present application can predict the temperature prediction values of the plurality of future control periods by using the preset temperature dynamic prediction model based on the temperature set value of the current control period, calculate the deviation between the temperature prediction value of each future control period and the temperature set value of the corresponding future control period, determine the preset optimization target based on the deviation calculation result, determine the reflux flow adjustment optimal control sequence of the current control period based on the preset optimization target, and adjust the reflux flow of the current control period according to the reflux flow adjustment optimal control sequence, thereby completing the control of the rectification section actual temperature of the current control period. Thus, the problem of insufficient temperature control precision and weak anti-interference ability in the NMP rectification process is solved, and efficient and stable NMP rectification production is achieved.

[0118] Figure 5 The electronic device provided by the embodiments of the present application is shown in the structural schematic diagram. The electronic device can include:

[0119] The memory 501, the processor 502, and the computer program stored in the memory 501 and executable on the processor 502.

[0120] The processor 502 implements the temperature control method for NMP rectification provided in the above embodiments when executing a program.

[0121] Further, the electronic device further comprises:

[0122] The communication interface 503 is configured to communicate between the memory 501 and the processor 502.

[0123] The memory 501 is configured to store a computer program executable on the processor 502.

[0124] The memory 501 can include a high-speed RAM (Random Access Memory) memory, and can also include a non-volatile memory, for example, at least one disk memory.

[0125] If the memory 501, the processor 502 and the communication interface 503 are implemented independently, the communication interface 503, the memory 501 and the processor 502 can be connected to each other through a bus and complete communication between each other. The bus can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the convenience of representation, Figure 5 In the figure, only one thick line is used to represent, but it does not mean that there is only one bus or one type of bus.

[0126] Optionally, in a specific implementation, if the memory 501, the processor 502 and the communication interface 503 are integrated on a chip, the memory 501, the processor 502 and the communication interface 503 can complete communication between each other through an internal interface.

[0127] The processor 502 can be a CPU (Central Processing Unit), or an ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement the embodiments of the present application.

[0128] The embodiments of the present application also provide a computer readable storage medium, which stores a computer program, and the program is executed by a processor to implement the above-mentioned temperature control method for NMP rectification.

[0129] The embodiment of the present application further provides a computer program product comprising a computer program which, when executed by a processor, implements the temperature control method for NMP rectification as above.

[0130] In addition, the terms "first", "second", "third", etc. are used herein only to describe various circumstances, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features. Therefore, the features defined with "first", "second", etc. can explicitly or implicitly include at least one of the features. In the description of the present application, the meaning of "a plurality of" is at least two, for example, two, three, etc., unless otherwise explicitly and specifically limited.

[0131] In the description of the present application, the description referring to the terms "one embodiment", "some embodiments", "an example", "a specific example", or "some examples" and the like means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the present application, the illustrative description of the above terms is not necessarily directed to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any appropriate manner in any one or more embodiments or examples. In addition, the person skilled in the art can combine and combine the different embodiments or examples described in the present application and the features of the different embodiments or examples without contradiction.

[0132] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present application, and the person skilled in the art can make changes, modifications, replacements and variations to the above embodiments within the scope of the present application.

Claims

1. A temperature control method for NMP distillation, characterized in that, The following steps are involved: Obtaining a temperature setting value for a current control cycle, and based on the temperature setting value for the current control cycle, using a preset temperature dynamic prediction model to predict temperature prediction values ​​for multiple future control cycles, wherein the preset temperature dynamic prediction model is obtained based on historical operating data of the distillation column and a dynamic matrix control principle; Obtaining temperature setting values ​​for the multiple future control periods, calculating deviations between the temperature prediction value for each future control period and the temperature setting value for the corresponding future control period, and determining a preset optimization target based on the deviation calculation results; Based on the preset optimization target, the optimal control sequence for reflux flow regulation of the current control cycle is determined, and the reflux flow of the current control cycle is adjusted according to the optimal control sequence for reflux flow regulation to complete the control of the actual temperature of the distillation section of the current control cycle.

2. The method according to claim 1, characterized in that Before predicting temperature prediction values ​​of multiple future control periods using the preset temperature dynamic prediction model based on the temperature setting value of the current control period, the method further includes: Obtaining historical operating data of a distillation column, and dividing the historical operating data into a training set and a validation set; Based on the training set and the dynamic matrix control principle, an initial temperature dynamic prediction model is constructed; Obtaining step response data of a distillation column control system, inputting the step response data into the distillation column control system to obtain corresponding distillation section temperature response data, and generating a reflux flow-temperature mapping relationship based on the step response data and the corresponding distillation section temperature response data; Based on the reflux-temperature mapping relationship, using the verification set to verify whether the initial temperature dynamic prediction model meets the preset standard; In the case that the initial temperature dynamic prediction model meets the preset standard, the initial temperature dynamic prediction model is used as the preset temperature dynamic prediction model.

3. The method according to claim 1, characterized in that The step of adjusting the reflux flow rate of the current control period according to the reflux flow rate adjustment optimal control sequence to complete the control of the actual temperature of the distillation section of the current control period includes: Determining a reflux flow adjustment amount for the current control period according to the reflux flow adjustment optimal control sequence, determining a target reflux flow value according to the reflux flow adjustment amount, and adjusting the current reflux flow of the distillation tower to meet the target reflux flow value; Obtaining the actual temperature of the current distillation section corresponding to the target reflux flow rate, and calculating a first deviation between the temperature setting value of the current control period and the actual temperature of the current distillation section; Based on the first deviation value and a preset weight distribution strategy, correcting the temperature prediction value of the next control cycle adjacent to the current control cycle, and using the corrected temperature prediction value of the next control cycle as the temperature setting value of the next control cycle; When the next control cycle is used as the current control cycle, the step of predicting temperature prediction values ​​of multiple future control cycles based on the temperature setting value of the current control cycle by using a preset temperature dynamic prediction model is re-executed.

4. The method according to claim 3, characterized in that The adjusting the current reflux flow of the distillation tower to meet the target reflux flow value includes: Obtaining an actual reflux flow rate of the current control period, and calculating a target opening adjustment amount of the regulating valve using a PID controller based on a second deviation value between the target reflux flow rate and the actual reflux flow rate; Based on the target opening adjustment amount, the current reflux flow of the distillation tower is adjusted to meet the target reflux flow value.

5. A temperature control device for NMP distillation, characterized in that, include: a prediction module, configured to obtain a temperature setting value for a current control cycle and, based on the temperature setting value for the current control cycle, predict temperature prediction values ​​for multiple future control cycles using a preset temperature dynamic prediction model, wherein the preset temperature dynamic prediction model is obtained based on historical operating data of the distillation column and a dynamic matrix control principle; a determination module, configured to obtain temperature setting values ​​for the plurality of future control periods, calculate the deviation between the temperature prediction value for each future control period and the temperature setting value for the corresponding future control period, and determine a preset optimization target based on the deviation calculation results; The adjustment module is used to determine the optimal control sequence for reflux flow adjustment in the current control cycle based on the preset optimization target, and adjust the reflux flow in the current control cycle according to the optimal control sequence for reflux flow adjustment to complete the control of the actual temperature of the distillation section in the current control cycle.

6. The device according to claim 5, characterized in that Before predicting the temperature prediction values ​​of multiple future control periods using the preset temperature dynamic prediction model based on the temperature setting value of the current control period, the prediction module is further configured to: Obtaining historical operating data of a distillation column, and dividing the historical operating data into a training set and a validation set; Based on the training set and the dynamic matrix control principle, an initial temperature dynamic prediction model is constructed; Acquire step response data of a distillation column control system, and verify, based on the step response data, using the validation set, whether the initial temperature dynamic prediction model meets a preset standard; In the case that the initial temperature dynamic prediction model meets the preset standard, the initial temperature dynamic prediction model is used as the preset temperature dynamic prediction model.

7. The device according to claim 5, characterized in that The adjustment module includes: an adjusting unit, configured to determine a reflux flow adjustment amount for the current control period according to the reflux flow adjustment optimal control sequence, determine a target reflux flow value according to the reflux flow adjustment amount, and adjust the current reflux flow of the distillation tower to meet the target reflux flow value; a calculation unit, configured to obtain a current actual temperature of the rectifying section corresponding to the target reflux flow rate, and calculate a first deviation between a temperature setting value of the current control period and the current actual temperature of the rectifying section; a correction unit, configured to correct a temperature prediction value of a next control period adjacent to the current control period based on the first deviation value and a preset weight distribution strategy, and use the corrected temperature prediction value of the next control period as a temperature setting value of the next control period; The execution unit is used to re-execute the step of predicting the temperature prediction values ​​of multiple future control cycles based on the temperature setting value of the current control cycle using a preset temperature dynamic prediction model when the next control cycle is used as the current control cycle.

8. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the temperature control method for NMP distillation according to any one of claims 1 to 4.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the temperature control method for NMP distillation according to any one of claims 1 to 4.

10. A computer program product, characterized in that The invention comprises a computer program, which, when executed by a processor, is used to implement the temperature control method for NMP distillation according to any one of claims 1 to 4.

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