Reaction kettle temperature stabilization control system and method for phosphorus pentachloride production
By collecting and analyzing data in real time during the phosphorus pentachloride production process and dynamically adjusting the PID controller parameters, the problem of slow temperature control in the traditional PID algorithm during phosphorus pentachloride production was solved, thus achieving stability of reactor temperature and improved production efficiency.
Patent Information
- Application Number
- CN202610782940.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-06-02
- Publication Date
- 2026-08-25
AI Technical Summary
Traditional PID algorithms cannot adaptively adjust parameters according to the real-time changes in the phosphorus pentachloride synthesis reaction during phosphorus pentachloride production, resulting in slow temperature control response and difficulty in meeting high stability requirements.
By collecting real-time data on chlorine consumption, reactor temperature, and circulating water flow, and analyzing their correlation and degree of correlation, the proportional parameters of the PID controller are dynamically adjusted to address the hysteresis effect of reactor temperature.
Stable temperature control of the reactor during phosphorus pentachloride production was achieved, avoiding frequent temperature fluctuations and improving production efficiency and product quality.
Smart Images
Figure CN122632943A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of reactor temperature control technology, specifically to a reactor temperature stabilization control system and method for phosphorus pentachloride production. Background Technology
[0002] Phosphorus pentachloride, a key phosphorus chloride, is widely used in the manufacture of pharmaceuticals, dyes, and chemical fibers, and is also an important upstream raw material in the lithium hexafluorophosphate industry chain. Currently, its mainstream production process uses the synthesis reaction of phosphorus trichloride and chlorine. Because this reaction is extremely sensitive to thermodynamic conditions, excessively high or low temperatures in the reactor will significantly reduce synthesis efficiency and product quality. Therefore, achieving high-precision and stable control of the reactor temperature is the core key to ensuring the smooth production of phosphorus pentachloride.
[0003] While traditional PID algorithms effectively handle common dynamic characteristics such as large temperature inertia and capacity lag, and are widely used in scenarios where reactor temperature is controlled by adjusting circulating water flow, their parameters are typically tuned to fixed values based on empirical engineering formulas such as the critical proportional method. However, the actual synthesis of phosphorus pentachloride is a strongly exothermic reaction, and the reactor temperature is affected by the dual coupling of "changes in the activity of the synthesis reaction" and "regulation of circulating water flow," resulting in varying degrees of dynamic lag. Because traditional PID algorithms cannot adaptively adjust parameters according to this real-time lag, they respond slowly to the above conditions, easily causing frequent temperature fluctuations and failing to meet the high temperature stability control requirements of phosphorus pentachloride production. Summary of the Invention
[0004] To address the aforementioned technical problems, the purpose of this application is to provide a temperature stabilization control system and method for a reactor used in the production of phosphorus pentachloride. The specific technical solution adopted is as follows: In a first aspect, embodiments of this application provide a method for stabilizing the temperature of a reactor used in the production of phosphorus pentachloride, the method comprising the following steps: Real-time data collection of chlorine consumption, reactor temperature, and circulating water flow during phosphorus pentachloride production; By analyzing the correlation between chlorine consumption and circulating water flow rate in each preset sampling period, the trend reversal coefficient under each sampling period is determined to characterize the degree of the opposite trend between the activity of phosphorus pentachloride synthesis reaction and circulating water flow rate; the trend change amplitude of chlorine consumption and circulating water flow rate in each sampling period, as well as the correlation between chlorine consumption and circulating water flow rate and temperature, are analyzed to determine the trend amplitude influence coefficient under each sampling period. By integrating the trend reversal coefficient and the trend amplitude influence coefficient, the response adjustment coefficient for each sampling period is determined to adjust the proportional parameter in the PID controller; based on the adjusted proportional parameter, the PID controller is used to control the reactor temperature in the next sampling period adjacent to each sampling period.
[0005] Preferably, the process for obtaining chlorine consumption is as follows: Real-time data collection of chlorine feed flow rate, exhaust gas emission, and chlorine concentration in the exhaust gas from the reactor; Calculate the product of exhaust gas emission and chlorine concentration, and record it as chlorine emission. The difference between chlorine feed flow rate and chlorine emission is taken as chlorine consumption.
[0006] Preferably, the method for determining the trend reversal coefficient under each sampling period is as follows: Calculate the correlation coefficient between the smoothed value of chlorine consumption and the smoothed value of circulating water flow rate in each sampling period; If the correlation coefficient is less than 0, the difference between 1 and the correlation coefficient is used as the trend reversal coefficient; otherwise, the trend reversal coefficient is set to 0.
[0007] Preferably, the process for determining the trend amplitude influence coefficient under each sampling period is as follows: Based on the correlation between chlorine consumption and circulating water flow rate and temperature in each sampling period, the correlation degree between chlorine and temperature and the correlation degree between circulating water flow rate and temperature in each sampling period were determined. The correlation between chlorine and temperature in each sampling period is used as the weight for the trend change of chlorine consumption, and the correlation between circulating water flow and temperature is used as the weight for the trend change of circulating water flow. The sum of the weighted results is used as the trend amplitude influence coefficient for each sampling period.
[0008] Preferably, the process for determining the trend changes in chlorine consumption and circulating water flow rate within each sampling period is as follows: The smoothed values of chlorine consumption and circulating water flow rate at all times within each sampling period were fitted to obtain the fitted straight lines for the smoothed values of chlorine consumption and circulating water flow rate, respectively. Calculate the absolute value of the arctangent function of the slope of the fitted straight line for the smoothed values of chlorine consumption and circulating water flow rate, and divide the absolute value by... The results were used as the trend change range of chlorine consumption and the trend change range of circulating water flow, respectively.
[0009] Preferably, the method for determining the chlorine-temperature correlation and the circulating water flow-temperature correlation within each sampling period is as follows: The smoothed values of chlorine consumption, circulating water flow, and temperature in each sampling period are used as inputs to the grey relational analysis algorithm. The algorithm outputs the correlation between the smoothed values of chlorine consumption and temperature, and the correlation between the smoothed values of circulating water flow and temperature. The normalized correlations are denoted as chlorine-temperature correlation and circulating water flow-temperature correlation, respectively.
[0010] Preferably, the response adjustment coefficients for each sampling period are positively correlated with the trend reversal coefficient and the trend amplitude influence coefficient, respectively.
[0011] Preferably, adjusting the proportional parameter in the PID controller includes: The expression for the adjusted proportional parameter is: ; This represents the scaling parameter in the (k+1)th sampling period; , These represent the upper and lower limits of the preset proportional parameters, respectively. represents the response adjustment coefficient in the kth sampling period; round[] represents the rounding function.
[0012] Preferably, the step of using a PID controller to control the reactor temperature within the next sampling period adjacent to each sampling period includes: In the next sampling period adjacent to each sampling period, the deviation between the real-time temperature in the reactor and the preset target temperature, as well as the adjusted proportional parameter, are input into the PID controller, which outputs a temperature control signal to control the temperature in the reactor in real time.
[0013] Secondly, embodiments of this application also provide a reactor temperature stabilization control system for phosphorus pentachloride production, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any of the above-described reactor temperature stabilization control methods for phosphorus pentachloride production.
[0014] This application has at least the following beneficial effects: This application performs correlation calculation and fitting analysis on the smoothed data. Specifically, it uses the negative degree of the correlation coefficient to quantify the risk of the antagonistic relationship between the exothermic reaction and the cooling water flow in the direction of change as a trend reversal coefficient. Combined with the trend change amplitude obtained by linear fitting and the weight obtained by grey relational analysis, the trend amplitude influence coefficient is calculated. This transforms the complex operating condition changes into intuitive dimensionless values, assesses the actual risk of temperature hysteresis fluctuations within the sampling period, and provides accurate and reliable data support for subsequent dynamic adjustment of control parameters. Furthermore, this application directly multiplies the trend reversal coefficient and trend amplitude influence coefficient, which respectively represent the "directionality" and "intensity" of change, to obtain the response adjustment coefficient, quantifying the overall temperature hysteresis risk. Then, using the preset lower limit of the proportional parameter as the base, the response adjustment coefficient is multiplied by the difference between the upper and lower limits of the parameter to calculate the new proportional parameter actually issued. This enables the PID controller to smoothly and accurately obtain the matching control strength between the upper and lower limits according to the actual risk level, effectively avoiding the control sluggishness or over-adjustment problems caused by single assessment, and improving the stability of temperature control in the reactor during the phosphorus pentachloride production process. Attached Figure Description
[0015] To more clearly illustrate the technical solutions and advantages in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0016] Figure 1 A flowchart illustrating the steps of a method for stabilizing the temperature of a reactor in the production of phosphorus pentachloride, provided in one embodiment of this application; Figure 2 This is a schematic diagram of the response adjustment coefficient extraction process provided in one embodiment of this application. Detailed Implementation
[0017] To further illustrate the technical means and effects adopted by this application to achieve the intended purpose of the invention, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of the reactor temperature stabilization control system and method for phosphorus pentachloride production proposed in this application. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.
[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.
[0019] The following, in conjunction with the accompanying drawings, details the specific scheme of the reactor temperature stabilization control system and method for phosphorus pentachloride production provided in this application.
[0020] Please see Figure 1 The diagram illustrates a flowchart of a method for stabilizing the temperature of a reactor in the production of phosphorus pentachloride, according to an embodiment of this application. The method includes the following steps: Step S1: Real-time data collection of chlorine consumption, reactor temperature, and circulating water flow during phosphorus pentachloride production.
[0021] In the current batch of phosphorus pentachloride production process, for the reaction stage of the target reactor, flow sensors are used to collect chlorine feed flow rate and exhaust gas emission rate, a chlorine detector is used to collect chlorine concentration data in the exhaust gas, and the temperature and circulating water flow rate inside the reactor are obtained from the water circulation temperature controller configured in the target reactor. All the above data collection uses the same data acquisition frequency and data sampling period. In this embodiment, the data acquisition frequency is set to 0.2Hz and the data sampling period is set to 2 minutes. In actual applications, as other implementation methods, implementers can set their own values according to specific circumstances; this embodiment does not impose any special limitations.
[0022] To eliminate the influence of dimensional differences between different types of data, the maximum and minimum values of the detection range of the corresponding instruments are used to normalize the collected data using the maximum-minimum normalization method. In practical applications, as another implementation method, implementers may also use other normalization methods such as z-score normalization to normalize the data according to specific circumstances. This embodiment does not impose any special restrictions. The process of normalizing the data using maximum-minimum normalization is a well-known technique and will not be described in detail here.
[0023] Since chlorine reacts rapidly upon contact with phosphorus trichloride, the amount of phosphorus trichloride dissolved and accumulated in the liquid is negligible. Therefore, the activity of the synthesis reaction can be directly characterized by the consumption of chlorine in the reactor. The specific process for obtaining the chlorine consumption is as follows: using the data before normalization, the product of the exhaust gas emission and the chlorine concentration is calculated and recorded as the chlorine emission. The difference between the chlorine feed flow rate and the chlorine emission is taken as the chlorine consumption.
[0024] Furthermore, the chlorine consumption was normalized using the maximum-minimum normalization method to eliminate the influence of dimensions.
[0025] Step S2: By analyzing the correlation between chlorine consumption and circulating water flow rate in each preset sampling period, the trend reversal coefficient under each sampling period is determined to characterize the degree of the opposite trend between the activity of phosphorus pentachloride synthesis reaction and circulating water flow rate; the trend change amplitude of chlorine consumption and circulating water flow rate in each sampling period, as well as the correlation between chlorine consumption and circulating water flow rate and temperature, are analyzed to determine the trend amplitude influence coefficient under each sampling period.
[0026] The synthesis reaction of phosphorus trichloride and chlorine is a strongly exothermic reaction. In actual production, the reaction vessel is mainly cooled and controlled by a water circulation temperature control device. The following coupling relationship exists in this dynamic process: the activity of the synthesis reaction inside the vessel is positively correlated with the vessel temperature (the higher the temperature, the more vigorous the reaction), while the circulating water flow rate is negatively correlated with the vessel temperature (the larger the flow rate, the faster the cooling). When the activity of the synthesis reaction and the circulating water flow rate show opposite trends, their interaction leads to a significant lag in the actual temperature change inside the vessel; and the greater the magnitude of these changes, the greater the lag fluctuation in temperature. Therefore, to overcome this lag effect and improve the dynamic response speed of the PID control system in the water circulation temperature control device to changes in vessel temperature, this embodiment analyzes the correlation between chlorine consumption and circulating water flow rate in each preset sampling period to determine the trend reversal coefficient for each sampling period; it also analyzes the trend change magnitude of chlorine consumption and circulating water flow rate in each sampling period, as well as the correlation between chlorine consumption, circulating water flow rate, and temperature, to determine the trend magnitude influence coefficient for each sampling period. The specific process is as follows: First, to reduce the interference of random noise introduced during data acquisition on the subsequent evaluation of the reaction activity and the true trend and magnitude of the circulating water flow, the acquired data sequence needs to be smoothed. Specifically, in this embodiment, the chlorine consumption, temperature, and circulating water flow in each sampling period are smoothed using a smoothing algorithm. The smoothing algorithm used in this embodiment is exponential smoothing. In practical applications, as other implementation methods, implementers may also choose other smoothing algorithms such as moving average method according to specific circumstances. This embodiment does not impose any special restrictions.
[0027] The process of smoothing data using exponential smoothing is a well-known technique and will not be elaborated further; the data used for analysis and calculation in the following content is the smoothed data.
[0028] Furthermore, this embodiment determines the trend reversal coefficient for each sampling period by analyzing the correlation between the smoothed value of chlorine consumption and the smoothed value of circulating water flow rate within each preset sampling period. Specifically: In this embodiment, the correlation coefficient between the smoothed value of chlorine consumption and the smoothed value of circulating water flow rate in each sampling period is calculated; If the correlation coefficient is less than 0, the difference between 1 and the correlation coefficient is used as the trend reversal coefficient. Conversely, if the correlation coefficient is greater than or equal to 0, the trend reversal coefficient is set to 0.
[0029] It should be noted that there are many commonly used methods for calculating correlation coefficients. In this embodiment, the Pearson correlation coefficient between the smoothed value of chlorine consumption and the smoothed value of circulating water flow in each sampling period is used as the correlation coefficient between the smoothed value of chlorine consumption and the smoothed value of circulating water flow in each sampling period. In practical applications, as other implementation methods, implementers may also use the Spearman correlation coefficient or Kendall's rank correlation coefficient calculation method according to specific circumstances. This embodiment does not impose any special restrictions.
[0030] The calculation method for the Pearson correlation coefficient is a well-known technique and will not be elaborated further.
[0031] Based on the trend reversal coefficient, it should be noted that when phosphorus pentachloride is in normal production and PID feedback control is effective, chlorine consumption (characterizing heat release load) and circulating water flow (characterizing cooling intervention) should show a significant synchronous positive correlation (i.e., the correlation coefficient is close to 1). When the correlation coefficient decreases or even becomes negative, it means that the adjustment of cooling flow has failed to match the changing trend of heat release load, and there is a serious risk of lag or misalignment. Therefore, subtracting the correlation coefficient from 1 can accurately quantify the degree to which the current operating condition deviates from the "ideal synchronous following state".
[0032] However, due to the dynamic changes in the internal and external environment of the reactor (such as internal temperature and pressure, and external temperature and humidity), the actual driving force of reaction activity and circulating water flow rate on the internal temperature varies at different times. This means that even if both have the same magnitude of change when they show opposite trends, the degree of temperature lag fluctuations they cause at different times will be quite different. Based on this, in order to enable the PID control system to accurately identify and quickly respond to such large lag changes with differences, this embodiment analyzes the trend change magnitude of chlorine consumption and circulating water flow rate in each sampling period, as well as the correlation between chlorine consumption, circulating water flow rate and temperature, to determine the trend magnitude influence coefficient under each sampling period. Specifically: In this embodiment, based on the correlation between chlorine consumption and circulating water flow rate and temperature in each sampling period, the chlorine-temperature correlation degree and the circulating water flow rate-temperature correlation degree in each sampling period are determined respectively. Specifically, the smoothed values of chlorine consumption, circulating water flow rate, and temperature in each sampling period are used as inputs to the grey relational analysis algorithm. The sequences formed by the smoothed values of chlorine consumption and circulating water flow rate are used as subsequences, and the sequence formed by the smoothed values of temperature is used as the parent sequence. The correlation degree between the smoothed values of chlorine consumption and temperature and the correlation degree between the smoothed values of circulating water flow rate and temperature are output. The normalized correlation degrees are recorded as the chlorine-temperature correlation degree and the circulating water flow rate-temperature correlation degree, respectively.
[0033] Furthermore, the correlation between chlorine and temperature within each sampling period is used as the weight for the trend change of chlorine consumption, and the correlation between circulating water flow and temperature is used as the weight for the trend change of circulating water flow. The sum of the weighted results is used as the trend amplitude influence coefficient for each sampling period.
[0034] Based on the trend amplitude influence coefficient, it can be understood that the combined effect of changes in chlorine consumption and temperature within the sampling period has a significant lag effect on the reactor temperature. Since the trend amplitude influence coefficient is obtained by multiplying the normalized trend change amplitude by the normalized correlation weight using the arctangent function, its dimension is also a dimensionless pure numerical value. The calculation of the trend amplitude influence coefficient is influenced by the trend change amplitudes of chlorine consumption and circulating water flow, as well as their respective correlation weights with temperature. The larger these trend change amplitudes are, and the stronger their correlation with temperature... The higher the correlation weight, the greater the influence coefficient of the trend amplitude. This reflects that even if the trend direction of reaction and cooling is not misjudged, the temperature will still fluctuate significantly due to the rapid and drastic changes. In this case, the control efforts must be increased. Conversely, the smaller the trend change amplitude of chlorine consumption and circulating water flow, and the smaller the correlation between the smoothed values of chlorine consumption and circulating water flow and the smoothed value of temperature, the smaller the influence coefficient of the trend amplitude. This reflects that the changes in materials and heat inside the reactor are relatively gentle, resulting in weak temperature lag fluctuations, which do not require excessive intervention.
[0035] It should be noted that there are many commonly used normalization methods. In this embodiment, the proportion of the chlorine-temperature correlation in the sum of the chlorine-temperature correlation and the circulating water flow-temperature correlation is used as the normalized value of the chlorine-temperature correlation. Similarly, the proportion of the circulating water flow-temperature correlation in the sum of the chlorine-temperature correlation and the circulating water flow-temperature correlation is used as the normalized value of the circulating water flow-temperature correlation. In practical applications, as other implementation methods, implementers may also adopt other normalization methods according to specific circumstances. This embodiment does not impose any special restrictions.
[0036] To further clarify, the process for determining the trend variation of chlorine consumption and circulating water flow rate within each sampling period is as follows: To eliminate the influence of the physical dimension of time on the slope calculation, all times arranged by time within each sampling period are first converted into a dimensionless sequence of arithmetic progressions (e.g., mapping times to a sequence of natural numbers 0, 1, 2…). Then, the smoothed values of chlorine consumption and circulating water flow rate under the dimensionless sequence are fitted to obtain the fitted straight lines for each sampling period. Further, the absolute values of the arctangent function of the slope of the fitted straight lines for chlorine consumption and circulating water flow rate are calculated, and the absolute values are divided by… The results were used as the trend change range of chlorine consumption and the trend change range of circulating water flow, respectively.
[0037] It should be noted that there are many commonly used fitting algorithms. In this embodiment, the least squares method is used to fit the chlorine consumption and temperature respectively. In practical applications, as other implementation methods, implementers may also use other fitting methods according to specific circumstances. This embodiment does not impose any special restrictions on the selection of fitting algorithms.
[0038] The process of calculating the correlation between data using the grey relational analysis algorithm and fitting the data using the least squares method are well-known techniques, and the specific process will not be described in detail.
[0039] Thus, this embodiment calculates and fits the correlation of the smoothed data, specifically using the negative degree of the correlation coefficient to quantify the risk of the antagonistic relationship between the exothermic reaction and the cooling water flow in the direction of change as a trend reversal coefficient. Combined with the trend change amplitude obtained from linear fitting and the weights obtained from grey relational analysis, the trend amplitude influence coefficient is calculated. This transforms complex operating condition changes into intuitive dimensionless values, assesses the actual risk of temperature hysteresis fluctuations within the sampling period, and provides accurate and reliable data support for subsequent dynamic adjustment of control parameters.
[0040] Step S3: Combine the trend reversal coefficient and the trend amplitude influence coefficient to determine the response adjustment coefficient for each sampling period, so as to adjust the proportional parameter in the PID controller; based on the adjusted proportional parameter, use the PID controller to control the reactor temperature in the next sampling period adjacent to each sampling period.
[0041] After obtaining the trend reversal coefficient and trend amplitude influence coefficient through the aforementioned steps, it is important to clarify that both assess the temperature hysteresis risk from two independent dimensions: "direction" and "intensity." Relying solely on a single coefficient for PID control often results in either overly slow (failure to identify the reversal trend) or overly aggressive (failure to accurately measure the magnitude of change) control action due to the lack of evaluation dimensions. Therefore, this embodiment integrates the trend reversal coefficient and the trend amplitude influence coefficient to determine the response adjustment coefficient for each sampling period, thereby adjusting the proportional parameters in the PID controller. Based on the adjusted proportional parameters, the PID controller controls the reactor temperature within the next adjacent sampling period. The specific calculation and control execution process is as follows: In this embodiment, the response adjustment coefficient for each sampling period is first determined by fusing the trend reversal coefficient and the trend amplitude influence coefficient. Specifically: The response adjustment coefficients for each sampling period are positively correlated with the trend reversal coefficient and the trend amplitude influence coefficient, respectively.
[0042] It should be understood that a positive correlation means that the dependent variable increases as the independent variable increases, and the dependent variable decreases as the independent variable decreases. The specific relationship can be additive or multiplicative, etc., and is determined by the actual application. This application does not impose any special restrictions.
[0043] Preferably, as one implementation method, in this embodiment, the product of the trend reversal coefficient and the trend amplitude influence coefficient under each sampling period is used as the response adjustment coefficient under each sampling period.
[0044] Preferably, the schematic diagram of the response adjustment coefficient extraction process provided in this embodiment is as follows: Figure 2 As shown.
[0045] Based on the response regulation coefficient, it can be understood that the response regulation coefficient is used to characterize the overall temperature lag risk faced by the reactor, reflecting the extent to which the PID controller needs to increase the response speed in the next moment. Since the response regulation coefficient is obtained by multiplying the dimensionless trend reversal coefficient and the trend amplitude influence coefficient, its dimension is also a dimensionless value. When the trend reversal coefficient and the trend amplitude influence coefficient are larger, the response regulation coefficient is larger, which reflects that the reactor is in a high-risk state of "direction reversal and extremely drastic change". If the PID response speed is not increased, the temperature will deviate significantly from the set value. Conversely, when the trend reversal coefficient and the trend amplitude influence coefficient are smaller, the response regulation coefficient is smaller, which reflects that the temperature control in the reactor is currently in a low-risk state. The PID controller only needs to maintain a normal or even slower response speed to avoid system jitter caused by over-adjustment.
[0046] Furthermore, in this embodiment, based on the aforementioned response adjustment coefficient, the proportional parameter in the PID controller is controlled, specifically: As one implementation method, in this embodiment, the expression for the adjusted proportional parameter is: ; This represents the scaling parameter in the (k+1)th sampling period; , These represent the upper and lower limits of the preset proportional parameters, respectively. represents the response adjustment coefficient in the kth sampling period; round[] represents the rounding function.
[0047] It should be noted that in this embodiment, the upper and lower limits of the preset proportional parameters are 7 and 3, respectively. These two values were obtained through tuning experiments using the critical proportional method (such as the Ziegler-Nichols method) during the actual trial production of phosphorus pentachloride. 3 represents the minimum safe proportional baseline that, under the basic hardware conditions of the reactor and water circulation temperature controller, can maintain the stability of the control system without significant oscillations. 7 represents the maximum aggressive response limit that the PID controller can tolerate, ensuring that the control system does not completely diverge and become uncontrollable. In practical applications, implementers need to conduct critical proportional tests again to determine the upper and lower limits that are suitable for their own operating conditions, based on the specific reactor volume, jacket heat transfer efficiency, circulating water pump power, and the allowable deviation range of the process requirements.
[0048] The adjustment process of the proportional parameter can be understood as follows: This process essentially transforms the abstract temperature hysteresis risk assessment result into a specific action command that the PID controller can directly execute. Using the preset lower limit of the proportional parameter as the base, the required additional proportional action is calculated by multiplying the response adjustment coefficient by the difference between the upper and lower limits of the parameter. Rounding to one decimal place is then used to ensure the engineering feasibility of the issued parameter. This design allows the proportional parameter to be amplified precisely and smoothly between the upper and lower limits according to a linear rule whenever the hysteresis risk is assessed to increase. This gives the PID controller stronger control force to suppress temperature deviation in the next cycle.
[0049] Furthermore, based on the adjusted proportional parameters, a PID controller is used to control the reactor temperature within the next sampling period adjacent to each sampling period. Specifically: In the next sampling period adjacent to each sampling period, the deviation between the real-time temperature in the reactor and the preset target temperature, as well as the adjusted proportional parameter, are input into the PID controller, which outputs a temperature control signal to control the temperature in the reactor in real time.
[0050] It should be noted that the preset target temperature should be set according to the theoretical optimal reaction temperature range of the phosphorus pentachloride synthesis process. In this embodiment, considering the conversion efficiency of the reaction between phosphorus trichloride and chlorine and the safety margin to prevent the decomposition of phosphorus pentachloride or side reactions, the preset target temperature is usually set to a stable value between 70°C and 80°C. In this embodiment, the preset target temperature is set to 75°C. In actual application, the implementer can also set it according to the specific situation. This embodiment does not impose any special restrictions.
[0051] Thus, in this embodiment, the trend reversal coefficient and trend amplitude influence coefficient, which respectively represent the "direction" and "intensity" of change, are directly multiplied to obtain the response adjustment coefficient, quantifying the overall temperature lag risk. Then, using the preset lower limit of the proportional parameter as the base, the difference between the response adjustment coefficient and the upper and lower limits of the parameter is multiplied to calculate the new proportional parameter actually issued. This allows the PID controller to smoothly and accurately obtain the matching control strength between the upper and lower limits according to the actual risk level, effectively avoiding the control sluggishness or over-adjustment problems caused by single evaluation, and improving the stability of temperature control in the reactor during the phosphorus pentachloride production process.
[0052] Based on the same inventive concept as the above methods, this application also provides a reactor temperature stabilization control system for phosphorus pentachloride production, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any one of the above-described reactor temperature stabilization control methods for phosphorus pentachloride production.
[0053] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, specific embodiments of this specification have been described above. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.
[0054] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.
[0055] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the principles of this application should be included within the protection scope of this application.
Claims
1. A method for stabilizing the temperature of a reactor used in the production of phosphorus pentachloride, characterized in that, The method includes the following steps: Real-time data collection of chlorine consumption, reactor temperature, and circulating water flow during phosphorus pentachloride production; By analyzing the correlation between chlorine consumption and circulating water flow rate in each preset sampling period, the trend reversal coefficient under each sampling period is determined to characterize the degree of the opposite trend between the activity of phosphorus pentachloride synthesis reaction and circulating water flow rate; the trend change amplitude of chlorine consumption and circulating water flow rate in each sampling period, as well as the correlation between chlorine consumption and circulating water flow rate and temperature, are analyzed to determine the trend amplitude influence coefficient under each sampling period. By integrating the trend reversal coefficient and the trend amplitude influence coefficient, the response adjustment coefficient for each sampling period is determined to adjust the proportional parameter in the PID controller; based on the adjusted proportional parameter, the PID controller is used to control the reactor temperature in the next sampling period adjacent to each sampling period.
2. The method for stabilizing the temperature of a reactor used in the production of phosphorus pentachloride as described in claim 1, characterized in that, The process for obtaining chlorine consumption data is as follows: Real-time data collection of chlorine feed flow rate, exhaust gas emission, and chlorine concentration in the exhaust gas from the reactor; Calculate the product of exhaust gas emission and chlorine concentration, and record it as chlorine emission. The difference between chlorine feed flow rate and chlorine emission is taken as chlorine consumption.
3. The method for stabilizing the temperature of a reactor used in the production of phosphorus pentachloride as described in claim 1, characterized in that, The method for determining the trend reversal coefficient for each sampling period is as follows: Calculate the correlation coefficient between the smoothed value of chlorine consumption and the smoothed value of circulating water flow rate in each sampling period; If the correlation coefficient is less than 0, the difference between 1 and the correlation coefficient is used as the trend reversal coefficient; otherwise, the trend reversal coefficient is set to 0.
4. The method for stabilizing the temperature of a reactor used in the production of phosphorus pentachloride as described in claim 1, characterized in that, The process for determining the trend amplitude influence coefficient for each sampling period is as follows: Based on the correlation between chlorine consumption and circulating water flow rate and temperature in each sampling period, the correlation degree between chlorine and temperature and the correlation degree between circulating water flow rate and temperature in each sampling period were determined. The correlation between chlorine and temperature in each sampling period is used as the weight for the trend change of chlorine consumption, and the correlation between circulating water flow and temperature is used as the weight for the trend change of circulating water flow. The sum of the weighted results is used as the trend amplitude influence coefficient for each sampling period.
5. The method for stabilizing the temperature of a reactor used in the production of phosphorus pentachloride as described in claim 4, characterized in that, The process for determining the trend changes in chlorine consumption and circulating water flow rate within each sampling period is as follows: The smoothed values of chlorine consumption and circulating water flow rate at all times within each sampling period were fitted to obtain the fitted straight lines for the smoothed values of chlorine consumption and circulating water flow rate, respectively. Calculate the absolute value of the arctangent function of the slope of the fitted straight line for the smoothed values of chlorine consumption and circulating water flow rate, and divide the absolute value by... The results were used as the trend change range of chlorine consumption and the trend change range of circulating water flow, respectively.
6. The method for stabilizing the temperature of a reactor used in the production of phosphorus pentachloride as described in claim 5, characterized in that, The methods for determining the chlorine-temperature correlation and the circulating water flow-temperature correlation within each sampling period are as follows: The smoothed values of chlorine consumption, circulating water flow, and temperature in each sampling period are used as inputs to the grey relational analysis algorithm. The algorithm outputs the correlation between the smoothed values of chlorine consumption and temperature, and the correlation between the smoothed values of circulating water flow and temperature. The normalized correlations are denoted as chlorine-temperature correlation and circulating water flow-temperature correlation, respectively.
7. The method for stabilizing the temperature of a reactor used in the production of phosphorus pentachloride as described in claim 1, characterized in that, The response adjustment coefficients for each sampling period are positively correlated with the trend reversal coefficient and the trend amplitude influence coefficient, respectively.
8. The method for stabilizing the temperature of a reactor used in the production of phosphorus pentachloride as described in claim 1, characterized in that, The adjustment of the proportional parameter in the PID controller includes: The expression for the adjusted proportional parameter is: ; This represents the scaling parameter in the (k+1)th sampling period; , These represent the upper and lower limits of the preset proportional parameters, respectively. represents the response adjustment coefficient in the kth sampling period; round[] represents the rounding function.
9. The method for stabilizing the temperature of a reactor used in the production of phosphorus pentachloride as described in claim 1, characterized in that, The method of using a PID controller to control the reactor temperature within the next adjacent sampling period includes: In the next sampling period adjacent to each sampling period, the deviation between the real-time temperature in the reactor and the preset target temperature, as well as the adjusted proportional parameter, are input into the PID controller, which outputs a temperature control signal to control the temperature in the reactor in real time.
10. A temperature stabilization control system for a reactor used in the production of phosphorus pentachloride, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the reactor temperature stabilization control method for phosphorus pentachloride production as described in any one of claims 1-9.