Intelligent anti-interference cascade control method for rectifying tower and related device

Abstract

The invention discloses an intelligent anti-interference cascade control method for a rectifying tower, an intelligent anti-interference cascade control device for the rectifying tower, intelligent anti-interference cascade control equipment and a computer readable storage medium. The method comprises the steps that S1, a main controlled variable, an auxiliary controlled variable and at least one feedforward disturbance variable in the rectifying process are monitored in real time; s2, according to the variable quantity of the feed-forward disturbance variable, a feed-forward compensation quantity is calculated through a dynamic feed-forward compensation model; s3, according to the deviation between the main controlled variable and the set value and the deviation between the auxiliary controlled variable and the set value, feedback control quantity is obtained through cascade control loop calculation; s4, adding the feedforward compensation quantity and the feedback control quantity to obtain a final control instruction; and S5, after amplitude constraint processing and change rate constraint processing are carried out on the final control instruction, the final control instruction is output to an execution mechanism for controlling manipulated variables of the rectifying tower. Product quality stability is improved, disturbance recovery time is shortened, and energy consumption is reduced.

Description

Technical Field

[0001] This invention belongs to the field of automatic control technology for chemical processes, and more specifically, relates to an intelligent anti-interference cascade control method for distillation columns, an intelligent anti-interference cascade control device for distillation columns, an intelligent anti-interference cascade control equipment, and a computer-readable storage medium. Background Technology

[0002] Distillation is one of the most important separation unit operations in industries such as chemical engineering, petrochemicals, pharmaceuticals, and food processing, and is widely used in the separation and purification of various mixtures. The control quality of distillation columns directly affects product quality, energy consumption, and production efficiency. With the increasing demands for product quality and the growing pressure to save energy and reduce consumption in industrial production, the performance optimization of distillation column control systems has become an important research direction in the field of process control.

[0003] In related technologies, industrial distillation columns commonly employ single-loop PID control or simple cascade control schemes. Single-loop control typically uses the product concentration at the top or bottom of the column as the controlled variable and the reboiler heating medium flow rate or reflux flow rate as the manipulated variable, forming a single feedback control loop. However, the distillation process is characterized by large time lag, large inertia, strong coupling, and time-varying nature, and is frequently affected by disturbances such as feed flow rate, feed composition, and feed temperature. Single-loop control has a slow response speed and weak anti-interference capability. When disturbances such as feed flow rate occur, it often takes a long time for the product quality to recover to the set value, resulting in the production of defective products and energy waste. Although simple cascade control introduces secondary controlled variables such as intermediate temperature to improve the response speed, it still uses passive feedback for measurable disturbances and cannot achieve active compensation, resulting in unsatisfactory control performance.

[0004] Therefore, how to quickly respond to measurable disturbances, effectively suppress product quality fluctuations, improve product quality stability, shorten disturbance recovery time, reduce energy consumption, and meet the needs of modern industrial production for efficient and stable control of the distillation process is a key issue of concern to those skilled in the art. Summary of the Invention

[0005] The purpose of this application is to provide an intelligent anti-interference cascade control method, an intelligent anti-interference cascade control device, an intelligent anti-interference cascade control equipment, and a computer-readable storage medium for distillation columns, so as to improve product quality stability, shorten disturbance recovery time, reduce energy consumption, and meet the needs of modern industrial production for efficient and stable control of the distillation process.

[0006] To address the aforementioned deficiencies or improvement needs of existing technologies, this invention provides an intelligent anti-interference cascade control method for distillation columns, comprising: S1: Real-time monitoring of the main controlled variable, the secondary controlled variable, and at least one feedforward disturbance variable in the distillation process; S2: Based on the change in the feedforward disturbance variable, the feedforward compensation amount is calculated using the dynamic feedforward compensation model; S3: Based on the deviations of the primary controlled variable and the secondary controlled variable from the set value, the feedback control quantity is calculated through a cascade control loop; wherein, the cascade control loop includes a primary controller and a secondary controller, the primary controller outputs the set value of the secondary controller based on the deviation of the primary controlled variable from the primary set value, and the secondary controller outputs the feedback control quantity based on the deviation of the secondary controlled variable from the set value; S4: Add the feedforward compensation amount to the feedback control amount to obtain the final control command; S5: After performing amplitude constraint processing and rate of change constraint processing on the final control command, it is output to the actuator of the manipulated variable controlling the distillation column.

[0007] Optionally, the primary controlled variable is the concentration of the top product or the concentration of the bottom product, the secondary controlled variable is the temperature of the sensitive plate of the distillation column, the feedforward disturbance variable is the feed flow rate of the distillation column, and the manipulated variable is the flow rate of the reboiler heating medium or the reflux flow rate.

[0008] Optionally, the dynamic feedforward compensation model adopts a lead-lag compensation form, and its transfer function is Kff×(τ1×s+1) / (τ2×s+1); where Kff is the feedforward gain, τ1 is the lead time constant, τ2 is the lag time constant, and s is the Laplace operator. The feedforward compensation amount is calculated by transforming the change of the feedforward disturbance variable using the transfer function.

[0009] Optionally, both the main controller and the secondary controller employ a PID control algorithm. The output of the main controller is limited and then used as the setpoint input for the secondary controller, while the output of the secondary controller is the feedback control quantity.

[0010] Optionally, the amplitude constraint processing is to limit the final control command between a preset upper limit value and a preset lower limit value, and the change rate constraint processing is to limit the change of the final control command relative to the control command at the previous moment to a preset maximum change rate range.

[0011] Optional, also includes: Based on the long-term control performance index of the master controlled variable, Kff in the dynamic feedforward compensation model is adaptively adjusted. The long-term control performance index is the integral sum of squares of the deviations between the master controlled variable and the corresponding set value; when the integral sum of squares exceeds a preset threshold, Kff is adjusted by a preset step size.

[0012] Optionally, the cascade control loop, the calculation of the dynamic feedforward compensation model, the addition of the feedforward compensation amount and the feedback control amount, and the constraint processing are all implemented in a distributed control system (DCS) or a programmable logic controller (PLC), and the actuator is an electric regulating valve or a pneumatic regulating valve.

[0013] This application also provides an intelligent anti-interference cascade control device for a distillation column, comprising: The variable monitoring module is used to monitor the main controlled variable, the secondary controlled variable, and at least one feedforward disturbance variable in the distillation process in real time. The feedforward compensation calculation module is used to calculate the feedforward compensation amount based on the change of the feedforward disturbance variable through a dynamic feedforward compensation model. The feedback control calculation module is used to calculate the feedback control quantity through a cascade control loop based on the deviations of the primary controlled variable and the secondary controlled variable from the setpoints. The cascade control loop includes a primary controller and a secondary controller. The primary controller outputs the setpoint of the secondary controller based on the deviation of the primary controlled variable from the primary setpoint, and the secondary controller outputs the feedback control quantity based on the deviation of the secondary controlled variable from the setpoint. The control command generation module is used to add the feedforward compensation amount and the feedback control amount to obtain the final control command; The constraint processing module is used to perform amplitude constraint processing and rate of change constraint processing on the final control command, and then output it to the actuator of the manipulated variable of the control distillation column.

[0014] This application also provides an intelligent anti-interference cascade control device, comprising: Memory, used to store computer programs; A processor is used to implement the steps of the intelligent anti-interference cascade control method described above when executing the computer program.

[0015] This application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the intelligent anti-interference cascade control method described above.

[0016] This application provides an intelligent anti-interference cascade control method for a distillation column, comprising: S1: real-time monitoring of the primary controlled variable, the secondary controlled variable, and at least one feedforward disturbance variable in the distillation process; S2: calculating a feedforward compensation amount based on the change of the feedforward disturbance variable using a dynamic feedforward compensation model; S3: calculating a feedback control amount based on the deviations of the primary and secondary controlled variables from setpoints using a cascade control loop; wherein the cascade control loop includes a primary controller and a secondary controller, the primary controller outputting a setpoint for the secondary controller based on the deviation of the primary controlled variable from the primary setpoint, and the secondary controller outputting the feedback control amount based on the deviation of the secondary controlled variable from the setpoint; S4: adding the feedforward compensation amount and the feedback control amount to obtain a final control command; S5: performing amplitude constraint processing and rate of change constraint processing on the final control command, and then outputting it to the actuator controlling the manipulated variable of the distillation column.

[0017] It has the following beneficial effects: By real-time monitoring of feedforward disturbance variables such as feed flow rate and calculating compensation amounts through a dynamic feedforward compensation model, proactive compensation for measurable disturbances is achieved. This allows control measures to be taken before disturbances affect product quality, significantly shortening product quality recovery time and effectively reducing product quality fluctuations. The introduction of a cascade control loop enables the system to respond quickly to changes in intermediate variables, further improving the dynamic response speed and anti-interference capability of the control system. The synergistic effect of feedforward compensation and feedback control combines rapid proactive compensation for disturbances with precise feedback correction of setpoint deviations, significantly improving control quality. By applying amplitude and rate-of-change constraints to the final control command, drastic changes in manipulated variables are avoided, protecting the actuators and improving the stability and safety of system operation, while also reducing energy waste, demonstrating significant industrial application value. Attached Figure Description

[0018] To more clearly illustrate the technical solutions 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 embodiments of this application. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0019] Figure 1 A flowchart illustrating an intelligent anti-interference cascade control method for a distillation column provided in this application embodiment; Figure 2 A schematic diagram of the structure of an intelligent anti-interference cascade control device for a distillation column provided in an embodiment of this application; Figure 3This is a schematic diagram of the structure of the intelligent anti-interference cascade control device provided in the embodiments of this application. Detailed Implementation

[0020] The purpose of this application is to provide an intelligent anti-interference cascade control method, an intelligent anti-interference cascade control device, an intelligent anti-interference cascade control equipment, and a computer-readable storage medium for distillation columns, so as to improve product quality stability, shorten disturbance recovery time, reduce energy consumption, and meet the needs of modern industrial production for efficient and stable control of the distillation process.

[0021] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0022] The following embodiment illustrates an intelligent anti-interference cascade control method for distillation columns provided in this application.

[0023] Please refer to Figure 1 , Figure 1 This is a flowchart illustrating an intelligent anti-interference cascade control method for a distillation column, provided as an embodiment of this application.

[0024] In this embodiment, the method may include: S101, real-time monitoring of the main controlled variable, the secondary controlled variable, and at least one feedforward disturbance variable in the distillation process; In this step, the primary controlled variable is the concentration of the top product XI (i.e., the mass percentage concentration of benzene), measured by an online gas chromatograph installed on the top distillation line, with a sampling period of 5 minutes. The secondary controlled variable is the temperature T of the distillation column's sensitive plate, located at the 15th plate, where the temperature is most sensitive to component changes; this is measured using a platinum resistance temperature sensor Pt100, with a sampling period of 5 seconds. The feedforward disturbance variable is the feed flow rate F of the distillation column, measured by a mass flow meter installed on the feed line, with a sampling period of 2 seconds.

[0025] All measurement signals are transmitted to the distributed control system (DCS) via a 4-20mA standard signal.

[0026] S102, the feedforward compensation amount is calculated by the dynamic feedforward compensation model based on the change of the feedforward disturbance variable; In this embodiment, the dynamic feedforward compensation model adopts a lead-lag compensation form, and its transfer function is: Kff×(τ1×s+1) / (τ2×s+1) Where Kff is the feedforward gain, τ1 is the lead time constant, τ2 is the lag time constant, and s is the Laplace operator.

[0027] The specific parameters are determined in the following way: The feedforward gain Kff was determined by steady-state material and energy balance calculations. When the feed flow rate increases by 1 t / h, the reboiler steam flow rate needs to increase by about 0.85 t / h to maintain the product quality. Therefore, Kff was initially set to 0.85.

[0028] The lead time constant τ1 was determined by step response testing. The time constant from the feed flow disturbance to the product concentration at the top of the tower was measured to be approximately 12 minutes, and τ1 was set to 720 seconds.

[0029] The lag time constant τ2 was determined by step response testing. The time constant from the change in reboiler steam flow rate to the concentration of the product at the top of the column was measured to be approximately 8 minutes, and τ2 was set to 480 seconds.

[0030] When a change in feed flow rate is detected, the DCS system calculates the change in feed flow rate ΔFfeed (t / h) and calculates the feedforward compensation amount ΔFf using a discretized dynamic feedforward compensation model. In the digital control system, this is achieved using a difference equation of a first-order inertial element. ΔFf(k) = α × ΔFf(k-1) + β × [Kff × ΔFfeed(k) - Kff × ΔFfeed(k-1)] Where α=τ2 / (τ2+Ts), β=τ1 / (τ2+Ts), Ts is the sampling period (Ts=5 seconds in this embodiment), and k is the current sampling time.

[0031] S103, based on the deviations of the main controlled variable and the secondary controlled variable from the set value, the feedback control quantity is calculated through the cascade control loop; wherein, the cascade control loop includes a main controller and a secondary controller, the main controller outputs the set value of the secondary controller based on the deviation of the main controlled variable from the main set value, and the secondary controller outputs the feedback control quantity based on the deviation of the secondary controlled variable from the set value. The cascade control loop includes a main controller and a secondary controller, both of which employ the PID control algorithm.

[0032] The main controller receives the deviation e1 between the setpoint SP1=99.5% of the product concentration at the top of the column and the measured value XI, and performs PID calculations: u1(k)=Kp1×e1(k)+Ki1×Σe1(k)+Kd1×[e1(k)-e1(k-1)]; The main controller PID parameters are set as follows: proportional coefficient Kp1=2.0, integral coefficient Ki1=0.05, and derivative coefficient Kd1=0.3.

[0033] The output u1 of the main controller is limited (to between 82°C and 88°C) and then used as the setpoint SP2 input of the secondary controller.

[0034] The secondary controller receives the deviation e2 between the temperature setpoint SP2 of the sensitive plate and the measured temperature T, and performs PID calculations: u2(k)=Kp2×e2(k)+Ki2×Σe2(k)+Kd2×[e2(k)-e2(k-1)]; The PID parameters for the secondary controller are set as follows: proportional coefficient Kp2 = 5.0, integral coefficient Ki2 = 0.8, and derivative coefficient Kd2 = 0.1.

[0035] The output u2 of the secondary regulator is the feedback control quantity ΔFc, and its unit is the change in reboiler steam flow rate (t / h).

[0036] S104, add the feedforward compensation amount and the feedback control amount to obtain the final control command; In the adder module of the DCS system, the feedforward compensation quantity ΔFf and the feedback control quantity ΔFc are added together: ΔFtotal(k) = ΔFf(k) + ΔFc(k), and the total control command ΔFtotal for the reboiler steam flow is obtained.

[0037] S105 performs amplitude and rate of change constraint processing on the final control command and outputs it to the actuator of the manipulated variable controlling the distillation column.

[0038] Among them, the amplitude constraint processing adds the final control command ΔF_total to the current steam flow reference value F_reference, and then limits it to between the preset upper limit value F_max = 25 t / h and the preset lower limit value F_min = 10 t / h: F_steam(k) = max[F_min, min(F_reference + ΔF_total(k), F_max)].

[0039] The rate of change constraint is designed to prevent system oscillations caused by excessively rapid changes in steam flow rate. The rate of change of steam flow rate is limited to ±2 t / h / min. If Fsteam(k) - Fsteam(k-1) > 2 × Ts / 60, then Fsteam(k) = Fsteam(k-1) + 2 × Ts / 60; if Fsteam(k) - Fsteam(k-1) < -2 × Ts / 60, then Fsteam(k) = Fsteam(k-1) - 2 × Ts / 60.

[0040] After being constrained, the control command F steam is output through the DCS to the reboiler steam regulating valve (pneumatic regulating valve). This regulating valve receives a 4-20mA standard signal and controls the steam flow rate to be adjusted within the set range.

[0041] After adopting the intelligent anti-interference cascade control method of this embodiment, when the feed flow rate increases stepwise from 50 t / h to 55 t / h, the maximum deviation of the product concentration at the top of the tower is only 0.15% (from 99.5% to 99.35%), and the time required to recover to the set value is approximately 8 minutes. In contrast, when using traditional cascade control (without feedforward compensation), the maximum deviation of the product concentration under the same disturbance reaches 0.48%, and the recovery time exceeds 25 minutes. This method significantly improves the anti-interference capability and response speed of the control system.

[0042] In summary, this embodiment achieves proactive compensation for measurable disturbances by real-time monitoring of feedforward disturbance variables such as feed flow rate and calculating compensation amounts through a dynamic feedforward compensation model. This allows for control measures to be taken before disturbances affect product quality, significantly shortening product quality recovery time and effectively reducing product quality fluctuations. The introduction of a cascade control loop enables the system to respond quickly to changes in intermediate variables, further improving the dynamic response speed and anti-interference capability of the control system. The synergistic effect of the feedforward compensation and feedback control quantities combines rapid proactive compensation for disturbances with precise feedback correction of setpoint deviations, significantly improving control quality. By applying amplitude and rate-of-change constraints to the final control command, drastic changes in manipulated variables are avoided, protecting the actuators and improving the system's operational stability and safety. Simultaneously, energy waste is reduced, demonstrating significant industrial application value.

[0043] Furthermore, another specific embodiment is provided.

[0044] This embodiment provides another intelligent anti-interference cascade control method for distillation columns, applied to an ethanol-water distillation column in a pharmaceutical company. The control objective is to ensure that the ethanol content in the wastewater at the bottom of the column is below 0.5%. Based on Embodiment 1, this method adds an adaptive adjustment function for the feedforward gain. The specific steps are as follows: S101 to S105 are the same as in the previous embodiment, but in this embodiment, the main controlled variable is the concentration of the bottom product, which is measured by an online infrared analyzer with a sampling period of 3 minutes; the secondary controlled variable is the temperature of the 5th tray of the distillation column; and the manipulated variable is the reflux flow rate, which is controlled by an electric regulating valve.

[0045] The initial parameters are set as follows: feedforward gain Kff = 1.2, lead time constant τ1 = 600 seconds, and lag time constant τ2 = 400 seconds.

[0046] S106. Adjust Kff in the dynamic feedforward compensation model adaptively according to the long-term control performance index of the main controlled variable.

[0047] To cope with the slow changes in the characteristics of the distillation column due to factors such as seasons and raw material components, an adaptive adjustment mechanism is designed in this embodiment: For the calculation of the long-term control performance index, the integral square sum (ISE) of the deviation between the main controlled variable and the corresponding set value is used as the performance index, and the statistical period is 24 hours: ISE = Σ[XI(i) - SP1]

[0054] ,

[0053] , ,

[0052] , , × Ts. Where i is all the sampling points within 24 hours.

[0048] Adaptive adjustment rule: Set the preset threshold ISE threshold = 50 (unit: % 2 h). When ISE > ISE threshold, it means that the control performance has declined and the feedforward gain needs to be adjusted. If, within the statistical period, the average value of the main controlled variable < SP1, that is, the product concentration is low, it means that the feedforward compensation is insufficient, and increase Kff by the preset step ΔK = 0.05: Kff_new = Kff_old + 0.05; if, within the statistical period, the average value of the main controlled variable > SP1, that is, the product concentration is high, it means that the feedforward compensation is excessive, and decrease Kff by the preset step ΔK = 0.05: Kff_new = Kff_old - 0.05.

[0049] Adjustment limit: To avoid parameter drift, limit the adjustment range of Kff to be between [0.8, 1.6], and adjust at most once every 24 hours.

[0050] It can be seen that after 30 days of continuous operation, the feedforward gain Kff is adaptively adjusted from the initial 1.2 to 1.35, the system ISE index is reduced from the initial 62% 2 h to 32% 2 h during stable operation, and the qualified rate of the product concentration is increased from 95.2% to 99.1%, significantly improving the adaptability of the control system to process characteristic changes.

[0051] Furthermore, another specific embodiment is provided.

[0052] This embodiment provides an intelligent anti-interference cascade control method implemented based on a programmable logic controller (PLC), which is applied to the methanol-water distillation column of a fine chemical enterprise, and the control objective is to ensure that the methanol purity at the top of the column ≥ 99.8%. The feature of this method is to use the PLC as the control platform, with a lower cost than the DCS system, and it is suitable for small and medium-sized devices. <00\00153>S101. Real-time monitor the main controlled variable, the secondary controlled variable, and at least one feedforward disturbance variable in the distillation process.

[0054] The primary controlled variable is the concentration of the product at the top of the column, measured by an online refractometer with a sampling period of 10 seconds. The measurement signal is transmitted to the PLC via the Modbus protocol. The secondary controlled variable is the temperature of the 22nd tray, measured using a type K thermocouple with a sampling period of 5 seconds. The feedforward disturbance variable is the feed flow rate, measured by an electromagnetic flowmeter with a sampling period of 2 seconds.

[0055] S102 to S105 are similar to the first embodiment, but the specific implementation methods are different: The dynamic feedforward compensation model is implemented in the PLC using structured text (ST) language programming, with the parameters set as follows: Kff=0.92, τ1=540 seconds, τ2=360 seconds.

[0056] The cascade control loop is implemented using the built-in PID function block of the PLC. The parameters of the main controller are: Kp1=1.8, Ki1=0.04, Kd1=0.25; the parameters of the secondary controller are: Kp2=4.5, Ki2=0.6, Kd2=0.08.

[0057] The amplitude constraint and the rate of change constraint are implemented through the limiting function block and the ramp function block of the PLC. The steam flow rate of the reboiler is limited to 8-20 t / h, and the rate of change is limited to ±1.5 t / h / min.

[0058] The PLC outputs a 4-20mA signal to the electric regulating valve through the analog output module (AO module) to control the steam flow of the reboiler.

[0059] In this embodiment, all control algorithms are implemented in a single Siemens S7-1200 series PLC, with a scan cycle set to 100ms. The PLC connects to a host SCADA system via Ethernet to enable parameter setting, trend display, and alarm management functions. Compared to the DCS system in Embodiment 1, the hardware cost of this embodiment is reduced by approximately 60%, while the control performance remains essentially the same.

[0060] During three consecutive months of operation, the system's average response time to feed flow disturbances was 6 minutes, the top product concentration qualification rate reached 98.5%, and energy consumption was reduced by about 8% compared to traditional single-loop control, verifying the feasibility and economy of the method of this invention on a PLC platform.

[0061] Furthermore, another specific embodiment is provided.

[0062] This invention provides an intelligent anti-interference cascade control system for implementing the above method, the system comprising: Sensor group: used to measure feed flow rate F, sensitive plate temperature T, and product quality index XI.

[0063] Main controller: Receives the deviation between the product quality setpoint SP1 and the measured value XI, and performs PID calculations.

[0064] The secondary controller receives the output of the primary controller as its setpoint SP2, receives the measured temperature value T of the sensitive board, performs PID calculations, and outputs the cascade control quantity ΔFc.

[0065] Dynamic feedforward compensator: Receives the feed flow signal and calculates the feedforward compensation amount ΔFf.

[0066] Adder: Used to add ΔFc and ΔFf to obtain the overall control command.

[0067] Output limiting module: Limits the amplitude and rate of change of the overall control command.

[0068] Actuator: Adjusts manipulated variables (such as steam regulating valves) according to the final control command.

[0069] This system adds a channel consisting of feed flow measurement and dynamic feedforward compensator Gff to the traditional cascade control (main controller Gc1, secondary controller Gc2, controlled objects Gp2 and Gp1).

[0070] When the feed flow rate F changes, the signal is immediately processed by the dynamic feedforward compensator Gff. Gff generates a leading compensation signal ΔFf based on a preset gain Kff (e.g., the steam / feed ratio calculated through steady-state energy balance) and dynamic parameters τ1 and τ2 (obtained through step testing). This signal is superimposed on the feedback control signal ΔFc generated by the cascade loop, and together they act on the actuator to adjust the reboiler steam valve position.

[0071] The output limiting module ensures that the total steam flow rate change ΔF_steam is always smooth and within the upper and lower limits ([Fmin, Fmax]) set by the process.

[0072] By properly tuning the PID and feedforward parameters, the system can achieve near-error-free control of feed disturbances, resulting in significantly smaller fluctuations in product quality XI compared to traditional control methods. 1. Fluorite (CaF2): Grade: Typically, a CaF2 content >97% is required. Impurity content is crucial because certain impurities can cause a range of problems: Silica (SiO2): is the most harmful impurity. It reacts with HF to produce gaseous silicon tetrafluoride (SiF4) and water (H2O): 4HF + SiO2 → SiF4↑ + 2H2O. This not only consumes valuable HF products, but the generated SiF4 also reacts with water in subsequent pipelines and equipment to form silica gel (SiO2nH2O) and H2SiF6, causing blockages and corrosion.

[0073] Carbonates (such as CaCO3): react with sulfuric acid to produce CO2 gas, causing the reactants to foam and overflow, while ineffectively consuming sulfuric acid.

[0074] Particle size: It needs to be crushed and ground to a suitable fineness (usually 80-95% passing through a 100-mesh sieve) to increase the contact area with sulfuric acid and improve the reaction rate and conversion rate.

[0075] 2. Sulfuric acid (H2SO4): Concentrated sulfuric acid with a concentration of 98% is usually used.

[0076] It should not contain reducing impurities to avoid the production of toxic or corrosive byproducts.

[0077] The entire process is a continuous operation and mainly includes the following units: 1. Raw material preparation and pretreatment: After being crushed, ground, and dried, fluorite is transported into the fluorite silo by a bucket elevator.

[0078] 98% concentrated sulfuric acid is stored in storage tanks.

[0079] 2. Reaction process: This is the heart of the entire process. Preheated fluorite powder and excess concentrated sulfuric acid (usually 10-15% excess) are continuously and quantitatively added to a rotary reactor.

[0080] Reactors are typically made of alloy steel (such as Hastelloy) and have internal tumblers for turning and propelling the materials to ensure thorough mixing.

[0081] The reaction temperature is strictly controlled between 200 and 250°C.

[0082] Low temperature: slow reaction rate and low conversion rate.

[0083] Excessive temperature can cause sulfuric acid to decompose and produce SO3. The byproduct calcium sulfate forms a dense, hard shell that encapsulates unreacted fluorite, hindering further reaction (a phenomenon known as "passivation") and exacerbating equipment corrosion.

[0084] The reaction is endothermic, and the heat is usually provided by gas or oil burners outside the furnace wall.

[0085] 3. Crude HF gas purification: The gas exiting the reactor is crude hydrofluoric acid gas, whose main component is HF, but it contains a large number of impurities. The entrained dust consists of solid calcium sulfate particles and unreacted fluorite powder.

[0086] Sulfuric acid mist.

[0087] Side reaction gases: SiF4, SO2, SO3, CO2, water vapor, etc.

[0088] Purification systems typically include: Cyclone separator: Removes most of the larger solid particles.

[0089] Scrubbing tower: Uses concentrated sulfuric acid to scrub the gas. Sulfuric acid can absorb moisture and sulfuric acid mist from HF gas, but HF has very low solubility in concentrated sulfuric acid, thus achieving separation and preliminary drying.

[0090] Condenser: Cools the gas and further condenses and separates impurities.

[0091] Electrolytic purification: For electronic-grade HF with extremely high requirements, a molten electrolysis method of KF2HF is used for deep purification.

[0092] 4. HF condensation and distillation: The purified cold HF gas enters the condenser and is condensed into liquid by the frozen brine.

[0093] Liquid crude anhydrous hydrofluoric acid enters the distillation column.

[0094] Distillation columns utilize the difference in boiling points between HF and low-boiling-point impurities (such as SiF4, SO2, and sulfuric acid) for separation. HF has a boiling point of 19.5°C, while SiF4 has a boiling point of -86°C, SO2 has a boiling point of -10°C, and sulfuric acid has a boiling point of 337°C.

[0095] By precisely controlling the temperature at the top and bottom of the column, low-boiling-point impurities are discharged from the top of the column, while high-purity liquid anhydrous hydrofluoric acid (AHF) flows out from the bottom of the column.

[0096] 5. Exhaust gas treatment and by-product recovery: All exhaust gases generated in all process steps (including non-condensable gases discharged from the top of the distillation column) are sent to the exhaust gas absorption system.

[0097] Multi-stage absorption is usually carried out using water or alkaline solutions (such as NaOH or Ca(OH)2 solution).

[0098] After HF and SiF4 are absorbed, a fluorosilicic acid (H2SiF6) solution is formed. 3SiF4 + 2H2O → 2H2SiF6 + SiO2 Fluorosilicic acid can be sold as a byproduct (used in water fluoridation, wood preservatives, and the production of fluorosilicates), or it can be safely discharged after neutralization with alkali.

[0099] 6. Residue treatment: The solid residue discharged from the reactor is mainly calcium sulfate (CaSO4), containing unreacted fluorite, sulfuric acid and a small amount of HF.

[0100] The residue needs to be neutralized and solidified before being sent to a dedicated landfill for safe disposal, as it still contains soluble fluorides and is classified as hazardous waste.

[0101] The following describes an intelligent anti-interference cascade control device for a distillation column provided by an embodiment of this application. The intelligent anti-interference cascade control device and the intelligent anti-interference cascade control method for a distillation column described below can be referred to in correspondence with each other.

[0102] Please refer to Figure 2 , Figure 2 This is a schematic diagram of the structure of an intelligent anti-interference cascade control device for a distillation column provided in an embodiment of this application.

[0103] In this embodiment, the device may include: The variable monitoring module 100 is used to monitor the main controlled variable, the secondary controlled variable, and at least one feedforward disturbance variable in the distillation process in real time. The feedforward compensation calculation module 200 is used to calculate the feedforward compensation amount based on the change of the feedforward disturbance variable through the dynamic feedforward compensation model. The feedback control calculation module 300 is used to calculate the feedback control quantity through a cascade control loop based on the deviations of the main controlled variable and the secondary controlled variable from the set value. The cascade control loop includes a main controller and a secondary controller. The main controller outputs the set value of the secondary controller based on the deviation of the main controlled variable from the main set value. The secondary controller outputs the feedback control quantity based on the deviation of the secondary controlled variable from the set value. The control command generation module 400 is used to add the feedforward compensation amount and the feedback control amount to obtain the final control command; The constraint processing module 500 is used to perform amplitude constraint processing and rate of change constraint processing on the final control command, and then output it to the actuator of the manipulated variable of the control distillation column.

[0104] This application also provides an intelligent anti-interference cascade control device; please refer to it. Figure 3 , Figure 3 This is a schematic diagram of the structure of the intelligent anti-interference cascade control device provided in the embodiments of this application. The intelligent anti-interference cascade control device may include: Memory, used to store computer programs; The processor, when executing a computer program, can implement the steps of any of the intelligent anti-interference cascade control methods for distillation columns described above.

[0105] like Figure 3The diagram shows the structural composition of an intelligent anti-interference cascade control device. This device may include a processor 10, a memory 11, a communication interface 12, and a communication bus 13. The processor 10, memory 11, and communication interface 12 all communicate with each other via the communication bus 13.

[0106] In this embodiment, the processor 10 may be a central processing unit (CPU), an application-specific integrated circuit, a digital signal processor, a field-programmable gate array, or other programmable logic devices.

[0107] The processor 10 can call the program stored in the memory 11. Specifically, the processor 10 can execute the operations in the embodiment of the abnormal IP identification method.

[0108] The memory 11 is used to store one or more programs. The programs may include program code, which includes computer operation instructions. In this embodiment, the memory 11 stores at least a program for implementing the following functions: S1: Real-time monitoring of the main controlled variable, the secondary controlled variable, and at least one feedforward disturbance variable in the distillation process; S2: The feedforward compensation amount is calculated using a dynamic feedforward compensation model based on the change in the feedforward disturbance variable. S3: The feedback control quantity is calculated through a cascade control loop based on the deviations of the primary and secondary controlled variables from the setpoints. The cascade control loop includes a primary controller and a secondary controller. The primary controller outputs the setpoint of the secondary controller based on the deviation of the primary controlled variable from the primary setpoint. The secondary controller outputs the feedback control quantity based on the deviation of the secondary controlled variable from the setpoint. S4: Add the feedforward compensation amount to the feedback control amount to obtain the final control command; S5: After performing amplitude and rate of change constraint processing on the final control command, it is output to the actuator of the manipulated variable controlling the distillation column.

[0109] In one possible implementation, the memory 11 may include a program storage area and a data storage area, wherein the program storage area may store the operating system and applications required for at least one function; and the data storage area may store data created during use.

[0110] In addition, memory 11 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device or other volatile solid-state storage device.

[0111] Communication interface 12 can be an interface for the communication module, used to connect with other devices or systems.

[0112] Of course, it should be noted that, Figure 3 The structure shown does not constitute a limitation on the intelligent anti-interference cascade control device in the embodiments of this application. In practical applications, the intelligent anti-interference cascade control device may include more than Figure 3 More or fewer components as shown, or combinations of certain components.

[0113] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, can implement the steps of any of the above-described intelligent anti-interference cascade control methods for distillation columns.

[0114] The computer-readable storage medium may include various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0115] For a description of the computer-readable storage medium provided in this application, please refer to the above method embodiments; further details will not be repeated here.

[0116] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to the method section.

[0117] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0118] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0119] The above provides a detailed description of the intelligent anti-interference cascade control method, device, equipment, and computer-readable storage medium for a distillation column provided in this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the embodiments above are merely for the purpose of helping to understand the method and its core ideas. It should be noted that those skilled in the art can make various improvements and modifications to this application without departing from its principles, and these improvements and modifications also fall within the protection scope of the claims of this application.

Claims

1. A smart anti-interference cascade control method for distillation columns, characterized in that, include: S1: Real-time monitoring of the main controlled variable, the secondary controlled variable, and at least one feedforward disturbance variable in the distillation process; S2: Based on the change in the feedforward disturbance variable, the feedforward compensation amount is calculated using the dynamic feedforward compensation model; S3: Based on the deviations of the primary controlled variable and the secondary controlled variable from the set value, the feedback control quantity is calculated through a cascade control loop; wherein, the cascade control loop includes a primary controller and a secondary controller, the primary controller outputs the set value of the secondary controller based on the deviation of the primary controlled variable from the primary set value, and the secondary controller outputs the feedback control quantity based on the deviation of the secondary controlled variable from the set value; S4: Add the feedforward compensation amount to the feedback control amount to obtain the final control command; S5: After performing amplitude constraint processing and rate of change constraint processing on the final control command, it is output to the actuator of the manipulated variable controlling the distillation column.

2. The intelligent anti-interference cascade control method according to claim 1, characterized in that, The primary controlled variable is the concentration of the top product or the bottom product, the secondary controlled variable is the temperature of the distillation column's sensitive plate, the feedforward disturbance variable is the feed flow rate of the distillation column, and the manipulated variable is the reboiler heating medium flow rate or the reflux flow rate.

3. The intelligent anti-interference cascade control method according to claim 2, characterized in that, The dynamic feedforward compensation model adopts a lead-lag compensation form, and its transfer function is Kff×(τ1×s+1) / (τ2×s+1); where Kff is the feedforward gain, τ1 is the lead time constant, τ2 is the lag time constant, and s is the Laplace operator. The feedforward compensation amount is calculated by transforming the change of the feedforward disturbance variable using the transfer function.

4. The intelligent anti-interference cascade control method according to claim 3, characterized in that, Both the main controller and the secondary controller employ PID control algorithms. The output of the main controller, after being limited, serves as the setpoint input for the secondary controller, and the output of the secondary controller is the feedback control quantity.

5. The intelligent anti-interference cascade control method according to claim 4, characterized in that, The amplitude constraint process restricts the final control command to a preset upper limit value and a preset lower limit value, and the rate of change constraint process restricts the change of the final control command relative to the control command at the previous moment to a preset maximum rate of change range.

6. The intelligent anti-interference cascade control method according to claim 5, characterized in that, Also includes: Based on the long-term control performance index of the master controlled variable, Kff in the dynamic feedforward compensation model is adaptively adjusted. The long-term control performance index is the integral sum of squares of the deviations between the master controlled variable and the corresponding set value; when the integral sum of squares exceeds a preset threshold, Kff is adjusted by a preset step size.

7. The intelligent anti-interference cascade control method according to claim 6, characterized in that, The cascade control loop, the calculation of the dynamic feedforward compensation model, the addition of the feedforward compensation amount and the feedback control amount, and the constraint processing are all implemented in the distributed control system DCS or programmable logic controller PLC. The actuator is an electric regulating valve or a pneumatic regulating valve.

8. An intelligent anti-interference cascade control device for a distillation column, characterized in that, include: The variable monitoring module is used to monitor the main controlled variable, the secondary controlled variable, and at least one feedforward disturbance variable in the distillation process in real time. The feedforward compensation calculation module is used to calculate the feedforward compensation amount based on the change of the feedforward disturbance variable through a dynamic feedforward compensation model. The feedback control calculation module is used to calculate the feedback control quantity through a cascade control loop based on the deviations of the primary controlled variable and the secondary controlled variable from the setpoints. The cascade control loop includes a primary controller and a secondary controller. The primary controller outputs the setpoint of the secondary controller based on the deviation of the primary controlled variable from the primary setpoint, and the secondary controller outputs the feedback control quantity based on the deviation of the secondary controlled variable from the setpoint. The control command generation module is used to add the feedforward compensation amount and the feedback control amount to obtain the final control command; The constraint processing module is used to perform amplitude constraint processing and rate of change constraint processing on the final control command, and then output it to the actuator of the manipulated variable of the control distillation column.

9. An intelligent anti-interference cascade control device, characterized in that, include: Memory, used to store computer programs; A processor, configured to implement the steps of the intelligent anti-interference cascade control method as described in any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the intelligent anti-interference cascade control method as described in any one of claims 1 to 7.

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