STM32-based adaptive ammonia synthesis control system and control method

Abstract

The invention discloses a self-adaptive ammonia synthesis control system and control method based on STM32, and relates to the technical field of ammonia synthesis. Ammonia synthesis equipment in the system is used for carrying out a synthesis reaction of ammonia gas; the analog quantity measurement module is used for collecting and processing analog quantity signals in ammonia synthesis equipment and sending the processed analog quantity signals to the control module; the control module is used for outputting a control signal based on an adaptive neural network PID (Proportion Integration Differentiation) algorithm according to the processed analog quantity signal and a set safety upper limit value of the analog quantity signal; the driving module is used for transmitting a control signal to the valve; the valve is used for controlling the circulating gas quantity and the gas output of the ammonia synthesis equipment; and the display interaction module is used for inputting a set temperature to the STM32 control system through the communication module, and is used for displaying current system state information. The control quality of the ammonia reaction process can be improved, and more accurate temperature control is realized.

Description

Technical Field

[0001] The present application relates to the technical field of ammonia synthesis, and in particular to an adaptive ammonia synthesis control system and a control method based on STM32. Background Art

[0002] Ammonia is an important raw material for fertilizer production and chemical industry. It is an important basic precursor for many products, such as fertilizers, chemical fibers, explosives, resins, etc. It also has good carbon-free energy storage fuel and is an indispensable chemical substance for production and life in modern human society. At present, the industry mainly combines nitrogen and hydrogen to produce ammonia through the Haber-Bosch process. The reaction rate and conversion rate are increased by high temperature and high pressure working conditions to obtain a high ammonia yield. However, this process consumes a lot of energy and will cause a large amount of CO2 greenhouse gas emissions. In recent years, with the gradual intensification of energy shortages and environmental pollution problems, the development of new chemical chain ammonia catalytic technology has attracted more and more attention. Chemical chain ammonia synthesis completes the chemical chain cycle through the consumption and regeneration of nitrogen-carrying gas, and the reaction structure of synthetic ammonia is used as a multi-step closed-loop reaction.

[0003] As the core component in the ammonia production process, the changes in pressure and temperature of the synthetic ammonia catalytic reactor directly affect the reaction rate and the equilibrium concentration of the product ammonia. Ammonia synthesis is a reversible exothermic reaction that must be carried out in the presence of a catalyst. When the temperature rises, the reaction rate increases, but the equilibrium concentration decreases. The catalyst can only show its catalytic activity within a certain temperature range; and this temperature range is small, so the temperature control of the synthetic reactor requires extremely high control accuracy and response speed. Stable temperature control is conducive to extending the life of the catalyst and slowing down the hydrogen erosion of the equipment. However, due to the special nonlinearity, time lag and irregularity between the temperature of the synthetic ammonia reactor and the intake volume, output and pressure, it is difficult to express it with an accurate mathematical function, and traditional control rules are difficult to achieve the expected control effect. Summary of the invention

[0004] The purpose of this application is to provide an adaptive ammonia synthesis control system and control method based on STM32, which can achieve more precise temperature control while having better adaptability and flexibility.

[0005] To achieve the above objectives, this application provides the following solutions: In a first aspect, the present application provides an adaptive ammonia synthesis control system based on STM32, including: a control module, ammonia synthesis equipment, a valve, a drive module, an analog measurement module, a communication module and a display interaction module.

[0006] The ammonia synthesis equipment is used for performing a synthesis reaction of ammonia.

[0007] The analog quantity measurement module is used to collect and process the analog quantity signals in the ammonia synthesis equipment, and send the processed analog quantity signals to the control module.

[0008] The control module is used to output a control signal based on an adaptive neural network PID algorithm according to the processed analog signal and the set safety upper limit value of the analog signal.

[0009] The driving module is used to transmit a control signal to the valve.

[0010] The valve is used to control the circulating gas volume and the gas outlet volume of the ammonia synthesis equipment.

[0011] The display interaction module is used to input the set temperature to the STM32 control system through the communication module, and is used to display the current system status information.

[0012] Optionally, the ammonia synthesis equipment includes a circulating gas compression module, a heating module, a synthesis reactor module, a gas outlet valve, a condensation module, a circulating valve and an ammonia separator module.

[0013] Optionally, the analog quantity signal includes temperature, pressure and gas flow in the ammonia synthesis equipment.

[0014] Optionally, the status information includes temperature, pressure and operating status.

[0015] Optionally, a storage module is also included; the storage module is used to store data generated by the control module during the ammonia synthesis process.

[0016] Optionally, a power supply module is also included; the power supply module is connected to the remaining modules in the control system and is used for power supply of each module.

[0017] Optionally, the control module adopts an STM32 central processing unit control module.

[0018] In a second aspect, the present application provides an adaptive ammonia synthesis control method based on the adaptive ammonia synthesis control system based on STM32, comprising: An analog quantity signal in an ammonia synthesis device is obtained; the analog quantity signal includes the current temperature, pressure and gas flow; the pressure includes the pressure in the synthesis tower of the ammonia synthesis device and the inlet pressure of the ammonia synthesis device.

[0019] Determine whether the pressure inside the synthesis tower and the inlet pressure in the ammonia synthesis equipment meet the set pressure threshold for ammonia synthesis.

[0020] If not, the pressure inside the synthesis tower and the inlet pressure will be adjusted until the set pressure threshold for ammonia synthesis is met.

[0021] If they meet the requirements, the set target temperature in the ammonia synthesis equipment and the obtained current temperature are compared based on the adaptive neural network PID algorithm to obtain a temperature deviation value.

[0022] According to the temperature deviation value, the PID parameters are dynamically adjusted through the adaptive neural network PID algorithm to control the temperature in the ammonia synthesis equipment.

[0023] Optionally, according to the temperature deviation value, PID parameters are dynamically adjusted by an adaptive neural network PID algorithm to control the temperature in the ammonia synthesis device, specifically including: According to the formula , determine the current value output to the control valve after the fuzzy PID controller is adjusted; the fuzzy PID controller is a controller based on adaptive fuzzy control rules; wherein, It is the current value output to the control valve after the fuzzy PID controller adjusts it. K p , K i , K d They are the proportional parameter value, differential parameter value and integral parameter value of PID adjustment respectively; , K’ p , K’ i , K’ d They are the initial setting proportional parameter value, differential parameter value and integral parameter value of the PID algorithm respectively. , , are the incremental values ​​of the proportional parameter value, the differential parameter value, and the integral parameter value respectively; Temperature deviation input, Temperature deviation rate of change input.

[0024] The valve opening is determined based on the current value output to the control valve after adjustment by the fuzzy PID controller.

[0025] According to the opening of the valve, the gas flow in the ammonia synthesis equipment is adjusted to achieve temperature control in the ammonia synthesis process.

[0026] Optionally, the adaptive fuzzy control rule specifically includes: When the temperature deviation value is greater than the set deviation value, the proportional parameter value selects the maximum value in its variation range, the integral parameter value selects the minimum value in its variation range, and the differential parameter value takes 0.

[0027] When the temperature deviation value is less than the set deviation value, the proportional parameter value is increased and the differential parameter value is decreased.

[0028] According to the specific embodiments provided in this application, this application discloses the following technical effects: The present application provides an adaptive ammonia synthesis control system and control method based on STM32, wherein the control system includes a control module, an ammonia synthesis device, a valve, a drive module, an analog measurement module, a communication module and a display interaction module; wherein the ammonia synthesis device is the core device for ammonia synthesis, and its internal reaction temperature is a key factor affecting the efficiency of ammonia synthesis, and provides the necessary chemical reaction environment for temperature control. Analog measurement module: responsible for accurately collecting analog signals such as temperature in the ammonia synthesis device, and performing necessary preprocessing to ensure the accuracy and stability of the signal. These processed signals are an important basis for the control module to make temperature control decisions. The control module uses an adaptive neural network PID algorithm to perform intelligent calculations based on the temperature signal provided by the analog measurement module, as well as the target temperature and safety upper limit set by the user through the display interaction module, and outputs an accurate control signal. The algorithm can adaptively adjust the control parameters according to real-time temperature feedback, thereby achieving accurate control of the temperature. As the executor of the control signal, the drive module converts the signal output by the control module into an electrical signal or mechanical signal that can be recognized by the valve, thereby driving the valve to act. The valve indirectly controls the reaction temperature by adjusting the circulating gas volume and the gas output volume of the ammonia synthesis device. When the control signal output by the control module requires lowering the temperature, the valve will reduce the circulating gas volume or increase the gas output, thereby lowering the reaction temperature; conversely, when the temperature is required to be increased, the valve will increase the circulating gas volume or reduce the gas output; the display interaction module allows the user to input the set temperature to the STM32 control system through the communication module, and display the current system status information (including temperature, etc.) in real time. This provides users with an intuitive temperature monitoring and control interface, which is convenient for users to adjust the set temperature or understand the system status according to actual needs. The communication module serves as a bridge between the display interaction module and the control module, ensuring that the temperature value set by the user can be accurately transmitted to the control module, and real-time feedback of the system status information to the display interaction module. This application integrates the above modules and uses the adaptive neural network PID algorithm to achieve precise temperature control. At the same time, it has better adaptability and flexibility, and can meet the strict requirements for temperature control in the ammonia synthesis process. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0030] Figure 1A schematic diagram of the structure of an adaptive ammonia synthesis control system based on STM32 is provided in one embodiment of the present application.

[0031] Figure 2 This is a schematic diagram of the structure of an ammonia synthesis device provided in one embodiment of the present application.

[0032] Figure 3 A schematic diagram of a temperature adaptive adjustment structure provided in one embodiment of the present application.

[0033] Figure 4 A fuzzy control rule representation is provided for an embodiment of the present application.

[0034] Figure 5 A schematic flow chart of an adaptive ammonia synthesis control method provided in one embodiment of the present application. DETAILED DESCRIPTION

[0035] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0036] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0037] Embodiment 1 like Figure 1 As shown, this embodiment provides an adaptive ammonia synthesis control system based on STM32, including: a control module, an ammonia synthesis device, a valve, a drive module, an analog measurement module, a communication module and a display interaction module.

[0038] The ammonia synthesis equipment is used for performing a synthesis reaction of ammonia.

[0039] The analog quantity measurement module is used to collect and process the analog quantity signals in the ammonia synthesis equipment, and send the processed analog quantity signals to the control module.

[0040] The control module is used to output a control signal based on an adaptive neural network PID algorithm according to the processed analog signal and the set safety upper limit value of the analog signal.

[0041] The driving module is used to transmit a control signal to the valve.

[0042] The valve is used to control the circulating gas volume and the gas outlet volume of the ammonia synthesis equipment.

[0043] The display interaction module is used to input the set temperature to the STM32 control system through the communication module, and is used to display the current system status information.

[0044] In this embodiment, the control hardware system and data acquisition hardware circuit in the adaptive ammonia synthesis control system adopt a modular structure design, mainly including an STM32 CPU control module and an external adapter power module, a drive module, an analog measurement module, a data storage and communication module, a display interaction module, etc.

[0045] Specifically, the power supply required by the control system, such as 24V, 5V, 3.3V, etc., is provided by the adapter power module; secondly, the data transmission between the analog measurement module and STM32 is used to realize the collection, processing and analysis of analog signals such as temperature, pressure, and flow. For example, the reactor temperature is detected by the thermocouple temperature sensor and converted into the voltage signal required by the system interface, and then converted into a digital quantity through the A / D converter. The value is converted into an actual value after being processed by software digital filtering, and then transmitted to the display interaction module through the 485 communication interface for display. In addition, the temperature value is compared with the set temperature and the difference is calculated. According to the difference, the adaptive fuzzy PID operation is used to adjust the control drive parameters; thirdly, the drive module is responsible for transmitting the control signal to the actuator such as the valve, and the purpose of controlling the temperature is achieved by controlling the circulating gas flow and the outlet gas flow. When the measured temperature and pressure values ​​exceed the safety upper limit set by the system, the control system responds through the fault handling module to protect the reactor and other functional equipment. Finally, the display interaction module inputs the set temperature to the STM32 control system through communication control and uses the drive circuit to control the circulating gas valve, and can display system information such as the current temperature, pressure and operating status of the system. The storage module is used to store the data generated by the control module during the ammonia synthesis process.

[0046] Wherein, in some embodiments, Figure 2 As shown, the ammonia synthesis equipment includes a circulating gas compression module, a heating module, a synthesis reactor module, a gas outlet valve, a condensation module, a circulating valve and an ammonia separator module.

[0047] In the ammonia synthesis equipment, the function of the circulating gas compression module is to compress the gas transmitted by the circulation valve and the gas provided by the raw material compressor, and transport it to the heating module for heating. The heated gas then enters the synthesis reactor in the synthesis reactor module to undergo an ammonia synthesis reaction. The reacted gas passes through the outlet valve and the condensation module in turn, and finally reaches the ammonia separator module. In the ammonia separator module, the gas is separated into liquid ammonia and purge gas.

[0048] Embodiment 2 like Figure 5As shown, the present application provides an adaptive ammonia synthesis control method based on the adaptive ammonia synthesis control system based on STM32, comprising: Step 501: Acquire an analog signal in an ammonia synthesis device; the analog signal includes the current temperature, pressure and gas flow; the pressure includes the pressure in the synthesis tower of the ammonia synthesis device and the inlet pressure of the ammonia synthesis device.

[0049] Step 502: Determine whether the pressure inside the synthesis tower and the inlet pressure in the ammonia synthesis equipment meet the set pressure threshold for ammonia synthesis.

[0050] Step 503: If not, the pressure in the synthesis tower and the inlet pressure are adjusted until they meet the set pressure threshold for ammonia synthesis.

[0051] Step 504: If the conditions are met, then based on the adaptive neural network PID algorithm, the set target temperature in the ammonia synthesis device and the obtained current temperature are compared to obtain a temperature deviation value.

[0052] Step 505: According to the temperature deviation value, the PID parameters are dynamically adjusted by the adaptive neural network PID algorithm to control the temperature in the ammonia synthesis equipment.

[0053] During the temperature control process of the synthesis reactor, once the pressure in the tower and the inlet pressure are stabilized at the preset values, the reaction temperature in the synthesis tower will be maintained within the upper and lower range of the set value. At this time, the gas flow rate of the synthesis reactor needs to be controlled within a specific set value. Since the outlet gas flow rate of ammonia is directly related to the temperature in the tower, the circulating gas flow rate can be regulated by monitoring the reactor circulating gas flow rate and adjusting the opening of the circulating gas valve, thereby controlling the reaction temperature in the reactor and making the temperature reach a balanced state. When the reactor pressure remains unchanged, the system inputs the target temperature through the setting controller, and the thermocouple temperature sensor measures the reactor temperature. After the temperature analog signal is converted by the control system A / D, the real-time temperature value is sent to the data buffer area. After the real-time value and the set value are processed and compared by the adaptive neural network PID algorithm in the controller, the control system drive circuit transmits the D / A converted control signal to the operating actuator to achieve temperature control by adjusting the circulating gas flow rate.

[0054] Specifically, the control system of the synthesis reactor consists of two parts: hardware and software. Its temperature control system adopts negative feedback regulation to form a closed-loop control system. The hardware part uses STM32 as a controller, which is responsible for controlling the gas outlet temperature of the ammonia synthesis tower to ensure that its operating temperature is constant at the set value, thereby ensuring the purity of the outlet ammonia. The set temperature is input to STM32 through the control communication interface. The temperature sensor measures the temperature of the synthesis gas, and after A / D conversion, the real-time digital measurement value is sent back to STM32. Inside STM32, the adaptive neural network PID algorithm written in C language controls the temperature of the synthesis reactor. Through the self-learning and training of the algorithm, the control signal is transmitted to the valve, and the precise balance control of the reactor temperature is achieved by adjusting the outlet gas flow rate and the circulating gas flow rate.

[0055] Specifically, during the operation of the algorithm, the deviation of the temperature value in the reactor and the rate of change of deviation Perform real-time monitoring calculations, and then perform adaptive fuzzy reasoning and operations to obtain K p , K i , K d (PID adjustment ratio, differential, integral parameter value) parameter increment value , , The adjusted K is obtained by the following formula: p , K i , K d The value of .

[0056] .

[0057] In the formula, K’ p , K’ i , K’ d It is the initial setting (proportional, differential, integral) parameters of the PID algorithm.

[0058] By adopting the digital PID control algorithm, the parameter value of the control quantity u(k) is obtained.

[0059] .

[0060] Where: Control quantity It is the current value output to the control valve after being adjusted by the fuzzy PID controller.

[0061] The valve opening is determined based on the current value output to the control valve after adjustment by the fuzzy PID controller.

[0062] According to the opening of the valve, the gas flow in the ammonia synthesis equipment is adjusted to achieve temperature control in the ammonia synthesis process.

[0063] Specifically, Figure 3 As shown, the circulating gas valve converts the given current value into a corresponding opening to drive the valve motor to work, adjusts the valve opening to adjust the circulating gas flow, realizes the control of the reactor circulation amount, and thus achieves balanced and stable control of the reaction tower temperature.

[0064] Fuzzy adaptive PID control based on temperature deviation and the rate of change of deviation As input variables, , , As output variables. The domains of these five variables are all set to (-5, 5), and the fuzzy sets are all defined as {NB (negative large), NM (negative medium), NS (negative small), Z (zero), PS (positive small), PM (positive medium), PB (positive large)}, and their internal elements NB, NM, NS, Z, PS, PM, PM are adaptive fuzzy language values. Input quantity T e and T ec The actual range of variation is (-0.5, 5), so the quantization factor Ke=Kec=5 / 0.5=10; the output The actual range of change is (-0.006, 0.006), , The actual range of change is (-0.009, 0.009), , , The proportional factors are K1=0.006 / 5=0.0012 and K2=K3=0.009 / 5=0.0018 respectively.

[0065] The core of adaptive control is adaptive fuzzy control rules. By formulating fuzzy control rules, the system can obtain better control performance. Therefore, when controlling temperature, the fuzzy adaptive PID controller has a good control effect on K. p , K i , K d The following principles should be formulated for adaptive adjustment.

[0066] When the temperature deviation value is greater than the set deviation value, the proportional parameter value selects the maximum value in its variation range, the integral parameter value selects the minimum value in its variation range, and the differential parameter value takes 0.

[0067] When the temperature deviation value is less than the set deviation value, the proportional parameter value is increased and the differential parameter value is decreased.

[0068] Specifically, this embodiment also considers the adjustment of proportional parameter values, differential parameter values, and integral parameter values ​​under different deviations, as follows: 1) When the deviation When it is large, in order to reduce the system response time and improve the response rate, K p A larger value should be taken; to avoid T e The instantaneous change is large, causing differential supersaturation, K d Take the smaller value; K i Set it to 0 to prevent the system from overshooting.

[0069] 2) When the deviation and the rate of change of deviation When the value of is medium, in order to have a small overshoot when controlling the temperature value, a smaller K should be used. p , K i , K d A moderate value can be selected, which can allow the system to maintain a relatively ideal response speed to a certain extent.

[0070] 3) When deviation When it is small, in order to avoid oscillation in the system and make the steady-state characteristics of the system good, K should be appropriately increased. p , reduce K i ; Considering the anti-interference ability of the system, K d According to T ec value to select, when T ec When the value is small, K d Take a larger value appropriately, when T ec When the value is large, K d According to the above rules and actual test operation experience, , , The control rules are as follows: Figure 4 shown.

[0071] In some embodiments, when executing step 505, the specific steps may be as follows: After the fuzzy control rule table is established, the input T e and T ec , the control system finds the corresponding fuzzy decision in the rule table and calculates it through the Mamdani adaptive fuzzy inference algorithm , , The amount of blur, and then use the area centroid method to , , Perform defuzzification calculation to obtain its exact value, and then obtain the adjusted K p, K i , K d , and finally the output is completed by the PID controller.

[0072] In summary, this application has the following technical effects: This application uses the adaptive PID control module in the control system to realize the core temperature control of the reactor synthesis tower. On the basis of conventional PID control and without manual intervention, adaptive fuzzy control is used to solve the problem that the parameters of the conventional PID controller cannot be self-tuned, and combined with operating experience and related algorithms to achieve advanced control, so that the service life of the catalyst is extended. Based on the STM32 adaptive ammonia synthesis reactor control solution, an adaptive network structure model is adopted, and mathematical methods are used to solve it directly, so that the model has strong expression ability and avoids the lengthy training process. It has strong stability, anti-interference ability and fault tolerance for large lag ammonia synthesis systems. In addition, the system uses STM32 as the control core, which has the advantages of small size and strong system embeddability.

[0073] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0074] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. An adaptive ammonia synthesis control system based on STM32, characterized in that: The adaptive ammonia synthesis control system based on STM32 includes: a control module, an ammonia synthesis device, a valve, a drive module, an analog measurement module, a communication module and a display interaction module; The ammonia synthesis equipment is used to perform a synthesis reaction of ammonia; The analog quantity measurement module is used to collect and process the analog quantity signals in the ammonia synthesis equipment, and send the processed analog quantity signals to the control module; The control module is used to output a control signal based on an adaptive neural network PID algorithm according to the processed analog signal and the set safety upper limit value of the analog signal; The driving module is used to transmit the control signal to the valve; The valve is used to control the circulating gas volume and gas output volume of the ammonia synthesis equipment; The display interaction module is used to input the set temperature to the STM32 control system through the communication module, and is used to display the current system status information.

2. The adaptive ammonia synthesis control system based on STM32 according to claim 1, characterized in that: The ammonia synthesis equipment comprises a circulating gas compression module, a heating module, a synthesis reactor module, a gas outlet valve, a condensation module, a circulating valve and an ammonia separator module.

3. The adaptive ammonia synthesis control system based on STM32 according to claim 1, characterized in that: The analog quantity signals include temperature, pressure and gas flow rate in the ammonia synthesis device.

4. The adaptive ammonia synthesis control system based on STM32 according to claim 1, characterized in that: The status information includes temperature, pressure and operating status.

5. The adaptive ammonia synthesis control system based on STM32 according to claim 1, characterized in that: It also includes a storage module; the storage module is used to store data generated by the control module during the ammonia synthesis process.

6. The adaptive ammonia synthesis control system based on STM32 according to claim 1, characterized in that: It also includes a power supply module; the power supply module is connected to the remaining modules in the control system and is used for power supply of each module.

7. The adaptive ammonia synthesis control system based on STM32 according to claim 1, characterized in that: The control module adopts the STM32 central processing unit control module.

8. An adaptive ammonia synthesis control method based on an adaptive ammonia synthesis control system based on STM32 according to any one of claims 1 to 7, characterized in that: include: Acquire an analog signal in an ammonia synthesis device; the analog signal includes current temperature, pressure and gas flow; the pressure includes the pressure in a synthesis tower in the ammonia synthesis device and the inlet pressure of the ammonia synthesis device; Determine whether the pressure inside the synthesis tower and the inlet pressure in the ammonia synthesis equipment meet the set pressure threshold for ammonia synthesis; If not, the pressure inside the synthesis tower and the inlet pressure are adjusted until they meet the set pressure threshold for ammonia synthesis; If they meet the requirements, the set target temperature in the ammonia synthesis equipment and the obtained current temperature are compared based on the adaptive neural network PID algorithm to obtain the temperature deviation value; According to the temperature deviation value, the PID parameters are dynamically adjusted through the adaptive neural network PID algorithm to control the temperature in the ammonia synthesis equipment.

9. The adaptive ammonia synthesis control method according to claim 8, characterized in that: According to the temperature deviation value, the PID parameters are dynamically adjusted through the adaptive neural network PID algorithm to control the temperature in the ammonia synthesis equipment, including: According to the formula , determine the current value output to the control valve after the fuzzy PID controller is adjusted; the fuzzy PID controller is a controller based on adaptive fuzzy control rules; wherein, It is the current value output to the control valve after the fuzzy PID controller adjusts it. K p , K i , K d They are the proportional parameter value, differential parameter value and integral parameter value of PID adjustment respectively; , K ’ p , K’ i , K’ d They are the initial setting proportional parameter value, differential parameter value and integral parameter value of the PID algorithm respectively. , , are the incremental values ​​of the proportional parameter value, the differential parameter value, and the integral parameter value respectively; Temperature deviation input, Temperature deviation change rate input; The valve opening is determined according to the current value output to the control valve after adjustment by the fuzzy PID controller; According to the opening of the valve, the gas flow in the ammonia synthesis equipment is adjusted to achieve temperature control in the ammonia synthesis process.

10. The adaptive ammonia synthesis control method according to claim 9, characterized in that: The adaptive fuzzy control rules specifically include: When the temperature deviation value is greater than the set deviation value, the proportional parameter value selects the maximum value in its variation range, the integral parameter value selects the minimum value in its variation range, and the differential parameter value takes 0; When the temperature deviation value is less than the set deviation value, the proportional parameter value is increased and the differential parameter value is decreased.

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