Adaptive PID pressure control method for aviation fuel synthesis units

Abstract

This invention relates to the field of fluid pressure control technology, and more particularly to an adaptive PID pressure control method for an aviation fuel synthesis unit. The method includes: acquiring real-time operating data of the reactor system; calculating the reaction thermal shock factor; calculating a pressure control sensitivity coefficient, and then correcting the basic proportional gain based on the pressure control sensitivity coefficient to obtain the dynamic proportional gain at the current moment; substituting the dynamic proportional gain into the PID control algorithm to calculate the valve control quantity, and adjusting the opening of the hydrogen supplementation regulating valve according to the valve control quantity to maintain reactor pressure stability. The technical solution of this invention can solve problems such as pressure regulation lag caused by thermo-pressure coupling in high-pressure hydrogenation reactors under complex operating conditions, and system oscillations and unplanned shutdowns caused by the inability of fixed-parameter PID control to adapt to changes in the dynamic response model.

Description

Technical Field

[0001] This invention relates to the field of fluid pressure control technology, and more particularly to an adaptive PID pressure control method for an aviation fuel synthesis device. Background Technology

[0002] The production of biomass sustainable aviation fuel (SAF) mainly relies on ester and fatty acid hydrogenation processes. The core equipment of this process is the high-pressure hydrogenation reactor (hereinafter referred to as the reactor). The reactor's function is to deoxygenate waste oils such as gutter oil and acidified oil and convert them into hydrocarbon fuels using hydrogen under high temperature and high pressure. In this complex chemical process, the stability of the reactor pressure is crucial, as it relates to product quality assurance, catalyst damage prevention, and equipment safety.

[0003] Currently, proportional-integral-derivative (PID) control algorithms are commonly used in industrial settings to maintain stable reactor pressure. The working principle is as follows: First, the reactor pressure is detected in real time by a pressure transmitter and compared with the set value to obtain the deviation. Then, the controller calculates the control quantity based on the magnitude, cumulative amount and rate of change of the deviation, thereby adjusting the opening of the hydrogen replenishment valve or exhaust valve. Typically, the distributed control system reads the 4-20mA signal from the field instruments, performs PID logic calculations, and outputs a signal to drive the pneumatic regulating valve.

[0004] However, despite the widespread application of PID control, it has serious drawbacks in SAF hydrogenation units. First, the hydrogenation reaction is a strongly exothermic reaction. When the feedstock is switched from vegetable oil to high-acid-value waste cooking oil, the difference in the unsaturation of the feedstock can cause sudden and drastic fluctuations in the hydrogen consumption rate and the heat of reaction. Sudden temperature changes can cause gas expansion or contraction, leading to pressure fluctuations. Conventional PID controllers cannot detect this temperature disturbance and can only start adjusting after the actual pressure deviates significantly, resulting in severe regulation lag. Second, the reactor's system response model changes during the initial and final stages of catalyst activity, or when facing different operating conditions with different feedstock components. Fixed-parameter PID controllers cannot simultaneously meet the requirements of rapid response and no overshoot. Under thermal shock, this can easily cause system oscillations, or even trigger high-pressure interlocks, leading to unplanned shutdowns and affecting production continuity. Summary of the Invention

[0005] To address the issues of regulation lag caused by thermo-pressure coupling and system oscillations caused by fixed parameters, this invention provides an adaptive PID pressure control method for an aviation fuel synthesis plant. This method rapidly stabilizes reactor pressure while significantly reducing pressure fluctuation amplitude and regulation lag, thereby improving the control adaptability, operational stability, and production safety of the aviation fuel synthesis plant.

[0006] This invention provides an adaptive PID pressure control method for an aviation fuel synthesis unit, comprising: acquiring real-time operating data of the reactor system, including real-time reactor pressure, average bed temperature, and feed flow rate; preprocessing the acquired real-time operating data to filter out signal noise; calculating a reaction thermal shock factor based on the changes in the average bed temperature and the feed flow rate, the reaction thermal shock factor being used to characterize the intensity of interference on reactor pressure caused by temperature changes and feed flow rate; calculating a pressure control sensitivity coefficient based on the deviation between the real-time pressure and a set target pressure value, and in conjunction with the reaction thermal shock factor; further correcting the base proportional gain based on the pressure control sensitivity coefficient to obtain the dynamic proportional gain at the current moment; substituting the dynamic proportional gain into the PID control algorithm to calculate the final valve control quantity; and adjusting the opening of the hydrogen supplementation regulating valve according to the valve control quantity to maintain reactor pressure stability.

[0007] By introducing a reaction thermal shock factor and a pressure control sensitivity coefficient, a cross-dimensional correlation model of bed average temperature, feed flow rate, and reactor pressure was constructed. This model enables early prediction and dynamic suppression of potential reactor pressure fluctuations, and dynamically adjusts the dynamic proportional gain based on real-time operating conditions. Under feed switching and thermal shock disturbances, the aviation fuel synthesis unit can quickly stabilize reactor pressure, while significantly reducing pressure fluctuation amplitude and regulation lag, thereby improving the control adaptability, operational stability, and production safety of the aviation fuel synthesis unit.

[0008] Preferably, the reaction thermal shock factor is calculated as follows:

[0009] In the formula, For a moment The reactive thermal shock factor, For a moment The average bed temperature, For a moment The previous Average bed temperature over one sampling period The sampling period is To determine the backtracking window size, For a moment The raw material feed flow rate. It is the natural logarithm function.

[0010] By introducing a temperature change rate term, the dynamic trend of thermal disturbance can be accurately captured; at the same time, by using the logarithmic flow rate term, the potential impact of feed can be quantified, which not only reflects the positive correlation between flow rate and thermal shock, but also avoids excessive amplification of the index under high flow rate conditions by using nonlinear functions, ensuring that the thermal shock factor can stably and reasonably characterize complex physical disturbance processes, thereby providing a reliable and calculable lead signal for subsequent adaptive control.

[0011] Preferably, the pressure control sensitivity coefficient is calculated as follows:

[0012] In the formula, For a moment Pressure control sensitivity coefficient, For a moment Real-time pressure, The target pressure value set for the process. Based on the stability constant, These are the coupling weight coefficients.

[0013] By linearly coupling the root mean square of the pressure deviation with the thermal shock factor, the control sensitivity can respond simultaneously to both actual pressure deviations and potential thermal disturbances. This design ensures that the system can proactively increase control sensitivity even when thermal shock has already occurred before significant pressure deviations, thereby enhancing control predictability and safety redundancy, and effectively avoiding blind spots that may arise from relying on a single signal.

[0014] Preferably, the dynamic proportional gain is calculated as follows:

[0015] In the formula, For a moment Dynamic proportional gain, The preset static proportional gain, The maximum design pressure of the reactor. To adjust the response index.

[0016] By introducing an exponential function based on the maximum design pressure to modify the proportional gain, the dynamic gain can be nonlinearly amplified according to the sensitivity coefficient. This design ensures that when abnormal operating conditions occur, the proportional action of the controller can be rapidly and significantly enhanced, thereby strongly suppressing pressure fluctuations; while under steady-state conditions, the proportional action of the controller remains gradual, thus optimizing the balance between system response speed and stability.

[0017] Preferably, the real-time operating data acquisition of the reactor system includes: acquiring the real-time pressure through an explosion-proof pressure transmitter installed on the top of the reactor; acquiring multiple temperature values ​​through multiple thermocouples distributed in the catalyst bed and calculating their average value as the average temperature of the bed; and acquiring the raw material feed flow rate through a mass flow meter at the outlet of the feed pump.

[0018] Preferably, an adaptive PID pressure control method for an aviation fuel synthesis unit further includes preprocessing the collected real-time operating data: collecting data on the real-time pressure, the average bed temperature, and the feed flow rate at a set sampling period; and performing moving average filtering on the collected data to smooth data fluctuations.

[0019] By setting a reasonable sampling period and implementing a moving average filter preprocessing operation, high-frequency noise and transient interference present in the field can be effectively filtered out, thereby obtaining smooth and accurate data. This method avoids noise signals misleading the control logic, significantly improving the system's anti-interference capability and overall robustness.

[0020] Preferably, the calculation of the final valve control quantity includes: calculating the pressure deviation between the real-time pressure and the target pressure value; using the product of the dynamic proportional gain and the pressure deviation as the proportional term output of the PID control; and summing the proportional term output by combining the integral term output and the derivative term output of the PID control to obtain the valve control quantity.

[0021] Preferably, the summation of the proportional term output by combining the integral and derivative term outputs of PID control includes: performing an integral operation on the pressure deviation and multiplying it by an integral coefficient to obtain the integral term output; performing a derivative operation on the rate of change of the pressure deviation and multiplying it by a derivative coefficient to obtain the derivative term output; and adding the proportional term output, the integral term output, and the derivative term output together as the valve control quantity.

[0022] Preferably, the The acquisition method is as follows: during system operation, the average bed temperature of each sampling period is stored in real time; the average bed temperature stored at a specific time interval before the current moment is read as the average bed temperature. The specific time interval is the product of the backtracking window size and the sampling period.

[0023] Preferably, an adaptive PID pressure control method for an aviation fuel synthesis device further includes performing moving average filtering on the collected real-time pressure, the average bed temperature, and the raw material feed flow rate.

[0024] The technical solution of the present invention has the following beneficial technical effects: This invention constructs a cross-dimensional correlation model encompassing temperature, flow rate, and pressure, while simultaneously monitoring the rate of temperature change and feed flow rate in real time. This allows the controller to anticipate pressure fluctuation trends, successfully overcoming the limitations of a single pressure feedback mode. Compared to existing technologies that rely solely on pressure deviation for adjustment, this invention implements control actions in advance, effectively solving the problem of significant hysteresis in the hydrogenation reaction process.

[0025] Furthermore, the present invention has the capability of full-condition self-adaptation. Under different conditions such as reactor heating stage, raw material switching stage and catalyst deactivation stage, it can sense the system status in real time and automatically adjust the control gain. This makes the pressure fluctuation amplitude significantly reduced compared with the prior art when encountering severe thermal shock. Attached Figure Description

[0026] Figure 1 This is a flowchart of the adaptive PID pressure control method for the aviation fuel synthesis device in this embodiment of the invention; Figure 2 This is a comparison diagram of the reactor pressure control response effect in embodiments of the present invention. Detailed Implementation

[0027] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are some embodiments of the present invention, but not all embodiments.

[0028] The specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0029] This invention discloses an adaptive PID pressure control method for an aviation fuel synthesis unit, referring to... Figure 1 This includes steps S1-S4: S1 collects real-time operating data of the reactor system, including real-time pressure, average bed temperature, and feed flow rate.

[0030] In one embodiment, when it is necessary to collect real-time operating data of the reactor system, real-time signals are first acquired through detection devices distributed at various key locations of the device. Specifically, the real-time pressure of the reactor is acquired through a pressure sensor installed at the top of the reactor, denoted as […]. Temperature sensors distributed throughout the catalyst bed are used to acquire the temperature at various points, and the average value is taken as the average temperature of the reactor bed, denoted as . The feed flow rate is obtained by measuring the flow meter at the outlet of the feed pump and recorded as follows: In this invention, the pressure sensor can be an explosion-proof pressure transmitter or a capacitive pressure transmitter; the temperature sensor can be a multi-point thermocouple or a sheathed resistance temperature detector; and the flow meter can be a mass flow meter or an oval gear flow meter. The specific type and style of the pressure sensor, temperature sensor, and flow meter can be selected by those skilled in the art according to actual needs, and are not limited herein.

[0031] It is important to note that before collecting real-time operating data from the reactor system, the sampling period of the control system must first be set. The specific setting of the sampling period is determined by the actual working conditions. In this embodiment of the invention, the sampling period is set to 1 second. Meanwhile, due to the complex industrial environment, the collected signals are often accompanied by high-frequency electromagnetic noise. Therefore, the system needs to perform moving average filtering on the collected real-time pressure of the reactor, the average temperature of the reactor bed, and the raw material feed flow rate to filter out peak interference and ensure that the data participating in subsequent calculations is smooth and reliable. The technology of performing moving average filtering on the collected signals is a mature technology in the field and will not be described in detail here.

[0032] In this way, by filtering and preprocessing the dataset, more accurate and smooth physical quantity data can be obtained, providing a reliable input basis for subsequent complex logical operations and avoiding controller malfunctions caused by instantaneous sensor noise.

[0033] S2, based on the changes in the average bed temperature and the feed flow rate, calculates the reaction thermal shock factor that characterizes the impact of temperature changes and feed flow rate on reactor pressure.

[0034] In one embodiment, pressure fluctuations in the hydrogenation process are often caused by drastic temperature changes. The magnitude of these temperature changes, i.e., the rate of temperature rise, is directly proportional to the feed flow rate; that is, a higher flow rate introduces more reactants and generates more potential heat. Therefore, this invention constructs an index to characterize the intensity of heat source interference, namely the reaction thermal shock factor. The method for calculating the reaction thermal shock factor is as follows:

[0035] in, For the current moment The average temperature of the bed was collected; The backtracking window size is used to calculate the temperature change trend over a short period of time. The system at the current moment The previous Historical temperature values ​​at each sampling period; The sampling period; For the current moment The raw material feed flow rate; It is the natural logarithm function; the constant 10 is used to prevent the logarithmic argument from being too small or negative.

[0036] In particular, The calculation method is as follows: ; It should be noted that, in order to satisfy the specifications of mathematical operations and logarithmic functions, the current time... The average bed temperature collected, the system at the current moment The previous Historical temperature value at each sampling period, sampling period, and current time. Before being substituted into the calculation, the raw material feed flow rate has been normalized by dividing by its respective unit reference value to ensure that the final calculated reaction thermal shock factor is a pure numerical value.

[0037] This scheme deeply integrates the thermo-pressure coupling dynamics of chemical reactors with modern feedforward-feedback adaptive control theory. The construction of the reaction thermal shock factor is not a simple mathematical combination. Its physical basis is that the transient exothermic rate in the hydrogenation reaction is not only strongly correlated with the bed temperature rise gradient, but also exhibits typical nonlinear logarithmic saturation characteristics with the amount of fresh material injected.

[0038] To more clearly illustrate the calculation method and function of the thermal shock factor, this invention provides an example of its calculation. Before calculating the thermal shock factor, the following settings are first established: the sampling period is 1 second; the backtracking window is 5; and the current time... The average bed temperature is 352 degrees Celsius; the historical temperature 5 seconds ago was 350 degrees Celsius; the current feed flow rate is 20.

[0039] The rate of temperature change term is: .

[0040] The logarithmic term of the flow is: .

[0041] The final calculated reaction thermal shock factor is: .

[0042] Thus, by mapping rapid temperature changes and flow rate magnitude to a dimensionless impact factor through this formula, the potential pressure fluctuation risk caused by exothermic reaction under current operating conditions can be accurately assessed, providing numerical basis for the controller's prediction.

[0043] S3 calculates the pressure control sensitivity coefficient based on the deviation between the real-time pressure and the set target pressure value, and in conjunction with the reaction thermal shock factor. Then, the basic proportional gain is corrected based on the pressure control sensitivity coefficient to obtain the dynamic proportional gain at the current moment.

[0044] In one embodiment, pressure fluctuations in the hydrogenation reaction are often caused by thermal shock. To overcome the regulation lag and insufficient response problems of traditional fixed-parameter PID control when facing thermal shock, and to ensure that the corrective force can be automatically enhanced to quickly restore system stability when the pressure deviates significantly or the disturbance is strong, it is necessary to determine whether the controller needs to intervene forcefully. This invention constructs a pressure control sensitivity coefficient. To determine whether the controller needs strong intervention, the pressure control sensitivity coefficient is calculated as follows: ; in, The current pressure control sensitivity coefficient; This represents the real-time pressure of the reactor at the current moment. The target pressure value set for the process; It is a basic stability constant, which is used to ensure that the values ​​inside the square root in the formula are always positive and maintain basic sensitivity in steady state; As a coupling weighting coefficient, its dimension is set to megapascals to maintain absolute consistency with the dimension of the preceding pressure deviation, and it is used to adjust the proportion of the thermal shock factor in the total sensitivity.

[0045] The pressure control sensitivity coefficient innovatively introduces a bias constant in the Euclidean norm space, thereby eliminating the system gain singularity that may be caused when the steady-state deviation approaches zero from the bottom layer of control theory. At the same time, the unmeasurable thermal disturbance is mapped into the pressure control sensitivity compensation in advance through the feedforward term. The final dynamic proportional gain adopts an exponential safety margin mapping based on the highest design pressure. This model is the optimal control system for preventing overheating or overpressure by fitting a large amount of operating data of high-risk hydrogenation units.

[0046] After calculating the pressure control sensitivity coefficient at the current moment, it is also necessary to use this sensitivity coefficient to correct the static proportional gain of the PID controller and calculate the dynamic proportional gain at the current moment. The dynamic proportional gain at the current moment is calculated as follows: ; in, This is the preset static proportional gain; The maximum design pressure of the reactor is used as the normalization denominator; To adjust the response index.

[0047] To more clearly illustrate the calculation method and function of dynamic proportional gain, this invention provides an example of calculating the pressure control sensitivity coefficient and dynamic proportional gain: In this example, continuing with the data from the previous example, and setting the following: the current real-time pressure of the reactor is 5.2 MPa; the target pressure set for the process is 5 MPa; the basic stability constant is 0.01; the regulation response index is 0.5; and the reaction thermal shock factor is 1.3604; then: Pressure deviation term ; Current pressure control sensitivity coefficient ; When calculating the dynamic proportional gain, the following settings are required: the preset static proportional gain is 2, the maximum design pressure is 10 MPa, and the regulation response index is 1; then: Dynamic proportional gain .

[0048] The above example clearly shows that due to thermal shock and pressure deviation in the system, the proportional gain automatically increases from the basic 2.0 to about 2.18, thereby automatically adjusting the correction force.

[0049] Thus, by introducing a sensitivity coefficient and dynamic gain calculation, the controller can automatically adjust the correction force according to the severity of the working condition. When the thermal shock is large or the pressure deviates far, the gain automatically increases, thereby achieving adaptive control under all working conditions.

[0050] S4. Substitute the dynamic proportional gain into the PID control algorithm to calculate the final valve control quantity, and adjust the opening of the hydrogen replenishment regulating valve according to the valve control quantity to maintain the reactor pressure stability.

[0051] In one embodiment, after the dynamic proportional gain is calculated, it is first substituted into the PID control algorithm to replace the proportional coefficient in the traditional fixed-parameter PID. Simultaneously calculate the current pressure deviation. And finally calculate the valve control quantity. The calculation method for valve control quantities is as follows:

[0052] in, This is the final valve control value; For dynamic proportional gain; This represents the current pressure deviation. The integral coefficient; These are the differential coefficients; It is the integral variable.

[0053] After calculating the valve control quantity, the controller converts the valve control quantity into a current signal and sends it to the on-site hydrogen replenishment regulating valve or exhaust valve for pressure regulation. In one implementation, if the valve control quantity increases, the opening of the hydrogen replenishment regulating valve increases, replenishing more hydrogen to increase pressure; if the valve control quantity decreases, the opening of the hydrogen replenishment regulating valve decreases, reducing hydrogen input to increase pressure.

[0054] like Figure 2 As shown, a typical raw material switching operation occurs at the 50th second of system operation, resulting in a severe exothermic shock inside the reactor. The target pressure value is set at 5 MPa. The pressure change curve of the conventional fixed-parameter PID controller cannot be maintained after the thermal shock at the 50th second and drops significantly. Subsequently, the system oscillates repeatedly, resulting in a long time required to recover to a stable state. However, the pressure change curve of the adaptive PID controller increases the proportional gain in advance according to the temperature change at the 50th second, making the valve action more decisive and resulting in a very small pressure drop. It then quickly returns to a stable state without significant subsequent oscillations.

[0055] Thus, by implementing PID control based on dynamic gain, the system's resistance to thermal shock can be significantly improved, and the pressure fluctuation amplitude can be reduced, thereby effectively ensuring the continuity and safety of the aviation fuel synthesis process.

[0056] It should be noted that those skilled in the art can make various modifications and improvements without departing from the inventive concept, and these all fall within the scope of protection of this invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

Claims

1. An adaptive PID pressure control method for an aviation fuel synthesis unit, characterized in that, include: Collect real-time operating data of the reactor system, including real-time pressure of the reactor, average bed temperature, and feed flow rate; Based on the changes in the average bed temperature and the feed flow rate, a reaction thermal shock factor is calculated to characterize the intensity of the disturbance to reactor pressure caused by temperature changes and feed flow rate. Based on the deviation between the real-time pressure and the set target pressure value, and in conjunction with the reactive thermal shock factor, the pressure control sensitivity coefficient is calculated. Then, the basic proportional gain is corrected based on the pressure control sensitivity coefficient to obtain the dynamic proportional gain at the current moment. The dynamic proportional gain is substituted into the PID control algorithm to calculate the final valve control quantity, and the opening of the hydrogen replenishment regulating valve is adjusted according to the valve control quantity to maintain the reactor pressure stability.

2. The adaptive PID pressure control method for the aviation fuel synthesis device according to claim 1, characterized in that, The method for calculating the reactive thermal shock factor is as follows: In the formula, For a moment The reactive thermal shock factor, For a moment The average bed temperature, For a moment The previous Average bed temperature over one sampling period The sampling period is To determine the backtracking window size, For a moment The raw material feed flow rate. It is the natural logarithm function.

3. The adaptive PID pressure control method for the aviation fuel synthesis device according to claim 2, characterized in that, The pressure control sensitivity coefficient is calculated as follows: In the formula, For a moment Pressure control sensitivity coefficient, For a moment Real-time pressure, The target pressure value set for the process. Based on the stability constant, These are the coupling weight coefficients.

4. The adaptive PID pressure control method for the aviation fuel synthesis device according to claim 3, characterized in that, The dynamic proportional gain is calculated as follows: In the formula, For a moment Dynamic proportional gain, The preset static proportional gain, The maximum design pressure of the reactor. To adjust the response index.

5. The adaptive PID pressure control method for the aviation fuel synthesis device according to claim 1, characterized in that, The real-time operating data of the reactor system includes: The real-time pressure is obtained by an explosion-proof pressure transmitter installed on top of the reactor; Multiple temperature values ​​are obtained by using multiple thermocouples distributed in the catalyst bed and their average value is calculated as the average temperature of the bed. The feed flow rate of the raw material is obtained by a mass flow meter at the outlet of the feed pump.

6. The adaptive PID pressure control method for the aviation fuel synthesis device according to claim 2, characterized in that, It also includes preprocessing the collected real-time operational data: Data on the real-time pressure, the average bed temperature, and the raw material feed flow rate are collected at a set sampling period. The collected data is processed by moving average filtering to smooth out data fluctuations.

7. The adaptive PID pressure control method for an aviation fuel synthesis device according to claim 1, characterized in that, The calculation of the final valve control quantity includes: Calculate the pressure deviation between the real-time pressure and the target pressure value; The product of the dynamic proportional gain and the pressure deviation is used as the proportional term output of the PID control. By combining the integral and derivative outputs of PID control, the proportional output is summed to obtain the valve control quantity.

8. The adaptive PID pressure control method for an aviation fuel synthesis apparatus according to claim 7, characterized in that, The summation of the proportional term output by combining the integral and derivative term outputs of PID control includes: The pressure deviation is integrated and multiplied by an integration coefficient to obtain the integral term output. The rate of change of the pressure deviation is differentiated and multiplied by the differential coefficient to obtain the differential term output; The proportional term output, the integral term output, and the derivative term output are added together to obtain the valve control quantity.

9. The adaptive PID pressure control method for an aviation fuel synthesis device according to claim 2, characterized in that, The The method of obtaining it is: During system operation, the average bed temperature for each sampling cycle is stored in real time; Read the average bed temperature stored at a specific time interval prior to the current moment as the... The specific time interval is the product of the backtracking window size and the sampling period.

10. The adaptive PID pressure control method for an aviation fuel synthesis device according to claim 1, characterized in that, The method further includes performing moving average filtering on the collected real-time pressure, average bed temperature, and raw material feed flow rate.

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