Electromagnetic valve flow regulation system based on adaptive fuzzy control

Abstract

This invention relates to a solenoid valve flow regulation system based on adaptive fuzzy control. The flow regulation system includes: a solenoid valve for regulating fluid flow and responding to control signals to achieve precise flow regulation; a flow sensor for real-time monitoring of fluid flow and feeding back the detected flow signal to the control system; a fuzzy control module for receiving the flow error signal and flow error change rate provided by the flow sensor, and outputting a control signal through fuzzy inference calculation; an adaptive algorithm module for dynamically adjusting fuzzy control rules and parameters according to changes in real-time error to optimize controller performance; and a PID controller for adjusting the opening of the solenoid valve according to the control signal output by the fuzzy control module to precisely regulate the flow. This application can automatically adjust the control signal based on the real-time feedback of flow error and change rate.

Description

Technical Field

[0001] This invention relates to the field of solenoid valve flow regulation, specifically to a solenoid valve flow regulation system based on adaptive fuzzy control, which is widely used in automated systems for high-precision liquid and gas flow control, HVAC systems, and chemical process control. Background Technology

[0002] Solenoid valves are widely used in liquid and gas flow control systems, playing a crucial role, especially in automation control, chemical engineering, and energy fields. Traditional solenoid valve flow control systems often employ PID control to adjust valve opening for precise flow control. While PID control is simple to operate, it is prone to issues such as response lag, overshoot, and insufficient stability when dealing with complex nonlinear systems and time-varying conditions. Its performance is particularly limited under conditions of significant load fluctuations and environmental changes.

[0003] With the development of fuzzy control theory, fuzzy control has been widely applied to complex and nonlinear systems, overcoming many shortcomings of traditional PID control. Fuzzy control handles uncertainties and nonlinearities in systems through fuzzy inference rules, rather than precise mathematical models, exhibiting strong adaptability. Adaptive fuzzy control further enhances control performance by dynamically adjusting control rules and gains based on real-time feedback information, thereby achieving higher precision flow regulation.

[0004] However, although fuzzy control improves the stability and accuracy of solenoid valve flow regulation systems to some extent, it still faces challenges in practical applications, such as real-time response, accuracy, and multi-parameter coordinated regulation. Therefore, how to combine adaptive fuzzy control with other intelligent optimization algorithms to further improve the system's response speed, accuracy, and intelligence level remains a key research issue. Summary of the Invention

[0005] To address the aforementioned shortcomings, the present invention aims to provide a solenoid valve flow regulation system based on adaptive fuzzy control. This system, by combining an adaptive fuzzy control algorithm and a PID controller, can precisely adjust the opening of the solenoid valve under different operating conditions, achieving high-precision flow control. Through real-time feedback of flow error and error change rate, the system can dynamically adjust the control signal, avoiding the lag problem of traditional PID control and ensuring high response speed and stability of the system in complex environments, thereby solving existing technical problems.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: An adaptive fuzzy control-based solenoid valve flow regulation system includes: a solenoid valve for regulating fluid flow and responding to control signals to achieve precise flow regulation; a flow sensor for real-time monitoring of fluid flow and feeding back the detected flow signal to the control system; a fuzzy control module for receiving the flow error signal and flow error change rate provided by the flow sensor, and outputting a control signal through fuzzy inference calculation; an adaptive algorithm module for dynamically adjusting fuzzy control rules and parameters according to changes in real-time error to optimize controller performance; and a PID controller for adjusting the opening of the solenoid valve according to the control signal output by the fuzzy control module to precisely regulate the flow.

[0007] According to the embodiments of this application, the solenoid valve flow regulation system based on adaptive fuzzy control includes a fuzzy control module comprising: an error input for receiving the error between the current flow rate and the target flow rate of the solenoid valve; an error change rate input for receiving the error change rate and generating a control signal according to a preset fuzzy rule; and a fuzzy inference engine for calculating the fuzzy output based on the input error and the error change rate, thereby deriving the control signal.

[0008] According to the embodiments of this application, the output control signal of the fuzzy control module is processed by the PID controller, which includes: proportional control (P) to adjust according to the error value of the fuzzy control output; integral control (I) to eliminate long-term deviations by processing the accumulation of errors; and derivative control (D) to adjust the rate of change of errors to ensure that the flow regulation system responds quickly.

[0009] According to the embodiment of this application, in the electromagnetic valve flow regulation system based on adaptive fuzzy control, the adaptive algorithm module dynamically adjusts the gain parameter of the fuzzy controller according to the following formula: K(t) = K_0 ⋅ (1 + α ⋅ |e(t)|) Where K(t) is the adjusted gain, e(t) is the flow error, α is the dynamic adjustment coefficient, and K_0 is the base gain value.

[0010] According to the embodiments of this application, the solenoid valve flow regulation system based on adaptive fuzzy control further includes: a real-time data acquisition and processing module, used to receive signals from the flow sensor in real time and convert the signals into digital signals suitable for processing by the control algorithm; and a remote control and monitoring module, used to transmit the status of the flow regulation system to a remote control center via wireless or wired means, so that users can remotely monitor and regulate the flow regulation system.

[0011] In the electromagnetic valve flow regulation system based on adaptive fuzzy control according to the embodiments of this application, the flow sensor is a vortex flow meter or a thermal flow sensor.

[0012] According to the embodiments of this application, the inference rule of the fuzzy controller for the electromagnetic valve flow regulation system based on adaptive fuzzy control is in the form of IF-THEN rule.

[0013] According to the embodiments of this application, the operation of the solenoid valve flow regulation system based on adaptive fuzzy control includes the following steps: Step 1: The flow sensor detects the flow rate in real time and transmits the data to the adaptive algorithm module; Step 2: The adaptive algorithm module dynamically adjusts the gain and rules of the fuzzy controller based on the flow error and the rate of change of the flow error; Step 3: The fuzzy controller calculates the control signal according to the adjusted rules and transmits it to the PID controller; Step 4: The PID controller adjusts the opening of the solenoid valve according to the control signal to output a precise flow rate; Step 5: The solenoid valve executes the control signal, adjusts the fluid flow rate, and returns the feedback signal to the flow regulation system.

[0014] According to the embodiments of this application, the solenoid valve flow regulation system based on adaptive fuzzy control adaptively adjusts the control strategy according to changes in operating conditions, thereby ensuring the accuracy of flow regulation and the stability of the flow regulation system.

[0015] According to the embodiments of this application, the proportional, integral, and derivative gains of the PID controller in the electromagnetic valve flow regulation system based on adaptive fuzzy control can be adjusted in real time and manually set to optimize the response of the flow regulation system.

[0016] The purpose of the electromagnetic valve flow regulation system based on adaptive fuzzy control proposed in this application is to address the shortcomings of traditional PID control methods under complex and dynamic operating conditions, and to improve the stability and accuracy of the system under different operating conditions by dynamically adjusting the fuzzy control rules and gain.

[0017] Due to the adoption of the above technical features, this invention has the following advantages and positive effects compared with the prior art: First, this application can overcome the challenges brought about by nonlinear and time-varying environments, and provide more stable and accurate flow control; Second, this application can automatically optimize the control strategy according to different working conditions to ensure stable operation in various complex environments; Third, this application can automatically adjust the control signal based on the real-time feedback of flow error and rate of change; Fourth, this application can flexibly adapt to flow fluctuations, environmental changes and external disturbances, significantly improving the accuracy of flow regulation and the system's response speed.

[0018] Of course, implementing any specific embodiment of the present invention does not necessarily have all of the above technical effects at the same time. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the electromagnetic valve flow regulation system based on adaptive fuzzy control in this application; Figure 2 This is a flowchart of the electromagnetic valve flow regulation system based on adaptive fuzzy control in this application; Figure 3 This is a schematic diagram of the adaptive adjustment process of the fuzzy controller in this application. Detailed Implementation

[0020] The following describes several preferred embodiments of the present invention in detail with reference to the accompanying drawings, but the present invention is not limited to these embodiments. The present invention encompasses any substitutions, modifications, equivalent methods, and solutions made within the spirit and scope of the present invention. To provide the public with a thorough understanding of the present invention, specific details are described in detail in the following preferred embodiments, but those skilled in the art will fully understand the present invention without these details. Furthermore, to avoid unnecessary misunderstanding of the essence of the present invention, well-known methods, processes, procedures, elements, etc., are not described in detail.

[0021] This application provides a solenoid valve flow regulation system based on adaptive fuzzy control. By combining an adaptive fuzzy control algorithm and a PID controller, the opening degree of the solenoid valve can be precisely adjusted under different operating conditions, achieving high-precision flow control. Through real-time feedback of flow error and error change rate, this system can dynamically adjust the control signal, ensuring high response speed and stability of the system in complex environments.

[0022] The electromagnetic valve flow regulation system based on adaptive fuzzy control in this application includes the following core components and steps: 1. Solenoid valves and flow sensors Solenoid valves: Used to regulate fluid flow. The solenoid valve adjusts its opening degree in response to a control signal, thereby regulating the flow rate. The flow sensor uses a vortex flow meter or a thermal flow sensor, featuring high precision and fast response, suitable for dynamic flow regulation needs. Precise flow regulation is crucial for many industrial systems, especially in liquid and gas control systems.

[0023] Flow sensor: The flow sensor is used to monitor the flow rate of fluid in real time and transmit the measured flow signal to the control system. The output signal y(t) of the flow sensor is fed back to the fuzzy control module as the control input.

[0024] The mathematical model of the flow sensor is:

[0025] y(t) is the measured flow rate. It is the sensor gain. It is the raw output of the flow signal.

[0026] 2. Fuzzy Control Module The fuzzy control module receives the flow error signal and flow error change rate provided by the flow sensor, and outputs a control signal through fuzzy inference calculation; that is, the fuzzy control module includes: Error input, used to receive the error e(t) between the current flow rate and the target flow rate of the solenoid valve; Error change rate input is used to receive the error change rate Δe(t) and generate a control signal according to a preset fuzzy rule; The fuzzy inference engine calculates the fuzzy output based on the input error and the rate of change of the error, and then derives the control signal.

[0027] In this embodiment, the main function of the fuzzy control module is to infer the control signal based on the flow error e(t) signal and the flow error change rate Δe(t). Compared with traditional PID control, fuzzy control does not rely on a precise mathematical model, but makes control decisions through fuzzy rules, making it more adaptable.

[0028] Input signal: Flow error: defined as target flow Compared with actual traffic Differences between them:

[0029] Flow error change rate : is the rate of change of flow error over time:

[0030] Fuzzy reasoning rules: Based on the flow error e(t) and the rate of change of the error Δe(t), the fuzzy controller generates a control signal u(t). For example, if the error is large and the rate of change is fast, the controller will output a large adjustment signal to quickly adjust the solenoid valve.

[0031] The inference rules for fuzzy control can be written in the form of IF-THEN rules:

[0032] In other words, "IF the flow error e(t) is large AND the error change rate Δe(t) increases rapidly THEN the control signal u(t) increases."

[0033] Control signal output: After fuzzy inference, the output control signal u(t) is transmitted to the PID controller. The formula for calculating the control signal is as follows:

[0034] in, It is the membership function. It is the output function of fuzzy rules.

[0035] 3. Adaptive Algorithm Module An adaptive algorithm module is used to dynamically adjust fuzzy control rules and parameters based on changes in real-time error, thereby optimizing controller performance. In this embodiment, the adaptive algorithm module dynamically adjusts the gain and control parameters of the fuzzy control rules based on real-time data of flow error and error change rate, ensuring that the system maintains optimal control performance under different operating conditions. The core objective of the adaptive algorithm module is to optimize the control rules in real time based on system operation feedback.

[0036] Gain adjustment: The adaptive algorithm module dynamically adjusts the gain parameter of the fuzzy controller using the following formula. In order to cope with changes in systematic errors:

[0037] in, This is the adjusted gain. It is the base gain. It is a dynamic adjustment coefficient. This is a flow error. Dynamic adjustment of the gain helps improve the system's adaptability and responsiveness.

[0038] Fuzzy control rule update: The adaptive algorithm also adjusts the rule base of fuzzy control based on the dynamic changes in flow error. For example, when the system load changes significantly, the parameters in the control rules (such as the boundaries of the fuzzy set and the weights of the rules) are automatically updated, thereby optimizing the control effect.

[0039] 4. PID controller A PID controller is used to adjust the opening of a solenoid valve based on the control signal output by the fuzzy control module in order to precisely regulate the flow rate. In this embodiment, the PID controller is responsible for adjusting the opening degree of the solenoid valve according to the control signal output by the fuzzy control module.

[0040] The output control signal of the fuzzy control module is processed by a PID controller, which includes: 1) Proportional control (P), which adjusts the output based on the error value of the fuzzy control; 2) Integral control (I) eliminates long-term deviations by processing the accumulation of errors; 3) Differential control (D) adjusts the rate of change of error to ensure rapid system response.

[0041] The role of a PID controller is to ensure system stability, reduce steady-state error, and improve response speed.

[0042] Control formula: The PID controller adjusts according to the control signal output by the fuzzy control module, and the control formula is as follows:

[0043] in, These are proportional, integral, and differential gains, respectively. For flow error, This is the control signal output by the PID controller.

[0044] 5. Control feedback loop The system continuously monitors the output flow of the solenoid valve through a feedback loop and calculates the flow error. and error change rate The feedback information is used to adjust the operating state of the adaptive fuzzy controller and the PID controller. Specifically: 1) When the flow error is large, the fuzzy controller will generate a large control signal, and the PID controller will adjust the opening of the solenoid valve according to this control signal.

[0045] 2) If the traffic does not reach the set target, the system will continue to adjust until the traffic meets the requirements.

[0046] 6. Remote monitoring and data acquisition module The solenoid valve flow regulation system further includes: 1) Real-time data acquisition and processing module, used to receive signals from the flow sensor in real time and convert the signals into digital signals suitable for processing by the control algorithm; 2) Remote control and monitoring module, used to transmit system status to a remote control center via wireless or wired means, so that users can remotely monitor and adjust the system.

[0047] This solenoid valve flow regulation system supports remote control and monitoring. Users can transmit system status data to a remote control center via wireless or wired communication. The remote control and monitoring module can provide real-time flow data, control signals, and the operating status of the solenoid valve, making operation more flexible and facilitating system maintenance and fault diagnosis.

[0048] As described above, this application has the following technical advantages: 1. High-precision control: By combining adaptive fuzzy control and PID control, the system can achieve high-precision flow regulation under various complex operating conditions. The fuzzy controller dynamically adjusts the control signal based on the flow error and its changes, while the PID controller precisely adjusts the opening of the solenoid valve.

[0049] 2. Good adaptability and robustness: Adaptive fuzzy control algorithms can dynamically adjust control rules based on real-time feedback information, adapting to constantly changing operating conditions such as flow rate, pressure, and temperature in the system, thereby improving the system's adaptability to external disturbances and changes in operating conditions.

[0050] 3. Real-time adjustment and rapid response: This invention combines a flow sensor with an adaptive control module, enabling the system to monitor flow and adjust control signals in real time, ensuring a rapid response capability and meeting the requirements for high-precision flow control.

[0051] 4. Simplified control structure: By combining fuzzy control and PID control, this invention simplifies the design of the control system, enabling the solenoid valve flow regulation system to maintain accuracy while effectively reducing the complexity of the control algorithm.

[0052] 5. Wide applicability: The electromagnetic valve flow regulation system of the present invention is not only suitable for liquid flow control, but also for gas flow control, industrial automation, HVAC (heating, ventilation and air conditioning) systems and other fields, and is especially suitable for fluid control systems that require high precision and fast response.

[0053] Please refer to Figure 1 , Figure 2 and Figure 3 The embodiments disclosed in this invention will now be described in further detail with reference to the accompanying drawings.

[0054] Example 1: Flow regulation under normal operating conditions The system operation process includes the following steps: Step 1: The flow sensor detects the flow rate in real time and transmits the data to the adaptive algorithm module; Step 2: The adaptive algorithm module dynamically adjusts the gain and rules of the fuzzy controller based on the flow error and rate of change; Step 3: The fuzzy controller calculates the control signal according to the adjusted rules and transmits it to the PID controller; Step 4: The PID controller adjusts the opening of the solenoid valve according to the fuzzy control signal to output a precise flow rate; Step 5: The solenoid valve executes the control signal, adjusts the fluid flow rate, and returns the feedback signal to the system.

[0055] like Figure 1 As shown, the solenoid valve flow regulation system in this embodiment includes a solenoid valve, a flow sensor, a fuzzy controller, an adaptive algorithm module, and a PID controller. The system monitors the fluid flow rate in real time through the flow sensor and dynamically adjusts the opening degree of the solenoid valve according to the control algorithm.

[0056] 1) Flow measurement and error calculation: The flow sensor will measure the actual flow rate The data is passed to the fuzzy controller. The fuzzy controller then sets the target flow rate. Compare and calculate flow error :

[0057] At the same time, calculate the rate of change of flow error. :

[0058] These signals serve as inputs to the fuzzy control module, used to generate control signals for adjusting the solenoid valve.

[0059] 2) Working principle of fuzzy controller: The fuzzy control module is based on the flow error. and error change rate Fuzzy rules generate control signals The reasoning rules are as follows:

[0060] Output control signal Further optimization was achieved through the adaptive algorithm module, adjusting the fuzzy rules and gain to improve the flow regulation effect.

[0061] 3) Adaptive gain adjustment: The adaptive algorithm module dynamically adjusts the gain of the fuzzy controller based on flow error and system feedback signals. For example, the gain can be dynamically adjusted using the following formula:

[0062] in, It is the base gain. It is the adjustment coefficient. It's a flow error. Dynamic gain adjustment ensures the system can respond quickly to load changes and external disturbances.

[0063] 4) PID controller regulates the solenoid valve: Based on the control signal generated by the fuzzy control module, the PID controller further adjusts the opening of the solenoid valve, as shown in the following formula:

[0064] in, These are the proportional, integral, and derivative gains of the PID controller. It's a flow error. It is the output of the PID controller.

[0065] 5) Solenoid valve performs regulation: The solenoid valve operates according to the output signal of the PID controller. Adjust the opening to ensure flow rate. Achieve the set target traffic .

[0066] 6) Feedback mechanism and adjustments: The system monitors the output flow of the solenoid valve in real time through a feedback loop. If the flow does not reach the set target, the system will continue to adjust the control signal until the flow approaches the target value.

[0067] Example 2: Robustness Enhancement under Special Working Conditions In practical applications, flow sensors may experience errors or data loss, affecting the stability and accuracy of the system. To address this issue, this embodiment introduces an adaptive algorithm module to enhance the system's robustness, enabling it to maintain stable operation even in environments with significant uncertainty.

[0068] 1. Historical data storage and learning: The adaptive algorithm module stores historical data (including flow errors, control signals, etc.) and corrects the control signals based on historical data and the current error when sensor data is inaccurate or lost. Historical data can be stored in the following formats:

[0069] in, This represents the stored historical dataset, including historical errors. Control signals And timestamps.

[0070] 2. Error correction: When the flow sensor malfunctions or data is lost, the system uses an adaptive algorithm module to calculate and correct the current error based on historical data. This module uses historical data to predict the current flow error e(t) and dynamically adjusts the gain and control signals. The corrected error value is calculated using the following formula:

[0071] in, This is the corrected flow error. The error is based on predictions made using historical data. It is the error adjustment amount calculated in real time.

[0072] 3. Adaptive adjustment of fuzzy control rules: Under special operating conditions, the fuzzy control module will adaptively adjust the fuzzy rules based on the current error and its changes. For example, it may increase the gain or change the weight coefficients in the fuzzy rules to cope with the impact of sensor errors or data loss.

[0073]

[0074] 4. PID controller and adaptive feedback: The solenoid valve flow regulation system can adaptively adjust the control strategy according to changes in operating conditions (such as temperature, pressure, etc.) to ensure the accuracy of flow regulation and the stability of the system; the proportional, integral, and derivative gains of the PID controller can be adjusted in real time and manually set to optimize the system response; The adaptive algorithm module adjusts the control signal accordingly. The input to the PID controller is adjusted, and the PID controller continues to perform flow regulation. In this way, even if the flow sensor fails, the system can still continue to operate and regulate the flow.

[0075] 5. System robustness and error compensation: The system can continue to perform error compensation and flow regulation even when sensor data is inaccurate. The adaptive algorithm makes the system highly robust, ensuring the accuracy of flow regulation and the stability of the system.

[0076] It should be noted that in the description of the embodiments of this application, the terms "front," "rear," "left," "right," "up," "down," etc., indicating the orientation or positional relationship are based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this application. The terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication between two elements. For those skilled in the art, the specific meaning of the above terms in this application can be understood according to the specific circumstances.

[0077] In summary, due to the adoption of the above technical features, the present invention has the following advantages and positive effects compared with the prior art: First, this application can overcome the challenges brought about by nonlinear and time-varying environments, and provide more stable and accurate flow control; Second, this application can automatically optimize the control strategy according to different working conditions to ensure stable operation in various complex environments; Third, this application can automatically adjust the control signal based on the real-time feedback of flow error and rate of change; Fourth, this application can flexibly adapt to flow fluctuations, environmental changes and external disturbances, significantly improving the accuracy of flow regulation and the system's response speed.

[0078] The preferred embodiments of the invention are merely illustrative of the invention. They do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the content of this specification. These embodiments have been selected and specifically described in this specification to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to make good use of the invention. The invention is limited only by the claims and their full scope and equivalents. The above disclosures are merely preferred embodiments of the invention, but are not intended to limit it. Any equivalent changes and modifications made by those skilled in the art without departing from the spirit and essence of the invention should fall within the protection scope of the invention.

Claims

1. A solenoid valve flow regulation system based on adaptive fuzzy control, characterized in that, The flow regulation system includes: Solenoid valves are used to regulate fluid flow and achieve precise flow regulation in response to control signals. A flow sensor is used to monitor the flow rate of a fluid in real time and feed the detected flow signal back to the control system. The fuzzy control module is used to receive the flow error signal and flow error change rate provided by the flow sensor, and to output the control signal through fuzzy inference calculation. The adaptive algorithm module is used to dynamically adjust the fuzzy control rules and parameters according to changes in real-time error, thereby optimizing controller performance; A PID controller is used to adjust the opening of a solenoid valve based on the control signal output by a fuzzy control module, thereby precisely regulating the flow rate.

2. The electromagnetic valve flow regulation system based on adaptive fuzzy control as described in claim 1, characterized in that, The fuzzy control module includes: Error input, used to receive the error between the current flow rate and the target flow rate of the solenoid valve; Error change rate input is used to receive the error change rate and generate a control signal according to a preset fuzzy rule; The fuzzy inference engine calculates the fuzzy output based on the input error and the rate of change of the error, and then derives the control signal.

3. The electromagnetic valve flow regulation system based on adaptive fuzzy control as described in claim 1, characterized in that, The output control signal of the fuzzy control module is processed by the PID controller, which includes: Proportional control (P) adjusts based on the error value of the fuzzy control output; Integral control (I) eliminates long-term deviations by processing the accumulation of errors; Differential control (D) adjusts the rate of change of error to ensure that the flow regulation system responds quickly.

4. The electromagnetic valve flow regulation system based on adaptive fuzzy control as described in claim 2, characterized in that, The adaptive algorithm module dynamically adjusts the gain parameter of the fuzzy controller according to the following formula: K(t) = K_0 ⋅ (1 + α ⋅ |e(t)|) Where K(t) is the adjusted gain, e(t) is the flow error, α is the dynamic adjustment coefficient, and K_0 is the base gain value.

5. The electromagnetic valve flow regulation system based on adaptive fuzzy control as described in claim 4, characterized in that, The flow regulation system also includes: The real-time data acquisition and processing module is used to receive signals from the flow sensor in real time and convert the signals into digital signals suitable for processing by the control algorithm. The remote control and monitoring module is used to transmit the status of the flow regulation system to a remote control center via wireless or wired means, so that users can remotely monitor and adjust the flow regulation system.

6. The electromagnetic valve flow regulation system based on adaptive fuzzy control as described in claim 1, characterized in that, The flow sensor is a vortex flow meter or a thermal flow sensor.

7. The electromagnetic valve flow regulation system based on adaptive fuzzy control as described in claim 4, characterized in that, The inference rules of the fuzzy controller are in the form of IF-THEN rules.

8. The electromagnetic valve flow regulation system based on adaptive fuzzy control as described in claim 7, characterized in that, The operation of the flow regulation system includes the following steps: Step 1: The flow sensor detects the flow rate in real time and transmits the data to the adaptive algorithm module; Step 2: The adaptive algorithm module dynamically adjusts the gain and rules of the fuzzy controller based on the flow error and the rate of change of the flow error; Step 3: The fuzzy controller calculates the control signal according to the adjusted rules and transmits it to the PID controller; Step 4: The PID controller adjusts the opening of the solenoid valve according to the control signal to output a precise flow rate; Step 5: The solenoid valve executes the control signal, adjusts the fluid flow rate, and returns the feedback signal to the flow regulation system.

9. The electromagnetic valve flow regulation system based on adaptive fuzzy control as described in claim 8, characterized in that, The flow regulation system adaptively adjusts the control strategy according to changes in operating conditions to ensure the accuracy of flow regulation and the stability of the flow regulation system.

10. The electromagnetic valve flow regulation system based on adaptive fuzzy control as described in claim 9, characterized in that, The proportional, integral, and derivative gains of the PID controller can be adjusted in real time and set manually to optimize the response of the flow regulation system.

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