Pneumatic control valve control system and control method thereof

Abstract

A pneumatic control valve control system and a control method thereof belong to the technical field of pneumatic control valve control, the system comprises a signal detection module, an execution module, a PLC control module and an upper computer monitoring module, and the PLC control module is connected with the signal detection module, the execution module and the upper computer monitoring module. The control method comprises the following steps: S1, establishing a mathematical model transfer function of the regulating valve control system; and S2, PID parameters are adjusted on line by using a fuzzy control method, and a PID controller is optimized, so that the PID controller has a function of self-tuning according to system changes. On the basis of a traditional PID algorithm, the pneumatic control valve opening mathematical model and the fuzzy controller are established, the fuzzy self-adaptive PID algorithm is used for controlling the pneumatic control valve in real time, and compared with a traditional PID self-tuning system, a pneumatic control valve control system of the fuzzy PID control algorithm is high in response speed, good in stability and small in overshoot; therefore, the dynamic performance of the pneumatic control valve control system is greatly improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of pneumatic control valve control, and particularly relates to a pneumatic control valve control system and a control method thereof. Background Art

[0002] In industrial production, pneumatic control valves play an extremely wide role as control instruments. As an auxiliary accessory of the pneumatic control valve, the valve positioner participates in the valve position control of the control valve to improve the control accuracy and stability of the control valve, and plays a key role in the process control of the control valve.

[0003] In the actual application process, the traditional valve positioner has poor control accuracy for the control valve, resulting in too large a deviation in the rotation angle of the actuator. Moreover, it needs to be calibrated and debugged repeatedly before use, and the operation is complex and cannot be flexibly controlled.

[0004] In the literature (Mao Jiajie. Application and Design of Intelligent Valve Positioner Control System [D]. China University of Mining and Technology, 2023. DOI: 10.27623 / d.cnki.gzkyu.2023.001631.), by analyzing the process of valve displacement, a valve control equation and a mathematical model of valve stem movement are established. The PID algorithm is selected as the valve position control algorithm. A fitness function is designed to find the optimal PID algorithm parameters. However, in industrial production, many controlled objects are affected by interference factors, resulting in changes in parameters or structural characteristics.

[0005] Scholars such as Zhang Han and Liu Tiejun proposed a genetically optimized PID tuning algorithm in the literature (Zhang Han, Liu Tiejun, Liu Bo, et al. Application of Genetic Optimization PID Tuning Algorithm in Valve Positioner [J]. Journal of Electronic Measurement and Instrumentation, 2021, 35(11): 215-222. DOI: 10.13382 / j.jemi.B2104036.). By using an improved genetic algorithm for PID parameter optimization, the control system accuracy is improved and the adjustment time is shortened. However, the value of Td in the genetic algorithm has a great influence on the system response. Increasing the differential action will bring sensitivity to disturbances and suppress the ability to resist external disturbances. On the contrary, the system response becomes slower and the stability is poor.

[0006] In summary, in today's industrial control, the accuracy requirements for pneumatic control valves are getting higher and higher. At the same time, when the pneumatic control valve is affected by external interference, it will cause large overshoot and large hysteresis of the controlled object. Therefore, it is necessary to invent a pneumatic control valve control system with strong reliability and high control accuracy. Summary of the Invention

[0007] To solve the above problems, the present invention proposes a pneumatic control valve control system, including a signal detection module, an execution module, a PLC control module, and a host computer monitoring module. The PLC control module is connected to the signal detection module, the execution module, and the host computer monitoring module.

[0008] Further, the PLC control module uses Siemens S7-1500PLC, and the signal detection module uses an angle sensor to detect the valve opening. When the system works, the angle sensor installed at the rear end of the actuator measures the valve opening of the pneumatic control valve, sends the signal to the PLC through the analog input module, and performs a comparison operation with the set valve opening. The analog output module converts the digital signal output by the PLC into an electrical signal to realize the control of the valve opening of the pneumatic control valve.

[0009] A control method for a pneumatic control valve control system includes the following steps:

[0010] S1. Establish the transfer function of the control valve control system mathematical model;

[0011] S2. Use the fuzzy control method to online adjust the PID parameters to optimize the PID controller so that it has the function of self-tuning according to the system changes.

[0012] Further, in step S1, the calculation formula of the control valve body operation mathematical model is as follows

[0013]

[0014] The calculation formula of the pneumatic actuator mathematical model is as follows

[0015]

[0016] The calculation formula of the electrical conversion analog control valve mathematical model is as follows

[0017]

[0018] The transfer function of the pneumatic control valve is

[0019]

[0020] The control expression of the traditional PID controller for controlling the pneumatic control valve is as shown in Equation (5):

[0021]

[0022] In the formula, u(t) is the valve position angle output curve of the pneumatic control valve, that is, the change curve of the PID output value with time, K pis the proportionality coefficient, e(t) is the deviation curve, that is, the curve of the deviation between the set value r(t) and the actual value y(t) of the pneumatic control valve changing with time, T i is the integral time, T d is the derivative time;

[0023] In actual engineering, before programming the PID, the analog formula is converted into a discrete formula. The discrete conversion formula is as shown in Equation (6):

[0024]

[0025] In the formula, K p is the proportionality coefficient; K i is the integral coefficient; K d is the derivative coefficient.

[0026] Furthermore, in the step S2, the fuzzy controller uses fuzzy rules to adaptively tune the three parameters K p , K i , K d of the PID controller, so that the PID controller can obtain the optimal parameters under different deviations e(t) and different deviation change rates ec(t)=de / dt.

[0027] Furthermore, the control process of the pneumatic control valve under fuzzy adaptive PID control includes the following steps:

[0028] S21. Take e(t) and ec(t) as the input variables of the fuzzy controller, and perform fuzzyfication after quantization factors K e , K ec ;

[0029] S22. According to the change of the valve position of the pneumatic control valve, take the basic domain of the error e(t) as e(t)={-6, 6}, and the fuzzy subset domain as {-6, 6}, then the quantization factor K e =3 / 6 = 0.5;

[0030] S23. Take the basic domain of the error change rate ec(t)={-12, 12}, and the fuzzy subset domain as {-6, 6}, then the quantization factor K ec =6 / 12 = 0.5;

[0031] S24. Then perform fuzzy inference according to the fuzzy rule table;

[0032] S25. Defuzzify the fuzzy control quantity obtained in the fuzzy inference process to obtain the output variables ΔK p , ΔK i and ΔK d ;

[0033] S26. Then add it to the initial parameters \(K\) p0 , \(K\) i0 and \(K\) d0 to obtain the real-time parameters \(K\) p , \(K\) i , \(K\) d of the fuzzy PID controller, achieving the purpose that the fuzzy PID controller can perform adaptive adjustment;

[0034] S27. The selected fuzzy domain of the output parameters of the fuzzy controller is [0, 6], and the language variables are selected as NL, NM, NS, ZE, PS, PM, and PL;

[0035] S28. Based on experience, design the fuzzy control rules of the parameters \(\Delta K\) p , \(\Delta K\) i , \(\Delta K\) d ;

[0036] S29. Use MATLAB to build a pneumatic control valve control system and conduct simulations.

[0037] The beneficial effects of the present invention are as follows: Based on the traditional PID algorithm, the present invention establishes a mathematical model of the opening of the pneumatic control valve and a fuzzy controller. The traditional PID algorithm and the fuzzy adaptive PID algorithm are respectively used to perform real-time control on the pneumatic control valve, and it is determined that the fuzzy PID control strategy can achieve precise control of the opening of the pneumatic control valve. It is proved that the pneumatic control valve control system designed with the fuzzy PID control algorithm in this paper has a faster response speed, better stability, and smaller overshoot than the traditional PID self-tuning, thus greatly improving the dynamic performance of the pneumatic control valve control system. Description of the Drawings

[0038] Figure 1 is the structural block diagram of the pneumatic control valve control system of the present invention;

[0039] Figure 2 is the control loop diagram of the traditional PID pneumatic control valve;

[0040] Figure 3 is the control principle diagram of the fuzzy PID pneumatic control valve;

[0041] Figure 4 is the output membership function curve diagram;

[0042] Figure 5 is the fuzzy editing interface diagram;

[0043] Figure 6 is the selected membership function interface diagram;

[0044] Figure 7 is the fuzzy rule interface diagram;

[0045] Figure 8 It is the simulation block diagram of the pneumatic control valve control system;

[0046] Figure 9 It is the valve opening response curve diagram of the pneumatic control valve;

[0047] Figure 10 It is the system control flow chart;

[0048] Figure 11 It is the program logic diagram of the deviation value fuzzification part. Specific implementation mode

[0049] To make the technical means and achieved purposes adopted by the present invention easy to understand, the present invention will be further described below in conjunction with specific implementation modes. A pneumatic control valve control system mainly consists of a signal detection module, an execution module, a PLC control module, and a host computer monitoring module. This system uses a Siemens S7-1500PLC as the core controller and a Weinview touch screen MT8121iE2 as the human-machine interface. When the system works, an angle sensor installed at the rear end of the actuator measures the valve opening of the pneumatic control valve, and sends the signal to the PLC through the analog input module, compares and calculates it with the set valve opening. The analog output module converts the digital signal output by the PLC into a 4-20Ma electrical signal to control the pneumatic control valve, thereby realizing the control of the valve opening of the pneumatic control valve. The control system structure diagram is as Figure 1 shown.

[0050] Based on the traditional PID, this control system proposes a control algorithm based on the fuzzy PID dynamic principle, that is, a control method for a pneumatic control valve control system, uses the fuzzy control method to adjust the PID parameters online, optimizes the PID controller, and enables it to have the function of self-tuning according to system changes.

[0051] Establish the transfer function of the control valve control system mathematical model. The calculation formula of the control valve body operation mathematical model is as follows

[0052]

[0053] The calculation formula of the pneumatic actuator mathematical model is as follows

[0054]

[0055] The calculation formula of the electrical conversion analog control valve mathematical model is as follows

[0056]

[0057] Therefore, the transfer function of the pneumatic control valve is

[0058]

[0059] The loop for controlling a pneumatic control valve by a traditional PID controller is as follows Figure 2 shown.

[0060] Its control expression is as shown in Equation (5):

[0061]

[0062] where u(t) is the output curve of the valve position angle of the pneumatic control valve, that is, the curve of the PID output value changing with time, and K p is the proportional coefficient, e(t) is the deviation curve, that is, the curve of the deviation between the valve position set value r(t) and the actual value y(t) of the pneumatic control valve changing with time, and T i is the integral time, and T d is the differential time.

[0063] In actual engineering, discrete data is used. Therefore, before programming the PID, it is necessary to convert the analog formula into a discrete formula. The discrete conversion formula is as shown in Equation (6):

[0064]

[0065] where K p is the proportional coefficient; K i is the integral coefficient; K d is the differential coefficient.

[0066] In the pneumatic control valve control system, for traditional PID control, the valve positioner needs to continuously repeat the calibration of the valve position, resulting in excessive oscillation of the valve position.

[0067] The fuzzy controller uses fuzzy rules to adaptively tune the three parameters K p , K i , and K d of the PID controller, so that the PID controller can obtain the optimal parameters under different deviations e(t) and different deviation change rates ec(t) = de / dt. The block diagram of the pneumatic control valve control system under fuzzy adaptive PID control is as follows Figure 3 shown.

[0068] Fuzzy adaptive PID control needs to first tune the fuzzy relationship between the PID controller parameters K p , K i , K d and e(t), ec(t). During the operation of the control system, the error e(t) and the error change rate ec(t) values are detected in real time, and the parameters K p , K i , and K d are tuned in real time according to the fuzzy control relationship to achieve the desired control effect.

[0069] Taking \(e(t)\) and \(ec(t)\) as the input variables of the fuzzy controller, after quantization factors \(K\) e and \(K\) ec , they are fuzzified. According to the valve position change of the pneumatic control valve, taking the basic domain of the error \(e(t)\) as \(e(t)=\{-6, 6\}\) and the fuzzy subset domain as \(\{-6, 6\}\), then the quantization factor \(K\) e = 3 / 6 = 0.5; taking the basic domain of the error change rate \(ec(t)=\{-12, 12\}\) and the fuzzy subset domain as \(\{-6, 6\}\), then the quantization factor \(K\) ec = 6 / 12 = 0.5. Then, fuzzy inference is carried out according to the fuzzy rule table. The fuzzy control quantity obtained from the fuzzy inference process is defuzzified to obtain the output variables \(\Delta K\) p , \(\Delta K\) i and \(\Delta K\) d . Then, adding them to the initial parameters \(K\) p0 , \(K\) i0 and \(K\) d0 of the PID controller to obtain the real-time parameters \(K\) p , \(K\) i , \(K\) d of the fuzzy PID controller, achieving the purpose that the fuzzy PID controller can be adaptively adjusted. The selected fuzzy domain of the fuzzy controller output parameters is \([0, 6]\), and the language variables are selected as NL, NM, NS, ZE, PS, PM, and PL. The curve of the output membership function of the variable is as shown in Figure 4 .

[0070] Based on experience, the fuzzy control rules of the parameters \(\Delta K\) p , \(\Delta K\) i , \(\Delta K\) d are designed, and the fuzzy control rules are shown in Tables 1 to 3.

[0071] Table 1 \(\Delta K\) p Fuzzy rule table

[0072]

[0073] Table 2 \(\Delta K\) i Fuzzy rule table

[0074]

[0075] Table 3 \(\Delta K\) d Fuzzy rule table

[0076]

[0077] According to the created fuzzy rule table, \(K\) p , \(K\) i , \(K\) dThe value, that is:

[0078]

[0079] To verify the control strategy of the above design and the control performance of the controlled system during operation, MATLAB is used to build a pneumatic control valve control system and conduct simulations. In the fuzzy controller module, the input quantities e(t) and ec(t) of the system are added, and then the output quantity ΔK p 、ΔK i and ΔK d are added to design a two-input three-output fuzzy inference editing system. As shown in Figure 5 shown.

[0080] For the three output quantities of the fuzzy controller, the membership functions are determined and output, and the output universe of discourse is set to [0, 6]. The 7 linguistic values used are NL, NM, NS, ZE, PS, PM, and PL. The membership function selection interface is as shown in Figure 6 shown.

[0081] According to the content of fuzzy control rule tables 1 to 3, the fuzzy rules are input into the fuzzy controller, and the output results are as shown in Figure 7 shown.

[0082] In MATLAB, the fuzzy PID controller and the controlled object are used to build a system flow chart through Simulink, and the response of the system when a given expected value is input is tested. The system flow chart is as shown in Figure 8 shown.

[0083] The simulation experiments respectively use traditional PID and fuzzy adaptive PID to conduct real-time control of the pneumatic control valve. The valve position response curve of its valve body is as shown in Figure 9 shown. It can be seen from the simulation curve graph that the response curve under conventional PID control has too large overshoot with oscillations and too long adjustment time. While the fuzzy adaptive PID control algorithm applied to the pneumatic control valve control system is easier to reach a stable state and reduces the overshoot and oscillation level of the system.

[0084] The programming is carried out using the TIA Portal software. The main program is written into OB1, and the control strategy program is written into the cyclic interrupt organization block OB35. The PLC is used to implement closed-loop control of the gas temperature control system. The program flow chart is as shown in Figure 10 shown.

[0085] In the pneumatic control valve control system, first e(t), ec(t), ΔK p 、ΔK i and ΔK dThe scale factor and quantization factor are stored in the PLC register. The PLC performs a logical operation on the received valve opening value and the valve opening set value, and then detects e(t) and ec(t). After fuzzy processing, they are stored in the data register. By comparing the fuzzy control rule table, the actual final output u(k) is obtained. Then, the adaptively changing K p and K i and K d are brought into the system to obtain the system output. During the control process, the three parameters of the PID controller under the fuzzy controller adaptively sense the changes in the system and thus change their own magnitudes, making the system output more stably track the input expected value.

[0086] According to the fuzzy rule table, the error e(t) and the error change rate ec(t) are stored in DB14.DBD0 and DB14.DBD4. The ΔK p is sequentially stored in the storage area from address DB16.DBD100 to DB16.DBD292 from left to right and top to bottom according to the fuzzy rule table. Similarly, the address of ΔK i is DB16.DBD296 to DB16.DBD488, and the address of ΔK d is DB16.DBD492 to DB16.DBD684. The three initial parameters K p0 and K i0 and K d0 data are stored in DB18.DBD0, DB18.DBD4, and DB18.DBD8. The obtained real-time parameters K p and K i and K d data storage addresses are DB19.DBD0, DB19.DBD4, and DB19.DBD8. The fuzzy PID control part of the program is as Figure 11 shown.

[0087] Overall machine calibration and experiment

[0088] In actual tests, the pneumatic control valve control systems under traditional PID and fuzzy PID controls are compared. During the test, the initial control valve opening is set to 0%, and the target control valve openings are 30%, 50%, 80%, and 100%. According to the valve position travel data of the pneumatic control valve in actual tests, the test data tables are as shown in Tables 4 to 7 below

[0089] Table 4 Target control valve opening 30%

[0090]

[0091] Table 5 Target control valve opening 50%

[0092]

[0093] Table 6 Target regulating valve opening 80%

[0094]

[0095] Table 7 Target regulating valve opening 100%

[0096]

[0097]

[0098] It can be obtained by comparing the tables that the two different control methods are basically consistent with the response curve during the control process. Among them, in Table 7 where the target regulating valve opening is 100%, the actual valve opening exceeds the maximum opening due to the reasons of the valve mechanical components. To sum up, the performance of the pneumatic regulating valve control system of the present invention has been significantly improved and meets the design requirements.

[0099] As described above, it is only the preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution and its concept of the present invention, making equivalent substitutions or changes should be covered within the protection scope of the present invention.

Claims

1. A pneumatic control valve control system, characterized in that, It includes a signal detection module, an execution module, a PLC control module and a host computer monitoring module, and the PLC control module is connected to the signal detection module, the execution module and the host computer monitoring module.

2. The pneumatic control valve control system according to claim 1, characterized in that, The PLC control module uses a Siemens S7-1500 PLC, and the signal detection module uses an angle sensor to detect the valve opening. When the system works, the angle sensor installed at the back end of the actuator measures the valve opening of the pneumatic control valve, sends the signal to the PLC through the analog input module, and performs a comparison operation with the set valve opening. The analog output module converts the digital signal output by the PLC into an electrical signal to achieve the control of the valve opening of the pneumatic control valve.

3. A control method for a pneumatic control valve system, characterized in that, It includes the following steps: S1. Establish the transfer function of the mathematical model of the control system of the control valve; S2. Use the fuzzy control method to adjust the PID parameters online, optimize the PID controller, and make it have the function of self-tuning according to the system changes.

4. The pneumatic control valve control system according to claim 3, wherein, In the step S1, the calculation formula of the mathematical model of the control valve body is as follows The calculation formula of the mathematical model of the pneumatic actuator is as follows The calculation formula of the mathematical model of the electrical conversion analog control valve is as follows The transfer function of the pneumatic control valve is The control expression of the traditional PID controller for controlling the pneumatic control valve is as shown in Equation (5): where \(u(t)\) is the output curve of the pneumatic control valve position angle, that is, the curve of the PID output value changing with time, \(K\) p is the proportional coefficient, \(e(t)\) is the deviation curve, that is, the curve of the deviation between the set value \(r(t)\) and the actual value \(y(t)\) of the pneumatic control valve position changing with time, \(T\) i is the integral time, \(T\) d is the differential time; In actual engineering, before programming the PID, convert the analog formula into a discrete formula, and the discrete conversion formula is as shown in Equation (6): where K p is the proportionality coefficient; K i is the integral coefficient; K d is the differential coefficient.

5. The pneumatic control valve control system according to claim 3, characterized in that, In the step S2, the fuzzy controller uses fuzzy rules to adaptively tune the three parameters, i.e., K p , K i , and K d of the PID controller, so that the PID controller can obtain optimal parameters under different deviation e(t) and different deviation change rate ec(t) = de / dt.

6. The pneumatic control valve control system according to claim 5, wherein The control process of the pneumatic control valve under fuzzy adaptive PID control includes the following steps: S21. Take e(t) and ec(t) as the input variables of the fuzzy controller, and perform fuzzification after quantization factors K e , K ec . S22. According to the valve position change of the pneumatic control valve, the basic domain of the error e(t) is e(t) = {-6, 6}, and the domain of the fuzzy subset is {-6, 6}, then the quantization factor K e = 3 / 6 = 0.5; S23. Take the basic domain of the error change rate ec(t) = {-12, 12}, and the fuzzy subset domain is {-6, 6}, then the quantization factor K ec = 6 / 12 = 0.5; S24. Then perform fuzzy inference according to the fuzzy rule table; S25. Defuzzify the fuzzy control quantity obtained from the fuzzy inference process to obtain the output variable ΔK of the fuzzy controller p , ΔK i and ΔK d ; S26. Then add it to the initial parameters \(K\) p0 , \(K\) i0 and \(K\) d0 of the PID controller to obtain the real-time parameters \(K\) p , \(K\) i , \(K\) d of the fuzzy PID controller, achieving the purpose that the fuzzy PID controller can perform adaptive adjustment; S27. The selected fuzzy domain of the output parameters of the fuzzy controller is [0, 6], and the language variables are selected as NL, NM, NS, ZE, PS, PM and PL; S28. Based on experience, design the parameter ΔK p and ΔK i and ΔK d fuzzy control rules; S29. Use MATLAB to build the control system of the pneumatic control valve and perform simulation.

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