Design method and device of pneumatic regulating valve control system based on QFT and DOB

Abstract

The present invention provides a design method and device for a pneumatic control valve control system based on QFT and DOB, and relates to the field of automatic control technology. The method includes establishing a mathematical model of a pneumatic control valve system; using the principle of quantitative feedback theory to systematically analyze and design the established mathematical model of the pneumatic control valve system; designing a two-degree-of-freedom controller including a feedback controller and a prefilter, and applying the controller to the pneumatic control valve system, and adjusting the two-degree-of-freedom controller so that the open-loop response curve of the system meets the performance requirements, including robust stability and tracking performance; considering the influence of equivalent disturbance (external disturbance + model uncertainty) on the system, and introducing a disturbance observer so that the system can perceive and compensate for the equivalent disturbance in real time. The present invention can more effectively resist the influence of external disturbance and model uncertainty on the system, and improve the stability and robustness of the system.

Description

Technical Field

[0001] The present invention relates to the field of automatic control technology, and in particular to a design method and device for a pneumatic regulating valve control system based on QFT (Quantitative Feedback Theory) and DOB (Disturbance Observer). Background Art

[0002] Pneumatic control valves are common control devices in industrial processes, and their systems usually have complex characteristics such as nonlinearity, time-varying and uncertainty. In the field of pneumatic control valve control systems, some existing technologies have attempted to solve the impact of external interference and uncertainty on system stability and performance, but there are some problems. A common method at present is to use a traditional PID (proportional-integral-differential) controller to regulate pneumatic control valves. However, PID controllers often perform poorly for complex industrial processes, especially when faced with external interference and uncertainty.

[0003] A major problem with traditional PID controllers is the lack of robustness to external disturbances. PID controllers are usually designed based on a mathematical model of the system, but external disturbances in industrial processes are often difficult to model accurately, causing the performance of PID controllers to be affected by disturbances and degraded. In addition, the parameters of PID controllers need to be adjusted manually, which places high demands on operators and often fails to meet the control requirements under different working conditions.

[0004] Another common solution is to use Model Predictive Control (MPC). MPC optimizes the performance of the controller by building a dynamic model of the system and considering the control actions in the future. However, one of the main disadvantages of MPC is its high computational complexity. Especially for large systems, the computation time is long, which affects the real-time performance. In addition, MPC has high requirements on the accuracy of the system model, while the models in industrial processes often have uncertainties, which limits the application of MPC.

[0005] In addition, there are some specific methods for external disturbances, such as sliding mode control and adaptive control. Sliding mode control suppresses the impact of disturbances on the system by designing a sliding surface, but it requires accurate system models and parameters, and the design of the sliding surface is often complex, which limits its practical application. Adaptive control can adjust control parameters in real time according to system changes, but it requires a large amount of real-time data to update the parameters, and has high requirements on the stability and convergence of the system.

[0006] Therefore, in order to solve the complex control problems of the pneumatic control valve system and improve the stability and performance of the pneumatic control valve control system, a new design method for the pneumatic control valve control system is urgently needed. Summary of the invention

[0007] To this end, an embodiment of the present invention provides a design method and device for a pneumatic control valve control system based on QFT and DOB, which is used to solve the problems of complex control, low stability and poor performance of the pneumatic control valve control system in the prior art.

[0008] In order to solve the above problems, an embodiment of the present invention provides a design method of a pneumatic control valve control system based on QFT and DOB, the method comprising:

[0009] Aiming at the external interference and uncertainty factors of pneumatic control valves in industrial processes, the mathematical model of pneumatic control valve system is established by analyzing the working principle of pneumatic control valves.

[0010] The established mathematical model of pneumatic control valve system is systematically analyzed and designed using the principle of quantitative feedback theory.

[0011] Design a two-degree-of-freedom controller including a feedback controller and a prefilter, and apply it to a pneumatic control valve system. By adjusting the two-degree-of-freedom controller, the open-loop response curve of the system meets the performance requirements, including robust stability and tracking performance.

[0012] Considering the impact of equivalent disturbance on the system, a disturbance observer is introduced to enable the system to perceive and compensate for the equivalent disturbance in real time. The equivalent disturbance includes external disturbance and model uncertainty.

[0013] Preferably, the uncertain factors include wear of moving parts of the actuator, changes in the elastic coefficient of the spring, and changes in internal friction damping.

[0014] Preferably, the mathematical model of the pneumatic control valve system is expressed as:

[0015]

[0016] Where, G(s) represents the mathematical model of the pneumatic control valve system; G1(s) represents the transfer function of the intelligent positioner module; G2(s) represents the transfer function of the pneumatic diaphragm actuator; G3(s) represents the transfer function between the air chamber and the valve stem actuator; G4(s) represents the transfer function between the air chamber output force and the valve stem displacement; K, ω, s, ξ are all system parameters; T v =C v R v , R v is the air conduction resistance, C v =V / K v, K v is the isothermal elastic modulus of the ideal gas, V is the volume of the gas before compression; A D is the effective area of ​​the air chamber diaphragm; m is the total mass of the actuator's moving part; k is the elastic coefficient of the internal telescopic spring of the actuator; and b is the internal friction damping of the actuator.

[0017] Preferably, the method of using the principle of quantitative feedback theory to systematically analyze and design the mathematical model of the established pneumatic control valve system specifically includes:

[0018] Design system robustness stability indicators:

[0019]

[0020] Where, L(jω) is the feedback controller to be designed; ω is the system parameter, and j is the imaginary unit;

[0021] Design systems to track performance metrics:

[0022]

[0023] Where, T u (s) is the upper bound of tracking performance, T l (s) is the lower bound of tracking performance;

[0024] A set of frequency points are selected, the system uncertainty model is calculated at each frequency point and an object template is drawn; then, a composite boundary curve formed by a robust stability boundary and a robust tracking boundary is drawn according to the stability index requirements.

[0025] Preferably, the designed two-degree-of-freedom controller includes a feedback controller and a prefilter and is applied to a pneumatic control valve system. By adjusting the two-degree-of-freedom controller, the open-loop response curve of the system meets the performance requirements, including robust stability and tracking performance, specifically including:

[0026] Design the controller: By adding gain, zero and pole to the nominal model, the low-frequency open-loop Nichols curve of the system is located above the response frequency point constraint boundary and as close to the boundary as possible; while the high-frequency amplitude and phase curves are located outside the robust stability boundary;

[0027] Design the pre-filter: Make the closed-loop frequency response curve within the desired tracking boundary to meet the tracking performance requirements.

[0028] Preferably, the disturbance observer is used to monitor the difference between the actual output of the controlled object and the output predicted by the model, and regards the difference as equivalent disturbance.

[0029] Preferably, the interference observer is expressed as:

[0030]

[0031] in

[0032]

[0033] In the formula, G dy (s) are the given input transfer function and disturbance transfer function respectively; U r (s) is the input signal; Y(s) is the output signal; D(s) is the external input disturbance; P(s) is the actual model affected by the disturbance; Q(s) is the low-pass filter to be designed; P n (s) is the nominal model.

[0034] Preferably, the low-pass filter Q(s) is expressed as:

[0035]

[0036] in

[0037]

[0038] In the formula, a Nk is the quadratic term coefficient, N is the order of the low-pass filter, NM is the relative order between the numerator and denominator of the low-pass filter, τ is the time constant, s is the system parameter, and k is the conventional coefficient.

[0039] Preferably, the relative order of the low-pass filter Q(s) is greater than or equal to P n -1 (s) relative order, where P n -1 (s) is the nominal model P n The inverse of (s).

[0040] Based on the same inventive concept, an embodiment of the present invention further provides a design device for a pneumatic control valve control system based on QFT and DOB, which is used to implement the design method for a pneumatic control valve control system based on QFT and DOB, specifically comprising:

[0041] The system model building module is used to establish a mathematical model of the pneumatic control valve system by analyzing the working principle of the pneumatic control valve in view of the external interference and uncertainty factors of the pneumatic control valve in the industrial process;

[0042] System analysis and design module, which is used to analyze and design the mathematical model of the established pneumatic control valve system using the principle of quantitative feedback theory;

[0043] The two-degree-of-freedom controller design and application module is used to design a two-degree-of-freedom controller including a feedback controller and a prefilter, and apply it to a pneumatic control valve system. By adjusting the two-degree-of-freedom controller, the open-loop response curve of the system meets the performance requirements, including robust stability and tracking performance;

[0044] The disturbance observer introduction and application module is used to consider the impact of equivalent disturbance on the system. By introducing the disturbance observer, the system can perceive and compensate for the equivalent disturbance in real time. The equivalent disturbance includes external disturbance and model uncertainty.

[0045] It can be seen from the above technical solutions that the present invention has the following beneficial effects:

[0046] The embodiment of the present invention provides a design method and device for a pneumatic control valve control system based on QFT and DOB. The present invention significantly improves the control performance of the pneumatic control valve system, including faster response speed, more stable control and more accurate tracking capability, through the design and optimization of a two-degree-of-freedom controller. By introducing a disturbance observer, the system has stronger robustness, can maintain stability in the face of external disturbances and uncertainties, and reduce the system's sensitivity to changes in the external environment. The present invention combines QFT and DOB to more effectively resist the impact of external disturbances on the system, improve the stability and robustness of the system, make the system more adaptable, and be able to cope with challenges such as changes in the working environment and load disturbances. Simulation analysis verifies the significant improvement of the system in disturbance suppression and control smoothness, and has broad application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the implementation cases of the present invention or the technical solutions in the prior art, the following is a brief description of the drawings required for use in the embodiments. By referring to the drawings, the features and advantages of the present invention will be more clearly understood. The drawings are schematic and should not be understood as limiting the present invention in any way. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0048] Figure 1 A flow chart of a design method of a pneumatic control valve control system based on QFT and DOB provided in an embodiment;

[0049] Figure 2 A schematic diagram of robust hybrid boundary and open-loop frequency response in an embodiment;

[0050] Figure 3 The frequency response curve of the open-loop system after shaping in the embodiment;

[0051] Figure 4 Tracking boundary response curve for closed-loop system in the embodiment;

[0052] Figure 5 It is a structural diagram of the interference observer in the embodiment;

[0053] Figure 6 It is an equivalent structure diagram of the disturbance observer in the embodiment;

[0054] Figure 7 It is a comparison diagram of valve position signals with and without interference observer under step signal interference in the embodiment;

[0055] Figure 8 A comparison diagram of valve position signals with and without interference observer under sinusoidal disturbance in the embodiment;

[0056] Fig. 9 Schematic diagram of the effect of system uncertainty on valve position signal in the embodiment;

[0057] Fig.10 It is a block diagram of a design device of a pneumatic regulating valve control system based on QFT and DOB provided in an embodiment. DETAILED DESCRIPTION

[0058] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0059] Embodiment 1

[0060] In view of the fact that the pneumatic control valve system may be subject to external disturbances and uncertainties in the industrial process, the present invention proposes a pneumatic control valve control system that can monitor and compensate for external disturbances in real time to improve the robustness of the system. Figure 1 As shown, an embodiment of the present invention proposes a design method for a pneumatic control valve control system based on QFT and DOB, the method comprising:

[0061] Step S1: In view of the external interference and uncertainty factors of the pneumatic control valve in the industrial process, the working principle of the pneumatic control valve is analyzed to establish a mathematical model of the pneumatic control valve system;

[0062] Step S2: using the principle of quantitative feedback theory to systematically analyze and design the mathematical model of the established pneumatic control valve system;

[0063] Step S3: designing a two-degree-of-freedom controller including a feedback controller and a pre-filter, and applying the controller to a pneumatic control valve system, and adjusting the two-degree-of-freedom controller so that an open-loop response curve of the system meets performance requirements, including robust stability and tracking performance;

[0064] Step S4: Considering the impact of equivalent disturbance on the system, a disturbance observer is introduced to enable the system to perceive and compensate for the equivalent disturbance in real time, wherein the equivalent disturbance includes external disturbance and model uncertainty.

[0065] It can be seen from the above technical scheme that the present invention provides a design method for a pneumatic control valve control system based on QFT and DOB. In view of the fact that pneumatic control valves are affected by external interference and uncertainty in industrial processes, a mathematical model of a pneumatic control valve system is established by analyzing the working principle of the pneumatic control valve. The established mathematical model of the pneumatic control valve system is systematically analyzed and designed using the principle of quantitative feedback theory. The quantitative feedback theory can quantify the stability and performance of the system, providing a theoretical basis for subsequent controller design. The two-degree-of-freedom controller is designed to include a feedback controller and a prefilter, and is applied to the pneumatic control valve system. By adjusting the two-degree-of-freedom controller, the open-loop response curve of the system meets the performance requirements, including robust stability and tracking performance. The system introduces a disturbance observer to monitor the difference between the actual output of the controlled object and the predicted output of the model, regards this difference as equivalent interference, and introduces it into the system through the control input. The design of the disturbance observer enables the system to perceive and compensate for external interference in real time, thereby improving the robustness and anti-interference ability of the system. In addition, the disturbance observer and the controller are independently designed to form a composite control framework. This design enables the disturbance observer and controller to be optimized independently and can be adjusted and improved according to the needs of specific application scenarios, thus improving the flexibility and applicability of the system.

[0066] In this embodiment, in step S1, in view of the external interference and uncertainty factors of the pneumatic control valve in the industrial process, the working principle of the pneumatic control valve is analyzed to establish a mathematical model of the pneumatic control valve system.

[0067] Specifically, the pneumatic control valve uses compressed air as the power source, a cylinder or a diaphragm head as the actuator, and uses accessories such as valve positioners, solenoid valves, and handwheels to drive the valve to achieve switching or proportional regulation, receive control signals from the automation system, and control the flow of fluid in the pipeline. Due to the complex structure of the pneumatic control valve system, it is difficult to model the system as a whole, so the system is divided into different functional modules according to the composition of the pneumatic control valve. According to the workflow and modularization concept of the pneumatic control valve system, the pneumatic control valve system is divided into an intelligent positioner module and a valve actuator module. The valve actuator selected for this system is a reaction pneumatic diaphragm control valve.

[0068] Furthermore, the intelligent positioner module is composed of a controller, an electrical conversion part, a pneumatic amplification part and a displacement sensor, wherein the transfer function of the displacement sensor is usually R(s)=1. The intelligent positioner module converts the valve position input signal of the system into the required air pressure signal through the electrical conversion part. The air pressure signal is converted into a high air pressure signal that can be input into the pneumatic valve actuator through the pneumatic amplification part to control the output of the valve actuator. The structure of this part is very complex, and the relationship between the output and the output of this part can be obtained through the system identification method. Through the system identification method, it can be obtained that this part is a second-order system:

[0069]

[0070] Where K, ω, s, and ξ are typical second-order system parameters.

[0071] Furthermore, the valve actuator module consists of a sealed air chamber and a valve stem actuator. The air chamber of the pneumatic diaphragm actuator can be understood as the conversion of the input air pressure signal into the pressure in the air chamber, which can be approximated as a resistance-capacitance link. The air chamber of the pneumatic actuator is mainly a first-order inertial link control system. After analysis and modeling, the transfer function of the pneumatic diaphragm actuator can be obtained as:

[0072]

[0073] Where P1(s) is the input air chamber pressure, P2(s) is the output air chamber pressure, T v =C v R v , P v is the air conduction resistance, C v =V / K v , K v is the isothermal elastic modulus of ideal gas, and V is the volume of the gas before compression.

[0074] The connection between the air chamber and the valve stem actuator is a force conversion link, which converts the air pressure in the air chamber into the pulling force of the actuator push rod. The magnitude of the force is related to the effective area A of the diaphragm in the air chamber. D The form of converting it into a transfer function is:

[0075]

[0076] In the formula, F(s) is the thrust output by the air chamber, P2(s) is the air pressure output by the air chamber, and A D is the effective area of ​​the air chamber membrane.

[0077] The dynamic characteristics of the pneumatic diaphragm actuator can be approximated as a mass, spring, and damping system. According to Newton's second law, the system equation for the output force of the air chamber is:

[0078]

[0079] Where m is the total mass of the actuator's moving part, x is the displacement of the actuator's push rod, k is the elastic coefficient of the actuator's internal telescopic spring, and b is the actuator's internal friction damping.

[0080] Under zero initial conditions, Laplace transform is performed to obtain the transfer function between the air chamber output force and the valve stem displacement:

[0081]

[0082] In the pneumatic control valve system, there are many uncertain factors, including the wear of the moving parts of the actuator, the change of the elastic coefficient of the spring, the change of the internal friction damping, and other factors such as environmental conditions and external interference. These uncertain factors jointly affect the performance and stability of the system.

[0083] Specifically, in the mathematical modeling of the pneumatic control valve system, the focus is on the dynamic behavior of the actuator, so the following three uncertain factors are mainly considered: the wear of the moving parts of the actuator, the change of the elastic coefficient of the spring, and the change of the internal friction damping. Therefore, the mathematical model of the pneumatic (diaphragm) control valve system is established as follows:

[0084]

[0085] Where G(s) represents the mathematical model of the pneumatic (diaphragm) control valve system.

[0086] In this embodiment, in step S2, the principle of quantitative feedback theory is used to perform system analysis and design on the established mathematical model of the pneumatic control valve system.

[0087] The central idea of ​​quantitative feedback theory is to convert the system's stability, tracking performance, anti-interference and other requirements into the control boundary curve on the Nichols diagram in a quantitative way, obtain the constraints of the controller, and then select the appropriate controller from the set of controllers that meet the conditions.

[0088] Specifically, according to the established mathematical model G(s) of the pneumatic (diaphragm) regulating valve system, an appropriate system transfer function is selected for it:

[0089]

[0090] The measured uncertainty parameter ranges are: m∈[0.040.05]kg; k∈

[810] N / mm; b∈[0.81]N / (mm / s).

[0091] Select m0=0.04kg; k0=8N / mm; b0=0.8N / (mm / s) as the nominal parameters of the system, and the transfer function of the nominal object is:

[0092]

[0093] Where G0(s) represents the nominal model.

[0094] Furthermore, the robust stability index of the design system is:

[0095] To achieve robust control of the system, we must first ensure a certain stability margin and use the maximum amplitude of the closed-loop frequency domain response. To ensure the robust stability of the system. This system guarantees a minimum amplitude margin of 5dB.

[0096] To ensure the robust stability of the system, the following conditions must be met:

[0097]

[0098] Where L(jω) is the feedback controller to be designed, ω is the system parameter, and j is the imaginary unit.

[0099] Furthermore, the system is designed to track performance indicators:

[0100] To maintain the tracking performance of the system, the following conditions must be met:

[0101]

[0102] in

[0103]

[0104]

[0105] Where, T u (s) is the upper bound of tracking performance, T l (s) is the lower bound of the tracking performance. The tracking boundary ensures that the overshoot of the closed-loop system step response does not exceed 5% and the adjustment time does not exceed 2.5s.

[0106] Furthermore, draw the boundary curve:

[0107] Select a set of frequency points ω = [0.01 0.05 0.1 0.5 1 5 10 50 100 500 1000] rad / s, calculate the system uncertainty model at each frequency point and draw the object template; then draw the composite boundary curve formed by the robust stability boundary and the robust tracking boundary according to the stability requirements, such as Figure 2 .

[0108] In this embodiment, in step S3, a two-degree-of-freedom controller is designed to include a feedback controller and a prefilter, and is applied to a pneumatic control valve system. By adjusting the two-degree-of-freedom controller, the open-loop response curve of the system meets the performance requirements, including robust stability and tracking performance, specifically including:

[0109] (1) Design of controller: The design of controller C(s) is actually the process of correcting the open-loop frequency response of the nominal model and loop shaping. By adding gain and zero poles to the nominal model, the low-frequency open-loop Nichols curve of the system is located above the constraint boundary of the response frequency point and as close to the boundary as possible; while the amplitude and phase curves of the high-frequency part are located outside the robust stability boundary. The controller C(s) is expressed as:

[0110]

[0111] like Figure 3 As shown, the open-loop amplitude-phase curve of the nominal model after shaping.

[0112] (2) Prefilter design: The design of the prefilter F(s) is to limit the closed-loop frequency response curve within the desired tracking boundary to meet the tracking performance requirements. The prefilter F(s) is expressed as:

[0113]

[0114] like Figure 4 As shown in Figure 3, the closed-loop frequency response boundary of the system is within the tracking performance boundary under parameter disturbance.

[0115] In this embodiment, in step S4, considering the impact of equivalent disturbance (external disturbance + model uncertainty) on the system, the system introduces a disturbance observer, which is used to monitor the difference between the actual output of the controlled object and the predicted output of the model, and regards this difference as equivalent disturbance. It is introduced into the system through the control input end, so that the system can perceive and compensate for the equivalent disturbance in real time.

[0116] In the pneumatic control valve control system, the disturbance observer is a key component of the composite controller, which is used to estimate the impact of disturbances in real time. The core goal of its design is to effectively perceive the difference between the actual output of the system and the theoretical model, regard this difference as an equivalent disturbance and reconstruct it; then perform real-time compensation through a feedforward mechanism to minimize the adverse effects of disturbances on system performance.

[0117] The disturbance observer structure is as follows: Figure 5 As shown. Among them, U r (s) is the input signal, U(s) is the control quantity, Y(s) is the output signal, D(s) is the external input disturbance, is the estimated value of the external input disturbance, P(s) is the actual model affected by the disturbance, and P n -1 (s) is P n (s) is the inverse of the nominal model, and Q(s) is the filter to be designed.

[0118] Depend on Figure 5 It can be seen that, with U r (s) and D(s) are inputs, then Y(s) can be expressed as:

[0119]

[0120] in

[0121]

[0122] In the formula, G dy (s) are the given input transfer function and disturbance transfer function respectively.

[0123] The disturbance observer can estimate not only the external disturbance but also the internal disturbance caused by model uncertainty. To show how the disturbance observer estimates the lumped disturbance consisting of the external and internal disturbances, Figure 6 Given Figure 5 The equivalent block diagram of the original block diagram in , where the lumped perturbation D l It can be expressed as:

[0124] D l (s) = P n -1 (s)P(s)D(s)+[P n -1 (s)P(s)-1]U(s)

[0125] Depend on Fig. 9 The estimated value of the disturbance can be obtained

[0126]

[0127] The lumped disturbance estimation error E d (s):

[0128]

[0129] Only when Q(s) is designed as a low-pass filter, that is, Lumped disturbance estimation error E d (s) will approach 0 over time, so we can get and Therefore, the design of the low-pass filter Q(s) is the key to the disturbance observer (DOB) so that the system can meet the required design performance indicators.

[0130] The designed low-pass filter Q(s) structure is binomial, and its structure is shown in the following formula:

[0131]

[0132] in

[0133]

[0134] In the formula, a Nk is the quadratic term coefficient, N is the order of the low-pass filter, NM is the relative order between the numerator and denominator of the low-pass filter, τ is the time constant, s is the system parameter, and k is the conventional coefficient.

[0135] Furthermore, in order to achieve P n -1 (s)Q(s) is regular, the relative order of the low-pass filter Q(s) must be greater than or equal to P n -1 A large relative order of the low-pass filter Q(s) will result in an excessively high amplitude, reduced robustness of the system near the resonant frequency, and a more complex structure. Therefore, the present invention designs the low-pass filter Q(s) as:

[0136]

[0137] The design of disturbance observer enables the system to perceive and compensate external disturbances in real time, thus improving the robustness and anti-interference ability of the system.

[0138] In order to further illustrate the beneficial effects of the present invention, that is, to verify whether the designed disturbance observer can effectively eliminate the influence of external disturbance and model uncertainty in a pneumatic control valve system based on quantitative feedback theory, the following is an implementation case of the present invention.

[0139] In the pneumatic control valve system, the stability and response speed of the valve position signal are crucial indicators. Under given nominal conditions, the system is expected to stabilize at the set valve position signal of 20mm. After the system reaches steady state, a step disturbance signal with an amplitude of 1 is suddenly applied at the 3rd second. We will verify the influence of the disturbance observer (DOB) on the valve position signal of the system through simulation comparison experiments, and further explore the improvement effect of the introduction of DOB on the system's anti-load disturbance performance.

[0140] Depend on Figure 7 It can be seen that when a step disturbance signal is added at the 3rd second, without DOB, the system may not respond in a timely and accurate manner, resulting in significant fluctuations or offsets in the valve position signal. In contrast, if the system is equipped with DOB, the disturbance observer will be able to monitor the disturbance signal in real time and adjust the control input accordingly to offset the impact of the disturbance, thereby making the valve position signal more stable.

[0141] Next, to further verify the effectiveness of DOB, we also add a sinusoidal disturbance signal at the 3rd second. Through simulation comparison experiments, we will verify the response of the system with and without DOB. Figure 8 It can be seen that when there is DOB, the valve position signal may recover to the vicinity of the set value faster and with a smaller fluctuation amplitude; while when there is no DOB, the valve position signal may have obvious overshoot and oscillation, and the adjustment time will also be prolonged.

[0142] Finally, under non-nominal conditions, the uncertainty of the system model may cause internal disturbances to affect the valve position signal. In order to evaluate whether DOB can eliminate the impact of uncertainty on the system, we will consider three indicators in the system model, namely parameters m0, k0, and b0, which fluctuate up and down by 10%. Fig. 9 It can be seen that the addition of DOB can eliminate the influence of uncertain factors on the system and ensure the rapidity and effectiveness of valve position signal tracking.

[0143] In summary, the introduction of DOB can not only reduce the valve position signal drop value caused by external disturbances in the system, but also effectively eliminate the impact of uncertainty on the system. At the same time, it also reduces the valve position signal recovery time, enhances the load disturbance suppression performance, and improves the control stability performance of the system.

[0144] Embodiment 2

[0145] like Fig.10 As shown, the present invention provides a design device for a pneumatic control valve control system based on QFT and DOB, which is used to implement the design method for a pneumatic control valve control system based on QFT and DOB of the first embodiment, specifically comprising:

[0146] The system model building module 100 is used to establish a mathematical model of the pneumatic control valve system by analyzing the working principle of the pneumatic control valve in view of the external interference and uncertainty factors of the pneumatic control valve in the industrial process;

[0147] The system analysis and design module 200 is used to perform system analysis and design on the established mathematical model of the pneumatic control valve system by using the principle of quantitative feedback theory;

[0148] A two-degree-of-freedom controller design and application module 300 is used to design a two-degree-of-freedom controller including a feedback controller and a prefilter, and apply it to a pneumatic control valve system. By adjusting the two-degree-of-freedom controller, the open-loop response curve of the system meets the performance requirements, including robust stability and tracking performance;

[0149] The disturbance observer introduction and application module 400 is used to consider the impact of equivalent disturbance on the system. By introducing the disturbance observer, the system can perceive and compensate for the equivalent disturbance in real time. The equivalent disturbance includes external disturbance and model uncertainty.

[0150] A design device for a pneumatic control valve control system based on QFT and DOB in this embodiment is used to implement the aforementioned design method for a pneumatic control valve control system based on QFT and DOB. Therefore, the specific implementation method of the design device for a pneumatic control valve control system based on QFT and DOB can be seen in the embodiment part of the design method for a pneumatic control valve control system based on QFT and DOB in the aforementioned text. For example, the system model building module 100, the system analysis and design module 200, the two-degree-of-freedom controller design and application module 300, and the interference observer introduction and application module 400 are respectively used to implement steps S1, S2, S3, and S4 in the aforementioned design method for a pneumatic control valve control system based on QFT and DOB. Therefore, its specific implementation method can refer to the description of the corresponding embodiments of each part. In order to avoid redundancy, it will not be repeated here.

[0151] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A design method for a pneumatic control valve control system based on QFT and DOB, characterized in that: include: Aiming at the external interference and uncertainty factors of pneumatic control valves in industrial processes, the mathematical model of pneumatic control valve system is established by analyzing the working principle of pneumatic control valves. The established mathematical model of pneumatic control valve system is systematically analyzed and designed using the principle of quantitative feedback theory. Design a two-degree-of-freedom controller including a feedback controller and a prefilter, and apply it to a pneumatic control valve system. By adjusting the two-degree-of-freedom controller, the open-loop response curve of the system meets the performance requirements, including robust stability and tracking performance. Considering the impact of equivalent disturbance on the system, by introducing a disturbance observer, the system can perceive and compensate for the equivalent disturbance in real time, wherein the equivalent disturbance includes external disturbance and model uncertainty; The disturbance observer is expressed as: in In the formula, G dy (s) are the given input transfer function and disturbance transfer function respectively; U r (s) is the input signal; Y(S) is the output signal; D(s) is the external input disturbance; P(s) is the actual model affected by the disturbance; Q(s) is the low-pass filter to be designed; P n (s) is the nominal model; The low-pass filter Q(s) is expressed as: in In the formula, a Nk is the quadratic term coefficient, N is the order of the low-pass filter, NM is the relative order between the numerator and denominator of the low-pass filter, τ is the time constant, s is the system parameter, and k is the conventional coefficient.

2. The design method of the pneumatic control valve control system based on QFT and DOB according to claim 1 is characterized in that: The uncertain factors include the wear of the moving parts of the actuator, the change of the elastic coefficient of the spring and the change of the internal friction damping.

3. The design method of a pneumatic control valve control system based on QFT and DOB according to claim 1 is characterized in that: The mathematical model of the pneumatic control valve system is expressed as: Where, G(s) represents the mathematical model of the pneumatic control valve system; G1(s) represents the transfer function of the intelligent positioner module; G2(s) represents the transfer function of the pneumatic diaphragm actuator; G3(s) represents the transfer function between the air chamber and the valve stem actuator; G4(s) represents the transfer function between the air chamber output force and the valve stem displacement; K, ω, s, ξ are all system parameters; T v =C ν R ν , R ν is the air resistance, C ν =V / K v , K v is the isothermal elastic modulus of the ideal gas, V is the volume of the gas before compression; A D is the effective area of ​​the air chamber diaphragm; m is the total mass of the actuator's moving part; k is the elastic coefficient of the internal telescopic spring of the actuator; and b is the internal friction damping of the actuator.

4. The design method of a pneumatic control valve control system based on QFT and DOB according to claim 1 is characterized in that: The method of using the principle of quantitative feedback theory to systematically analyze and design the mathematical model of the established pneumatic control valve system specifically includes: Design system robustness stability indicators: Where, L(jω) is the feedback controller to be designed; ω is the system parameter, and j is the imaginary unit; Design systems to track performance metrics: Where, T u (s) is the upper bound of tracking performance, T l (s) is the lower bound of tracking performance; A set of frequency points are selected, the system uncertainty model is calculated at each frequency point and an object template is drawn; then, a composite boundary curve formed by a robust stability boundary and a robust tracking boundary is drawn according to the stability index requirements.

5. The design method of a pneumatic control valve control system based on QFT and DOB according to claim 1 is characterized in that: The designed two-degree-of-freedom controller includes a feedback controller and a prefilter and is applied to a pneumatic control valve system. By adjusting the two-degree-of-freedom controller, the open-loop response curve of the system meets the performance requirements, including robust stability and tracking performance, specifically including: Design the controller: By adding gain, zero and pole to the nominal model, the low-frequency open-loop Nichols curve of the system is located above the response frequency point constraint boundary and as close to the boundary as possible; while the high-frequency amplitude and phase curves are located outside the robust stability boundary; Design the pre-filter: Make the closed-loop frequency response curve within the desired tracking boundary to meet the tracking performance requirements.

6. The design method of a pneumatic control valve control system based on QFT and DOB according to claim 1 is characterized in that: The disturbance observer is used to monitor the difference between the actual output of the controlled object and the output predicted by the model, and regards the difference as equivalent disturbance.

7. The design method of a pneumatic control valve control system based on QFT and DOB according to claim 1 is characterized in that: The relative order of the low-pass filter Q(s) is greater than or equal to P n -1 (s) relative order, where P n -1 (s) is the nominal model P n The inverse of (s).

8. A design device for a pneumatic control valve control system based on QFT and DOB, characterized in that: The system is used to implement the design method of a pneumatic control valve control system based on QFT and DOB according to any one of claims 1 to 7, specifically comprising: The system model building module is used to establish a mathematical model of the pneumatic control valve system by analyzing the working principle of the pneumatic control valve in view of the external interference and uncertainty factors of the pneumatic control valve in the industrial process; System analysis and design module, which is used to analyze and design the mathematical model of the established pneumatic control valve system using the principle of quantitative feedback theory; The two-degree-of-freedom controller design and application module is used to design a two-degree-of-freedom controller including a feedback controller and a prefilter, and apply it to a pneumatic control valve system. By adjusting the two-degree-of-freedom controller, the open-loop response curve of the system meets the performance requirements, including robust stability and tracking performance; The disturbance observer introduction and application module is used to consider the impact of equivalent disturbance on the system. By introducing the disturbance observer, the system can perceive and compensate for the equivalent disturbance in real time. The equivalent disturbance includes external disturbance and model uncertainty.

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