A vacuum pressure control method, system, device, and medium

Abstract

The application provides a vacuum pressure control method, system, device and medium, relates to the field of vacuum pressure control, and obtains the running state information of a vacuum pressure system, so as to predict the corresponding preset observer bandwidth of the vacuum pressure system according to the running state information, obtain system pressure estimation information and system total disturbance estimation information; subsequently, disturbance compensation adaptive adjustment is performed according to the system total disturbance estimation information and in combination with a preset disturbance compensation coefficient to obtain disturbance compensation information, and pressure control is performed according to the disturbance compensation information, in combination with the system total disturbance estimation information, the system pressure estimation information and the corresponding preset pressure control parameters of the vacuum pressure system, to obtain a pressure control result, so that accurate control of the vacuum pressure is realized, the dynamic response performance and the steady-state control precision of the system can be taken into account, and the problem that the prior art is difficult to simultaneously take into account the dynamic response performance and the steady-state control precision of the system in vacuum pressure control is solved.

Description

Technical Field

[0001] This application relates to the field of vacuum pressure control, and more specifically, to a vacuum pressure control method, system, device, and medium. Background Technology

[0002] In industrial production processes such as semiconductor processing and vacuum coating, vacuum pressure is a critical parameter, and its stability and precise control directly affect product quality and process stability. However, vacuum pressure control systems typically include multiple components such as butterfly valves, vacuum pumps, and sensors, which exhibit significant nonlinear characteristics and time-varying parameters during operation. Furthermore, vacuum pressure control systems are highly susceptible to various external disturbances, including load fluctuations, sudden changes in gas flow, and sensor noise. Therefore, high demands are placed on vacuum pressure control algorithms, requiring them to possess rapid response speed, strong anti-interference capabilities, and high-precision steady-state control.

[0003] Traditional proportional-integral-derivative (PID) control relies on an accurate system model, which is prone to problems such as pressure overshoot, slow regulation, and large steady-state fluctuations under complex disturbances, making it difficult to meet the requirements of high-precision vacuum pressure control. Linear Active Disturbance Rejection Control (LADRC) technology, with its unique Linear Extended State Observer (LESO), can observe and effectively compensate for the total disturbance experienced by the system in real time. It has the advantages of simple structure, strong disturbance rejection capability, and no reliance on an accurate model, and is therefore increasingly used in vacuum pressure control scenarios. However, the standard LADRC method uses a fixed disturbance compensation strategy, meaning it cannot adaptively adjust according to the magnitude of the actual disturbance, which has significant shortcomings in practical applications.

[0004] To address the aforementioned issues, existing technologies urgently need improvement. Summary of the Invention

[0005] In view of this, this application provides a vacuum pressure control method, system, device and medium to solve the problem that the existing technology is unable to simultaneously take into account the dynamic response performance and steady-state control accuracy of the system in vacuum pressure control.

[0006] In a first aspect, this application provides a vacuum pressure control method, comprising: acquiring operating status information of a vacuum pressure system; predicting based on the operating status information and a preset observer bandwidth corresponding to the vacuum pressure system to obtain system pressure estimation information and system total disturbance estimation information; adaptively adjusting disturbance compensation based on the system total disturbance estimation information and a preset disturbance compensation coefficient to obtain disturbance compensation information; and performing pressure control based on the disturbance compensation information, the system total disturbance estimation information, the system pressure estimation information, and preset pressure control parameters corresponding to the vacuum pressure system to obtain the pressure control result corresponding to the vacuum pressure system.

[0007] Through the above scheme, this embodiment of the application obtains the operating status information of the vacuum pressure system, and based on the operating status information, combined with the preset observer bandwidth corresponding to the vacuum pressure system, makes predictions to obtain system pressure estimation information and system total disturbance estimation information; subsequently, based on the system total disturbance estimation information, combined with the preset disturbance compensation coefficient, the disturbance compensation is adaptively adjusted to obtain disturbance compensation information; based on the disturbance compensation information, combined with the system total disturbance estimation information, system pressure estimation information, and the preset pressure control parameters corresponding to the vacuum pressure system, pressure control is performed, which can adaptively adjust the disturbance compensation according to the actual disturbance magnitude, realize precise control of vacuum pressure, and thus take into account both the dynamic response performance and steady-state control accuracy of the system.

[0008] Optionally, based on the total system disturbance estimation information and combined with the preset disturbance compensation coefficient, the disturbance compensation is adaptively adjusted to obtain the disturbance compensation information, including: using the total system disturbance estimation information to determine the disturbance intensity coefficient of the vacuum pressure system; and based on the disturbance intensity coefficient and combined with the disturbance compensation coefficient, the disturbance compensation intensity is corrected to obtain the disturbance compensation information.

[0009] The above scheme uses the total system disturbance estimation information to determine the disturbance intensity coefficient. Based on this disturbance intensity coefficient, the disturbance compensation intensity is corrected in combination with the disturbance compensation coefficient, thereby achieving adaptive adjustment of disturbance compensation.

[0010] Optionally, the disturbance intensity coefficient of the vacuum pressure system is determined using the total disturbance estimation information of the system, including: extracting the total disturbance estimate from the total disturbance estimation information of the system; and determining the absolute value of the total disturbance estimate as the disturbance intensity coefficient.

[0011] The above scheme allows for the precise determination of the disturbance intensity coefficient by extracting the absolute value of the total disturbance estimate of the system, so that the disturbance compensation can be adaptively adjusted based on the disturbance intensity coefficient in the future.

[0012] Optionally, based on the disturbance intensity coefficient and combined with the disturbance compensation coefficient, the disturbance compensation intensity is corrected to obtain disturbance compensation information, including: using the disturbance intensity coefficient and dividing it by the sum of the disturbance intensity coefficient and the disturbance compensation coefficient to obtain the disturbance compensation weight; based on the disturbance compensation weight, using the total system disturbance estimation information, the disturbance compensation intensity is dynamically corrected to obtain disturbance compensation information.

[0013] The above scheme allows us to obtain the disturbance compensation weight by dividing the disturbance intensity coefficient by the sum of the disturbance intensity coefficient and the disturbance compensation coefficient. By calculating the disturbance compensation weight and using the total disturbance estimation information of the system, we can dynamically correct the disturbance compensation intensity, thereby achieving dynamic correction of the disturbance compensation intensity.

[0014] Optionally, the total system disturbance estimation information in this embodiment includes a total system disturbance estimate. Based on the disturbance compensation weight, the disturbance compensation intensity is dynamically corrected using the total system disturbance estimation information to obtain disturbance compensation information, including: multiplying the disturbance compensation weight by the total system disturbance estimate to obtain a weighted compensation amount; and determining the weighted compensation amount as the disturbance compensation information.

[0015] The above scheme allows us to multiply the disturbance compensation weight by the estimated total disturbance of the system to obtain the weighted compensation amount, which in turn allows us to accurately obtain disturbance compensation information.

[0016] Optionally, pressure control is performed based on disturbance compensation information, combined with system total disturbance estimation information, system pressure estimation information, and preset pressure control parameters corresponding to the vacuum pressure system, to obtain the pressure control result corresponding to the vacuum pressure system. This includes: obtaining preset pressure control parameters corresponding to the vacuum pressure system, including vacuum pressure setpoints; determining pressure tracking error using vacuum pressure setpoints and system pressure estimation information; performing active disturbance rejection pressure control based on disturbance compensation information and pressure tracking error to obtain pressure control quantity; and controlling the gas flow area of ​​the vacuum pressure system based on the pressure control quantity to obtain the pressure control result.

[0017] The above scheme can be used to determine the pressure tracking error by using the vacuum pressure setpoint and system pressure estimation information. Based on the disturbance compensation information and the pressure tracking error, active disturbance rejection pressure control can be performed, thereby achieving precise control of the vacuum pressure system through active disturbance rejection pressure control.

[0018] Optionally, the pressure tracking error is determined using the vacuum pressure setpoint and system pressure estimation information, including: extracting the vacuum pressure estimate of the vacuum pressure system from the system pressure estimation information; and determining the pressure tracking error using the difference between the vacuum pressure setpoint and the vacuum pressure estimate.

[0019] Optionally, the system pressure estimation information includes an estimated system pressure change rate, and the pressure control parameters also include a preset controller bandwidth and control gain corresponding to the vacuum pressure system. Based on disturbance compensation information and combined with the pressure tracking error, active disturbance rejection pressure control is performed to obtain the pressure control quantity, including: calculating the first control quantity corresponding to the pressure tracking error using the pressure tracking error and the controller bandwidth; calculating the second control quantity corresponding to the estimated system pressure change rate using the estimated system pressure change rate and the controller bandwidth; and performing active disturbance rejection control based on the first and second control quantities, combined with dynamic compensation information and control gain, to obtain the pressure control quantity.

[0020] Secondly, this application also proposes a vacuum pressure control system, comprising: The information acquisition module is used to acquire the operating status information of the vacuum pressure control system; The prediction module is used to make predictions based on the operating status information and the preset observer bandwidth of the vacuum pressure control system to obtain system pressure estimation information and system total disturbance estimation information. An adaptive adjustment module is used to perform adaptive adjustment of disturbance compensation based on the total disturbance estimation information of the system and a preset disturbance compensation coefficient to obtain disturbance compensation information. The pressure control module is used to perform pressure control based on the disturbance compensation information, combined with the total system disturbance estimation information, the system pressure estimation information, and the preset pressure control parameters of the vacuum pressure control system, to obtain the pressure control result of the vacuum pressure control system.

[0021] Thirdly, this application provides a vacuum pressure control device, comprising: a processor and a memory; wherein the memory is used to store a computer program; and the processor is used to execute the program stored in the memory to implement the steps of the vacuum pressure control method as described in any one of the first aspects of this application.

[0022] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the vacuum pressure control method as described in any of the first aspects of this application above.

[0023] In summary, the vacuum pressure control method, system, device, and medium provided in this application acquire the operating status information of the vacuum pressure system. Based on this operating status information and a preset observer bandwidth corresponding to the vacuum pressure system, predictions are made to obtain system pressure estimation information and system total disturbance estimation information. Subsequently, based on the system total disturbance estimation information and a preset disturbance compensation coefficient, disturbance compensation is adaptively adjusted. This allows for adaptive adjustment of disturbance compensation according to the actual disturbance magnitude, yielding disturbance compensation information. Based on this disturbance compensation information, combined with the system total disturbance estimation information, system pressure estimation information, and preset pressure control parameters corresponding to the vacuum pressure system, pressure control is performed to achieve precise vacuum pressure control and obtain the corresponding pressure control result for the vacuum pressure system. This approach balances the dynamic response performance and steady-state control accuracy of the system, effectively solving the problems of response lag under strong disturbances and noise amplification under weak disturbances. It significantly improves the dynamic performance and steady-state accuracy of vacuum pressure control, meeting the pressure control accuracy requirements. Attached Figure Description

[0024] Figure 1 This is a schematic flowchart illustrating the steps of a vacuum pressure control method provided in an embodiment of this application. Figure 2 A structural block diagram of a vacuum pressure control system provided in an embodiment of this application; Figure 3 This is a structural block diagram of a vacuum pressure control device provided in an embodiment of this application. Detailed Implementation

[0025] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0026] In many high-precision industrial manufacturing fields, such as plasma etching of semiconductor chips, vacuum coating of optical lenses, and physical vapor deposition of advanced materials, the pressure of the vacuum environment is an extremely critical and sensitive process parameter. Even slight fluctuations in vacuum pressure can directly affect the quality of the final product, yield, and the stability of the process. A typical vacuum pressure control system usually consists of a vacuum chamber, a pumping unit such as a molecular or mechanical pump, a butterfly valve for regulating gas flow, and a pressure sensor for real-time monitoring of the chamber pressure. In actual operation, this entire system exhibits significant nonlinear characteristics; its response behavior is not a simple linear relationship. Furthermore, the parameters change with factors such as operating time and temperature variations, exhibiting time-varying characteristics. Adding to the complexity, it is continuously subjected to various internal and external disturbances, such as load fluctuations caused by the sudden introduction of large amounts of reactive gas during the process, sudden changes in gas flow caused by the slow release of gas from the vacuum chamber wall material under temperature changes, and the inherent measurement noise of the pressure sensor itself. These complex dynamic characteristics and varied disturbances place extremely stringent demands on the control algorithm's rapid response capability, strong anti-interference capability, and control accuracy under steady-state conditions.

[0027] Traditional PID control, while simple in structure and widely used, relies heavily on an accurate mathematical model for its design. However, for the complex vacuum pressure described above, establishing a mathematical model that accurately describes all its dynamic characteristics is extremely difficult, even impractical. Therefore, when faced with strong disturbances, PID controllers based on inaccurate models often perform poorly, potentially leading to severe pressure overshoot (the pressure value exceeds the setpoint before being pulled back), or an abnormally slow adjustment process that fails to reach the set pressure value for an extended period. Even after reaching steady state, the pressure value may continue to fluctuate slightly around the setpoint, failing to meet the pressure stability requirements of high-precision processes.

[0028] To overcome the limitations of traditional PID control, LADRC technology has been introduced into the field of vacuum pressure control. A core advantage of this LADRC method lies in its internal linear extended state observer. This observer can treat all unknown disturbances acting on the system, including external load changes and internal parameter perturbations, as a total disturbance in real time and accurately estimate it. Based on this estimated total disturbance, the controller can actively compensate. This design makes the LADRC control method independent of a precise controlled object model, possessing inherently strong anti-interference capabilities and good adaptability. However, standard linear active disturbance rejection control also reveals an inherent flaw in practical applications: its disturbance compensation strategy is fixed. That is, the standard LADRC method uses a fixed disturbance compensation strategy; once the controller parameters are set, the compensation magnitude is constant and cannot adaptively adjust according to the actual disturbance magnitude. This fixed compensation strategy becomes inadequate when facing dynamically changing disturbances.

[0029] Specifically, when the vacuum is subjected to a severe and significant disturbance, such as a sudden large injection of process gas, the fixed compensation level may be insufficient, leading to a lag in compensation, a slower pressure response, and a significant increase in the tracking error between the actual pressure value and the set value. Conversely, when in a stable operating state, or when only weak disturbances exist, such as only the sensor's own measurement noise, this fixed compensation level may be too strong. In this case, the controller will treat the weak measurement noise as a real disturbance and compensate for it. This excessive compensation behavior will amplify the impact of the noise, causing unnecessary micro-vibrations in the control output, which in turn will cause small, high-frequency oscillations in the vacuum pressure near the set point.

[0030] Therefore, the standard LADRC method, which employs a fixed disturbance compensation strategy, has significant shortcomings in practical applications: when the system is subjected to strong disturbances, the fixed compensation level may be insufficient, leading to pressure response lag and increased tracking error; conversely, when the system is in a steady state or subjected to only weak disturbances, excessive compensation may amplify measurement noise and cause small pressure oscillations. This makes it difficult for the standard LADRC to simultaneously achieve both dynamic response performance and steady-state control accuracy.

[0031] Currently, most improvements to LADRC (Laser-Dependent Control) improve performance by adjusting the observer bandwidth or increasing the complexity of the control structure. However, these methods often significantly increase the computational load of the algorithm, leading to a marked increase in the difficulty of parameter tuning, making them unsuitable for real-time operation on embedded controllers with limited computing resources. Furthermore, overly complex control structures can reduce system reliability, failing to meet the engineering requirements of long-term stability and low-cost deployment in vacuum systems. Therefore, these improvements fail to truly solve the core problem of balancing dynamic performance and steady-state accuracy in vacuum pressure control.

[0032] Based on the above, this application provides a vacuum pressure control method, system, device, and medium to solve the problem that existing technologies cannot simultaneously take into account the dynamic response performance and steady-state control accuracy of the system in vacuum pressure control.

[0033] Reference Figure 1 The diagram illustrates a step flow of a vacuum pressure control method provided in an embodiment of this application. Figure 1 As shown in the embodiments of this application, the vacuum pressure control method specifically includes the following steps: Step 110: Obtain the operating status information of the vacuum pressure system; The operating status information of the vacuum pressure system refers to various information related to the operating status of the vacuum pressure system. Specifically, it may include various real-time data used to describe the current working status of the vacuum pressure during the vacuum pressure control process, such as, but not limited to, the actual vacuum pressure of the vacuum pressure system. This application embodiment does not limit this.

[0034] For example, the actual vacuum pressure of the vacuum pressure system can be the real-time pressure value inside the chamber continuously collected with extremely high time resolution by a pressure sensor connected to the vacuum chamber. This application embodiment does not impose specific restrictions on the method of obtaining the operating status information of the vacuum pressure system.

[0035] Step 120: Based on the operating status information and combined with the preset observer bandwidth corresponding to the vacuum pressure system, prediction is performed to obtain system pressure estimation information and system total disturbance estimation information; In this context, the preset observer bandwidth for the vacuum pressure system refers to a key parameter set in advance for the linear extended state observer in the vacuum pressure control method. This parameter is set before the system starts operating and remains unchanged throughout the control process. It determines the convergence speed of the observer's estimation of the system state and disturbances, as well as its ability to suppress measurement noise. For example, in the LADRC framework, the observer bandwidth, as a fixed parameter of the linear extended state observer, can be understood as the speed of the observer's dynamic response, that is, the sensitivity of the observer in tracking changes in the actual system state and disturbances.

[0036] System pressure estimation information refers to information related to the system pressure state that is estimated in real time through prediction. It may include, but is not limited to, system state information such as vacuum pressure estimate and pressure change rate estimate. This application embodiment does not limit this.

[0037] The total system disturbance estimation information refers to the information related to system disturbances estimated in real time through prediction. Specifically, it can be used to determine the magnitude of system disturbances, and may include, but is not limited to, the total system disturbance estimation value. This application embodiment does not limit this.

[0038] Specifically, after obtaining the operating status information of the vacuum pressure system, this embodiment of the application can predict the vacuum pressure state of the vacuum pressure system based on the operating status information and the preset observer bandwidth corresponding to the vacuum pressure system. For example, a fixed observer bandwidth can be used to perform linear active disturbance rejection control (ADC) calculation on the obtained operating status information. Thus, the system pressure information and system disturbance information can be estimated in real time and accurately through ADC calculation. The real-time estimated system pressure information can be used as the system pressure estimation information, and the real-time estimated total disturbance information can be determined as the system total disturbance estimation information. This provides key input data for subsequent disturbance compensation adaptive adjustment and pressure control, thereby effectively dealing with the complexity and uncertainty in vacuum pressure control and simplifying algorithm deployment.

[0039] Step 130: Based on the total system disturbance estimation information and combined with the preset disturbance compensation coefficient, perform adaptive adjustment of disturbance compensation to obtain disturbance compensation information; Specifically, after obtaining the total system disturbance estimation information, this embodiment of the application can use the total system disturbance estimation information to determine the current disturbance magnitude of the vacuum pressure system. Based on the current disturbance magnitude, combined with a preset disturbance compensation coefficient, the disturbance compensation can be adaptively adjusted. This allows the disturbance compensation to be automatically adjusted according to the system disturbance magnitude, achieving dynamic adjustment of the disturbance compensation and obtaining disturbance compensation information. This information can then be used to control the pressure and achieve adaptive disturbance compensation.

[0040] The preset disturbance compensation coefficient refers to a compensation proportional coefficient pre-set in the vacuum pressure control method. This coefficient, as a pre-defined compensation proportional factor, is determined before the control process begins. In the subsequent adaptive disturbance compensation adjustment stage, it is combined with the real-time determined total system disturbance estimate to jointly correct the disturbance compensation intensity, allowing for dynamic determination of the appropriate compensation intensity based on the magnitude of the current disturbance. If a severe disturbance is detected, adaptive disturbance compensation adjustment based on the total system disturbance estimate and the preset disturbance compensation coefficient can enhance the compensation strength for rapid suppression. If a weak disturbance or steady-state noise is detected, adaptive disturbance compensation adjustment based on the total system disturbance estimate and the preset disturbance compensation coefficient can weaken the compensation strength to avoid overreacting to noise. This solves the problem in existing technologies where fixed disturbance compensation strategies make it difficult to simultaneously consider the system's dynamic response performance and steady-state control accuracy in vacuum pressure control.

[0041] Step 140: Based on the disturbance compensation information, combined with the total system disturbance estimation information, the system pressure estimation information, and the preset pressure control parameters corresponding to the vacuum pressure system, pressure control is performed to obtain the pressure control result corresponding to the vacuum pressure system.

[0042] Specifically, in this embodiment of the application, after obtaining the disturbance compensation information generated by the disturbance compensation adaptive adjustment, active disturbance rejection pressure control processing can be performed based on the disturbance compensation information, combined with the total system disturbance estimation information, the system pressure estimation information, and the preset pressure control parameters corresponding to the vacuum pressure system, to obtain the final pressure control quantity. Pressure control can be performed according to the pressure control quantity. For example, the gas flow area of ​​the vacuum pressure system can be adjusted according to the pressure control quantity to adjust the vacuum pressure, thereby achieving effective control of the vacuum pressure and obtaining the pressure control result corresponding to the vacuum pressure system.

[0043] In summary, the vacuum pressure control method provided in this application obtains the operating status information of the vacuum pressure system, and based on this operating status information and the corresponding preset observer bandwidth, predicts and obtains system pressure estimation information and system total disturbance estimation information. Subsequently, based on the system total disturbance estimation information and the preset disturbance compensation coefficient, adaptive disturbance compensation adjustment is performed to adjust the disturbance compensation according to the actual disturbance magnitude, thereby obtaining disturbance compensation information. Then, based on the disturbance compensation information, combined with the system total disturbance estimation information, system pressure estimation information, and the corresponding preset pressure control parameters of the vacuum pressure system, pressure control is performed to adaptively adjust the control quantity of vacuum pressure according to the actual disturbance magnitude, thereby achieving precise control of vacuum pressure. This method can balance the dynamic response performance and steady-state control accuracy of the system, thus solving the problem that existing technologies cannot simultaneously balance the dynamic response performance and steady-state control accuracy of the system in vacuum pressure control.

[0044] To facilitate understanding of the embodiments of this application, the following will provide exemplary descriptions in conjunction with the accompanying drawings and specific examples, but these specific examples do not constitute a limitation on the embodiments of this application.

[0045] As a specific implementation of this application, in order to accurately obtain the vacuum pressure state and total disturbance information to support subsequent adaptive control decisions, while avoiding increasing the computational load and parameter tuning difficulty of the algorithm, a lightweight improvement can be made to the standard linear active disturbance rejection control framework to address the nonlinear, variable, and time-varying characteristics of the vacuum pressure control system. This results in the construction of a disturbance adaptive weighted LADRC vacuum pressure control method, which retains the standard LADRC linear structure throughout, has low computational load, and is compatible with embedded vacuum controllers. The specific implementation steps are as follows: First, the vacuum pressure system is equivalent to a second-order controlled object. The third-order linear extended state observer (LESO) is used to estimate the system state information and the total system disturbance estimate in real time. The real-time estimated system state information is used as the system pressure estimate information, and the estimated total system disturbance estimate is used as the total system disturbance estimate information.

[0046] For example, a vacuum pressure system can be equivalent to a second-order controlled object, and its mathematical model is as follows: ,in, Used to represent actual vacuum pressure output The butterfly valve control quantity used to indicate the vacuum pressure system can be used to adjust the gas flow area in order to adjust the vacuum pressure value of the vacuum pressure system. This refers to the total system disturbance, specifically the magnitude of the total disturbance in a vacuum pressure system. This is the control gain for the vacuum pressure system.

[0047] In addition, a third-order linear extended state observer (LESO) can be used to estimate the system state and total disturbance in real time, thereby providing the estimated vacuum pressure value. and estimated rate of change of pressure This information serves as a system stress estimation tool, and the estimated total system disturbance value can be used as a reference. This serves as an estimate of the total system disturbance.

[0048] As an example of this application, after obtaining the operating status information of the vacuum pressure system, the actual vacuum pressure output of the system can be determined using this operating status information. If the obtained operating status information includes the butterfly valve control quantity of the vacuum pressure system Control gain and total system disturbance In this case, the butterfly valve control quantity can be based on the vacuum pressure system. Control gain and total system disturbance Determine the actual vacuum pressure output of the system. Then, based on the actual vacuum pressure output of the system... Using a third-order linear extended state observer, a vacuum pressure system is employed with a preset observer bandwidth. butterfly valve control quantity of vacuum pressure system Control gain Real-time estimation of system state information and total system disturbance estimate The preset estimation formula for this third-order linear extended state observer is as follows: ; in, This is a vacuum pressure estimate. Compared to the raw data measured directly by the sensor, this vacuum pressure estimate can better filter out noise and provide a smoother pressure feedback that is closer to the real physical state. Vacuum pressure estimate The first derivative is used to represent the vacuum pressure estimate. The rate of change; As an estimate of the rate of change of pressure, it can reflect the trend of pressure change and provide the possibility for predictive control; The estimated rate of change of pressure The first derivative is used to represent the estimated rate of pressure change. The rate of change; This is the total disturbance estimate of the system, specifically the total disturbance estimate from the third-order LESO output; The estimated total disturbance of the system The first derivative is used to represent the estimate of the total system disturbance. The rate of change; The observer bandwidth is fixed and requires no dynamic adjustment, meaning that online adjustment of the observer bandwidth is unnecessary during operation. This method of using a vacuum pressure system corresponding to a preset fixed observer bandwidth for prediction greatly simplifies the structure of the prediction algorithm, reduces the computational burden, and makes the entire control method highly suitable for efficient operation on embedded industrial controllers with limited computing resources. It also reduces the complexity and difficulty of parameter tuning.

[0049] Next, based on the total system disturbance estimate, we proceed to the most innovative aspect of the proposed technical solution: adaptive adjustment of disturbance compensation. Specifically, traditional linear active disturbance rejection control (AID) directly uses the entire estimated total disturbance value for compensation; however, the method in this application introduces an intelligent adjustment mechanism. Based on the total system disturbance estimate and a preset disturbance compensation coefficient, it adaptively adjusts the disturbance compensation. For example, it can adjust the total system disturbance estimate output by LESO. By combining a preset disturbance compensation coefficient, the controller performs an adaptive adjustment of the disturbance compensation, ultimately obtaining dynamically changing disturbance compensation information. The core idea of ​​this adjustment process is to dynamically determine the appropriate compensation strength based on the magnitude of the current disturbance. If a severe, strong disturbance is detected, the adjustment mechanism will increase the compensation strength to achieve rapid suppression; if a weak disturbance or steady-state noise is detected, the adjustment mechanism will decrease the compensation strength to avoid overreacting to noise.

[0050] The preset disturbance compensation coefficient, a pre-defined compensation ratio factor, can be a dimensionless constant, such as 1. It works in conjunction with the real-time calculated disturbance intensity coefficient to correct the disturbance compensation intensity. The real-time calculated disturbance intensity coefficient refers to the system disturbance intensity coefficient determined based on the total system disturbance estimation information. This coefficient, as a real-time characterization of the magnitude of disturbances in the vacuum pressure system, can be used to quickly distinguish between strong disturbances such as sudden load changes and flow fluctuations, and weak disturbances such as steady-state drift and sensor noise.

[0051] In an optional embodiment of this application, based on the total system disturbance estimation information and a preset disturbance compensation coefficient, adaptive adjustment of disturbance compensation is performed to obtain disturbance compensation information. Specifically, this may include: using the total system disturbance estimation information to determine the disturbance intensity coefficient of the vacuum pressure system; and based on the disturbance intensity coefficient and the disturbance compensation coefficient, performing disturbance compensation intensity correction to obtain the disturbance compensation information. Specifically, in order to quantify the severity of the disturbance currently experienced by the vacuum pressure system, this embodiment can extract an index that intuitively reflects the magnitude of the disturbance from the total system disturbance estimation information output by the observer. This index is referred to as the disturbance intensity coefficient in this application. The calculation of this disturbance intensity coefficient is the foundation of the entire adaptive mechanism, providing a quantitative and real-time basis for subsequent compensation intensity correction. After determining the real-time disturbance intensity coefficient, the compensation intensity can be dynamically corrected based on this disturbance intensity coefficient and a preset disturbance compensation coefficient used to adjust the sensitivity of the adaptive law. This correction process generates the final disturbance compensation information used for the control law. In this way, the intensity of disturbance compensation is no longer constant, but can be intelligently and adaptively adjusted according to the magnitude of the real-time disturbance, thereby achieving differentiated processing of disturbances of different intensities.

[0052] Optionally, the process of determining the disturbance intensity coefficient of the vacuum pressure system using the total system disturbance estimation information may specifically include: extracting the total system disturbance estimate from the total system disturbance estimation information; and determining the absolute value of the total system disturbance estimate as the disturbance intensity coefficient. Specifically, considering that the core content of the total system disturbance estimation information is the total system disturbance estimate output in real time by the linearly extended state observer, this value directly reflects the magnitude and direction of the currently acting equivalent total disturbance. To focus only on the magnitude of the disturbance and not its direction—that is, whether it is a positive or negative disturbance, only the degree of deviation from the normal state is measured—this embodiment of the application directly extracts this total system disturbance estimate and calculates its absolute value, defining the absolute value of the total system disturbance estimate as the disturbance intensity coefficient. This is a very simple and efficient method for quantifying disturbance intensity. For example, based on the total system disturbance estimate output by LESO... It can be calculated according to the preset disturbance intensity coefficient formula. Calculate the disturbance intensity coefficient To estimate the absolute value of the total system disturbance It is directly determined as the disturbance intensity coefficient. The advantage of this approach is that the calculation is extremely simple, consumes almost no additional computing resources, and can very effectively characterize the intensity of the disturbance. A large absolute value clearly indicates that a strong disturbance such as a sudden load change or flow fluctuation is occurring; while a very small absolute value indicates that the situation is in a steady state or that it is only subject to a weak disturbance such as sensor noise.

[0053] Optionally, to achieve dynamic correction of the compensation intensity, embodiments of this application can design an adaptive weighting law based on the disturbance intensity coefficient. Using the disturbance intensity coefficient, the corresponding disturbance compensation weight is calculated according to the adaptive weighting law. Based on this disturbance compensation weight, the system's total disturbance estimation information is used to dynamically correct the disturbance compensation intensity, resulting in the final disturbance compensation information. In an optional embodiment of this application, the disturbance compensation intensity correction based on the disturbance intensity coefficient and the disturbance compensation coefficient to obtain the disturbance compensation information may specifically include the following sub-steps: Sub-step S11: The disturbance intensity coefficient is divided by the sum of the disturbance intensity coefficient and the disturbance compensation coefficient to obtain the disturbance compensation weight. Sub-step S12: Based on the disturbance compensation weight, the disturbance compensation intensity is dynamically corrected using the total system disturbance estimation information to obtain the disturbance compensation information.

[0054] Specifically, in order to achieve dynamic correction of the compensation intensity, after calculating the disturbance intensity coefficient, the present application embodiment can execute an adaptive weighting law calculation formula through the controller to determine the disturbance compensation weight using the currently calculated disturbance intensity coefficient, thereby achieving adaptive adjustment of the disturbance compensation weight. Through the adaptive adjustment of the disturbance compensation weight, dynamic correction of the dynamic compensation intensity is achieved, thereby significantly improving the steady-state control accuracy.

[0055] For example, taking a preset disturbance compensation coefficient of 1 as an example, that is, when the preset disturbance compensation coefficient is 1, in order to achieve dynamic correction of the disturbance compensation intensity, according to the disturbance intensity coefficient... An adaptive weighting law is designed, and its calculation formula is used to calculate the disturbance compensation weight corresponding to the current disturbance intensity coefficient. The calculation formula is as follows: Among them, the disturbance compensation weight The value of α ranges from greater than 0 to less than or equal to 1, i.e., 0 < α ≤ 1. When the system is subjected to a strong disturbance, the disturbance intensity coefficient... When the disturbance is relatively large, the disturbance compensation weight α approaches 1, at which point the compensation strength is increased; when the disturbance is weak or in steady state, the disturbance strength coefficient... When the value is relatively small, the disturbance compensation weight α approaches 0, which suppresses noise amplification.

[0056] As can be seen, after calculating the disturbance intensity coefficient, this embodiment of the application can use this disturbance intensity coefficient to divide the sum of the disturbance intensity coefficient and a preset disturbance compensation coefficient. The result of this calculation is defined as the disturbance compensation weight. This preset disturbance compensation coefficient can be understood as an adjustment parameter used to adjust the sensitivity of the weighting function to changes in disturbance intensity. Its value can be tuned once according to the specific application scenario and the desired control performance. The value of this disturbance compensation weight will dynamically change within a range between 0 and the preset disturbance compensation coefficient, depending on the magnitude of the disturbance intensity coefficient. Its behavior characteristics are very consistent with control requirements. When subjected to a strong disturbance, the value of the disturbance intensity coefficient will be large, and the calculated disturbance compensation weight will be very close to the preset disturbance compensation coefficient. When in a weak disturbance or steady state, the value of the disturbance intensity coefficient will be small, and the calculated disturbance compensation weight will approach 0. This nonlinear mapping relationship enables the disturbance compensation weight to act as a sensitive and intelligent adjustment factor. Thus, while maintaining the linear structure and low computational cost of LADRC, it solves the problem that traditional LADRC methods, which use fixed compensation strategies, are unable to simultaneously consider the dynamic response performance and steady-state control accuracy of the system in practical applications, thereby achieving a balance between dynamic performance and steady-state accuracy.

[0057] After obtaining the dynamically changing disturbance compensation weight, this embodiment of the application can use the controller to perform weighted correction on the original total disturbance estimate information output by the observer, thereby realizing dynamic adjustment of the disturbance compensation intensity and obtaining the final disturbance compensation information. Optionally, the system total disturbance estimate information in this embodiment of the application includes a system total disturbance estimate value. The step of dynamically correcting the disturbance compensation intensity based on the disturbance compensation weight and using the system total disturbance estimate information to obtain the disturbance compensation information can specifically include: multiplying the disturbance compensation weight by the system total disturbance estimate value to obtain a weighted compensation amount; and determining the weighted compensation amount as the disturbance compensation information.

[0058] For example, the controller can directly multiply the adaptively changing disturbance compensation weights calculated in the previous step by the total system disturbance estimate output by the linear extended state observer; the result of this multiplication is the weighted compensation amount. This weighted compensation amount is the intelligently adjusted disturbance compensation information that will ultimately be used in the pressure control law. In this way, when the disturbance is severe, because the disturbance compensation weight is close to 1, by multiplying this disturbance compensation weight (close to 1) by the estimated total disturbance of the system, the calculated weighted compensation amount is approximately equal to the original estimated total disturbance of the system. In the final pressure control law, this weighted compensation amount is used to offset the disturbance, thus achieving almost complete and powerful compensation. When the system is stable and the disturbance is weak, because the disturbance compensation weight is close to 0, the weighted compensation amount also becomes very small, that is, the calculated weighted compensation amount is significantly weakened. This means that the controller can largely ignore these weak disturbances that are judged as noise, making the final output pressure control amount exceptionally smooth, keeping the vacuum pressure value of the vacuum pressure system at an extremely stable position, thereby achieving precise control of the vacuum pressure and enabling rapid tracking and stable control of the vacuum pressure.

[0059] Finally, after generating adaptively adjusted disturbance compensation information, pressure control is performed based on this information, combined with the system total disturbance estimation information, system pressure estimation information, and the corresponding preset pressure control parameters of the vacuum pressure system. For example, linear active disturbance rejection control calculations can be performed based on the disturbance compensation information and the pressure tracking error of the vacuum pressure system to obtain the target control quantity. This target control quantity can then be used as the pressure control quantity and directly output to the vacuum butterfly valve actuator of the vacuum pressure system. The vacuum butterfly valve actuator adjusts the gas flow area according to the target control quantity, thereby controlling the gas flow area of ​​the vacuum pressure control system based on the target control quantity, achieving pressure control results, and realizing rapid tracking and stable control of vacuum pressure. The pressure tracking error of the vacuum pressure system can be determined using the system pressure estimation information and the corresponding preset pressure control parameters of the vacuum pressure system. For example, the vacuum pressure setpoint can be extracted from the corresponding preset pressure control parameters of the vacuum pressure system, and the pressure tracking error can be determined using the vacuum pressure setpoint and the system pressure estimation information.

[0060] Optionally, in this embodiment of the application, pressure control is performed based on the disturbance compensation information, combined with the system total disturbance estimation information, the system pressure estimation information, and the preset pressure control parameters corresponding to the vacuum pressure system, to obtain the pressure control result corresponding to the vacuum pressure system. Specifically, this includes: obtaining the preset pressure control parameters corresponding to the vacuum pressure system, wherein the pressure control parameters include a vacuum pressure setpoint; determining the pressure tracking error using the vacuum pressure setpoint and the system pressure estimation information; performing active disturbance rejection pressure control based on the disturbance compensation information and the pressure tracking error to obtain a pressure control quantity; and controlling the gas flow area of ​​the vacuum pressure system based on the pressure control quantity to obtain the pressure control result.

[0061] Specifically, the system pressure estimation information in this application embodiment includes the estimated vacuum pressure value and the estimated system pressure change rate of the vacuum pressure system. The pressure tracking error is determined using the vacuum pressure setpoint and the system pressure estimation information. Specifically, this may include: extracting the estimated vacuum pressure value of the vacuum pressure system from the system pressure estimation information; and then determining the pressure tracking error using the difference between the vacuum pressure setpoint and the estimated vacuum pressure value, such as subtracting the estimated vacuum pressure value from the setpoint to determine the difference between the setpoint and the estimated vacuum pressure value as the pressure tracking error.

[0062] In this embodiment of the application, after determining the pressure tracking error of the vacuum pressure control system, linear active disturbance rejection control calculations can be performed based on disturbance compensation information and the pressure tracking error to obtain the pressure control quantity. Thus, the gas flow area of ​​the vacuum pressure control system can be controlled based on the pressure control quantity to obtain the pressure control result.

[0063] Optionally, the pressure control parameters obtained in this embodiment may include not only the vacuum pressure setpoint, but also the preset controller bandwidth and control gain corresponding to the vacuum pressure system. After determining the pressure tracking error using the difference between the vacuum pressure setpoint and the estimated vacuum pressure, this embodiment can perform linear active disturbance rejection control (AID) calculations based on disturbance compensation information, combined with the pressure tracking error and the preset controller bandwidth corresponding to the vacuum system. For example, based on the control gain and the preset controller bandwidth, the AID can be solved using the disturbance compensation information and the pressure tracking error to obtain the final control quantity. This final control quantity can then be used as the pressure control quantity to control the gas flow area of ​​the vacuum pressure system, thereby achieving rapid tracking and stable control of the vacuum pressure. Among them, the controller bandwidth, as a core control parameter in linear active disturbance rejection control, can be set to a fixed value to avoid the computational burden and parameter tuning complexity caused by dynamic adjustment of the controller bandwidth. This retains the advantages of the standard LADRC structure being simple and having low computational load, making it more suitable for long-term stable and low-cost deployment on embedded vacuum controllers. This solves the problem of a significant increase in algorithm computation caused by the existing technology of improving the performance of vacuum pressure control system by dynamically adjusting the observer bandwidth, thus achieving "lightweight improvement".

[0064] Optionally, based on the disturbance compensation information and the pressure tracking error, active disturbance rejection pressure control is performed to obtain a pressure control quantity. Specifically, this may include: calculating a first control quantity corresponding to the pressure tracking error using the pressure tracking error and the controller bandwidth; calculating a second control quantity corresponding to the estimated system pressure change rate using the estimated system pressure change rate and the controller bandwidth; and performing active disturbance rejection control based on the first and second control quantities, combined with the disturbance compensation information and the control gain, to obtain the pressure control quantity. The first control quantity is used to eliminate the current static error; the second control quantity is used to perform advance control based on the pressure change trend to suppress overshoot and oscillation.

[0065] For example, when using a vacuum pressure setpoint Compared with vacuum pressure estimates The difference is used to determine the pressure tracking error. Then, pressure tracking error can be applied according to the pre-set LADRC control law. and controller bandwidth Calculations were performed to obtain the pressure tracking error. The corresponding first control quantity So that the first control quantity can be used subsequently. Eliminate the current static error of the vacuum pressure system; and use the estimated value of the system pressure change rate. and controller bandwidth Calculations were performed to obtain an estimate of the system pressure change rate. The corresponding second control quantity So that the second control quantity can be used later. By taking proactive measures based on the trend of pressure changes, overshoot and oscillation can be effectively suppressed.

[0066] Specifically, in this embodiment of the application, after obtaining the first control quantity and the second control quantity, active disturbance rejection control can be performed based on the first control quantity and the second control quantity, combined with the disturbance compensation information and the control gain. For example, when the disturbance compensation information is an adaptively weighted disturbance compensation quantity... In this case, the weighted disturbance compensation amount can be used. Substitute the preset LADRC control law to the disturbance compensation amount. Combining pressure tracking error The corresponding first control quantity and estimated system pressure change rate The corresponding second control quantity Generate the final control quantity This allows the final generated control quantity to be... As a pressure control quantity, the vacuum butterfly valve pressure is controlled according to the pressure control quantity, such as the control quantity The output is directly sent to the vacuum butterfly valve actuator, allowing the actuator to control the quantity accordingly. This adjusts the gas flow area to achieve rapid tracking and stable control of the vacuum pressure. The preset LADRC control law is as follows: ; Among them, controller bandwidth As a core control parameter in the LADRC control law, it can be set to a fixed value to avoid the computational burden and parameter tuning complexity caused by dynamic adjustment of the controller bandwidth. This solves the problem of a significant increase in algorithm computation caused by the existing technology of improving the performance of the vacuum pressure control system by dynamically adjusting the observer bandwidth, and achieves "lightweight improvement".

[0067] In summary, this embodiment of the application obtains the operating status information of the vacuum pressure system, and based on the operating status information and the preset observer bandwidth corresponding to the vacuum pressure system, makes predictions to obtain system pressure estimation information and system total disturbance estimation information. Subsequently, based on the system total disturbance estimation information and the preset disturbance compensation coefficient, disturbance compensation adaptive adjustment is performed to introduce a disturbance compensation adaptive adjustment mechanism, which can dynamically adjust the compensation intensity according to the magnitude of the actual disturbance. Furthermore, the LADRC control theory with disturbance rejection and decoupling functions is applied to the vacuum pressure control system, thus meeting the pressure control accuracy requirements.

[0068] Furthermore, even with a fixed controller bandwidth, vacuum pressure control using the vacuum pressure control method provided in this application embodiment can effectively balance dynamic response performance and steady-state control accuracy without increasing the complexity of dynamic adjustment of the controller bandwidth itself. This effectively solves the problems of response lag under strong disturbances and noise amplification under weak disturbances, significantly improving the dynamic performance and steady-state accuracy of vacuum pressure control. In other words, it solves the problem in the prior art where it is difficult to simultaneously balance the dynamic response performance and steady-state control accuracy of the system in vacuum pressure control due to the use of the standard LADRC fixed compensation strategy.

[0069] It should be noted that, for the sake of simplicity, the method embodiments are described as a series of actions. However, those skilled in the art should know that the embodiments of this application are not limited to the described order of actions, because according to the embodiments of this application, some steps may be performed in other orders or simultaneously.

[0070] Figure 2 This is a structural block diagram of a vacuum pressure control system provided in an embodiment of this application. Figure 2 As shown, the vacuum pressure control system provided in this application embodiment may specifically include the following modules: The information acquisition module 210 is used to acquire the operating status information of the vacuum pressure control system; Prediction module 220 is used to make predictions based on the operating status information and the preset observer bandwidth of the vacuum pressure control system to obtain system pressure estimation information and system total disturbance estimation information. The adaptive adjustment module 230 is used to perform adaptive adjustment of disturbance compensation based on the total disturbance estimation information of the system and in combination with the preset disturbance compensation coefficient, so as to obtain disturbance compensation information. The pressure control module 240 is used to perform pressure control based on the disturbance compensation information, combined with the total system disturbance estimation information, the system pressure estimation information, and the preset pressure control parameters of the vacuum pressure control system, to obtain the pressure control result of the vacuum pressure control system.

[0071] Optionally, the adaptive adjustment module 230 may specifically include the following sub-modules: The disturbance intensity coefficient submodule is used to determine the disturbance intensity coefficient of the vacuum pressure system using the total system disturbance estimation information; The compensation strength correction submodule is used to correct the disturbance compensation strength based on the disturbance strength coefficient and the disturbance compensation coefficient to obtain disturbance compensation information.

[0072] Optionally, the disturbance intensity coefficient submodule may specifically include the following units: The extraction unit is used to extract the total system disturbance estimate from the total system disturbance estimate information; The intensity coefficient determination unit is used to determine the absolute value of the total disturbance estimate of the system as the disturbance intensity coefficient.

[0073] Optionally, the compensation strength correction submodule may specifically include the following units: The compensation weight calculation unit is used to obtain the disturbance compensation weight by dividing the disturbance intensity coefficient by the sum of the disturbance intensity coefficient and the disturbance compensation coefficient. The dynamic correction calculation unit is used to dynamically correct the disturbance compensation intensity based on the disturbance compensation weight and the total disturbance estimation information of the system, so as to obtain the disturbance compensation information.

[0074] Optionally, the total system disturbance estimation information in this embodiment includes a total system disturbance estimation value. The dynamic correction calculation unit is specifically used to: multiply the disturbance compensation weight by the total system disturbance estimation value to obtain a weighted compensation amount; and determine the weighted compensation amount as disturbance compensation information.

[0075] Optionally, the pressure control module may specifically include the following sub-modules: The parameter acquisition submodule is used to acquire the preset pressure control parameters corresponding to the vacuum pressure system. The pressure control parameters include the vacuum pressure setpoint. The tracking error determination submodule is used to determine the pressure tracking error using the vacuum pressure setpoint and system pressure estimation information. The active disturbance rejection pressure control submodule is used to perform active disturbance rejection pressure control based on disturbance compensation information and pressure tracking error to obtain pressure control quantity; The gas flow area control module is used to control the gas flow area of ​​the vacuum pressure system based on the pressure control amount, thereby obtaining the pressure control result.

[0076] Optionally, the system pressure estimation information in this embodiment includes the vacuum pressure estimate and the system pressure change rate estimate of the vacuum pressure system. The tracking error determination submodule is specifically used to: determine the pressure tracking error by using the difference between the vacuum pressure setpoint and the vacuum pressure estimate. Optionally, the pressure control parameters in this embodiment of the application also include the preset controller bandwidth and control gain corresponding to the vacuum pressure system, and the active disturbance rejection pressure control submodule may specifically include the following units: The first control quantity calculation unit is used to calculate the first control quantity corresponding to the pressure tracking error using the pressure tracking error and the controller bandwidth. The second control quantity calculation unit is used to calculate the second control quantity corresponding to the estimated system pressure change rate using the system pressure change rate estimate and the controller bandwidth. The active disturbance rejection control unit is used to perform active disturbance rejection control based on the first control quantity and the second control quantity, combined with dynamic compensation information and control gain, to obtain the pressure control quantity.

[0077] It should be noted that the vacuum pressure control system provided in this application embodiment can execute the vacuum pressure control method provided in any of the above embodiments of this application, and has the corresponding functions and beneficial effects of the execution method.

[0078] In practical implementation, the aforementioned vacuum pressure control system can be integrated into electronic devices such as personal computers and servers. This allows the electronic device to act as a vacuum pressure control device, acquiring the operating status information of the vacuum pressure system. Based on this operating status information and a preset observer bandwidth corresponding to the vacuum pressure system, it can predict and obtain system pressure estimation information and total system disturbance estimation information. Then, based on the total system disturbance estimation information and a preset disturbance compensation coefficient, it can adaptively adjust disturbance compensation to achieve adaptive disturbance compensation. Furthermore, based on the disturbance compensation information, combined with the total system disturbance estimation information, system pressure estimation information, and preset pressure control parameters corresponding to the vacuum pressure system, it can perform pressure control, thereby achieving precise vacuum pressure control. It can also adaptively adjust disturbance compensation according to the actual disturbance magnitude, effectively solving the problems of response lag under strong disturbances and noise amplification under weak disturbances, significantly improving the dynamic performance and steady-state accuracy of vacuum pressure control.

[0079] like Figure 3 As shown in the figure, this application embodiment also provides a vacuum pressure control device 300, which includes a processor 310 and a memory 320. The memory 320 is used to store computer programs; when the processor 310 executes the computer program stored in the memory 320, it implements the steps of the vacuum pressure control method described in any of the above-described method embodiments of this application.

[0080] Specifically, the vacuum pressure control device 300 provided in this application embodiment serves as a control device in a vacuum pressure control system and is configured to implement the steps of the vacuum pressure control method described in any of the above embodiments of this application. By applying the LADRC control theory with anti-disturbance and decoupling functions to the vacuum pressure control system, the pressure control accuracy requirements are met, and disturbance adaptive compensation is achieved. The compensation intensity can be automatically adjusted according to the magnitude of the disturbance in the vacuum system, effectively solving the problems of response lag under strong disturbance and noise amplification under weak disturbance, and significantly improving the dynamic performance and steady-state accuracy of vacuum pressure control.

[0081] This application also provides a computer-readable storage medium having a computer program stored thereon, characterized in that, when the computer program is executed by a processor, it implements the steps of the vacuum pressure control method as described in any of the above-described method embodiments of this application.

[0082] It should be noted that the various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the embodiments of apparatus, devices, and storage media, since they are basically similar to the method embodiments, the descriptions are relatively simple, and relevant parts can be referred to the descriptions of the method embodiments.

[0083] In this document, relational terms such as “first” and “second” are used merely to distinguish one entity or operation from another, without necessarily requiring or implying any such actual relationship or order between these entities or operations. Furthermore, the terms “comprising,” “including,” or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase “comprising one…” does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0084] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0085] The above description is merely an embodiment of this application and is not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A vacuum pressure control method, characterized in that, include: Obtain the operating status information of the vacuum pressure system; Based on the operating status information, and combined with the preset observer bandwidth corresponding to the vacuum pressure system, prediction is performed to obtain system pressure estimation information and system total disturbance estimation information; Based on the total system disturbance estimation information and combined with the preset disturbance compensation coefficient, the disturbance compensation is adaptively adjusted to obtain the disturbance compensation information; Based on the disturbance compensation information, combined with the total system disturbance estimation information, the system pressure estimation information, and the preset pressure control parameters corresponding to the vacuum pressure system, pressure control is performed to obtain the pressure control result corresponding to the vacuum pressure system. The step of adaptively adjusting disturbance compensation based on the total system disturbance estimation information and a preset disturbance compensation coefficient to obtain disturbance compensation information includes: using the total system disturbance estimation information to determine the disturbance intensity coefficient of the vacuum pressure system; and based on the disturbance intensity coefficient and the disturbance compensation coefficient, performing disturbance compensation intensity correction to obtain the disturbance compensation information. The step of correcting the disturbance compensation intensity based on the disturbance intensity coefficient and the disturbance compensation coefficient to obtain the disturbance compensation information includes: dividing the disturbance intensity coefficient by the sum of the disturbance intensity coefficient and the disturbance compensation coefficient to obtain the disturbance compensation weight; and using the total system disturbance estimation information based on the disturbance compensation weight to dynamically correct the disturbance compensation intensity to obtain the disturbance compensation information. The step of performing pressure control based on the disturbance compensation information, combined with the system total disturbance estimation information, the system pressure estimation information, and the preset pressure control parameters corresponding to the vacuum pressure system, to obtain the pressure control result corresponding to the vacuum pressure system, includes: acquiring the preset pressure control parameters corresponding to the vacuum pressure system, the pressure control parameters including a vacuum pressure setpoint; determining the pressure tracking error using the vacuum pressure setpoint and the system pressure estimation information; performing active disturbance rejection pressure control based on the disturbance compensation information and the pressure tracking error to obtain a pressure control quantity; and controlling the gas flow area of ​​the vacuum pressure system based on the pressure control quantity to obtain the pressure control result.

2. The vacuum pressure control method according to claim 1, characterized in that, The step of determining the disturbance intensity coefficient of the vacuum pressure system using the total system disturbance estimation information includes: Extract the total system disturbance estimate from the total system disturbance estimate information; The absolute value of the total disturbance estimate of the system is determined as the disturbance intensity coefficient.

3. The vacuum pressure control method according to claim 1, characterized in that, The total system disturbance estimation information includes a total system disturbance estimate. The disturbance compensation information is obtained by dynamically correcting the disturbance compensation intensity based on the disturbance compensation weight and the total system disturbance estimation information, including: The weighted compensation amount is obtained by multiplying the disturbance compensation weight by the estimated total system disturbance. The weighted compensation amount is determined as the disturbance compensation information.

4. The vacuum pressure control method according to claim 1, characterized in that, The step of determining the pressure tracking error using the vacuum pressure setpoint and the system pressure estimation information includes: Extract the vacuum pressure estimate of the vacuum pressure system from the system pressure estimation information; The pressure tracking error is determined by the difference between the vacuum pressure setpoint and the vacuum pressure estimate.

5. The vacuum pressure control method according to claim 1, characterized in that, The system pressure estimation information includes an estimated system pressure change rate. The pressure control parameters also include the preset controller bandwidth and control gain corresponding to the vacuum pressure system. The active disturbance rejection pressure control based on the disturbance compensation information and the pressure tracking error yields the pressure control quantity, including: The first control variable corresponding to the pressure tracking error is obtained by calculating using the pressure tracking error and the controller bandwidth. The second control variable corresponding to the estimated system pressure change rate is obtained by using the estimated system pressure change rate and the controller bandwidth. Based on the first control quantity and the second control quantity, active disturbance rejection control is performed in combination with the disturbance compensation information and the control gain to obtain the pressure control quantity.

6. A vacuum pressure control system, characterized in that, include: The information acquisition module is used to acquire the operating status information of the vacuum pressure control system; The prediction module is used to make predictions based on the operating status information and the preset observer bandwidth of the vacuum pressure control system to obtain system pressure estimation information and system total disturbance estimation information. An adaptive adjustment module is used to perform adaptive adjustment of disturbance compensation based on the total disturbance estimation information of the system and a preset disturbance compensation coefficient to obtain disturbance compensation information. The pressure control module is used to perform pressure control based on the disturbance compensation information, combined with the total system disturbance estimation information, the system pressure estimation information, and the preset pressure control parameters of the vacuum pressure control system, to obtain the pressure control result of the vacuum pressure control system. The step of adaptively adjusting disturbance compensation based on the total system disturbance estimation information and a preset disturbance compensation coefficient to obtain disturbance compensation information includes: using the total system disturbance estimation information to determine the disturbance intensity coefficient of the vacuum pressure system; and based on the disturbance intensity coefficient and the disturbance compensation coefficient, performing disturbance compensation intensity correction to obtain the disturbance compensation information. The step of correcting the disturbance compensation intensity based on the disturbance intensity coefficient and the disturbance compensation coefficient to obtain the disturbance compensation information includes: dividing the disturbance intensity coefficient by the sum of the disturbance intensity coefficient and the disturbance compensation coefficient to obtain the disturbance compensation weight; and using the total system disturbance estimation information based on the disturbance compensation weight to dynamically correct the disturbance compensation intensity to obtain the disturbance compensation information. The step of performing pressure control based on the disturbance compensation information, combined with the system total disturbance estimation information, the system pressure estimation information, and the preset pressure control parameters corresponding to the vacuum pressure system, to obtain the pressure control result corresponding to the vacuum pressure system, includes: acquiring the preset pressure control parameters corresponding to the vacuum pressure system, the pressure control parameters including a vacuum pressure setpoint; determining the pressure tracking error using the vacuum pressure setpoint and the system pressure estimation information; performing active disturbance rejection pressure control based on the disturbance compensation information and the pressure tracking error to obtain a pressure control quantity; and controlling the gas flow area of ​​the vacuum pressure system based on the pressure control quantity to obtain the pressure control result.

7. A vacuum pressure control device, characterized in that, include: Processor and memory; The memory is used to store computer programs; When the processor executes the program stored in the memory, it implements the steps of the vacuum pressure control method as described in any one of claims 1-5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the vacuum pressure control method as described in any one of claims 1-5.

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