Temperature control method and system for chemical vapor deposition gas supply system

Abstract

The invention provides a temperature control method and system for a chemical vapor deposition gas supply system, and the method comprises the steps: dividing the chemical vapor deposition gas supply system into a plurality of temperature control regions, collecting the temperature data of each temperature control region, and carrying out the preprocessing of the collected temperature data; establishing a model library and a PID parameter setting rule library; performing offline model identification by adopting a step response method; selecting an initial model from a model library, performing online model identification by adopting a recursive least square method, and updating model parameters in real time; fusing the online model parameters with corresponding offline model parameters in a model library, and determining parameters of a self-adaptive PID controller of each temperature control area according to the fused model parameters; and the microcontroller automatically adjusts the output of the PID controller in each temperature control area according to the model identification result and the PID controller parameters, and controls the heating power of the heating device in the corresponding area according to the output of the PID controller in each temperature control area, thereby realizing the temperature control of each temperature control area.

Description

Technical Field

[0001] The present invention relates to the technical field of temperature control, and specifically, to a temperature control method and system for a chemical vapor deposition gas supply system. Background Art

[0002] The traditional PID control method, that is, according to the deviation between the set temperature and the actual temperature, through the operations of three links: proportional (P), integral (I), and derivative (D), outputs a control signal to adjust the power of the heater; in order to improve the performance of the traditional PID control, various improved PID algorithms and intelligent control methods have emerged, such as fuzzy logic control, neural network control, etc. These methods attempt to simulate human control experience to achieve the control of complex systems.

[0003] However, when the above-mentioned existing technologies are applied to the temperature control of a chemical vapor deposition (CVD) gas supply system, the following deficiencies or disadvantages exist: The traditional PID control usually does not rely on an accurate system model, or only uses a very simple model, and cannot accurately describe the complex dynamic characteristics of the CVD gas supply system. Moreover, its parameters are usually fixed or only adjusted manually, and cannot adapt to the influence of factors such as process parameter changes and equipment aging, making it difficult to achieve independent and precise control of multiple regions of the CVD gas supply system, lacking self-adaptability. When the system characteristics change, it is necessary to manually readjust the PID parameters, which is time-consuming and laborious; Although the improved PID algorithms have improved the performance of the traditional PID control to a certain extent, there are still problems such as inaccurate models and insufficient self-adaptability; while intelligent control methods (such as fuzzy logic control, neural network control) usually require a large amount of historical data for training, and the CVD process parameters change frequently, the data acquisition and model training costs are relatively high, and the design process of the controller lacks transparency, and the control effect is difficult to predict and explain. Summary of the Invention

[0004] Aiming at the deficiencies in the prior art, the purpose of the present invention is to provide a temperature control method and system for a chemical vapor deposition gas supply system to achieve precise temperature control of each temperature control region of the CVD gas supply system and improve temperature uniformity and stability.

[0005] To solve the above problems, the technical solution of the present invention is as follows:

[0006] A temperature control method for a chemical vapor deposition gas supply system, comprising the following steps:

[0007] Divide the chemical vapor deposition gas supply system into multiple temperature control regions, collect the temperature data of each temperature control region, and preprocess the collected temperature data;

[0008] Establish a model library and a PID parameter tuning rule library;

[0009] The step response method is used for offline model identification;

[0010] An initial model is selected from the model library, and the recursive least squares method is used for online model identification to update the model parameters in real time;

[0011] The online model parameters are fused with the corresponding offline model parameters in the model library, and based on the fused model parameters, the parameters of the adaptive PID controller for each temperature control region are determined;

[0012] The microcontroller automatically adjusts the output of the PID controller for each temperature control region according to the model identification result and the PID controller parameters, and controls the heating power of the heating device in the corresponding region according to the output of the PID controller for each temperature control region to achieve temperature control of each temperature control region.

[0013] Preferably, the step of dividing the chemical vapor deposition gas supply system into multiple temperature control regions, collecting the temperature data of each temperature control region, and preprocessing the collected temperature data specifically includes: dividing the chemical vapor deposition gas supply system into multiple temperature control regions along the gas flow direction, setting at least one temperature measurement module and one heating device in each temperature control region, collecting the data of the temperature measurement module in each temperature control region, and preprocessing the collected temperature data.

[0014] Preferably, the step of using the step response method for offline model identification specifically includes:

[0015] Applying a step input signal with an amplitude of Δu to the heating device in the target temperature control region, collecting the temperature response data of this region, and preprocessing the collected data to obtain a step response curve including the initial temperature and the steady-state temperature;

[0016] Automatically detect the inflection point of the step response curve, determine the tangent line passing through the inflection point, calculate the intersection point of the tangent line and the initial temperature horizontal line, corresponding to time t1, and the intersection point of the tangent line and the steady-state temperature horizontal line, corresponding to time t2;

[0017] Based on the time t1, time t2, the amplitude Δu of the step input signal, and the steady-state change amount Δy of the temperature response data, that is, the difference between the steady-state temperature and the initial temperature, use the tangent method to calculate the parameters of the first-order inertia plus pure time-delay model G(s) = K*exp(-τs) / (Ts + 1), and the specific calculation is as follows:

[0018] Calculate the static gain K: K = Δy / Δu;

[0019] Calculate the pure time-delay τ: τ = t1;

[0020] Calculate the time constant T: T = t2 - t1;

[0021] Store the identified model parameters K, T, τ and the corresponding set temperature value during identification into the model library.

[0022] Preferably, the step of selecting an initial model from the model library, performing online model identification using the recursive least squares method, and updating the model parameters in real time specifically includes: during the operation of the system, continuously perform online model identification, select the closest initial model from the model library according to the current set temperature, and use the parameters of this model as the initial value for online model identification, and perform online model identification using the recursive least squares method to update the model parameters in real time.

[0023] Preferably, the step of fusing the online model parameters with the corresponding offline model parameters in the model library and determining the parameters of the adaptive PID controller for each temperature control region according to the fused model parameters specifically includes: performing weighted averaging on the model parameters obtained by online identification and the selected model parameters in the model library, and then selecting the Ziegler-Nichols rule from the PID parameter tuning rule library, and finally determining the parameters of the adaptive PID controller for each temperature control region.

[0024] Preferably, the method further includes the step of: the microcontroller uploads the temperature data, model parameters, PID parameters, etc. of each temperature control region to the host computer through the communication module for real-time display and monitoring.

[0025] Furthermore, the present invention also provides a temperature control system for a chemical vapor deposition gas supply system, including a microcontroller, multiple temperature measurement modules, multiple heating devices, and multiple heating control devices. The CVD gas supply system is divided into multiple temperature control regions along the gas flow direction. Each temperature control region is provided with at least one temperature measurement module and one heating device for measuring the temperature of this region. The heating device is used to heat each temperature control region of the CVD gas supply system. The heating control device uses a PID controller to control the on / off and power adjustment of the heating device. The microcontroller is used to collect temperature data, execute the model identification algorithm, calculate the PID controller parameters, and control the heating device. Using the microcontroller, according to the model identification result and the PID controller parameters, automatically adjust the output of the PID controller for each temperature control region, and according to the output of the PID controller for each temperature control region, control the heating power of the heating device corresponding to the region to achieve temperature control of each temperature control region.

[0026] Preferably, the system further includes a communication module. The microcontroller uploads the temperature data, model parameters, PID parameters, etc. of each temperature control region to the host computer through the communication module for real-time display and monitoring.

[0027] Preferably, the system further includes a power supply module for supplying power to the entire system.

[0028] Preferably, the system further includes a storage module for storing a model library and a PID parameter tuning rule library.

[0029] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0030] 1. By combining online model identification and offline model identification, the present invention can accurately obtain the dynamic models of each temperature control region of the CVD gas supply system, which provides a reliable basis for the parameter tuning of the PID controller, thereby achieving more precise temperature control. Precise temperature control is crucial for ensuring the quality and uniformity of the thin film in the CVD process.

[0031] 2. Through online model identification and adaptive PID control, the present invention realizes the automatic adjustment of the system. The system can automatically update the model parameters according to real-time data and accordingly adjust the parameters of the PID controller, reducing manual intervention, improving the automation level and the robustness of the control system.

[0032] 3. The present invention divides the CVD gas supply system into multiple temperature control regions and performs independent temperature control for each region, which can effectively solve the temperature control problem caused by the thermal characteristic differences of each region. Each region has its own heating control device and heating device, and can perform precise temperature control according to its own characteristics, avoiding mutual interference between regions and improving the overall temperature control effect.

[0033] 4. Through online model identification, the present invention can track the changes of system parameters in real time. The adaptive PID controller automatically adjusts the parameters of the PID controller according to the changes of the model parameters, so that the system always maintains the best control state.

[0034] 5. The recursive least squares method and the PID control algorithm adopted by the present invention have relatively small computational complexity, good real-time performance, and are easy to implement in an embedded system (such as a microcontroller), thereby reducing the difficulty and cost of engineering implementation. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] By reading the following detailed description of the non-limiting embodiments with reference to the accompanying drawings, other features, objects and advantages of the present invention will become more apparent:

[0036] Figure 1 is the module architecture diagram of the temperature control system for the chemical vapor deposition gas supply system of the present invention;

[0037] Figure 2 is the flowchart of the temperature control method for the chemical vapor deposition gas supply system of the present invention;

[0038] Figure 3 This is the flowchart for the off-line model identification of the present invention using the step response method;

[0039] Figure 4 This is the flowchart for the on-line model identification of the present invention using the recursive least squares method. Specific embodiments

[0040] The present invention will be described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several changes and improvements can still be made. These all fall within the protection scope of the present invention.

[0041] Specifically, the present invention provides a temperature control system for a chemical vapor deposition gas supply system, as Figure 1 shown, the system includes a plurality of temperature measurement modules, a plurality of heating devices, a plurality of heating control devices, a microcontroller, a communication module, a power supply module, and a storage module. The CVD gas supply system is divided into a plurality of temperature control regions along the gas flow direction, and at least one temperature measurement module and one heating device are provided in each temperature control region for measuring the temperature of the region, and the heating device is used to heat each temperature control region of the CVD gas supply system. The plurality of heating control devices are used to control the on / off and power adjustment of the heating devices. In the present invention, the heating control device adopts a PID controller.

[0042] The microcontroller serves as the control core and is used to collect temperature data, execute the model identification algorithm, calculate the PID controller parameters, and control the heating devices. Using the microcontroller, according to the model identification result and the PID controller parameters, the output of the PID controller for each temperature control region is automatically adjusted, and according to the output of the PID controller for each temperature control region, the heating power of the heating device in the corresponding region is controlled to achieve the temperature control of each temperature control region.

[0043] The communication module is used to communicate with the upper computer or the touch screen to achieve parameter setting, data monitoring, and remote control. The microcontroller uploads the temperature data, model parameters, PID parameters, etc. of each temperature control region to the upper computer or the touch screen through the communication module for real-time display and monitoring.

[0044] The power supply module is used to provide power for the entire system. The storage module is used to store the model library and the PID parameter tuning rule library.

[0045] Furthermore, the present invention also provides a temperature control method for a chemical vapor deposition gas supply system, as Figure 2 shown, the method includes the following steps:

[0046] S1: Divide the chemical vapor deposition gas supply system into multiple temperature control zones, collect the temperature data of each temperature control zone, and preprocess the collected temperature data;

[0047] Specifically, divide the chemical vapor deposition (CVD) gas supply system into multiple temperature control zones along the gas flow direction. At least one temperature measurement module and one heating device are set in each temperature control zone. Collect the data of the temperature measurement module in each temperature control zone, and preprocess the collected temperature data.

[0048] S2: Establish a model library and a PID parameter tuning rule library;

[0049] Specifically, in this embodiment, establish a model library, store the model parameters obtained by offline model identification at multiple set temperature points. Each set temperature point corresponds to a set of model parameters, as shown in Table 1 below. Each model entry includes: set temperature value, model parameters (K, T, τ).

[0050] Set temperature (°C) Static gain K Time constant T (s) Dead time τ (s) 30 1.2 60 5 60 1.5 55 4 90 1.8 50 4 120 2.1 48 3 ... ... ... ...

[0051] Table 1

[0052] Establish a PID parameter tuning rule library, store multiple rules for converting model parameters into PID controller parameters, such as Ziegler-Nichols rule, Cohen-Coon rule, user-defined rule, etc., as shown in Table 2 below.

[0053]

[0054] Table 2

[0055] In this embodiment, the model library and the PID parameter tuning rule library are stored in the Flash memory of the microcontroller.

[0056] S3: Perform offline model identification using the step response method;

[0057] Specifically, as Figure 3 shown, when the system starts, is maintained, or meets the preset trigger conditions, perform offline model identification. Set the system to enter the offline identification mode, set the set temperature of the CVD gas supply system. In this embodiment, the set temperature range is from 0 °C to 300 °C, and a temperature point is set every 30 °C. For each set temperature point, perform offline model identification using the step response method, which specifically includes the following steps:

[0058] Step 1: Apply a step input signal with an amplitude of Δu to the heating device in the target temperature control zone, collect the temperature response data of this zone, and preprocess the collected data to obtain a step response curve including the initial temperature and the steady-state temperature;

[0059] Step 2: Automatically detect the inflection point of the step response curve, determine the tangent line passing through the inflection point, and calculate the intersection point of the tangent line and the initial temperature horizontal line (corresponding to time t1) and the intersection point of the tangent line and the steady-state temperature horizontal line (corresponding to time t2);

[0060] Step 3: Based on the time t1, time t2, the amplitude Δu of the step input signal, and the steady-state change amount Δy of the temperature response data (i.e., the difference between the steady-state temperature and the initial temperature), use the tangent method to calculate the parameters of the first-order inertia plus pure delay (FOPDT) model G(s) = K*exp(-τs) / (Ts + 1), and the specific calculation is as follows:

[0061] Calculate the static gain K: K = Δy / Δu;

[0062] Calculate the pure delay time τ: τ = t1;

[0063] Calculate the time constant T: T = t2 - t1;

[0064] Step 4: Store the identified model parameters K, T, τ and the corresponding set temperature value during identification into the model library.

[0065] S4: Select an initial model from the model library, use the recursive least squares method for online model identification, and update the model parameters in real time;

[0066] Specifically, during the operation of the system, continuous online model identification is performed. According to the current set temperature, select the closest initial model from the model library, and use the parameters of this model as the initial value of the online model identification. Use the recursive least squares method for online model identification and update the model parameters in real time. As Figure 4 shown, the steps of using the recursive least squares method (RLS) for online model identification are as follows:

[0067] Initialize the parameter vector θ(0) and the covariance matrix P(0);

[0068] For each new data point Calculate the gain vector K(k): Update the parameter vector θ(k): Update the covariance matrix P(k): Calculate the model parameters K, T, τ according to the updated parameter vector θ(k), where λ is the forgetting factor.

[0069] For forward difference, the discretized FOPDT model is: y(k) = -a1y(k - 1) + b0u(k - d), where:

[0070]

[0071] θ = [a1, b0]^T

[0072] T = -a1Ts / (1 + a1)

[0073] K = b0*(1 - a1)

[0074] τ = d*Ts

[0075] where Ts is the sampling time and d is the lag order.

[0076] Monitor the deviation between the model parameters identified online and the corresponding model parameters in the model library. If the deviation exceeds the preset threshold, or the system temperature fluctuation exceeds the preset range, trigger offline identification.

[0077] S5: Integrate the online model parameters with the corresponding offline model parameters in the model library, and determine the parameters of the adaptive PID controller for each temperature control area according to the integrated model parameters;

[0078] Specifically, to achieve adaptive PID control, the system first integrates the online model parameters with the corresponding offline model parameters in the model library, then selects rules from the PID parameter tuning rule library, and finally determines the parameters of the adaptive PID controller for each temperature control area. The PID controller can adopt a two-degree-of-freedom PID controller.

[0079] Perform weighted averaging on the model parameters (K_online, T_online, τ_online) obtained from online identification and the model parameters (K_offline, T_offline, τ_offline) selected in the model library:

[0080] K_final = α*K_online + (1 - α)*K_offline

[0081] T_final = α*T_online + (1 - α)*T_offline

[0082] τ_final = α*τ_online + (1 - α)*τ_offline

[0083] where α is the weight coefficient.

[0084] Select a suitable rule from the PID parameter tuning rule library. In this embodiment, the Ziegler-Nichols rule is selected. According to the fused model parameters (K_final, T_final, τ_final), calculate the parameters (Kp, Ki, Kd, β, γ) of the two-degree-of-freedom PID controller. The controller output u is: u = Kp * (βr - y) + Ki * (r - y) / s + Kd * (γr - y) * s. Where r is the reference signal, y is the measured output signal of the controlled object, and β and γ are the setpoint weights.

[0085] Ziegler-Nichols rule parameter calculation formula:

[0086] Kp = 1.2 * T / (K * τ)

[0087] Ki = Kp / (0.5 * τ)

[0088] Kd = Kp * 0.125 * τ

[0089] Where β and γ are set as needed.

[0090] S6: The microcontroller automatically adjusts the output of each temperature control zone PID controller according to the model identification result and the PID controller parameters. According to the output of each temperature control zone PID controller, control the heating power of the heating device in the corresponding zone to achieve temperature control of each temperature control zone.

[0091] Furthermore, the microcontroller can also upload the temperature data, model parameters, PID parameters, etc. of each temperature control zone to the host computer or touch screen through the communication module for real-time display and monitoring.

[0092] The specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Without conflict, the embodiments of the present application and the features in the embodiments can be combined arbitrarily.

Claims

1. A temperature control method for a chemical vapor deposition gas supply system, characterized in that, The method includes the following steps: Divide the chemical vapor deposition gas supply system into multiple temperature control zones, collect the temperature data of each temperature control zone, and preprocess the collected temperature data; Establish a model library and a PID parameter tuning rule library; Use the step response method for offline model identification; Select an initial model from the model library, use the recursive least squares method for online model identification, and update the model parameters in real time; Fuse the online model parameters with the corresponding offline model parameters in the model library, and determine the parameters of the adaptive PID controller for each temperature control zone according to the fused model parameters; The microcontroller automatically adjusts the output of the PID controller for each temperature control zone according to the model identification result and the PID controller parameters, and controls the heating power of the heating device in the corresponding zone according to the output of the PID controller for each temperature control zone, so as to realize the temperature control of each temperature control zone.

2. The temperature control method for a chemical vapor deposition gas supply system according to claim 1, characterized in that, The step of dividing the chemical vapor deposition gas supply system into multiple temperature control zones, collecting the temperature data of each temperature control zone, and preprocessing the collected temperature data specifically includes: dividing the chemical vapor deposition gas supply system into multiple temperature control zones along the gas flow direction, setting at least one temperature measurement module and one heating device in each temperature control zone, collecting the data of the temperature measurement module in each temperature control zone, and preprocessing the collected temperature data.

3. The temperature control method for a chemical vapor deposition gas supply system according to claim 1, characterized in that The step of using the step response method for offline model identification specifically includes: Apply a step input signal with an amplitude of Δu to the heating device in the target temperature control zone, collect the temperature response data of this zone, and preprocess the collected data to obtain a step response curve including the initial temperature and the steady-state temperature; Automatically detect the inflection point of the step response curve, determine the tangent line passing through the inflection point, calculate the intersection point of the tangent line and the initial temperature horizontal line, corresponding to time t1, and the intersection point of the tangent line and the steady-state temperature horizontal line, corresponding to time t2; Based on the time t1, time t2, the amplitude Δu of the step input signal, and the steady-state change amount Δy of the temperature response data, that is, the difference between the steady-state temperature and the initial temperature, use the tangent method to calculate the parameters of the first-order inertia plus pure time-delay model G(s) = K*exp(-τs) / (Ts + 1), and the specific calculation is as follows: Calculate the static gain K: K = Δy / Δu; Calculate the pure time-delay τ: τ = t1; Calculate the time constant T: T = t2 - t1; Store the identified model parameters K, T, τ and the corresponding set temperature value during identification into the model library.

4. The temperature control method for a chemical vapor deposition gas supply system according to claim 1, characterized in that, The step of selecting an initial model from the model library, using the recursive least squares method for online model identification, and updating the model parameters in real time specifically includes: during the operation of the system, perform continuous online model identification, select the closest initial model from the model library according to the current set temperature, and use the parameters of this model as the initial value of the online model identification, and use the recursive least squares method for online model identification to update the model parameters in real time.

5. The temperature control method for the chemical vapor deposition gas supply system according to claim 1, wherein The step of fusing the online model parameters with the corresponding offline model parameters in the model library and determining the parameters of the adaptive PID controller for each temperature control region according to the fused model parameters specifically includes: performing weighted averaging on the model parameters obtained by online identification and the selected model parameters in the model library, then selecting the Ziegler-Nichols rule from the PID parameter tuning rule library, and finally determining the parameters of the adaptive PID controller for each temperature control region.

6. The temperature control method for a chemical vapor deposition gas supply system according to claim 1, wherein The method further includes the step of: the microcontroller uploads the temperature data, model parameters, PID parameters, etc. of each temperature control region to the host computer through the communication module for real-time display and monitoring.

7. A temperature control system for a chemical vapor deposition gas supply system, characterized in that, The system includes a microcontroller, multiple temperature measurement modules, multiple heating devices, and multiple heating control devices. The CVD gas supply system is divided into multiple temperature control regions along the gas flow direction. Each temperature control region is provided with at least one temperature measurement module and one heating device for measuring the temperature of this region. The heating device is used to heat each temperature control region of the CVD gas supply system. The heating control device adopts a PID controller and is used to control the on / off and power adjustment of the heating device. The microcontroller is used to collect temperature data, execute the model identification algorithm, calculate the PID controller parameters, and control the heating device. Using the microcontroller, according to the model identification result and the PID controller parameters, automatically adjust the output of the PID controller for each temperature control region, and according to the output of the PID controller for each temperature control region, control the heating power of the heating device in the corresponding region to achieve temperature control of each temperature control region.

8. The temperature control system for a chemical vapor deposition gas supply system according to claim 7, characterized in that, The system further includes a communication module. The microcontroller uploads the temperature data, model parameters, PID parameters, etc. of each temperature control region to the host computer through the communication module for real-time display and monitoring.

9. The temperature control system for a chemical vapor deposition gas supply system according to claim 7, wherein, The system further includes a power supply module for supplying power to the entire system.

10. The temperature control system for a chemical vapor deposition gas supply system according to claim 7, characterized in that, The system further includes a storage module for storing the model library and the PID parameter tuning rule library.

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