A method and system for intelligent temperature control of MPCVD equipment

Abstract

This invention belongs to the field of intelligent control technology, specifically relating to an intelligent temperature control method and system for MPCVD equipment, including the following steps: S1, real-time acquisition of multi-dimensional thermal field data of the MPCVD equipment, and preprocessing of the multi-dimensional thermal field data to obtain smooth time series data; S2, based on the microwave power data and temperature data in the time series data, constructing a thermal energy coupling efficiency index, which characterizes the efficiency of unit net input energy being absorbed by the load and converted into heat energy at the current moment. This invention solves the problems of thermal resistance drift and spurious balance in PID control caused by crystal growth during MPCVD diamond growth, and realizes active feedforward control based on thermal accumulation effect, effectively preventing crystal overheating.

Description

Technical Field

[0001] This invention belongs to the field of intelligent control technology, specifically relating to an intelligent temperature control method and system for MPCVD equipment. Background Technology

[0002] Microwave plasma chemical vapor deposition (MPCVD) is a core technology for preparing high-quality large single-crystal diamonds. Maintaining a constant crystal surface temperature is a crucial factor determining crystal quality during the long growth cycle of diamond, directly affecting its colorlessness and defect density. Any minute temperature fluctuation or long-term temperature drift can lead to crystal growth failure.

[0003] Currently, the mainstream MPCVD temperature control method in the industry typically adopts an "infrared temperature measurement + PID closed-loop control" mode. This mode reads the base temperature using an infrared thermometer, compares the read value with the set value, and uses a PID algorithm to adjust the output power of the microwave source in an attempt to maintain temperature stability.

[0004] However, the growth cycle of a single diamond crystal can take several weeks. As the crystal thickness increases from millimeters to centimeters, the upper surface of the crystal gradually approaches the high-temperature core region of the plasma sphere. Simultaneously, the increased crystal thickness alters its thermal resistance; this slow, variable change in physical structure is known as thermal resistance drift. Under existing PID control logic, the controller often maintains a constant power to keep the temperature reading constant. However, in reality, due to the increased efficiency of microwave energy capture as the crystal grows, the same power will cause the actual surface temperature of the crystal to gradually rise, creating a "false equilibrium." This drift in system characteristics caused by growth cannot be detected by current technology, ultimately leading to crystal overheating, twinning, or even crystal breakage. Summary of the Invention

[0005] This invention provides an intelligent temperature control method and system for MPCVD equipment to solve the technical problem of crystal overheating failure caused by thermal resistance drift during diamond growth in MPCVD.

[0006] In a first aspect, the present invention provides an intelligent temperature control method for MPCVD equipment, comprising the following steps:

[0007] S1: Real-time acquisition of multidimensional thermal field data from the MPCVD equipment, and preprocessing of the multidimensional thermal field data to obtain smooth time series data;

[0008] S2. Based on the microwave power data and temperature data in the time series data, a thermal energy coupling efficiency index is constructed. The thermal energy coupling efficiency index is used to characterize the efficiency of the load absorbing and converting a unit of net input energy into heat energy at the current moment.

[0009] S3, analyze the evolution trend of thermal coupling efficiency index with growth time, calculate the growth thermal resistance drift coefficient, the growth thermal resistance drift coefficient is used to characterize the heat accumulation effect caused by the change of crystal growth height.

[0010] S4 generates a negative power compensation amount based on the growth thermal resistance drift coefficient, and combines it with the output value of the PID controller to determine the final target set power sent to the microwave source, so as to achieve temperature control of the MPCVD equipment.

[0011] Its effects are as follows: By constructing a thermal energy coupling efficiency index and a growth thermal resistance drift coefficient, this invention transforms the invisible physical thermal resistance changes during crystal growth into visible mathematical control variables, thereby achieving real-time quantitative evaluation of the thermal accumulation effect. This mechanism can generate negative power compensation commands in advance based on the drift coefficient before the temperature fluctuates significantly, automatically offsetting the natural temperature rise caused by the crystal growing close to the core region of the plasma sphere. This maintains the absolute constancy of the true temperature of the crystal surface during the growth cycle of several weeks, significantly improving the colorlessness and yield of single-crystal diamond, and effectively avoiding the risks of twinning and cracking.

[0012] Furthermore, real-time acquisition of multi-dimensional thermal field data from the MPCVD equipment, including:

[0013] The incident power of the microwave generator, the reflected power of the microwave, the real-time process temperature of the crystal or substrate, and the effective running time of the current growth batch are collected via an industrial bus at a preset frequency.

[0014] The collected raw data is filtered by moving average to remove high-frequency electromagnetic interference noise.

[0015] Its effect is that by comprehensively collecting core thermal field parameters, eliminating interference noise, and unifying time series characteristics, it provides high-quality data support for subsequent construction of thermal energy coupling efficiency indicators, evaluation of thermal resistance drift, and realization of precise power compensation, which directly affects the accuracy and stability of the temperature control algorithm.

[0016] Furthermore, a thermal coupling efficiency index is constructed, including: calculating the thermal coupling efficiency index at the current moment using the following formula:

[0017]

[0018] In the formula, As a thermal energy coupling efficiency index, This refers to the real-time process temperature of the crystal or substrate. The incident power of the microwave generator. This is the microwave reflected power. It is the thermal hysteresis constant. This is the weighting factor for reflection loss. Moving forward from the current moment Incident power over time.

[0019] Its effect lies in establishing a quantitative correlation model of energy input, thermal conversion efficiency, and temperature output, breaking through the limitation of traditional temperature control that only focuses on temperature values, and achieving an explicit and precise description of the core implicit variable, thermal conversion efficiency. Its output... The index is not only the core input for subsequent calculation of the growth thermal resistance drift coefficient, but also the key bridge for the entire intelligent temperature control solution to upgrade from passive feedback to active feedforward, directly determining the accuracy of subsequent power compensation.

[0020] Furthermore, multi-dimensional thermal field data of the MPCVD equipment are acquired in real time, including: directly reading the analog feedback signal of the microwave source power controller as the incident power of the microwave generator; reading the reflected wave signal as the microwave reflected power through the directional coupler connected to the waveguide transmission line; and obtaining the real-time process temperature of the crystal or the substrate by non-contact measurement through a dual-color infrared thermometer aimed at the center of the substrate through the vacuum window.

[0021] Its effect is as follows: through customized design of hardware and acquisition path, it breaks through the complex working conditions of MPCVD equipment such as vacuum, high temperature and strong electromagnetic interference, and realizes distortion-free, highly synchronous and long-term stable acquisition of core thermal field parameters. This lays the data fidelity foundation for subsequent construction of performance indicators, calculation of thermal resistance drift coefficient and generation of accurate power compensation. It is the key support for the entire intelligent temperature control solution to be implemented from theoretical algorithm to engineering use.

[0022] Further, the growth thermal resistance drift coefficient is calculated, including: calculating the growth thermal resistance drift coefficient at the current moment using the following formula:

[0023]

[0024] In the formula, This is the growth thermal resistance drift coefficient. This is the baseline performance value during the early stages of growth. It is the natural logarithm function. It is the absolute value symbol. The growth rate is a time factor, where t is the effective growth time. This is an indicator of thermal energy coupling efficiency.

[0025] Its effect lies in the fact that, through a quadruple design of deviation quantification, trend smoothing, time adaptation, and robustness assurance, the implicit chain of crystal growth → thermal resistance drift → performance change in MPCVD equipment is transformed into explicit parameters that can be directly used for control. It is not only a key bridge connecting performance indicators and power compensation, but also the core technology supporting the entire intelligent temperature control solution to achieve active feedforward, anti-interference, and long-term stability. It directly determines the constant accuracy of the actual temperature during crystal growth, ultimately ensuring the colorlessness and low defect density of diamond.

[0026] Furthermore, the calculation of the growth thermal resistance drift coefficient also includes: using the absolute value sign to calculate the absolute value of the difference between the thermal energy coupling performance index and the performance benchmark value, ensuring that the true value of the logarithmic function is always greater than 1, and preventing mathematical logic errors when the thermal energy coupling performance index is less than the performance benchmark value due to process adjustments or air pressure fluctuations.

[0027] Further, determining the target set power to be finally sent to the microwave source includes: calculating the target set power using the following formula:

[0028]

[0029] In the formula, Set the power for the target. The base power value calculated by the PID algorithm. As the baseline process power, To compensate for the gain coefficient, This represents the growth thermal resistance drift coefficient.

[0030] Further, the target set power to be sent to the microwave source is determined, including: when the effective growth time is zero, the growth thermal resistance drift coefficient is zero, and the base power value calculated by the PID algorithm is used as the target set power; as the effective growth time increases, the growth thermal resistance drift coefficient increases, and the negative power compensation amount is calculated by the compensation gain coefficient, and the base power value is subtracted to obtain the target set power.

[0031] Furthermore, the process of determining the target set power to be sent to the microwave source includes: as the effective growth time increases, the crystal growth leads to an increase in the thermal coupling efficiency index, which in turn increases the growth thermal resistance drift coefficient, causing the target set power to decrease from the base power value to offset the natural temperature rise caused by crystal growth.

[0032] Secondly, an intelligent temperature control system for MPCVD equipment includes the following modules:

[0033] The data acquisition module is used to acquire multidimensional thermal field data of the MPCVD equipment in real time and preprocess the multidimensional thermal field data to obtain smooth time series data.

[0034] The efficiency index construction module is used to construct a thermal energy coupling efficiency index based on microwave power data and temperature data in time series data. The thermal energy coupling efficiency index is used to characterize the efficiency of the load absorbing and converting a unit of net input energy into heat energy at the current moment.

[0035] The drift coefficient calculation module is used to analyze the evolution trend of thermal coupling efficiency index with growth time and calculate the growth thermal resistance drift coefficient. The growth thermal resistance drift coefficient is used to characterize the heat accumulation effect caused by the change in crystal growth height.

[0036] The power regulation module is used to generate a negative power compensation amount based on the growth thermal resistance drift coefficient. Combined with the output value of the PID controller, it determines the target set power to be sent to the microwave source in order to achieve temperature control of the MPCVD equipment.

[0037] The beneficial effects are as follows: The core innovation of this invention lies in proposing a dynamic feedforward temperature control architecture based on thermal coupling efficiency drift analysis. The MPCVD cavity is considered as a dynamic system evolving over time. By analyzing the ratio between input power and generation temperature, a thermal coupling efficiency index characterizing crystal growth is extracted. Utilizing the evolution trend of this index over time, the thermal accumulation effect caused by crystal growth is accurately evaluated mathematically, achieving a leap from passive feedback to active feedforward control. Furthermore, this scheme relies entirely on electrical and temperature data, eliminating the need for visual monitoring. This solves the problem of machine vision failure caused by the blackening of the deposited carbon film on the MPCVD observation window. The robust design introduced in the formula ensures the system's stability under disturbances such as power grid fluctuations. Attached Figure Description

[0038] Figure 1 This is a flowchart of the intelligent temperature control method for MPCVD equipment in this invention.

[0039] Figure 2 This is a graph showing the adaptive adjustment curve of the microwave generator output power in this invention. Detailed Implementation

[0040] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0041] An embodiment of the intelligent temperature control method for MPCVD equipment provided by this invention:

[0042] like Figure 1 As shown, the intelligent temperature control method for MPCVD equipment includes the following steps:

[0043] S1 acquires multidimensional thermal field data from the MPCVD equipment in real time and preprocesses the multidimensional thermal field data to obtain smooth time series data.

[0044] In this embodiment, the system acquires real-time operating data of the MPCVD equipment at a frequency of 10Hz via an industrial bus. The acquired data includes: the incident power of the microwave generator, obtained by reading the analog feedback signal of the microwave source power controller; the microwave reflected power, obtained by reading the reflected wave signal through a directional coupler connected to the waveguide transmission line; the real-time process temperature of the crystal or substrate, obtained by non-contact measurement through a dual-color infrared thermometer aligned with the center of the substrate via a vacuum window; and the effective running time of the current growth batch, obtained by the system clock that starts counting from the moment of plasma excitation.

[0045] After acquiring the raw data, a moving average filter is applied to the collected raw data, with the window size set to 50 sampling points, in order to filter out high-frequency electromagnetic interference noise and obtain smooth time series data.

[0046] For example, if there are a few abnormal spikes caused by electrical spark interference among the 50 consecutive temperature sampling points collected at the current moment, such as a sudden jump to 1200℃, these spikes can be smoothed out by using moving average filtering, preserving the true temperature trend, such as 900℃.

[0047] By using high-frequency acquisition and filtering, we can obtain clean data that truly reflects the operating status of the equipment, laying a reliable data foundation for subsequent accurate calculations.

[0048] S2. Based on the microwave power and temperature data in the time series data, a thermal energy coupling efficiency index is constructed. The thermal energy coupling efficiency index is used to characterize the efficiency of the load absorbing and converting a unit of net input energy into heat energy at the current moment.

[0049] In this embodiment, to evaluate the current heating efficiency, it is necessary to remove the power lost due to reflection and focus on the portion actually absorbed by the load and converted into heat energy. The system calculates the thermal coupling efficiency index at the current moment using the following formula:

[0050]

[0051] In the formula, As a thermal energy coupling efficiency index, This refers to the real-time process temperature of the crystal or substrate. The incident power of the microwave generator. Moving forward from the current moment Incident power over time This is the microwave reflected power. It is the thermal hysteresis constant. This is the weighting factor for reflection loss.

[0052] in, To address the time difference between power changes and temperature changes, during equipment commissioning, a step power signal is given, and the temperature response delay time is measured. The temperature response delay time is typically 3-8 seconds, and this is set as a fixed constant. The nonlinear subtraction used to correct the contribution of reflected power to actual heating is determined by the Q-value characteristics of the resonant cavity, and the value ranges from 0.8 to 1.0, with an empirical value of 0.9 usually taken.

[0053] Assume that at a certain moment, the real-time temperature is 900℃, the incident power is 5.0kW, and the reflected power is 0.5kW. If we take 0.9, the calculation process is as follows:

[0054] Reflection ratio term: ; Denominator (net absorbed power): Thermal coupling efficiency index: The larger this value, the higher the temperature that can be generated with the same power, which means that the heating efficiency is higher.

[0055] By constructing a thermal-energy coupling efficiency index, we can transform from simply monitoring temperature to monitoring energy conversion efficiency, effectively identifying the heating efficiency improvement caused by crystal growth.

[0056] S3. Analyze the evolution trend of thermal coupling efficiency index with growth time, and calculate the growth thermal resistance drift coefficient. The growth thermal resistance drift coefficient is used to characterize the heat accumulation effect caused by the change in crystal growth height.

[0057] In this embodiment, because the growth process is extremely slow and accompanied by random fluctuations, directly using instantaneous values ​​would cause control oscillations. Therefore, a formula incorporating logarithmic smoothing and time weighting is designed to calculate the accumulated drift. The growth thermal resistance drift coefficient at the current moment is calculated using the following formula:

[0058]

[0059] In the formula, This is the growth thermal resistance drift coefficient. This is the baseline performance value during the early stages of growth. It is the natural logarithm function. It is the absolute value symbol. t represents the growth rate time factor, where t is the effective growth time.

[0060] The performance benchmark value is obtained by taking the arithmetic mean of the thermal coupling performance indicators within the first 30 minutes after the growth enters the stable stage. The growth rate time factor is determined based on the historical process database; if the batch growth rate is fast, such as 20 micrometers / hour, a larger value is taken, such as 0.1, and vice versa. The absolute value sign in the formula ensures that the argument of the logarithmic function is always greater than 1, regardless of the fluctuation of the performance indicators, thus guaranteeing the validity of the formula logic.

[0061] Assuming a performance baseline of 190, the currently calculated thermal coupling performance index is 197.8, the effective growth time is 50 hours, and the growth rate time factor is 0.005.

[0062] First, calculate the performance deviation ratio: ; Calculate the logarithmic term: ; Calculate the time-weighted term: ; Calculate the final growth thermal resistance drift coefficient: .

[0063] By calculating the growth thermal resistance drift coefficient, minute efficiency changes can be transformed into stable drift trend signals through time and logarithmic functions, avoiding the interference of instantaneous fluctuations and accurately assessing the heat accumulation effect.

[0064] S4 generates a negative power compensation amount based on the growth thermal resistance drift coefficient, and combines it with the output value of the PID controller to determine the final target set power sent to the microwave source, so as to achieve temperature control of the MPCVD equipment.

[0065] In this embodiment, the calculated drift coefficient is converted into a specific power reduction amount and superimposed on the output of the PID controller; the target set power finally sent to the microwave source is calculated using the following formula:

[0066]

[0067] In the formula, Set the power for the target. This is the base power value calculated by the PID algorithm based on temperature error. As the baseline process power, The gain compensation factor is typically set to 0.05-0.15.

[0068] Assuming the base power calculated by the current PID is 5.0kW, the reference process power is 5.0kW, the compensation gain coefficient is 0.1, and the growth thermal resistance drift coefficient is 0.0447.

[0069] Calculate the compensation amount: ; Calculate the target power: .

[0070] As can be seen, although the PID controller aims to output 5.0kW, the actual output is reduced to [a lower value] after compensation using this method. kW. As growth time increases, the crystal grows taller, the drift coefficient increases slowly, and the reduction term increases, causing the target power to be forcibly lowered from the base power value.

[0071] By generating nonlinear power compensation commands, the power can be actively reduced before the PID response. The reduced power is used to offset the increased heat absorption capacity brought about by the growth of the crystal height, thereby maintaining a constant true temperature on the crystal surface.

[0072] Reference Figure 2 This figure visually illustrates the significant differences in microwave power output control strategies between the present invention and existing technologies over a continuous 120-hour growth cycle. The existing technology curve shows that under conventional control, the microwave power remains relatively constant around 5.0 kW throughout the cycle, with only minor random fluctuations. This method fails to detect changes in thermal resistance, leading to crystal overheating. The present invention curve shows that the output power exhibits a smooth, slow decreasing trend over the growth period. This indicates that the present system actively reduces power based on the detuning factor and drift coefficient, precisely balancing the natural temperature rise caused by crystal growth and achieving isothermal growth. The detuning factor, obtained by multiplying the reflection loss weighting factor by the ratio of microwave reflected power to incident power, quantifies the impedance mismatch between the microwave and the load; a larger value indicates lower microwave energy absorption efficiency and more severe detuning.

[0073] The intelligent temperature control system for MPCVD equipment provided by this invention includes the following modules:

[0074] The data acquisition module is used to acquire multidimensional thermal field data of the MPCVD equipment in real time and preprocess the multidimensional thermal field data to obtain smooth time series data.

[0075] The efficiency index construction module is used to construct a thermal energy coupling efficiency index based on microwave power data and temperature data in time series data. The thermal energy coupling efficiency index is used to characterize the efficiency of the load absorbing and converting a unit of net input energy into heat energy at the current moment.

[0076] The drift coefficient calculation module is used to analyze the evolution trend of thermal coupling efficiency index with growth time and calculate the growth thermal resistance drift coefficient. The growth thermal resistance drift coefficient is used to characterize the heat accumulation effect caused by the change in crystal growth height.

[0077] The power regulation module is used to generate a negative power compensation amount based on the growth thermal resistance drift coefficient. Combined with the output value of the PID controller, it determines the target set power to be sent to the microwave source in order to achieve temperature control of the MPCVD equipment.

[0078] The above are all preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Therefore, all equivalent changes made in accordance with the structure, shape and principle of the present invention should be covered within the scope of protection of the present invention.

Claims

1. A method for intelligent temperature control of MPCVD equipment, characterized in that, Includes the following steps: S1: Real-time acquisition of multidimensional thermal field data from the MPCVD equipment, and preprocessing of the multidimensional thermal field data to obtain smooth time series data; S2, based on microwave power and temperature data from the time series data, construct a thermal coupling efficiency index, including: , As a thermal coupling efficiency index, This refers to the real-time process temperature of the crystal or substrate. The incident power of the microwave generator. This is the microwave reflected power. It is the thermal hysteresis constant. This is the weighting factor for reflection loss. Moving forward from the current moment Incident power over time; thermal coupling efficiency index is used to characterize the efficiency of a unit net input energy being absorbed by the load and converted into heat energy at the current moment; S3, analyze the evolution trend of thermal coupling efficiency index with growth time, and calculate the growth thermal resistance drift coefficient, including: , This is the growth thermal resistance drift coefficient. This is the baseline performance value during the early stages of growth. It is the natural logarithm function. It is the absolute value symbol. The growth rate time factor is t, where t is the effective growth time; the growth thermal resistance drift coefficient is used to characterize the heat accumulation effect caused by the change in crystal growth height. S4 generates a negative power compensation amount based on the growth thermal resistance drift coefficient, and combines it with the output value of the PID controller to determine the final target set power sent to the microwave source, so as to achieve temperature control of the MPCVD equipment.

2. The intelligent temperature control method for MPCVD equipment according to claim 1, characterized in that, Real-time acquisition of multidimensional thermal field data from MPCVD equipment, including: The incident power of the microwave generator, the reflected power of the microwave, the real-time process temperature of the crystal or substrate, and the effective running time of the current growth batch are collected via an industrial bus at a preset frequency. The collected raw data is filtered by moving average to remove high-frequency electromagnetic interference noise.

3. The intelligent temperature control method for MPCVD equipment according to claim 2, characterized in that, Real-time acquisition of multi-dimensional thermal field data of MPCVD equipment includes: directly reading the analog feedback signal of the microwave source power controller as the incident power of the microwave generator; reading the reflected wave signal as the microwave reflected power through the directional coupler connected to the waveguide transmission line; and obtaining the real-time process temperature of the crystal or the substrate by non-contact measurement through a dual-color infrared thermometer aligned with the center of the substrate via a vacuum window.

4. The intelligent temperature control method for MPCVD equipment according to claim 1, characterized in that, The calculation of the growth thermal resistance drift coefficient also includes: using the absolute value sign to calculate the absolute value of the difference between the thermal energy coupling performance index and the performance benchmark value, ensuring that the true value of the logarithmic function is always greater than 1, and preventing mathematical logic errors when the thermal energy coupling performance index is less than the performance benchmark value due to process adjustments or air pressure fluctuations.

5. The intelligent temperature control method for MPCVD equipment according to claim 1, characterized in that, Determining the target set power to be finally transmitted to the microwave source includes calculating the target set power using the following formula: In the formula, Set the power for the target. The base power value calculated by the PID algorithm. As the baseline process power, To compensate for the gain coefficient, This represents the growth thermal resistance drift coefficient.

6. The intelligent temperature control method for MPCVD equipment according to claim 5, characterized in that, Determining the target set power to be sent to the microwave source includes: when the effective growth time is zero, the growth thermal resistance drift coefficient is zero, and the base power value calculated by the PID algorithm is used as the target set power; as the effective growth time increases, the growth thermal resistance drift coefficient increases, and the negative power compensation amount is calculated by the compensation gain coefficient, and then subtracted from the base power value to obtain the target set power.

7. The intelligent temperature control method for MPCVD equipment according to claim 5, characterized in that, The process of determining the target set power to be sent to the microwave source includes: as the effective growth time increases, the crystal growth leads to an increase in the thermal coupling efficiency index, which in turn increases the growth thermal resistance drift coefficient, causing the target set power to decrease from the base power value to offset the natural temperature rise caused by crystal growth.

8. An intelligent temperature control system for MPCVD equipment, characterized in that, Includes the following modules: The data acquisition module is used to acquire multidimensional thermal field data of the MPCVD equipment in real time and preprocess the multidimensional thermal field data to obtain smooth time series data. The performance index construction module is used to construct thermal coupling performance indices based on microwave power and temperature data from time-series data, including: , As a thermal coupling efficiency index, This refers to the real-time process temperature of the crystal or substrate. The incident power of the microwave generator. This is the microwave reflected power. It is the thermal hysteresis constant. This is the weighting factor for reflection loss. Moving forward from the current moment Incident power over time; thermal coupling efficiency index is used to characterize the efficiency of a unit net input energy being absorbed by the load and converted into heat energy at the current moment; The drift coefficient calculation module is used to analyze the evolution trend of thermal coupling efficiency index with growth time and calculate the growth thermal resistance drift coefficient, including: , This is the growth thermal resistance drift coefficient. This is the baseline performance value during the early stages of growth. It is the natural logarithm function. It is the absolute value symbol. The growth rate time factor is t, where t is the effective growth time; the growth thermal resistance drift coefficient is used to characterize the heat accumulation effect caused by the change in crystal growth height. The power regulation module is used to generate a negative power compensation amount based on the growth thermal resistance drift coefficient. Combined with the output value of the PID controller, it determines the target set power to be sent to the microwave source in order to achieve temperature control of the MPCVD equipment.

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