Temperature control method and system of semiconductor heater and storage medium

Abstract

The invention provides a temperature control method and system for a semiconductor heater and a storage medium, and the method comprises the steps: obtaining the actual temperature of the semiconductor heater, and calculating a temperature error and an error change rate according to the actual temperature of the semiconductor heater, then determining a corresponding proportionality coefficient variable and an integral coefficient variable according to the temperature error and the error change rate, determining a corresponding proportionality coefficient base value and an integral coefficient base value according to the actual temperature at the current moment, and determining a target proportionality coefficient according to the proportionality coefficient variable and the proportionality coefficient base value; a target integral coefficient is determined according to the integral coefficient variable and the integral coefficient base value, and finally the actual temperature of the semiconductor heater is controlled according to the temperature error, the target proportionality coefficient and the target integral coefficient, so that the actual temperature of the semiconductor heater reaches the target temperature. The temperature control method can well adapt to the complex working conditions of the actual semiconductor manufacturing process, and the temperature control precision and stability are high.

Description

Technical Field

[0001] This application relates to the field of semiconductor technology, specifically to a temperature control method, system, and storage medium for a semiconductor heater. Background Technology

[0002] In semiconductor manufacturing processes, semiconductor heaters play a crucial role in supporting the wafer and providing a stable temperature field. Their temperature control accuracy and stability directly determine the deposition rate, compositional uniformity, and crystal quality of thin films on the wafer surface, making them one of the core process steps affecting the performance and yield of semiconductor devices.

[0003] Currently, the industry generally adopts traditional PI control, which uses fixed PI parameters to achieve closed-loop temperature regulation to meet the temperature control requirements of semiconductor heaters. However, traditional PI control is difficult to adapt well to the complex operating conditions of actual semiconductor manufacturing processes, and is prone to control anomalies and cascading process risks, resulting in the inability to meet the process requirements of high temperature control accuracy and high stability. Summary of the Invention

[0004] In view of this, this application provides a temperature control method, system and storage medium for a semiconductor heater, which can well adapt to the complex working conditions of actual semiconductor manufacturing processes and has high temperature control accuracy and stability.

[0005] The first aspect of this application provides a temperature control method for a semiconductor heater. The temperature control method includes: acquiring the actual temperature of the semiconductor heater; calculating a temperature error and an error change rate based on the actual temperature of the semiconductor heater; the temperature error being the difference between a preset target temperature and the actual temperature at the sampling time, and the error change rate being the ratio of the difference between the temperature error at the current time and the temperature error at the previous time to the time interval between the current time and the previous time; determining corresponding proportional coefficient variables and integral coefficient variables based on the temperature error and the error change rate; determining corresponding proportional coefficient base values ​​and integral coefficient base values ​​based on the actual temperature at the current time; determining a target proportional coefficient based on the proportional coefficient variables and the proportional coefficient base values, and determining a target integral coefficient based on the integral coefficient variables and the integral coefficient base values; and controlling the actual temperature of the semiconductor heater based on the temperature error, the target proportional coefficient, and the target integral coefficient to ensure that the actual temperature of the semiconductor heater reaches the target temperature.

[0006] In one embodiment, determining the corresponding proportional coefficient variable and integral coefficient variable based on the temperature error and the error change rate includes: determining the fuzzy level of the temperature error based on the temperature error, and determining the fuzzy level of the error change rate based on the error change rate; determining the proportional coefficient adjustment level and the integral coefficient adjustment level based on the fuzzy level of the temperature error, the fuzzy level of the error change rate, and a preset fuzzy rule; wherein the fuzzy rule is used to indicate the correspondence between the proportional coefficient adjustment level, the integral coefficient adjustment level, and the fuzzy level of the temperature error and the fuzzy level of the error change rate; determining the proportional coefficient variable based on the proportional coefficient adjustment level, and determining the integral coefficient variable based on the integral coefficient adjustment level; wherein the proportional coefficient variable is related to the proportional coefficient adjustment level, and the integral coefficient variable is related to the integral coefficient adjustment level.

[0007] In one embodiment, the fuzzy rules include: when the temperature error fuzzy level represents temperature overshoot and the error change rate fuzzy level represents a heating trend, the greater the heating trend represented by the error change rate fuzzy level, the greater the proportional coefficient adjustment level and the smaller the integral coefficient adjustment level; when the temperature error fuzzy level represents temperature undershoot and the error change rate fuzzy level represents a cooling trend, the greater the cooling trend represented by the error change rate fuzzy level, the greater the proportional coefficient adjustment level and the smaller the integral coefficient adjustment level; when the temperature error fuzzy level represents temperature overshoot and the error change rate fuzzy level represents a cooling trend, the greater the cooling trend represented by the error change rate fuzzy level, the smaller the proportional coefficient adjustment level and the larger the integral coefficient adjustment level; when the temperature error fuzzy level represents temperature undershoot and the error change rate fuzzy level represents a heating trend, the greater the heating trend represented by the error change rate fuzzy level, the smaller the proportional coefficient adjustment level and the larger the integral coefficient adjustment level.

[0008] In one embodiment, the proportional coefficient base value is negatively correlated with the actual temperature of the semiconductor heater, and the integral coefficient base value is positively correlated with the actual temperature of the semiconductor heater.

[0009] In one embodiment, controlling the actual temperature of the semiconductor heater based on the temperature error, the target proportional coefficient, and the target integral coefficient includes: integrating the temperature error to obtain an initial integral error; determining a target integral error based on the initial integral error; and controlling the actual temperature of the semiconductor heater based on the temperature error, the target proportional coefficient, the target integral error, and the target integral coefficient.

[0010] In one embodiment, determining the target integration error based on the initial integration error includes: when the initial integration error is greater than 0 and less than a preset upper limit value, taking the initial integration error as the target integration error; or, when the initial integration error is greater than or equal to the preset upper limit value, taking the preset upper limit value as the target integration error; or, when the initial integration error is less than 0, multiplying the initial integration error by a preset attenuation coefficient to obtain the target integration error.

[0011] In one embodiment, after determining the target proportional coefficient and the target integral coefficient, the temperature control method further includes: confirming whether the actual temperature of the semiconductor heater meets preset stability conditions; if so, maintaining the target proportional coefficient and the target integral coefficient unchanged; if not, re-determining the target proportional coefficient and the target integral coefficient; wherein the semiconductor heater includes an inner region and an outer region, and the stability conditions include: the temperature difference between the actual temperature of the inner region and the actual temperature of the outer region is less than or equal to a first set value; and, the temperature error of the actual temperature of the inner region relative to the target temperature and the temperature error of the actual temperature of the outer region relative to the target temperature are both not greater than a second set value; and, the oscillation frequency of the actual temperature of the inner region and the oscillation frequency of the actual temperature of the outer region are both not greater than a third set value.

[0012] In one embodiment, the temperature control method further includes: when the actual temperature at the current moment is less than a first preset temperature threshold, controlling the actual temperature of the semiconductor heater to change at a preset target rate; when the actual temperature at the current moment is greater than or equal to the first preset temperature threshold and less than a second preset temperature threshold, determining corresponding proportional coefficient variables and integral coefficient variables based on temperature error and error change rate, wherein the integral coefficient variable is 0; when the actual temperature at the current moment is greater than or equal to the second preset temperature threshold, determining corresponding proportional coefficient variables and integral coefficient variables based on temperature error and error change rate, wherein the integral coefficient variable is not 0.

[0013] The second aspect of this application provides a temperature control system for a semiconductor heater. The temperature control system includes a temperature sensor and a controller. The temperature sensor is disposed adjacent to the semiconductor heater and is used to detect the actual temperature of the semiconductor heater. The controller is electrically connected to the temperature sensor and the semiconductor heater and is used to execute the temperature control method described in the first aspect or any embodiment of the first aspect.

[0014] A third aspect of this application provides a computer-readable storage medium storing a computer program that is loaded by a processor to execute the temperature control method described in the first aspect or any embodiment of the first aspect.

[0015] Compared with the prior art, this application has at least the following advantages: The temperature control method of this application uses fuzzy PI adaptive control of proportional and integral coefficient variables, combined with dynamic adjustment of the base values ​​of proportional and integral coefficients, to dynamically optimize the PI parameters. This allows the PI parameters to adapt well to the complex operating conditions of actual semiconductor manufacturing processes, meeting the process requirements of high temperature control accuracy and high stability in semiconductor manufacturing. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of a semiconductor heater provided in an embodiment of this application.

[0017] Figure 2 This is a connection diagram of a temperature control system provided in an embodiment of this application.

[0018] Figure 3 This is a flowchart of a temperature control method for a semiconductor heater provided in an embodiment of this application.

[0019] Figure 4 yes Figure 3 A control loop diagram of the method.

[0020] Figure 5 yes Figure 3 A detailed flowchart of step S13 in the process.

[0021] Figure 6 yes Figure 5 A schematic diagram of the method.

[0022] Figure 7 yes Figure 3 A detailed flowchart of step S16 in the process.

[0023] Figure 8 This is a schematic diagram of a temperature control method for a semiconductor heater provided in an embodiment of this application.

[0024] Explanation of main component symbols Semiconductor heater-10, ceramic substrate-11, support shaft-12, inner heating element-111 Outer heating element-112, inner zone-113, outer zone-114, process chamber-20, wafer-30, power supply-40, controller-50, temperature sensor-60, host computer-70, temperature control system-100. Detailed Implementation

[0025] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application. Unless otherwise specified, the different embodiments and features described below can be combined with each other.

[0026] In semiconductor manufacturing processes, semiconductor heaters play a crucial role in supporting the wafer and providing a stable temperature field. The wafer is the fundamental material used to manufacture semiconductor devices. Semiconductor manufacturing processes include, but are not limited to, thin-film deposition processes, which can include chemical vapor deposition (CVD) and physical vapor deposition (PVD).

[0027] Specifically, such as Figure 1 As shown, the semiconductor heater 10 includes a ceramic substrate 11, an inner heating element 111, and an outer heating element 112. The ceramic substrate 11 is housed within a process chamber 20, and the wafer 30 can be placed on the ceramic substrate 11. The ceramic substrate 11 can be supported by a support shaft 12, a portion of which extends outside the process chamber 20. The ceramic substrate 11 is made of a ceramic material with high thermal conductivity and low coefficient of thermal expansion, such as aluminum nitride (AlN) ceramic.

[0028] The inner heating element 111 and the outer heating element 112 are, for example, heating wires, heating tubes, or graphite heating elements. The inner heating element 111 and the outer heating element 112 are concentrically arranged and spaced apart within the ceramic substrate 11, with the inner heating element 111 located near the center of the ceramic substrate 11 and the outer heating element 112 located on the outer periphery of the inner heating element 111, near the edge of the ceramic substrate 11. Therefore, the semiconductor heater 10 can be divided into an inner region 113 and an outer region 114, where the area enclosed by the inner heating element 111 within the ceramic substrate 11 (including the area within the inner heating element 111 and the arrangement range of the inner heating element 111 itself) is the inner region 113, and the remaining area of ​​the ceramic substrate 11, i.e., the area where the outer heating element 112 is located, is the outer region 114.

[0029] like Figure 2 As shown, the inner heating element 111 and the outer heating element 112 are also electrically connected to a power supply 40, which is connected to a controller 50. Both the power supply 40 and the controller 50 can be general-purpose circuits or integrated modules that perform the corresponding functions. The controller 50 can be used to control the power supply 40 to output power to the inner heating element 111 and the outer heating element 112. The power output range of the power supply 40 can be, for example, 0~3000W. After power is applied, the inner heating element 111 can heat the inner region 113 of the ceramic substrate 11, and the outer heating element 112 can heat the outer region 114 of the ceramic substrate 11. Thus, the semiconductor heater 10 can heat the wafer 30 to promote the deposition process and form a thin film on the wafer 30.

[0030] The semiconductor heater 10 is also disposed adjacent to a temperature sensor 60. The temperature sensor 60 can be located, for example, at the bottom of the ceramic substrate 11 and near its center. The temperature sensor 60 can be a common temperature sensing element such as a thermocouple. At least one temperature sensor 60 can be used, depending on the actual situation. The temperature sensor 60 is electrically connected to the controller 50. The temperature sensor 60 can detect the actual temperature of the semiconductor heater 10 and feed it back to the controller 50. The controller 50 can control the actual temperature to reach a preset target temperature by adjusting the output power of the power supply 40. The controller 50 can also be electrically connected to a host computer 70. The controller 50 can control the operation and heating temperature of the semiconductor heater 10 according to instructions or configuration information sent by the host computer. Alternatively, the controller 50 can also send relevant data during the temperature control process to the host computer 70. The host computer 70 includes, but is not limited to, industrial control computers, user terminal devices (such as mobile phones, computers), etc.

[0031] Understandably, the temperature control accuracy and stability of the semiconductor heater 10 directly determine the deposition rate, compositional uniformity, and crystal quality of the thin film on the wafer surface, and are one of the core process steps affecting the performance and yield of semiconductor devices.

[0032] Currently, the industry generally uses traditional PI control. The core theoretical basis of traditional PI control is based on the simplified thermal dynamic equilibrium relationship of semiconductor heaters, that is, it follows the thermal equilibrium equation: (1).

[0033] In the formula, The power input to the heating element in the semiconductor heater 10; dT / dt represents the total power lost by the semiconductor heater 10 through various means such as heat conduction, heat radiation, and convection; C represents the specific heat capacity of the semiconductor heater 10, which is an inherent property of the material; and dT / dt represents the instantaneous temperature change rate of the semiconductor heater 10.

[0034] The core design idea of ​​traditional PI control is to approximate the thermal dynamic system of the semiconductor heater 10 as a linear system model, and to control the temperature of the semiconductor heater 10 in a closed loop by preset fixed PI parameters (i.e., proportional coefficient Kp and integral coefficient Ki). The output equation is, for example: (2).

[0035] In the formula, The output control parameter can be used to control the actual temperature of the semiconductor heater 10; t is the sampling time. This is for temperature error; This is the integral error, which is also the temperature error. Historical accumulation, .

[0036] By leveraging the synergistic effect of the proportional term to quickly respond to temperature errors and the integral term to eliminate steady-state errors, closed-loop temperature regulation can be achieved to meet the temperature control requirements of the semiconductor heater 10 in the conventional process temperature range (e.g., 200℃~300℃) and the highest extreme process temperature range (e.g., 600℃).

[0037] However, the applicant's research revealed that, under the complex operating conditions of actual semiconductor thin film deposition processes, the inherent limitations of the control logic and parameter design of traditional PI control methods lead to numerous technical defects, such as: 1. Fixed PI parameters have poor adaptability and are prone to causing various temperature control anomalies and cascading process risks: In actual semiconductor thin film deposition processes, in order to meet the deposition requirements of different thin film materials, process parameters (such as the gas flow rate and working pressure in the reaction chamber) need to be dynamically adjusted according to the process steps. Changes in these parameters will directly change the heat dissipation environment of the semiconductor heater 10 (such as increased gas flow rate accelerating convection heat dissipation, and pressure changes affecting heat transfer efficiency), resulting in continuous fluctuations in operating conditions.

[0038] Traditional technologies use fixed PI parameters, which cannot adapt to dynamic changes in operating conditions in real time. This easily leads to two types of core temperature control anomalies: First, steady-state error, where the actual temperature fails to consistently reach the target temperature, causing the thin film deposition rate to deviate from the preset process window, resulting in poor process performance. Second, significant overshoot and oscillation, where the temperature fluctuates repeatedly after exceeding the target value. Since the ceramic substrate 11 typically employs an independent heating structure for inner and outer zones to ensure uniform wafer heating, overshoot and oscillation can cause the temperatures of the two zones to interfere with and couple with each other, making it impossible for each zone to maintain stability. In extreme cases, the temperature difference between the inner and outer zones can exceed the thermal stress tolerance limit of the ceramic material, causing the ceramic substrate 11 to crack. Simultaneously, uneven temperature fluctuations directly lead to differences in the thin film deposition rate and composition in different areas of the wafer surface, severely affecting the uniformity of wafer thin film deposition and reducing the yield of semiconductor products.

[0039] 2. Inability to adapt to nonlinear thermal dynamic systems, resulting in severely inadequate control performance: The heat dissipation process of the semiconductor heater 10 exhibits significant temperature dependence. The actual thermal dynamics of the semiconductor heater 10 consists of two parts: linear heat dissipation power in the low-temperature range (e.g., below 300℃, where heat conduction is the primary method and the heat dissipation rate is linearly related to the temperature difference) and nonlinear heat dissipation power in the high-temperature range (e.g., above 300℃, especially near the extreme temperature of 600℃, where the proportion of heat radiation and convection increases dramatically, the heat dissipation rate increases exponentially with increasing temperature, and the heat dissipation capacity is significantly amplified). This characteristic leads to a strong nonlinearity in the overall thermal dynamics of the semiconductor heater 10. The core design premise of traditional PI control is that the system is a linear model. Its fixed Kp and Ki parameters cannot dynamically adapt to the drastically different thermal dynamics of the high and low temperature ranges. This results in potential temperature lag in the low-temperature range and over- or under-temperature control in the high-temperature range, failing to meet the temperature control requirements of both low and high-temperature environments, and exhibiting significant deficiencies in control accuracy and long-term stability.

[0040] 3. Slow control response speed significantly impacts production efficiency: Traditional PI control lacks a rapid adaptation mechanism to changes in operating conditions and nonlinear characteristics. When faced with process disturbances such as changes in ventilation volume and pressure, as well as switching between high and low temperature ranges, it requires a considerable amount of time to adjust and regain a stable state. This slow response speed leads to extended heating and stabilization cycles in a single thin film deposition process, reducing the number of wafers that can be processed per unit time. This significantly reduces the production efficiency of semiconductor thin film deposition and fails to meet the large-scale, high-efficiency production demands of the semiconductor manufacturing industry.

[0041] In short, traditional PI control methods are difficult to adapt well to the complex operating conditions of actual semiconductor manufacturing processes, which can easily lead to control anomalies and cascading process risks, resulting in the inability to meet the process requirements of high temperature control accuracy and high stability.

[0042] Therefore, this application provides a temperature control method for a semiconductor heater, which can be executed by a controller 50. This temperature control method can effectively control the temperature of the semiconductor heater 10 during the heating process to adapt to the complex working conditions of actual semiconductor manufacturing processes and achieve high temperature control accuracy and high temperature control stability.

[0043] The temperature control method provided in the embodiments of this application is described below.

[0044] Please see Figure 3 and Figure 4 The temperature control method provided in this application embodiment may include the following steps: Step S11: Obtain the actual temperature of the semiconductor heater.

[0045] The actual temperature of the semiconductor heater can be obtained by periodically detecting it using a temperature sensor.

[0046] Step S12: Calculate the temperature error and error change rate based on the actual temperature of the semiconductor heater.

[0047] Here, temperature error is the difference between the preset target temperature and the actual temperature at the sampling time, which can be expressed as e(t). Understandably, temperature error characterizes the degree of deviation of the actual temperature from the target temperature. For example, a temperature error within the allowable deviation range means the temperature is close to or has reached the target temperature, that is, the temperature is approaching a steady state; a temperature error exceeding the allowable deviation range means the temperature deviates, for example, a negative temperature error represents temperature overshoot, and a positive temperature error represents temperature undershoot.

[0048] The rate of change of error is the ratio of the difference between the temperature error at the current moment and the temperature error at the previous moment to the time interval between the current moment and the previous moment, which can be expressed as ec(t), ec(t) = [e(t) - e(t-1)] / Δt. Here, t represents the current moment, t-1 represents the previous moment, and Δt represents the time interval, i.e., the sampling interval, which can be 1 second, 1 minute, or other durations, without specific limitations. Since the time interval Δt is a fixed and known value, ec(t) can also be expressed as: ec(t) = e(t) - e(t-1). Understandably, the rate of change of error characterizes the trend of temperature error change. For example, if the rate of change of error is within the allowable deviation range, it means the temperature error is approaching a steady state; if the rate of change of error exceeds the allowable deviation range, it means the temperature error will change. For example, in the case of temperature overshoot, a negative rate of change of error represents a cooling trend, the temperature error will decrease, and the temperature will drop; in the case of temperature overshoot, a positive rate of change of error represents a heating trend, the temperature error will increase, and the temperature will increase overshoot. In the case of temperature under-adjustment, the rate of change of the negative polarity error represents a cooling trend, the temperature error will increase, and the temperature will be further under-adjusted; in the case of temperature under-adjustment, the rate of change of the positive polarity error represents a heating trend, the temperature error will decrease, and the temperature will rise.

[0049] Step S13: Determine the corresponding proportional coefficient variable and integral coefficient variable based on the temperature error and the rate of change of error.

[0050] There is a certain correspondence between temperature error and the rate of change of error, and the proportional coefficient and integral coefficient variables. Therefore, the corresponding proportional coefficient and integral coefficient variables can be calculated based on the temperature error and the rate of change of error.

[0051] In some embodiments, the temperature error e(t) and the rate of change of error ec(t) can be subjected to fuzzy control processing to obtain the proportional coefficient variable ΔKp and integral coefficient variable ΔKi corresponding to the temperature error e(t) and the rate of change of error ec(t).

[0052] Please refer to the following: Figure 5 and Figure 6 The fuzzy control processing is based on a fuzzy control knowledge base, which includes preset input membership functions, preset fuzzy rules, and preset output membership functions. Therefore, the process of performing fuzzy control processing on the temperature error e(t) and the rate of change of error ec(t) can include the following steps: Step S131: Determine the fuzzy level of temperature error based on temperature error, and determine the fuzzy level of error change rate based on error change rate.

[0053] It is understandable that the fuzziness level of temperature error is related to the temperature error, and the fuzziness level of error change rate is related to the error change rate.

[0054] For example, suppose the temperature error e(t) is divided into 7 fuzzy levels: Level 1 is large negative (i.e., severe temperature overshoot), Level 2 is medium negative (i.e., moderate temperature overshoot), Level 3 is small negative (i.e., slight temperature overshoot), Level 4 is close (i.e., the temperature is close to or equal to the target temperature, tending to steady state), Level 5 is small positive (i.e., slight temperature undershoot), Level 6 is medium positive (i.e., moderate temperature undershoot), and Level 7 is large positive (i.e., severe temperature undershoot).

[0055] The rate of change of error ec(t) is divided into 7 fuzzy levels: Level 1 is large positive (i.e., the temperature error increases significantly, severely aggravating overshoot or undershoot), Level 2 is medium positive (i.e., the temperature error increases moderately, moderately aggravating overshoot or undershoot), Level 3 is small positive (i.e., the temperature error increases slightly, slightly aggravating overshoot or undershoot), Level 4 is close (i.e., the temperature error is close to or equal to zero, tending to a steady state), Level 5 is small negative (i.e., the temperature error decreases slightly, slightly reducing overshoot or undershoot), Level 6 is medium negative (i.e., the temperature error decreases moderately, moderately reducing overshoot or undershoot), and Level 7 is large negative (i.e., the temperature error decreases significantly, greatly reducing overshoot or undershoot).

[0056] Assuming the current temperature error e(t) is 10℃ and the error change rate ec(t) is -2℃ / min, then the fuzzy level of the temperature error is 7 (i.e., large positive) and the fuzzy level of the error change rate is 5 (i.e., small negative).

[0057] In some embodiments, the input membership function indicates the mapping relationship between the fuzzy level of temperature error and temperature error, and the mapping relationship between the fuzzy level of error change rate and error change rate. Therefore, in step S131, the temperature error and error change rate can be fuzzified by the input membership function to obtain the fuzzy level of temperature error to which the temperature error belongs, and the fuzzy level of error change rate to which the error change rate belongs.

[0058] Step S132: Determine the adjustment level of the proportional coefficient and the adjustment level of the integral coefficient based on the fuzziness level of the temperature error, the fuzziness level of the error change rate, and the preset fuzziness rules.

[0059] It can be understood that the fuzzy rules indicate the correspondence between the proportional coefficient adjustment level, the integral coefficient adjustment level, and the fuzzy levels of temperature error and error change rate. Therefore, in step S132, the corresponding proportional coefficient adjustment level and integral coefficient adjustment level can be obtained by performing fuzzy reasoning on the fuzzy levels of temperature error and error change rate through fuzzy rules.

[0060] For ease of understanding, the example from step S131 will be used as an example for illustration. In this example, the fuzzy rules are shown in Tables 1 and 2.

[0061] Table 1 represents the adjustment levels of the proportional coefficient under each temperature error fuzziness level (i.e., the first column, denoted as e) and each error change rate fuzziness level (i.e., the first row, denoted as ec). Different proportional coefficient adjustment levels represent different adjustment magnitudes of the proportional coefficient. For example, in this example, with level 4 as the center, the further the proportional coefficient adjustment level deviates from level 4, the greater the adjustment magnitude of the proportional coefficient. Levels less than 4 are negative adjustments, and levels greater than 4 are positive adjustments. Therefore, the increase or decrease magnitude of the proportional coefficient at level 4 is close to or equal to 0, the decrease magnitude of the proportional coefficient at level 1 is the largest, and the increase magnitude of the proportional coefficient at level 7 is the largest.

[0062] Table 1 Table 2 represents the integral coefficient adjustment levels for each temperature error fuzziness level (i.e., the first column, denoted as e) and each error change rate fuzziness level (i.e., the first row, denoted as ec). Different integral coefficient adjustment levels represent different adjustment magnitudes for the integral coefficient. For example, in this example, with level 4 as the center, the further the integral coefficient adjustment level deviates from level 4, the greater the adjustment magnitude of the integral coefficient. Levels less than 4 are positive adjustments, and levels greater than 4 are negative adjustments. Therefore, the increase or decrease magnitude of the integral coefficient at level 4 is close to or equal to 0, the increase magnitude of the integral coefficient at level 1 is the largest, and the decrease magnitude of the integral coefficient at level 7 is the largest.

[0063] Table 2 Therefore, in step S132, the proportional coefficient adjustment level can be obtained by looking up Table 1 based on the fuzziness level of the temperature error and the fuzziness level of the error change rate, and the integral coefficient adjustment level can be obtained by looking up Table 2 based on the fuzziness level of the temperature error and the fuzziness level of the error change rate. For example, if the fuzziness level of the temperature error is 7 and the fuzziness level of the error change rate is 7, the proportional coefficient adjustment level can be obtained as 7 and the integral coefficient adjustment level as 4 after looking up the tables.

[0064] As can be seen from Tables 1 and 2, the fuzzy rules include: (1) When the temperature error fuzzy level represents temperature overshoot and the error change rate fuzzy level represents the temperature rise trend, the greater the temperature rise trend represented by the error change rate fuzzy level, the greater the proportional coefficient adjustment level and the smaller the integral coefficient adjustment level.

[0065] (2) When the temperature error fuzzy level represents the temperature under-adjustment and the error change rate fuzzy level represents the cooling trend, the greater the cooling trend represented by the error change rate fuzzy level, the greater the proportional coefficient adjustment level and the smaller the integral coefficient adjustment level.

[0066] (3) When the temperature error fuzzy level represents temperature overshoot and the error change rate fuzzy level represents cooling trend, the greater the cooling trend represented by the error change rate fuzzy level, the smaller the proportional coefficient adjustment level and the larger the integral coefficient adjustment level.

[0067] (4) When the temperature error fuzzy level represents the temperature under-adjustment and the error change rate fuzzy level represents the temperature rise trend, the greater the temperature rise trend represented by the error change rate fuzzy level, the smaller the proportional coefficient adjustment level and the larger the integral coefficient adjustment level.

[0068] In other words, when the temperature deviates and there is a tendency for the deviation to intensify, increasing the proportional gain to strengthen the proportional effect can quickly bring the temperature back down, while decreasing the integral gain to weaken the integral effect can prevent integral saturation and amplified overshoot. When the temperature deviates and there is a tendency for the deviation to weaken, decreasing the proportional gain to weaken the proportional effect can prevent overshoot and oscillation, while increasing the integral gain to strengthen the integral effect can eliminate steady-state error.

[0069] For example, when the temperature error fuzziness level is 1 and the error change rate fuzziness level is 1, the temperature overshoot is likely to continue. Therefore, the largest proportional coefficient adjustment level (i.e., level 7) can be selected to increase Kp and speed up the system response. At the same time, the smallest integral coefficient adjustment level (i.e., level 1) can be selected to decrease Ki, thereby avoiding integral saturation. This effectively suppresses overshoot and improves dynamic performance, allowing the actual temperature to quickly stabilize near the target temperature.

[0070] For example, when the temperature error fuzziness level is 1 and the error change rate fuzziness level is 7, the temperature overshoots and has a relatively large downward trend. Therefore, the proportional coefficient adjustment level can be appropriately reduced (i.e., adjusted to level 4) to appropriately reduce Kp, while the integral coefficient adjustment level can be appropriately increased (i.e., adjusted to level 3) to appropriately increase Ki, so as to avoid temperature oscillation and make the temperature stabilize quickly.

[0071] Therefore, based on fuzzy rules, the integral coefficient and proportional coefficient can be adjusted in a coordinated manner, so that the actual temperature can be accurately approximated and stabilized at the target temperature, making the temperature control have fast response, high control accuracy and high stability.

[0072] Step S133: Determine the proportional coefficient variable based on the proportional coefficient adjustment level, and determine the integral coefficient variable based on the integral coefficient adjustment level.

[0073] It is understandable that the proportional coefficient variable is related to the proportional coefficient adjustment level, and the integral coefficient variable is related to the integral coefficient adjustment level. For example, when the proportional coefficient adjustment level is 7, the proportional coefficient variable ΔKp is 120% of the proportional coefficient base value. When the proportional coefficient adjustment level is 1, the proportional coefficient variable ΔKp is -20% of the proportional coefficient base value.

[0074] In some embodiments, the output membership function indicates the mapping relationship between the proportional coefficient variable and the proportional coefficient adjustment level, and the mapping relationship between the integral coefficient variable and the integral coefficient adjustment level. Therefore, in step S133, the proportional coefficient adjustment level and the integral coefficient adjustment level can be clarified by the output membership function to obtain the proportional coefficient variable ΔKp corresponding to the proportional coefficient adjustment level and the integral coefficient variable ΔKi corresponding to the integral coefficient adjustment level.

[0075] Step S14: Determine the corresponding proportional coefficient base value and integral coefficient base value based on the actual temperature at the current moment.

[0076] The proportional gain base value Kpbase is negatively correlated with the actual temperature of the semiconductor heater, while the integral gain base value Kibase is positively correlated with the actual temperature of the semiconductor heater. For example, when the actual temperature is <300℃ (i.e., the low-temperature range), Kpbase is 100% of the initial value of the proportional gain, and Kibase is 80% of the initial value of the integral gain. When the actual temperature is ≥300℃ (i.e., the high-temperature range), Kpbase decreases to 60% of the initial value of the proportional gain as the temperature increases, while Kibase increases to 150% of the initial value of the integral gain. The initial values ​​of both the proportional gain and the integral gain can be set according to the actual situation and are not limited here.

[0077] In some embodiments, the relationship between the proportional coefficient base value Kpbase and the actual temperature of the semiconductor heater can be expressed as a negative linear function, and the relationship between the integral coefficient base value Kibase and the actual temperature of the semiconductor heater can be expressed as a positive linear function. Therefore, in step S14, the proportional coefficient base value Kpbase corresponding to the actual temperature can be calculated using a negative linear function, and the integral coefficient base value Kibase corresponding to the actual temperature can be calculated using a positive linear function.

[0078] Step S15: Determine the target proportional coefficient based on the proportional coefficient variable and the proportional coefficient base value, and determine the target integral coefficient based on the integral coefficient variable and the integral coefficient base value.

[0079] Specifically, the target proportional coefficient Kptarget can be obtained by superimposing the proportional coefficient variable ΔKp and the proportional coefficient base value Kpbase, and the target integral coefficient Kitarget can be obtained by superimposing the integral coefficient variable ΔKi and the integral coefficient base value Kibase. This can be expressed as follows: Kptarget=Kpbase+a △Kp (3).

[0080] Kitarget = Kibase + b △Ki (4).

[0081] Here, a and b are preset fixed coefficients. The values ​​of a and b can be set according to the actual situation, for example, a and b can both be 1, which is not limited here.

[0082] Step S16: Control the actual temperature of the semiconductor heater according to the temperature error, the target proportional coefficient, and the target integral coefficient, so that the actual temperature of the semiconductor heater reaches the target temperature.

[0083] For example, you can first determine the temperature error. Obtain the target integral error Then based on the temperature error Target scaling factor Kpbase, target integral factor Kitarget, and target integral error The control parameters obtained through processing are: (5).

[0084] in, For the P term in fuzzy PI control, This refers to the I term of the fuzzy PI control. Control parameters. For example, it could be the operating parameters of a power supply, and then a control signal could be generated based on these parameters. This control signal can be used to regulate the power of the semiconductor heater 10 (e.g., controlling power ≤ 200W, or controlling the power change rate ≤ 100W / min), thereby regulating the actual temperature of the semiconductor heater 10 so that the actual temperature accurately and smoothly approaches the target temperature and eventually stabilizes at the target temperature.

[0085] In some embodiments, after step S15 and before step S16, the temperature control method may further include the following steps: Confirm whether the actual temperature of the semiconductor heater meets the preset stability conditions.

[0086] If yes, then maintain the target proportional coefficient and target integral coefficient unchanged. If no, then redetermine the target proportional coefficient and target integral coefficient.

[0087] The stability conditions can include, for example, all of the following conditions: Condition 1: The temperature difference between the actual temperature of the inner zone and the actual temperature of the outer zone of the semiconductor heater is less than or equal to the first set value.

[0088] Condition 2: The temperature error between the actual temperature of the inner zone and the target temperature, and the temperature error between the actual temperature of the outer zone and the target temperature, are both no greater than the second set value.

[0089] Condition 3: The oscillation frequency of the actual temperature in the inner zone and the oscillation frequency of the actual temperature in the outer zone are both not greater than the third set value.

[0090] For example, the controller can periodically (e.g. every second) determine whether the temperature difference between the actual temperature of the inner zone and the actual temperature of the outer zone is less than or equal to 2°C (i.e., the first set value), and at the same time, whether the temperature error of the actual temperature of the inner zone relative to the target temperature and the temperature error of the actual temperature of the outer zone relative to the target temperature are both less than or equal to 2°C (i.e., the second set value), and whether the oscillation frequency of the actual temperature of the inner zone and the oscillation frequency of the actual temperature of the outer zone are both less than or equal to 1 time / min (i.e., the third set value).

[0091] If so, it means that the actual temperature of the semiconductor heater meets the stability condition, and the current target proportional coefficient and target integral coefficient remain unchanged. Otherwise, return to step S11 to redetermine the target proportional coefficient and target integral coefficient, that is, to re-perform fuzzy PI control.

[0092] Specifically, if the actual temperature exceeds the allowable fluctuation range, it can be determined that the actual temperature is fluctuating. The first, second, and third settings, as well as the allowable fluctuation range, can all be set according to the actual situation and are not limited here.

[0093] This design ensures stable temperature control, improves the accuracy of fuzzy PI control, and reduces the risk of ceramic substrate breakage.

[0094] In summary, the temperature control method for a semiconductor heater provided in this application has at least the following advantages: 1. Significantly improves temperature control accuracy and process stability, effectively ensuring product yield: By adaptively adjusting the proportional and integral coefficient variables through fuzzy PI control, combined with dynamically adjusting the base values ​​of the proportional and integral coefficients, the PI parameters can be dynamically optimized, effectively eliminating the steady-state error and overshoot oscillation problems caused by fixed PI parameters in traditional PI control methods. In some experiments, the method of this application can control the steady-state error of the semiconductor heater temperature within ±0.5℃, which is far superior to the ±3℃ accuracy of traditional PI control methods. At the same time, it avoids the mutual coupling interference between the inner and outer temperatures of the ceramic substrate, avoiding the risk of heating plate breakage due to excessive temperature difference, and significantly improves the uniformity and stability of the temperature field of the ceramic substrate, reducing the uniformity error of thin film deposition on the wafer surface by more than 50%, effectively ensuring the yield of semiconductor products and reducing the scrap rate in the production process.

[0095] 2. Precisely adapts to nonlinear thermal dynamic systems, significantly enhancing operational adaptability: The fuzzy PI adaptive control mechanism can dynamically adjust PI parameters based on the temperature error e(t) and the error change rate ec(t), achieving precise adaptation to nonlinear thermal dynamic characteristics. Combined with the adjustment strategy of the proportional coefficient base value and the integral coefficient base value, it can indirectly expand the parameter adjustment range of fuzzy PI control, further optimizing parameter adaptability in high-temperature ranges and completely solving the core defect of traditional linear PI control in being unable to handle both high and low temperature environments.

[0096] In addition, the synergistic effect of fuzzy PI adaptive control and PI base value adjustment strategy enables the temperature control to have strong disturbance compensation capability, effectively resisting the influence of various interference factors such as air volume fluctuations, pressure changes, and ambient temperature changes in actual processes; even under complex process disturbances, it can still maintain the stability of ceramic substrate temperature, avoiding process interruptions or product defects caused by temperature fluctuations, significantly improving the reliability and continuity of semiconductor thin film deposition equipment operation, and reducing equipment maintenance costs.

[0097] Moreover, the proportional coefficient adjustment level and the integral coefficient adjustment level are based on the same temperature error and error change rate as well as the same fuzzy rule, so there is a specific correlation between them. This allows the dynamically adjusted proportional coefficient and integral coefficient to work synergistically in temperature control, achieving a faster response speed and higher control accuracy and stability.

[0098] Therefore, the method of this application embodiment can be well adapted to the complex operating conditions of actual semiconductor manufacturing processes and can maintain stable control performance within the entire process temperature range (e.g., 100℃~600℃).

[0099] 3. Significantly reduced temperature stabilization time and improved production efficiency: The method described in this application can quickly respond to fluctuations in process parameters (such as changes in airflow and pressure) and changes in thermal dynamic characteristics, accelerating the attainment of a stable temperature control state. In some experiments, compared with traditional PI control methods, the temperature stabilization time of the method described in this application is reduced by more than 40%, the total cycle of a single thin film deposition process is significantly shortened, and the wafer throughput per unit time is increased, effectively improving the production efficiency of semiconductor thin film deposition and meeting the needs of large-scale production in the semiconductor manufacturing industry.

[0100] In addition, the integral term design of the traditional PI control method has obvious defects. For example, the ceramic substrate 11 has a large heat capacity and a slow heating rate. When PI control is used for a long time, the integral term will continue to accumulate temperature error, resulting in abnormally high output heating power. This not only wastes energy, but may also accelerate the aging of the heating element, or even cause local overheating and damage to the ceramic substrate 11.

[0101] For this, please refer to Figure 7 Step S16 in this embodiment may include the following steps: Step S161: Integrate the temperature error to obtain the initial integral error.

[0102] In other words, the initial integration error .

[0103] Step S162: Determine the target integration error based on the initial integration error.

[0104] Specifically, step S162 may include the following sub-steps: Step S162A: When the initial integration error is greater than 0 and less than the preset upper limit value, the initial integration error is taken as the target integration error.

[0105] In other words, the initial integration error is when the integral is not saturated. The magnitude is acceptable, therefore it can be directly used as the target integration error. use.

[0106] Step S162B: When the initial integration error is greater than or equal to the preset upper limit value, the preset upper limit value is taken as the target integration error.

[0107] In other words, when integration reaches saturation, it's necessary to freeze the integration accumulation to prevent the integration error from increasing. The preset upper limit can be set according to actual conditions, for example, to 2% of the target temperature. When the preset upper limit value is reached, the target integral error It will be fixed at the preset upper limit value.

[0108] Step S162C: When the initial integration error is less than 0, multiply the initial integration error by the preset attenuation coefficient to obtain the target integration error.

[0109] In other words, if the integration error accumulates negatively, then the initial integration error will be... Multiplying by a preset attenuation coefficient K reduces the integral error. The preset attenuation coefficient can be set according to the actual situation, for example, to 1.5.

[0110] Step S163: Control the actual temperature of the semiconductor heater based on the temperature error, target proportional coefficient, target integral error, and target integral coefficient.

[0111] The process of controlling the actual temperature of the semiconductor heater based on the temperature error, target proportional coefficient, target integral error, and target integral coefficient can be referred to the relevant description of step S16 above, and will not be repeated here.

[0112] It is understandable that, based on the steps S161~S163 described above, integral saturation can be suppressed, resulting in a suitable integral error, which is beneficial to the accuracy of PI control. Furthermore, it can avoid the decrease in response speed, stability, and control accuracy, and even problems such as abnormally high power, power and temperature oscillations, caused by oversaturation of the integral error. Therefore, it is beneficial to improve the controllability, temperature control accuracy, and temperature control stability of the semiconductor heater, achieving stable heating and reducing the risk of ceramic substrate breakage and high-temperature aging of the heating element.

[0113] In addition, the integral term design of traditional PI control has other obvious defects. For example, in small-range temperature rise scenarios (such as rising from 100℃ to 110℃, with a temperature difference of only 10℃), if the integral function is activated too early, the integral term will quickly accumulate a small temperature error, resulting in excessive output power (i.e., overshoot). Then the integral term accumulates in the opposite direction, resulting in insufficient output power (i.e., undershoot), and so on. This leads to oscillations between power and temperature, destroying control stability and making it impossible to achieve smooth temperature rise.

[0114] Therefore, the temperature control method in this application embodiment may further include: Step A: When the actual temperature at the current moment is less than the first preset temperature threshold, control the actual temperature of the semiconductor heater to change according to the preset target rate.

[0115] Step B: When the actual temperature at the current moment is greater than or equal to the first preset temperature threshold and less than the second preset temperature threshold, determine the corresponding proportional coefficient variable and integral coefficient variable based on the temperature error and the rate of change of error, wherein the integral coefficient variable is 0.

[0116] Step C: When the actual temperature at the current moment is greater than or equal to the second preset temperature threshold, determine the corresponding proportional coefficient variable and integral coefficient variable based on the temperature error and the rate of change of error, wherein the integral coefficient variable is not 0.

[0117] The first preset temperature threshold can be, for example, a temperature value or temperature range within 90% to 95% of the target temperature, or, for example, the target temperature minus a set temperature value (e.g., target temperature - 10℃). The second preset temperature threshold can be, for example, the sum of half the temperature difference between the target temperature and the first preset temperature threshold, or, for example, the sum of half the set temperature value and the first preset temperature threshold. The target rate can be, for example, 3℃ / min, 0.015℃ / s, etc. It should be understood that the first preset temperature threshold, the second preset temperature threshold, and the target rate can all be set according to actual conditions and are not limited to the examples provided in this application.

[0118] For example, assuming the initial temperature of the semiconductor heater is 20°C, the target temperature is 100°C, and the set temperature value is 10°C, then the first preset temperature threshold is 90°C and the second preset temperature threshold is 95°C.

[0119] So, if Figure 8 As shown, before the actual temperature of the semiconductor heater reaches 90°C, that is, when it is in the range of [20°C, 90°C), the actual temperature of the semiconductor heater is controlled to rise at a fixed target rate. This control method can be called the slope control method.

[0120] Once the actual temperature of the semiconductor heater reaches 90℃, i.e., within the range of [90℃, 100℃], the actual temperature of the semiconductor heater is controlled according to the aforementioned steps S11~S16. This control method can be called fuzzy PI control. Specifically, when the actual temperature of the semiconductor heater is within the range of [90℃, 95℃), the integral coefficient is 0, meaning the integral coefficient does not participate in temperature control; therefore, this is actually a dynamic PI control method. When the actual temperature of the semiconductor heater is within the range of [95℃, 100℃], the integral coefficient is not 0, meaning the integral coefficient participates in temperature control; therefore, this is also a dynamic PI control method.

[0121] It is understandable that, based on steps A through C above, integral separation and delayed activation can be achieved, avoiding power oscillation issues caused by premature activation of the integral in small-scale heating scenarios. Furthermore, different control methods can be employed to address the distinctly different thermal dynamic characteristics of the semiconductor heater 10 in high-temperature and low-temperature ranges (e.g., approximately linear in the low-temperature range and nonlinear in the high-temperature range), thus avoiding heating lag in the low-temperature range and over- or under-temperature control in the high-temperature range. This achieves refined control of the entire heating process of the semiconductor heating device, improving temperature control accuracy, efficiency, and long-term stability, which is beneficial to the production efficiency and quality of semiconductor thin film deposition.

[0122] In summary, the method of this application, based on steps S161-S163 and steps A-C, proposes an integral saturation upper limit constraint, precise limitation of integral separation activation conditions, and a negative cumulative decay mechanism for integral errors. Based on the synergistic effect of these three mechanisms, integral control can be rationally designed, fundamentally solving the problem of abnormally high power caused by excessive accumulation of the integral term in traditional PI control. Simultaneously, it effectively avoids power oscillations caused by premature activation of the integral term in small-range temperature rise scenarios. Experimental verification shows that after adopting the method of this application, the power fluctuation amplitude of the semiconductor heater is reduced by more than 60%, the temperature error is controlled within 2℃, and the temperature control stability is significantly improved.

[0123] It should be noted that, for the sake of simplicity, the aforementioned method embodiments are described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, because according to this application, some steps may be performed in other orders or simultaneously.

[0124] This application also provides a temperature control system for a semiconductor heater. This temperature control system can be applied to semiconductor heating equipment with a semiconductor heater, such as a thin film deposition equipment.

[0125] Please refer to it again. Figure 2 The temperature control system 100 includes a connected temperature sensor 60 and a controller 50. The controller 50 can be used to obtain the actual temperature of the semiconductor heater through the temperature sensor 60. The controller 50 can be used to implement the above-mentioned temperature control method for the semiconductor heater to control the heating temperature of the semiconductor heater.

[0126] It should be understood that other details regarding the temperature sensor 60, controller 50, and semiconductor heater can be found in the preceding descriptions and will not be repeated here.

[0127] This application also provides a temperature control device. This temperature control device can be used to implement the temperature control method for the semiconductor heater described above.

[0128] The temperature control device includes an acquisition module, a calculation module, a first determination module, a second determination module, a third determination module, and a control module.

[0129] The first acquisition module is used to acquire the actual temperature of the semiconductor heater.

[0130] The calculation module is used to calculate the temperature error and error change rate based on the actual temperature of the semiconductor heater. The temperature error is the difference between the preset target temperature and the actual temperature at the sampling time. The error change rate is the ratio of the difference between the temperature error at the current time and the temperature error at the previous time to the time interval between the current time and the previous time.

[0131] The first determining module is used to determine the corresponding proportional coefficient variable and integral coefficient variable based on the temperature error and the rate of change of the error.

[0132] The second determining module is used to determine the corresponding proportional coefficient base value and integral coefficient base value based on the actual temperature at the current moment.

[0133] The third determination module is used to determine the target proportional coefficient based on the proportional coefficient variable and the proportional coefficient base value, and to determine the target integral coefficient based on the integral coefficient variable and the integral coefficient base value.

[0134] The control module is used to control the actual temperature of the semiconductor heater based on the temperature error, the target proportional coefficient, and the target integral coefficient, so that the actual temperature of the semiconductor heater reaches the target temperature.

[0135] It is understood that the division of the various modules in the above temperature control device is only for illustrative purposes. In other embodiments, the temperature control device can be divided into different modules as needed to complete all or part of the functions of the above temperature control device.

[0136] The specific implementation of each module in the embodiments of this application can also refer to the corresponding descriptions in the preceding temperature control method embodiments, and therefore will not be detailed here. The above-mentioned temperature control device may also include more modules to implement other steps mentioned in the preceding temperature control method.

[0137] In the various embodiments of this application, all functional modules can be integrated into one processing module / unit, or each module can be a separate module, or two or more modules can be integrated into one module; the integrated module can be implemented in hardware or in the form of hardware plus software functional modules.

[0138] If the integrated modules described above in this application are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROM, RAM, magnetic disks, or optical disks.

[0139] This application also provides a computer-readable storage medium for storing computer programs or code, which, when loaded and executed by a processor, implement all or part of the steps in the above-described temperature control method. The computer-readable storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules or other data), which are not listed here.

[0140] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application and are not intended to limit it. Although this application has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of this application without departing from the spirit and scope of the technical solutions of this application.

Claims

1. A method for temperature control of a semiconductor heater, characterized in that, The temperature control method includes: Obtain the actual temperature of the semiconductor heater; The temperature error and error change rate are calculated based on the actual temperature of the semiconductor heater; the temperature error is the difference between the preset target temperature and the actual temperature at the sampling time, and the error change rate is the ratio of the difference between the temperature error at the current time and the temperature error at the previous time to the time interval between the current time and the previous time. Determine the corresponding proportional coefficient variable and integral coefficient variable based on the temperature error and the rate of change of the error; Determine the corresponding proportional coefficient base value and integral coefficient base value based on the actual temperature at the current moment; The target proportional coefficient is determined based on the proportional coefficient variable and the proportional coefficient base value; the target integral coefficient is determined based on the integral coefficient variable and the integral coefficient base value. The actual temperature of the semiconductor heater is controlled based on the temperature error, the target proportional coefficient, and the target integral coefficient, so that the actual temperature of the semiconductor heater reaches the target temperature.

2. The temperature control method as described in claim 1, characterized in that, The step of determining the corresponding proportional coefficient variable and integral coefficient variable based on the temperature error and the rate of change of the error includes: The temperature error fuzziness level is determined based on the temperature error, and the error change rate fuzziness level is determined based on the error change rate. Based on the temperature error fuzziness level, the error change rate fuzziness level, and the preset fuzziness rules, the proportional coefficient adjustment level and the integral coefficient adjustment level are determined; wherein, the fuzziness rules are used to indicate the correspondence between the proportional coefficient adjustment level, the integral coefficient adjustment level, and the temperature error fuzziness level and the error change rate fuzziness level; The proportional coefficient variable is determined based on the proportional coefficient adjustment level, and the integral coefficient variable is determined based on the integral coefficient adjustment level; wherein, the proportional coefficient variable is related to the proportional coefficient adjustment level, and the integral coefficient variable is related to the integral coefficient adjustment level.

3. The temperature control method as described in claim 2, characterized in that, The fuzzy rules include: When the temperature error fuzzy level represents temperature overshoot and the error change rate fuzzy level represents the temperature rise trend, the greater the temperature rise trend represented by the error change rate fuzzy level, the greater the proportional coefficient adjustment level and the smaller the integral coefficient adjustment level. When the temperature error fuzzy level represents temperature under-adjustment and the error change rate fuzzy level represents cooling trend, the greater the cooling trend represented by the error change rate fuzzy level, the greater the proportional coefficient adjustment level and the smaller the integral coefficient adjustment level. When the temperature error fuzzy level represents temperature overshoot and the error change rate fuzzy level represents cooling trend, the greater the cooling trend represented by the error change rate fuzzy level, the smaller the proportional coefficient adjustment level and the larger the integral coefficient adjustment level. When the temperature error fuzzy level represents temperature under-adjustment and the error change rate fuzzy level represents the temperature rise trend, the greater the temperature rise trend represented by the error change rate fuzzy level, the smaller the proportional coefficient adjustment level, and the larger the integral coefficient adjustment level.

4. The temperature control method as described in claim 1, characterized in that, The proportional coefficient base value is negatively correlated with the actual temperature of the semiconductor heater, and the integral coefficient base value is positively correlated with the actual temperature of the semiconductor heater.

5. The temperature control method as described in claim 1, characterized in that, The step of controlling the actual temperature of the semiconductor heater based on the temperature error, the target proportional coefficient, and the target integral coefficient includes: The temperature error is integrated to obtain the initial integral error; The target integration error is determined based on the initial integration error. The actual temperature of the semiconductor heater is controlled based on the temperature error, the target proportional coefficient, the target integral error, and the target integral coefficient.

6. The temperature control method as described in claim 5, characterized in that, Determining the target integration error based on the initial integration error includes: When the initial integration error is greater than 0 and less than the preset upper limit value, the initial integration error is taken as the target integration error; Alternatively, when the initial integration error is greater than or equal to a preset upper limit value, the preset upper limit value is used as the target integration error; Alternatively, when the initial integration error is less than 0, the initial integration error is multiplied by a preset attenuation coefficient to obtain the target integration error.

7. The temperature control method according to any one of claims 1 to 6, characterized in that, After determining the target proportional coefficient and the target integral coefficient, the temperature control method further includes: Confirm whether the actual temperature of the semiconductor heater meets the preset stability conditions; If yes, then the target proportional coefficient and the target integral coefficient remain unchanged; if no, then the target proportional coefficient and the target integral coefficient are redefined. The semiconductor heater includes an inner region and an outer region, and the stabilization conditions include: The temperature difference between the actual temperature of the inner zone and the actual temperature of the outer zone is less than or equal to a first set value; And, the temperature error of the actual temperature of the inner zone relative to the target temperature and the temperature error of the actual temperature of the outer zone relative to the target temperature are both not greater than the second set value; And, the oscillation frequency of the actual temperature in the inner region and the oscillation frequency of the actual temperature in the outer region are both not greater than the third set value.

8. The temperature control method according to any one of claims 1 to 6, characterized in that, The temperature control method further includes: When the actual temperature at the current moment is less than a first preset temperature threshold, the actual temperature of the semiconductor heater is controlled to change at a preset target rate. When the actual temperature at the current moment is greater than or equal to the first preset temperature threshold and less than the second preset temperature threshold, the corresponding proportional coefficient variable and integral coefficient variable are determined according to the temperature error and the error change rate, wherein the integral coefficient variable is 0; When the actual temperature at the current moment is greater than or equal to the second preset temperature threshold, the corresponding proportional coefficient variable and integral coefficient variable are determined according to the temperature error and the error change rate, wherein the integral coefficient variable is not 0.

9. A temperature control system for a semiconductor heater, characterized in that, The temperature control system includes a temperature sensor and a controller. The temperature sensor is disposed adjacent to the semiconductor heater and is used to detect the actual temperature of the semiconductor heater. The controller is electrically connected to the temperature sensor and the semiconductor heater and is used to execute the temperature control method as described in any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, which is loaded by a processor to execute the temperature control method as described in any one of claims 1 to 8.

Images