Column box heating and cooling control method

Abstract

The invention relates to the technical field of column box temperature control, in particular to a column box heating and cooling control method, which ensures accurate temperature control by setting linear control heating and fuzzy control cooling and according to real-time temperature error and power dynamic adjustment, can consider heating stability and repeatability, and can reduce fluctuation during cooling, thereby improving the accuracy of column box temperature control. According to the control mode, temperature adjustment is optimized through an intelligent algorithm, it is ensured that the temperature in the column box is evenly distributed, GC analysis precision and efficiency are improved, and the method is suitable for detection of various complex samples.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of column oven temperature control, and particularly relates to a column oven temperature control method. BACKGROUND

[0002] The column oven is a key supporting device of the high performance liquid chromatograph, and is mainly used for accurately controlling the working temperature of the column, so as to meet the requirements of the pharmacopoeia and the modern analysis method on the column temperature, improve the column efficiency, improve the chromatographic peak separation degree, and ensure the repeatability of the analysis result.

[0003] When the temperature of the column oven is linearly controlled, there are some fluctuations or response delays. Purely controlling according to the temperature stage target may cause temperature rising fluctuations. Purely controlling according to the speed and error may cause the temperature curve to be translated if the position is different when starting to rise in temperature, thereby affecting the temperature rising repeatability. When the temperature is lowered, there are mainly problems of large fluctuations and long time, and if the air door is not reasonably designed, there may also be oscillations in the later stage of the temperature lowering process. Therefore, the present application provides a column oven temperature control method. SUMMARY

[0004] In order to solve the above technical problems in the prior art, the present application provides a column oven temperature control method.

[0005] In order to solve the above technical problems, the present application provides the following technical scheme: a column oven temperature control method, the control method comprising the following steps:

[0006] S1, linearly rising in temperature

[0007] It is judged whether the current temperature reaches the stage target temperature. If the current temperature does not reach the stage target temperature, the temperature is normally controlled by PID, the air door is closed, and the fan speed is reduced, so that the temperature rising speed is accelerated.

[0008] If the current temperature reaches the stage target temperature, it is judged whether the rising rate is consistent. If the rising rate is too high, the heating power is reduced, otherwise the heating power is increased, so as to ensure uniform temperature rising. When the heating power is controlled to be reduced, the temperature rising amplitude in each time interval of the linear temperature rising is the same.

[0009] S2, fuzzy control for lowering temperature

[0010] The fan power and the air door angle are dynamically adjusted according to the difference between the current temperature and the final target temperature and the size of the heating power. When the difference between the current temperature and the final target temperature and the heating power are both large, the air door angle is quickly adjusted.

[0011] When the difference between the current temperature and the final target temperature and the heating power are both small, the air door angle is finely adjusted, and the fan runs at low speed.

[0012] Preferably, step S1 specifically includes the following:

[0013] S11, determine a final target temperature PID parameter value with overshoot and no oscillation by self-tuning or the number-matching method as a reference. Overshoot and no oscillation means that the second overshoot is within 1 / 4 of the first overshoot.

[0014] S12: Set the linear heating rate and calculate the target temperature for each stage based on the linear heating rate. Gradually approaching the final target temperature, ensuring that temperature changes at each step are controllable;

[0015] S13 uses PID control to heat the system to reach the target temperature for a given stage. During heating, the damper is closed, and the fan speed is reduced to the default speed. After reaching the target temperature, it checks whether the actual temperature increase is equal to the theoretical increase. If the actual increase is less than the theoretical increase, the heating power is increased; otherwise, it is decreased. Let represent the integral value at the initial time step, then the integral value calculated at the current time step. for:

[0016] ;

[0017] exist If the heating power remains constant, then the change in heating power is:

[0018] ;

[0019] in, This represents the speed coefficient, which can be 1 or the I value in PID control. This represents the integral value at the previous moment. This indicates the rate difference after a single temperature increase. Indicates the temperature difference. This represents the I value in the PID controller;

[0020] S14: After the temperature rises normally to the final target temperature according to step S13, it switches to normal PID control.

[0021] Preferably, in step S11, the specific process of determining the PID parameter values ​​through self-tuning is as follows:

[0022] A target temperature is set for the learning process. When the actual temperature is lower than the target temperature, the heating power is 1; when the actual temperature is higher than the target temperature, the heating power is 0. After three cycles, the intermediate quantity is calculated using the amplitude and period via the Åström-Hägglund method. The PID parameter values ​​are calculated using the coefficient scheme provided by Ziegler-Nichols. The calculation formula is as follows:

[0023] ;

[0024] in, This indicates the maximum heating power. This indicates the temperature amplitude.

[0025] Preferably, in step S2, during cooling, PID control directly performs rapid cooling. During the cooling process, it is determined whether the current temperature is the final target temperature, and simultaneously the difference between the current temperature and the final target temperature is determined. The heating power is controlled based on the difference result. Specifically:

[0026] When the difference between the current temperature and the final target temperature is greater than the set error threshold, the damper will be fully opened and the fan will be turned to maximum. At this time, the heating power will be 0.

[0027] When the difference between the current temperature and the final target temperature is less than the set error threshold, the PID controller will control the temperature normally.

[0028] Preferably, in step S2, the difference between the current temperature and the final target temperature is less than a set error threshold, i.e., within the error threshold range. The fan power and damper angle are dynamically adjusted based on the difference between the current temperature and the final target temperature and the magnitude of the heating power, and the damper angle corresponding to the current heating power is calculated. And control is implemented by calculating using a set exponential decay model. The specific calculation formula is as follows:

[0029] ;

[0030] in, The values ​​represent heating power, and 88.37, -0.033, and 4.18 represent parameter values ​​fitted to the experimental gas chromatography equipment according to the exponential decay model.

[0031] The greater the power, the greater the required movement angle of the damper; conversely, the smaller the power, the smaller the required movement angle of the damper.

[0032] The damper angle corresponding to the current power and fan power The linear relationship is:

[0033] ;

[0034] Here, 20, 37, and 50 all represent parameter values ​​fitted to the experimental gas chromatography equipment according to the exponential decay model.

[0035] Preferably, in step S2, the temperature control has a lag, and the temperature difference is related to the control time interval before the moving damper. The relationship is as follows:

[0036] The greater the temperature difference, the more stable the temperature trend, and the shorter the reaction time required to wait for the temperature change before initiating control of the moving damper. The shorter;

[0037] The smaller the temperature difference, the more unstable the temperature trend, and the longer the reaction time required to wait for the temperature change before initiating control of the moving damper. The longer;

[0038] The specific calculation formula is as follows:

[0039] ;

[0040] Among them, 105000, 189, 2, 0.6 and 21 all represent parameter values ​​fitted on the experimental gas chromatography equipment according to the exponential decay model.

[0041] Preferably, in step S2, when the temperature decreases, the temperature decrease follows an exponential decay model. The lower the final target temperature value, the slower the temperature decreases and the less the overshoot. At this point, the node for calculating the heating temperature... According to linear control at the node of heating temperature Initiate heating to reduce overshoot; heating temperature node The calculation formula is:

[0042] ;

[0043] Where X represents the target temperature, and 2, 50 and 1 represent the parameter values ​​fitted on the experimental gas chromatography equipment according to the exponential decay model.

[0044] Preferably, in step S2, when heating begins to reduce overshoot, the PID controller normally controls the temperature and calculates the damper angle corresponding to the current power. and control time interval Based on the calculation results, the damper angle is jointly controlled, and the damper is moved to the damper angle corresponding to the current power according to the calculation results. Then, wait for the control time interval. The temperature is read again for the next control cycle.

[0045] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0046] 1. This invention sets up linear control for heating and fuzzy control for cooling, and dynamically adjusts the temperature based on real-time temperature error and power to ensure accurate temperature control. It can balance stable heating and repeatability, while reducing fluctuations during cooling and suppressing fluctuations in the early stage to prevent later fluctuations. This control method optimizes temperature regulation through intelligent algorithms to ensure uniform temperature distribution in the column oven, improves the accuracy and efficiency of GC analysis, and is suitable for the detection of various complex samples.

[0047] 2. Through a composite control strategy, the system can achieve optimal adjustment at different temperature control stages, significantly improving the accuracy and response speed of temperature control, ensuring the high efficiency and reliability of equipment operation, suitable for column box temperature control requirements, and dynamically adjusting the fan and damper according to the temperature difference and power, accurately controlling heat dissipation, avoiding temperature overshoot, and achieving efficient and stable temperature control. Attached Figure Description

[0048] Fig. 1 This is a schematic diagram of the linear heating process of the present invention;

[0049] Fig. 2 This is a schematic diagram of the cooling fuzzy control process of the present invention;

[0050] Fig. 3 This is a schematic diagram of the PID coefficient scheme of the present invention. Detailed Implementation

[0051] The present invention will be further described below with reference to the accompanying drawings and embodiments, which illustrate the above and other technical features and advantages of the present invention. However, the following embodiments are merely preferred embodiments of the present invention and are not exhaustive.

[0052] Example 1:

[0053] like Figs. 1-3 As shown, the present invention provides a method for controlling the heating and cooling of a column box, the method comprising the following steps:

[0054] S1, linear heating

[0055] Determine if the current temperature has reached the target temperature for the stage: If the current temperature has not reached the target temperature for the stage, the PID controls the temperature normally, while closing the damper and reducing the fan speed to accelerate the heating rate;

[0056] If the current temperature reaches the target temperature for the stage, determine whether the rate of heating is consistent each time. If the rate is too high, reduce the heating power; otherwise, increase it to ensure uniform heating. When controlling the decrease in heating power, the heating amplitude is the same in each time interval of linear heating.

[0057] S2, Fuzzy control cooling

[0058] The fan power and damper angle are dynamically adjusted based on the difference between the current temperature and the final target temperature and the heating power: when both the difference between the current temperature and the final target temperature and the heating power are large, the damper angle is quickly adjusted.

[0059] When the difference between the current temperature and the final target temperature and the heating power are both small, the damper angle is finely adjusted and the fan runs at low speed.

[0060] In this embodiment, step S1 specifically includes the following:

[0061] S11, determine a final target temperature PID parameter value with overshoot and no oscillation by self-tuning or the number-matching method as a reference. Overshoot and no oscillation means that the second overshoot is within 1 / 4 of the first overshoot.

[0062] The first overshoot is within 1 / 4 of the target temperature of 100℃. When the temperature rises, it starts to drop after reaching 101℃. When the temperature drops below 100℃, the power increases. After the second overshoot, the power starts to drop from 100.25℃.

[0063] S12: Set the linear heating rate and calculate the target temperature for each stage based on the linear heating rate. Gradually approaching the final target temperature, ensuring that temperature changes at each step are controllable;

[0064] S13 uses PID control to heat the system to reach the target temperature for a given stage. During heating, the damper is closed, and the fan speed is reduced to the default speed. After reaching the target temperature, it checks whether the actual temperature increase is equal to the theoretical increase. If the actual increase is less than the theoretical increase, the heating power is increased; otherwise, it is decreased. Let represent the integral value at the initial time step, then the integral value calculated at the current time step. for:

[0065] ;

[0066] exist If the heating power remains constant, then the change in heating power is:

[0067] ;

[0068] in, This represents the speed coefficient, which can be 1 or the I value in PID control. This represents the integral value at the previous moment. This indicates the rate difference after a single temperature increase. Indicates the temperature difference. This represents the I value in the PID controller;

[0069] S14: After the temperature rises normally to the final target temperature according to step S13, it switches to normal PID control.

[0070] In this embodiment, the specific process of determining the PID parameter values ​​through self-tuning in step S11 is as follows:

[0071] A target temperature is set for the learning process. When the actual temperature is lower than the target temperature, the heating power is 1; when the actual temperature is higher than the target temperature, the heating power is 0. After three cycles, the intermediate quantity is calculated using the amplitude and period via the Åström-Hägglund method. The PID parameter values ​​are calculated using the coefficient scheme provided by Ziegler-Nichols. The calculation formula is as follows:

[0072] ;

[0073] in, This indicates the maximum heating power. This indicates the temperature amplitude.

[0074] In this embodiment, in step S2, during cooling, the PID control directly performs rapid cooling. During the cooling process, it is determined whether the current temperature is the final target temperature, and at the same time, the difference between the current temperature and the final target temperature is determined. The heating power is controlled based on the difference result. Specifically:

[0075] When the difference between the current temperature and the final target temperature is greater than the set error threshold, the damper will be fully opened and the fan will be turned to maximum. At this time, the heating power will be 0.

[0076] When the difference between the current temperature and the final target temperature is less than the set error threshold, the PID controller will control the temperature normally.

[0077] In this embodiment, in step S2, if the difference between the current temperature and the final target temperature is less than the set error threshold (i.e., within the error threshold range), the fan power and damper angle are dynamically adjusted based on the difference between the current temperature and the final target temperature and the magnitude of the heating power, and the damper angle corresponding to the current power is calculated. And control is implemented by calculating the exponential decay model based on the set heating power and damper angle. The specific calculation formula is as follows:

[0078] ;

[0079] in, The values ​​represent heating power, and 88.37, -0.033, and 4.18 represent parameter values ​​fitted to the experimental gas chromatography equipment according to the exponential decay model.

[0080] The greater the power, the greater the required movement angle of the damper; conversely, the smaller the power, the smaller the required movement angle of the damper.

[0081] The damper angle corresponding to the current power and fan power The linear relationship is:

[0082] ;

[0083] Here, 20, 37, and 50 all represent parameter values ​​fitted to the experimental gas chromatography equipment according to the exponential decay model.

[0084] In this embodiment, in step S2, the temperature control has a lag, which is the time interval between the temperature difference and the control before the moving damper. The relationship is as follows:

[0085] The greater the temperature difference, the more stable the temperature trend, and the shorter the reaction time required to wait for the temperature change before initiating control of the moving damper. The shorter;

[0086] The smaller the temperature difference, the more unstable the temperature trend, and the longer the reaction time required to wait for the temperature change before initiating control of the moving damper. The longer;

[0087] The specific calculation formula is as follows:

[0088] ;

[0089] Among them, 105000, 189, 2, 0.6 and 21 all represent parameter values ​​fitted on experimental gas chromatography equipment according to the exponential decay model.

[0090] In this embodiment, in step S2, when the temperature decreases, the temperature decrease follows an exponential decay model. The lower the final target temperature value, the slower the temperature decreases and the less the overshoot. At this time, the node for calculating the heating temperature... According to linear control at the node of heating temperature Initiate heating to reduce overshoot; heating temperature node The calculation formula is:

[0091] ;

[0092] Where X represents the target temperature, and 2, 50 and 1 represent the parameter values ​​fitted on the experimental gas chromatography equipment according to the exponential decay model.

[0093] In this embodiment, during step S2, when heating begins to reduce overshoot, the PID controller maintains normal temperature control and calculates the damper angle corresponding to the current power. and control time interval Based on the calculation results, the damper angle is jointly controlled, and the damper is moved to the damper angle corresponding to the current power according to the calculation results. Then, wait for the control time interval. Reread the temperature for the next control cycle;

[0094] Overall, when the damper is closed, the fan operates at its default speed; when the damper is open, the fan speed increases; the higher the heating power, the more dampers are closed, the more stable the temperature, and the less the damper moves.

[0095] When controlling the fan, set the minimum single movement, maximum single movement, maximum damper opening, maximum fan power, and minimum fan power.

[0096] When the difference is greater than the maximum single movement amount, only the maximum single movement amount is moved; when the difference is less than the minimum single movement amount, the minimum single movement amount is moved; when the difference is between the minimum and maximum single movement amounts, the damper is controlled to close according to the target temperature difference.

[0097] Once the temperature drops below 10°C, it will tend to stabilize. When the actual temperature is lower than or less than the target temperature, the minimum single movement amount will be adjusted each time the device is turned off or on.

[0098] Example 2:

[0099] S1, Linear Heating: PID parameters are obtained using a self-tuning method. Assuming the final target temperature is 100℃, the temperature is increased from 50℃. Initially, the power is 1, and after reaching 100℃, the power is 0. This cycle repeats for three cycles, with an amplitude of 2 and a period of 5 seconds per cycle. The intermediate values ​​are calculated from the last two cycles. :

[0100] ;

[0101] in, ,cycle According to the basic coefficients given by Ziegler-Nichols, we can obtain , The final target temperature PID parameter value is obtained;

[0102] Assuming the final target temperature is 100℃, and the temperature needs to be increased from 50℃ to 100℃ at a rate of 10℃ per minute, the entire process takes 5 minutes. With a temperature control interval of 100ms, the calculated value for a single temperature increase is 0.016℃. That is, the target temperature for the next stage is 50.016, at which point the error... ;

[0103] Similarly, the target temperature for the next stage is 50.032℃. When the temperature is 50.01℃, the temperature difference is 0.006℃. Therefore, this stage... Then it is: When the temperature is 50.022℃, then it is... The remaining calculation parameters remain unchanged during normal calculations.

[0104] Continue heating until the temperature reaches 100℃, at which point the integral value is... Switch to normal calculation, speed coefficient Take the I value from the PID controller, that is:

[0105] ;

[0106] At this point, the remaining calculation parameters remain unchanged, and the temperature can be kept constant.

[0107] S2, Fuzzy control cooling: When the temperature needs to be reduced to 50℃ and the cooling threshold is 10℃, that is, when the temperature difference is less than 10℃, the dampers will be fully opened and the heating power will be set to 0.

[0108] When the temperature drops to 60℃, the heating power is calculated according to the PID formula. Under normal circumstances, the calculated heating power is 0. When the temperature drops to 51℃ (a temperature difference of 1℃), the heating power is also 0. Then The calculation is performed with a positive value of 1. Then, each time, it checks whether the normally calculated heating power is 0. If it is not 0, it switches to the PID state for normal heating power calculation; otherwise, it switches to the normal heating power calculation state. It will always take a positive value;

[0109] This is the initial temperature control state, requiring rapid stabilization to the target temperature of 50 degrees Celsius. At this point, the damper angle is 92.5 degrees and the fan power is 100 watts. The damper angle should be adjusted according to the current power. and fan power The linear relationship formula takes into account the control of the damper angle;

[0110] In Example 1, the amount of movement of the damper each time was calculated according to the exponential decay model. In this example, the second method is used, which directly defines the amount of movement of the damper each time. First, we establish our fuzzy function rules:

[0111] Assuming the maximum single movement is 7.5 degrees and the minimum movement is 0.2 degrees, since the temperature difference is the factor for determining whether a steady state has been reached, and the lower the power, the more stable the system. Therefore, when the heating power is high, temperature control will result in wasted resources. Thus, when there is heating power, the damper moves inward and the opening decreases; when the heating power is too low, the damper moves outward and the opening increases.

[0112] Assuming the heating power threshold parameters are 0.035 and 0.01, that is, when the heating power is less than 0.01, the opening degree increases, when the heating power is greater than 0.035, the opening degree decreases, and when it is between 0.01 and 0.035, the opening degree remains unchanged. Based on this, a corresponding relationship is established.

[0113] Assuming the damper moves 0.2 degrees per increment when the temperature is between 0 and 0.02 degrees, and 0.4 degrees per increment when the temperature is between 0.02 and 0.06 degrees, the damper angle is calculated using an exponential decay model for other temperatures. ,according to Value shifting: Based on the shifting rule that the power is below 0.035, a shifting rule for the damper based on power is established. First, a piecewise linear function is set:

[0114] For example: the movement corresponding to power in the range of [0.5-1] is [5-7];

[0115] Power values ​​between [0.3-0.5] correspond to [2-5];

[0116] Power values ​​in the range of [0.1-0.3] correspond to [0.6-2].

[0117] If the value is below 0.1, the default movement is only 0.2 degrees;

[0118] Each segment is assumed to be a linear model Y=KX+b. By fitting the model, a fuzzy rule function equation can be obtained. Then, based on the power calculated from the PID parameters and the current temperature read, the control damper angle can be calculated according to the function equation.

[0119] After controlling the damper angle, a fuzzy rule for the control time is established. When establishing the rule, the control time interval is obtained based on the damper angle, heating power, and temperature response lag time.

[0120] Assuming a temperature of 55 degrees Celsius and a power of 0.5, the temperature response time might be 2000 ms. By repeatedly acquiring data on the damper angle, heating power, and temperature response lag time, and fitting these data, parameter values ​​are obtained. Based on this, the fuzzy function for controlling the time interval is derived as follows:

[0121] ;

[0122] Therefore, the damper can be slowly closed when the temperature is within 0℃-0.06℃ (i.e., when the temperature is stable), while in other cases the temperature can be allowed to quickly approach the temperature point.

[0123] The above are merely preferred embodiments of the present invention and are illustrative in nature, not restrictive. Those skilled in the art will understand that many changes, modifications, and even equivalents can be made within the spirit and scope defined by the claims of the present invention, all of which will fall within the protection scope of the present invention.

Claims

1. A column oven temperature control method, characterized by, The control method comprises the following steps: S1, linear temperature rise Determine whether the current temperature reaches the stage target temperature: if the current temperature does not reach the stage target temperature, PID normally controls the temperature, at the same time, the damper is closed and the fan speed is reduced to accelerate the temperature rise rate; If the current temperature reaches the stage target temperature, determine whether the temperature rise rate is consistent each time, if the rate is too high, reduce the heating power, otherwise increase, to ensure uniform temperature rise, when the heating power is controlled to decrease, the temperature rise amplitude in each time interval of linear temperature rise is the same; S2, fuzzy control cooling According to the difference between the current temperature and the final target temperature and the size of the heating power, dynamically adjust the fan power and the damper angle: when the difference between the current temperature and the final target temperature and the heating power are both large, quickly adjust the damper angle; When the difference between the current temperature and the final target temperature and the heating power are both small, fine-tune the damper angle and the fan runs at low speed.

2. The column oven temperature control method of claim 1, wherein, The step S1 specifically comprises the following contents: S11, determine a final target temperature PID parameter value with overshoot and without oscillation as a reference through self-tuning or rounding method, that is, the second overshoot is within 1 / 4 of the first overshoot; S12, set the linear heating rate, according to the linear heating rate to calculate the stage target temperature, , gradually approaching the final target temperature, ensure that the temperature change of each step is controllable; S13, heating to reach the target temperature by PID control, during heating, the damper is closed, the fan speed is reduced to the default speed, after reaching the target temperature, it is judged whether the actual increase value of each temperature is the theoretical increase value, if the actual increase value is less than the theoretical increase value, the heating power is increased, otherwise it is reduced, The integral value at the initial moment is represented, and the integral value calculated at the current moment is : ； In The amount of change in heating power is therefore: ； wherein, represents a speed coefficient, which is 1 or the I value in PID; represents an integral value at the previous time, represents a temperature rise speed difference; S14, after normally heating to the final target temperature according to step S13, convert to normal PID control.

3. The column oven temperature control method of claim 2, wherein, In the step S11, the specific process of determining the PID parameter value through self-tuning is as follows: Set the target temperature of learning, the actual temperature is lower than the target temperature, the heating power is 1, the actual temperature is higher than the target temperature, the heating power is 0, after running three cycles, use amplitude and period, through Åström-Hägglund calculation of intermediate quantity , PID parameters are calculated by the coefficient scheme provided by Ziegler-Nichols.

4. The column oven temperature ramping method of claim 1, wherein, In the step S2, during the cooling, PID control directly cools quickly, during the cooling process, determine whether the current temperature is the final target temperature, and at the same time, determine the difference between the current temperature and the final target temperature, control the heating power according to the difference result, specifically: When the difference between the current temperature and the final target temperature is greater than the set error threshold, fully open the damper and adjust the fan to the maximum, at this time, the heating power is 0; When the difference between the current temperature and the final target temperature is less than the set error threshold, PID normally controls the temperature.

5. The column oven temperature control method of claim 4, wherein, In the step S2, when the difference between the current temperature and the final target temperature is less than the set error threshold, that is, within the error threshold range, the fan power and the damper angle are dynamically adjusted according to the difference between the current temperature and the final target temperature and the size of the heating power, and the damper angle corresponding to the current heating power is calculated and control, the set exponential decay model is calculated ; The greater the power is, the greater the damper moving angle is, and vice versa, the smaller the power is, the smaller the damper moving angle is.

6. The column oven temperature ramping method of claim 5, wherein, The temperature control in step S2 has a hysteresis, and the temperature difference and the control time interval before the moving damper The relationship is as follows: The greater the temperature difference, the more stable the temperature trend, and the shorter the reaction time required to wait for the temperature change result before initiating control of the moving damper is shorter. The smaller the temperature difference, the more unstable the temperature trend, the longer the reaction time required to wait for the temperature change result before initiating the control to move the damper, i.e. the longer.

7. The column oven temperature ramping method of claim 1, wherein, In the step S2, when the temperature drops, the temperature drop conforms to an exponential decay model, the lower the final target temperature value, the slower the temperature drop speed, and the less the overshoot amount. At this time, the node of the heating temperature is calculated According to linear control, the node of the heating temperature is calculated to start heating to reduce the overshoot amount.

8. The column oven temperature control method of claim 6, wherein, In the step S2, when the heating is started to reduce the overshoot, the PID normally controls the temperature, and the damper angle corresponding to the current power is calculated and the control time interval According to the calculation result, the damper angle is jointly controlled, and the damper is controlled to move to the damper angle corresponding to the current power according to the calculation result After that, the control time interval is waited, and the temperature is re-read for the next control.

Images