High-precision non-magnetic temperature control device with self-tuning PID (Proportion Integration Differentiation) control algorithm

Abstract

The invention relates to a high-precision non-magnetic temperature control device with a self-tuning PID (Proportion Integration Differentiation) control algorithm. The method is suitable for magnetic field measurement. According to the technical scheme of the invention, the high-precision non-magnetic temperature control device comprises a main controller; the heating module is used for converting the electric energy into heat energy and transmitting the heat energy to a heating object; the heating driving module is used for generating a high-frequency sine wave signal or a high-frequency square wave signal for driving the heating module to work based on a control signal of the main controller; the temperature measurement module is excited by adopting a high-frequency alternating-current excitation source and is used for collecting temperature information of a heating object; the external communication module is connected to the main controller and used for being in communication connection with an upper computer; the main controller is internally provided with a self-tuning PID controller module, and the main controller generates a control signal for controlling the heating driving module based on the preset target temperature and the heating frequency in combination with the heating object temperature information collected by the temperature measuring module.

Description

Technical Field

[0001] The invention relates to a high-precision non-magnetic temperature control device with a self-tuning PID control algorithm, which is applicable to the field of magnetic field measurement. Background Art

[0002] SERF (Spin-Exchange Relaxation-Free) magnetometer is a high-precision instrument that uses alkali metal atoms in a spin-free state to measure external magnetic fields. It is used in many fields. Due to its very high sensitivity in magnetic field measurement, it has extremely high requirements for the level of external magnetic noise. At the same time, due to the high number density of alkali metal atoms, the atomic gas chamber needs to work at a temperature of 200°C or higher, so high temperature control is required.

[0003] At present, the commonly used heating method is electric heating. A large current is passed through the resistance wire, but the resistance wire is a metal material. When the current passes through it, magnetic noise will be generated, which seriously affects the sensitivity of the magnetometer. Therefore, it is very important to study methods and devices based on SERF magnetometers with low magnetic noise and high temperature control accuracy.

[0004] Commonly used methods to reduce heating magnetic noise include using laser heating and hot air flow heating, but the disadvantage of the former is that the temperature is difficult to reach 200°C, and the disadvantage of the latter is that the temperature control accuracy is poor and it is difficult to stabilize within 0.005°C.

[0005] Most of the temperature control devices on the market use a DC power supply to directly drive the heating film for heating. The low-frequency magnetic noise caused by this method will greatly reduce the measurement sensitivity of the system in the field of weak magnetic field measurement. Therefore, how to reduce the magnetic field noise and improve the temperature control accuracy while using electric heating is a technical difficulty.

[0006] From the perspective of the heating current waveform, the sine waveform has a single frequency and is not easy to generate harmonic components. However, the high-power sine current needs to be amplified by a power amplifier, and the power amplifier itself also has a certain amount of electrical noise, which will generate additional magnetic noise on the heating film. The greater the power of the amplifier, the lower its bandwidth is limited by the gain-bandwidth product parameter of the amplifier. There are fewer choices of power amplifiers that can simultaneously meet the requirements of gain, bandwidth and output power, and the price is relatively expensive. At the same time, it has higher requirements for heat dissipation devices, which increases the design difficulty. The square wave is generated by the MOS tube controlled by the full-bridge controller through chopping. Its low-frequency electrical noise is smaller than that of the power amplifier, and because it is not limited by the power amplifier, its achievable power is larger. Under the same voltage supply conditions, the square wave heating power is twice that of the sine wave heating power. However, it can be seen from the Fourier expansion of the square wave that the square wave is synthesized by a series of sine waves, which will produce harmonic components, which will bring additional challenges to the overall noise analysis of the circuit.

[0007] In addition, as one of the subsystems of the SERF magnetometer, the heating temperature control system sometimes needs to be independently controlled to ensure a high number density of alkali metal atoms, and sometimes needs to be combined with temperature control such as during optical rotation angle testing. Therefore, two modes of independent control and external control are required for the heating temperature control system. However, the existing devices do not consider the independence and integration required by the heating system. Either only external control can be achieved, such as NI board card temperature acquisition and labview program overall control, which makes the magnetometer system large and complex and expensive; or only internal single control can be performed, such as a temperature controller with an integrated DSP chip, which makes the system redundancy, interactivity and integration poor.

[0008] In terms of temperature accuracy, conventional PID parameter determination methods include fast PID, fuzzy PID, etc. However, the parameters of the fast PID method are fixed, and it is difficult to automatically select and adapt according to different set temperatures. Although the adjustment is faster, the control accuracy is poor; fuzzy PID adjusts the control signal by determining the membership function according to the set range reached by the collected temperature. It has higher accuracy but poorer speed. Summary of the invention

[0009] The technical problem to be solved by the present invention is: in view of the above-mentioned problems, a high-precision non-magnetic temperature control device with a self-tuning PID control algorithm is provided.

[0010] The technical solution adopted by the present invention is: a high-precision non-magnetic temperature control device with a self-tuning PID control algorithm, characterized in that it includes:

[0011] Main controller;

[0012] A heating module is used to convert electrical energy into thermal energy and transfer the thermal energy to a heating object;

[0013] A heating driving module, used for generating a high-frequency sine wave signal or a high-frequency square wave signal for driving the heating module to work based on the control signal of the main controller;

[0014] The temperature measurement module is excited by a high-frequency AC excitation source and is used to collect temperature information of the heating object;

[0015] An external communication module is connected to the main controller and is used for communication with the host computer;

[0016] The main controller is equipped with a self-tuning PID controller module, which generates a control signal for controlling the heating drive module based on a preset target temperature and heating frequency and in combination with the temperature information of the heating object collected by the temperature measurement module.

[0017] The heating drive module comprises:

[0018] A DAC module, used for converting the control signal of the main controller into an analog control signal;

[0019] A DDS waveform generation module is used to generate a high-frequency sine wave signal, the amplitude of which is based on the analog control signal output by the DAC module, and the frequency of which is based on the control signal of the main controller;

[0020] The power amplifier module is used to amplify the sine wave signal output by the DDS waveform generation module.

[0021] The heating drive module comprises:

[0022] A DAC module, used for converting the control signal of the main controller into an analog control signal;

[0023] A power amplifier module, used to amplify the analog control signal output by the DAC module;

[0024] The square wave generating module is used to generate a high-frequency square wave signal, the amplitude of which is based on the analog control signal output by the DAC module, and the frequency of which is based on the control signal of the main controller.

[0025] The heating drive module comprises:

[0026] A DAC module, used for converting the control signal of the main controller into an analog control signal;

[0027] A DDS waveform generation module is used to generate a high-frequency sine wave signal, the amplitude of which is based on the analog control signal output by the DAC module, and the frequency of which is based on the control signal of the main controller;

[0028] A power amplifier module, used to amplify the sine wave signal output by the DDS waveform generation module in the sine wave output mode, and to amplify the analog control signal output by the DAC module in the square wave output mode;

[0029] The square wave generating module is used to generate a high-frequency square wave signal, the amplitude of which is based on the analog control signal output by the DAC module, and the frequency of which is based on the control signal of the main controller.

[0030] The DDS waveform generation module and the filtering module filter out the inherent high-frequency noise brought by the DDS chip.

[0031] The square wave generating module has a full-bridge controller, the frequency of which is controlled by a PWM signal generated by a main controller module, and the amplitude is generated by a power amplifier module.

[0032] The temperature measurement module comprises:

[0033] PT1000 sensor;

[0034] A high-precision AC current source module, used to generate an AC current of a preset frequency and magnitude based on a control signal from a main controller, applied to a PT1000 sensor, and generate a high-frequency AC voltage across the PT1000 sensor;

[0035] RMS analog converter, used to convert the high-frequency AC voltage across the PT1000 sensor into its RMS value;

[0036] The ADC module is connected to the main controller and is used for converting the root mean square value output by the root mean square analog converter into a digital signal.

[0037] The PT1000 sensor is demagnetized.

[0038] The PID parameter determination method of the PID controller module comprises:

[0039] Obtain the preset target temperature and the temperature information collected in real time by the temperature measurement module;

[0040] Based on the target temperature and real-time temperature information, the grid is selected in combination with the preset parameters, and the PID parameters are selected by the gridding fast method;

[0041] Based on the target temperature and real-time temperature information, the amplitude information in the control signal is generated through the PID controller module after parameter selection;

[0042] When the PID parameters determined by the grid fast selection method make the temperature error T error When it is within the preset range, it enters the PID self-tuning repair mode to fine-tune the PID parameters;

[0043] The parameter selection grid includes a temperature error T error The constructed P parameter selection grid is based on the integral error S error The I parameter selection grid constructed, and the differential error D error The constructed D parameter selection grid;

[0044] Among them, the temperature error T error is the difference between the target temperature and the real-time temperature information; the integral error S error is the sum of temperature errors; differential error D error It is the difference between the current temperature and the last temperature.

[0045] The step of entering the PID self-tuning repair mode to fine-tune the PID parameters includes:

[0046] Keep the PID parameters unchanged, including the proportional gain P, integral time I and differential time D determined by the gridding fast method;

[0047] Gradually increase the proportional gain P until the system shows continuous periodic oscillation. At this time, the proportional gain P is the critical proportional gain Ku;

[0048] Measure the oscillation period Tu in the previous step;

[0049] According to the critical proportional gain Ku and the oscillation period Tu, the final proportional gain Kp, integral time Ti and differential time Td are calculated:

[0050] The final Kp, Ti, and Td are input into the module of the PID controller, and the amplitude information in the control signal is generated by combining the target temperature and real-time temperature information.

[0051] The beneficial effects of the present invention are as follows: the magnetic field measurement range of the SERF magnetometer is a low-frequency range, and the influence of magnetic noise on the magnetic measurement system is shielded by adjusting the heating frequency to a high frequency.

[0052] The present invention uses a high-frequency AC excitation source to perform real-time temperature measurement at the temperature measurement end, and uses a high-frequency sine wave and a high-frequency square wave signal to drive the heating film at the heating end, so as to modulate the magnetic noise caused by the temperature measurement and the heating drive to outside the sensitive frequency band of the entire measurement and control system. After simple data processing, the magnetic noise effect of the temperature control circuit on the magnetic measurement system can be suppressed, and the system inheritance and redundancy are improved by using internal and external dual control signals.

[0053] The present invention designs currents with two waveforms, sinusoidal and square, which can meet different heating scenarios and requirements, and further comprehensively consider the sensitivity index and heating power.

[0054] The main controller module of the present invention has a built-in self-tuning PID controller module, so the main controller should have sufficient computing resources and computing speed. In addition, the main controller module needs to have a common communication interface for configuring other external chips and communicating data with the outside. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 is a device block diagram in an embodiment.

[0056] Figure 2 It is the PID control flow chart in the embodiment.

[0057] 1. Main controller; 2. High-precision AC current source module; 3. PT1000 sensor; 4. ADC module; 5. RMS analog converter; 6. DAC module; 7. DDS waveform generation module; 8. Square wave generation module; 9. Power amplifier module; 10. Heating film; 11. External communication module. DETAILED DESCRIPTION

[0058] like Figure 1 As shown, this embodiment is a high-precision non-magnetic temperature control device with a self-tuning PID control algorithm, including: a main controller 1, a heating module, a heating drive module, a temperature measurement module and an external communication module 11, etc.

[0059] In this embodiment, the main controller 1 module has a built-in self-tuning PID controller module, so the main controller 1 should have sufficient computing resources and computing speed. In addition, the main controller 1 module needs to have a common communication interface to configure other external chips and communicate data with the outside. The main controller 1 that meets the requirements includes high-performance single-chip microcomputers, ARM, DSP and FPGA processors.

[0060] In this example, the heating module uses a heating film 10 to convert electrical energy into thermal energy and transfer the thermal energy to the heating object. In this embodiment, the material and winding method of the heating film 10 should be a multi-layer spiral winding method to make the current distribution more uniform and make the magnetic fields generated by each layer of winding offset each other, so as to minimize the magnetic noise caused by the heating film 10 itself.

[0061] In this embodiment, the heating driving module generates a corresponding high-frequency sine wave signal or a high-frequency square wave signal based on the heating mode selected by the main controller 1 to drive the heating module to work. The frequency and amplitude of the high-frequency sine wave signal or the high-frequency square wave signal are determined based on the control signal of the main controller 1.

[0062] In this example, the heating drive module includes a DAC module 6, a DDS waveform generating module 7, a square wave generating module 8 and a power amplifier module 9, etc. The DAC module 6 is connected to the main controller 1 module and the DDS waveform generating module 7 and the power amplifier module 9, wherein the DAC module 6 converts the control signal of the main controller 1 module into an analog control signal.

[0063] When the device is set to the sinusoidal wave output mode, the control signal output by the DAC module 6 controls the DDS waveform generating module 7 to change the amplitude of the output sinusoidal wave. In addition, the DDS waveform generating module is also controlled by the main controller 1 module to change the frequency of the output sinusoidal waveform. The DDS waveform generating module 7 generates a sinusoidal wave with adjustable frequency and amplitude, and outputs the sinusoidal wave to the power amplifier module 9. The power amplifier module 9 will amplify the sinusoidal wave by 10 to 20 times and greatly enhance its load-carrying capacity, and finally drive the heating film 10 to heat the heating object.

[0064] When the device is set to square wave output mode, the analog control signal generated by the DAC module 6 is directly connected to the power amplifier module 9, which amplifies the signal to increase the amplitude and load capacity of the signal. The signal output by the power amplifier module 9 is connected to the square wave generating module 8 as the amplitude of the square wave signal; the square wave generating module 8 is also connected to the main controller 1 module, and is controlled by the main controller 1 module to change the frequency of the square wave; the square wave generating module 8 is finally connected to the heating film 10 to drive the heating film 10 to heat the controlled object.

[0065] The DAC module 6 is generally not less than 16 bits. The accuracy of the DAC module 6 has a great influence on the final temperature control accuracy. To ensure the temperature control accuracy, the higher the number of bits of the DAC module 6, the better. However, the 16-bit DAC module 6 can already meet the temperature control accuracy of 0.005°C.

[0066] In this embodiment, the DDS waveform generating module 7 is used to generate a sine wave, and the module is required to be able to generate a standard sine waveform of not less than 1 MHz. Generally speaking, the DDS waveform generator module should be equipped with a good reconstruction filter module, and the bandwidth of the filter is set at 1 MHz to filter out other frequency components brought by the DAC inside the DDS chip during the waveform generation process to ensure the purity of the generated waveform.

[0067] In this example, the square wave generating module 8 is generated by the full-bridge controller, and its frequency is controlled by the PWM signal generated by the main controller 1 module, and the amplitude is generated by the power amplifier module 9. The generation of square waves is different from that of sine waves. According to the Fourier expansion formula, the frequency component of sine waves is single, while square waves themselves contain a lot of frequency components. Therefore, for square waves and sine waves of the same frequency, the bandwidth requirement of the square wave on the back-end power amplifier module 9 is at least ten times that of the sine wave, which greatly increases the bandwidth requirement for the power operational amplifier and greatly increases the design difficulty. However, by adopting this design method in the present invention, the power amplifier module 9 only amplifies the direct current, and the bandwidth requirement is very low. The square wave frequency is only limited by the dead time of the full-bridge controller matching the MOS tube control signal, so the frequency of the generated square wave can reach at least 1MHz.

[0068] In this embodiment, the power amplifier module 9 amplifies the sine wave or DC signal and finally drives the heating film 10. In order to drive the heating film 10 to reach the set power, the power amplifier module 9 should have a large gain bandwidth ratio and a large power output capacity, and can meet the signal driving capacity of more than 80W.

[0069] In this embodiment, the temperature measurement module includes a high-precision AC current source module 2, a PT1000 sensor 3, an ADC module 4, a root mean square value analog converter, etc.

[0070] In this example, the high-precision AC current source module 2 is connected to the PT1000 sensor 3 and the main controller 1 module. The high-precision AC current source module 2 generates AC currents of different frequencies and sizes according to the configuration of the main controller 1 module, which are applied to the PT1000 sensor 3 and generate high-frequency AC voltage at both ends of the PT1000 sensor 3; the root mean square value analog converter is connected to the PT1000 sensor 3, converts the high-frequency AC voltage at both ends of the PT1000 sensor 3 into its root mean square value, and is converted into a digital signal by the ADC module 4, and converted into current temperature information in the main controller 1 module through the characteristic formula of PT1000.

[0071] In this embodiment, the PT1000 sensor 3 should be equipped with an external magnetic shielding layer, and graphene should be used instead to reduce the magnetic field of the PT1000 itself and avoid the influence of the magnetic field brought by the PT1000 itself.

[0072] In this example, the current passing through the temperature measuring resistor is AC with a frequency of 10kHz; the amplitude is selectable from 100uA to 100mA, and the current accuracy is not less than 10nA.

[0073] In this embodiment, the RMS analog converter 5 should have higher accuracy and higher bandwidth, matching the parameter requirements of the device itself for temperature measurement accuracy.

[0074] In this example, there are two ways to implement the RMS analog converter 5. One is an analog RMS analog converter 5. This method is relatively simple to implement, but its device model selection is limited, and it is difficult to take into account various parameters. When the temperature measurement accuracy is extremely high (greater than 0.001°C), this method cannot be achieved due to the parameter limitations of the analog device itself; the other method is a digital method, which uses a high-precision ADC analog-to-digital converter to oversample the AC signal, and then performs mathematical operations and other digital signal processing inside the digital processor. This implementation method is technically complex, but it is flexible to use and can achieve very high measurement accuracy.

[0075] In this embodiment, the ADC module 4 is used to collect analog signals with high precision. Considering that different temperature control systems have different temperature control precision indicators, the requirements for ADC conversion precision are also different. However, in actual use, the number of bits of ADC is generally not less than 16. Since temperature data is a slowly varying physical quantity, the requirements for ADC acquisition speed are generally not high.

[0076] In this embodiment, the external communication module 11 is connected to the main controller 1 and is used to communicate with the host computer to communicate with the outside world and receive external control signals. The external communication module 11 is mainly used for human-computer interaction, usually a host computer, and is used to modify the set temperature value and store temperature data in the final temperature control system.

[0077] When the device is set to external control signal input and sine wave output mode, the device receives an external input control signal. The sine wave control signal can be directly input from the outside, or the ADC of the main control module can collect the size of the external input DC signal to control the DDS waveform generation module 7 to generate a sine wave waveform with adjustable amplitude and frequency. Then the sine wave is amplified by 10 to 20 times by the power amplifier module 9 to drive the heating film 10.

[0078] When the device is set to external control signal input and square wave output mode, the device receives an external DC control signal, the power amplifier module 9 amplifies the signal, and the output signal is connected to the square wave generating module 8 as the amplitude of the square wave signal; the frequency of the square wave is controlled by the main controller 1 module.

[0079] In this embodiment, the main controller 1 generates a control signal for controlling the heating drive module based on the preset target temperature and heating frequency in combination with the temperature information of the heating object collected by the temperature measurement module and using the built-in PID controller module.

[0080] like Figure 2 As shown, in this embodiment, PID parameters are determined by combining gridding fast selection and self-tuning repair during temperature control, specifically including:

[0081] S1. Obtaining a preset target temperature (such as 200° C.) and temperature information collected in real time by a temperature measurement module;

[0082] S2. Based on the target temperature and real-time temperature information, the grid is selected in combination with the preset parameters, and the PID parameters are selected by the grid fast method.

[0083] In this embodiment, the parameter selection grid includes a temperature error T error The constructed P parameter selection grid is based on the integral error S error The I parameter selection grid constructed, and the differential error D error Construct the selected grid of D parameters.

[0084] Among them, the temperature error T error is the target temperature T step With real-time temperature information T measure The difference

[0085] T error =T step -T measure

[0086] Integration error S error is the sum of the temperature errors:

[0087] S error =∑T error

[0088] Differential error D error The difference between the current temperature and the last temperature:

[0089] D error =T error -T last error

[0090] In this example, the PID parameters are selected by the gridding fast method. The specific steps are as follows:

[0091] 1. When T error When the temperature is >30℃ (the actual temperature is less than 170℃), the heating is performed at full power and the PID adjustment mode is not entered.

[0092] 2. When T error When the temperature is less than 30℃ (the actual temperature is greater than 170℃), quickly select the PID parameters according to the set temperature in the following range:

[0093] Table 1 Selected grid for P parameters

[0094]

[0095]

[0096] Table 2 Selected grids for I parameters

[0097] <![CDATA[S error Range ℃]]> I 0～5000 0.006 5000～10000 0.005 10000～15000 0.004 15000～20000 0.003 20000～25000 0.002 25000～30000 0.001 More than 30,000 0.0005

[0098] Table 3D parameters of selected mesh

[0099] <![CDATA[D error Range ℃]]> D 0～0.1 0.01 0.1～0.2 0.05 0.2～0.3 0.1 0.3～0.4 0.15 0.4～0.5 0.2 0.5～0.6 0.25

[0100] The corresponding relationship of parameters in the grid is determined by the critical gain and critical period rules of the experimentally measured system. The higher the target temperature, the dynamic characteristics of the system response may change. For example, higher temperatures may lead to greater temperature changes and higher control requirements, so higher proportional gains and higher integral gains may be required.

[0101] S3. Based on the target temperature and the real-time temperature information, the amplitude information in the control signal is generated through the PID controller module after parameter selection.

[0102] After the PID parameters are determined, the main controller 1 module outputs a 0-5V control signal through the DAC to change the waveform amplitude, thereby changing the heating power and adjusting the temperature.

[0103] S4. When the PID parameters determined by the grid quick selection method make the temperature error T error When the temperature is within the preset range (0.1℃, actual temperature 199.9℃~200.1℃), enter the PID self-tuning repair mode to fine-tune the PID parameters. The specific steps include:

[0104] 1) First, keep the PID parameters unchanged, i.e., proportional gain P, integral time I and differential time D determined by the gridding fast method;

[0105] 2) Gradually increase the proportional gain P until the system exhibits continuous periodic oscillation, at which point the proportional gain P is the critical proportional gain Ku;

[0106] 3) Measure the oscillation period Tu in the previous step;

[0107] 4) According to the critical proportional gain Ku and the oscillation period Tu, calculate the final proportional gain Kp, integral time Ti and differential time Td:

[0108] Kp=0.6Ku;

[0109] Ti = 0.5Tu;

[0110] Td = 0.125Tu;

[0111] 5) The final obtained Kp, Ti, Td are input into the PID controller, and the main controller 1 module outputs a 0-5V control signal through the DAC to change the waveform amplitude, thereby changing the heating power and adjusting the temperature;

[0112] 6) When the final steady-state temperature is below 0.005°C, PID control is considered successful; otherwise, the self-tuning step is repeated.

[0113] After the grid fast selection method is used to initially adjust the PID parameters and the self-tuning repair method is used to fine-tune the PID parameters, the final steady state is reached. If the set temperature is not changed, the PID adjustment is considered to be completed. If the set temperature is changed, return to the first step and re-use the grid fast selection method to determine the PID parameters.

[0114] Those skilled in the art can understand that the above are only preferred examples of the invention and are not intended to limit the invention. Although the invention is described in detail with reference to the above examples, those skilled in the art can still modify the technical solutions recorded in the above examples or replace some of the technical features therein with equivalents. Any modification, equivalent replacement, etc. made within the spirit and principle of the invention shall be included in the protection scope of the invention.

Claims

1. A high-precision non-magnetic temperature control device with a self-tuning PID control algorithm, characterized in that: include: Main controller (1); A heating module is used to convert electrical energy into thermal energy and transfer the thermal energy to a heating object; A heating drive module, used for generating a high-frequency sine wave signal or a high-frequency square wave signal for driving the heating module to work based on a control signal of the main controller (1); The temperature measurement module is excited by a high-frequency AC excitation source and is used to collect temperature information of the heating object; An external communication module (11) is connected to the main controller (1) and is used for communication with a host computer; The main controller (1) has a built-in self-tuning PID controller module. The main controller (1) generates a control signal for controlling the heating drive module based on a preset target temperature and heating frequency in combination with the temperature information of the heating object collected by the temperature measurement module.

2. The high-precision non-magnetic temperature control device with a self-tuning PID control algorithm according to claim 1 is characterized in that: The heating drive module comprises: A DAC module, used for converting the control signal of the main controller (1) into an analog control signal; A DDS waveform generation module, used for generating a high-frequency sine wave signal, wherein the amplitude of the sine wave signal is based on the analog control signal output by the DAC module, and the frequency of the sine wave signal is based on the control signal of the main controller (1); A power amplifier module (9) is used to amplify the sinusoidal wave signal output by the DDS waveform generation module.

3. The high-precision non-magnetic temperature control device with a self-tuning PID control algorithm according to claim 1 is characterized in that: The heating drive module comprises: A DAC module, used for converting the control signal of the main controller (1) into an analog control signal; A power amplifier module (9), used for amplifying the analog control signal output by the DAC module; The square wave generating module (8) is used to generate a high-frequency square wave signal, the amplitude of the square wave signal is based on the analog control signal output by the DAC module, and the frequency of the square wave signal is based on the control signal of the main controller (1).

4. The high-precision non-magnetic temperature control device with a self-tuning PID control algorithm according to claim 1 is characterized in that: The heating drive module comprises: A DAC module, used for converting the control signal of the main controller (1) into an analog control signal; A DDS waveform generation module, used for generating a high-frequency sine wave signal, wherein the amplitude of the sine wave signal is based on the analog control signal output by the DAC module, and the frequency of the sine wave signal is based on the control signal of the main controller (1); A power amplifier module (9), used for amplifying the sine wave signal output by the DDS waveform generation module in a sine wave output mode, and for amplifying the analog control signal output by the DAC module in a square wave output mode; The square wave generating module (8) is used to generate a high-frequency square wave signal, the amplitude of the square wave signal is based on the analog control signal output by the DAC module, and the frequency of the square wave signal is based on the control signal of the main controller (1).

5. The high-precision non-magnetic temperature control device with a self-tuning PID control algorithm according to claim 2 or 4, characterized in that: The DDS waveform generation module and the filtering module filter out the inherent high-frequency noise brought by the DDS chip.

6. The high-precision non-magnetic temperature control device with a self-tuning PID control algorithm according to claim 3 or 4, characterized in that: The square wave generating module (8) has a full-bridge controller, the frequency of which is controlled by a PWM signal generated by the main controller (1) module, and the amplitude of which is generated by the power amplifier module (9).

7. The high-precision non-magnetic temperature control device with a self-tuning PID control algorithm according to claim 1, characterized in that: The temperature measurement module comprises: PT1000 sensor; A high-precision AC current source module (2), used for generating an AC current of a preset frequency and magnitude based on a control signal of the main controller (1), applying the AC current to the PT1000 sensor, and generating a high-frequency AC voltage at both ends of the PT1000 sensor; A root mean square value analog converter (5), used for converting the high frequency AC voltage across the PT1000 sensor into its root mean square value; The ADC module is connected to the main controller (1) and is used to convert the root mean square value output by the root mean square value analog converter (5) into a digital signal.

8. The high-precision non-magnetic temperature control device with a self-tuning PID control algorithm according to claim 7, characterized in that: The PT1000 sensor is demagnetized.

9. The high-precision non-magnetic temperature control device with a self-tuning PID control algorithm according to claim 1, characterized in that: The PID parameter determination method of the PID controller module comprises: Obtain the preset target temperature and the temperature information collected in real time by the temperature measurement module; Based on the target temperature and real-time temperature information, the grid is selected in combination with the preset parameters, and the PID parameters are selected by the gridding fast method; Based on the target temperature and real-time temperature information, the amplitude information in the control signal is generated through the PID controller module after parameter selection; When the PID parameters determined by the grid fast selection method make the temperature error T error When it is within the preset range, it enters the PID self-tuning repair mode to fine-tune the PID parameters; The parameter selection grid includes a temperature error T error The constructed P parameter selection grid is based on the integral error S error The I parameter selection grid constructed, and the differential error D error The constructed D parameter selection grid; Among them, the temperature error T error is the difference between the target temperature and the real-time temperature information; the integral error S error is the sum of temperature errors; differential error D error It is the difference between the current temperature and the last temperature.

10. The high-precision non-magnetic temperature control device with a self-tuning PID control algorithm according to claim 1, characterized in that: The step of entering the PID self-tuning repair mode to fine-tune the PID parameters includes: Keep the PID parameters unchanged, including the proportional gain P, integral time I and differential time D determined by the gridding fast method; Gradually increase the proportional gain P until the system shows continuous periodic oscillation. At this time, the proportional gain P is the critical proportional gain Ku; Measure the oscillation period Tu in the previous step; According to the critical proportional gain Ku and the oscillation period Tu, the final proportional gain Kp, integral time Ti and differential time Td are calculated: The final Kp, Ti, and Td are input into the module of the PID controller, and the amplitude information in the control signal is generated by combining the target temperature and real-time temperature information.

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