Fumigation instrument self-adapting PID constant temperature control method and system

Abstract

The application provides a kind of fumigation and washing instrument self-adapting PID constant temperature control method and system, the method includes collecting target temperature and real-time temperature, calculating temperature error and error change rate, and obtaining initial proportion, integral and differential quantity according to this, inertia parameter is updated simultaneously;The difference between the maximum output value of controller and the sum of proportion, differential quantity determines the basic limit space, predicts the future peak temperature and the predicted overshoot based on real-time temperature and error change rate, and constructs predictive suppression factor in combination with inertia parameter, to dynamically reduce the upper limit of integration;The minimum output value of controller is determined to the lower limit of integration, and the upper and lower limits of initial integral are obtained to obtain the final integral, and the control output value is generated by superposition with proportion, differential, to adjust the heating power of fumigation and washing instrument.

Description

Technical Field

[0001] This application belongs to the field of medical devices, and in particular relates to an adaptive PID constant temperature control method and system for a fumigation and washing device. Background Technology

[0002] Traditional Chinese medicine fumigation therapy uses heated medicinal liquid to generate steam, which is then used to fumigate and bathe the affected area. The synergistic effect of heat and medicinal properties achieves effects such as unblocking meridians and promoting blood circulation. With the development of modern medical equipment, intelligent fumigation devices are gradually being applied in medical institutions and home healthcare settings. During the operation of the fumigation device, temperature is a key factor affecting the treatment effect, user comfort, and safety. If the temperature is too low, the effective components of the medicinal liquid cannot fully volatilize, affecting the treatment effect; if the temperature is too high, it may destroy the effective components of the medicine and increase the risk of burns to the patient's skin. However, the heating process of fumigation devices typically has large inertia, hysteresis, and nonlinear characteristics, and is easily affected by factors such as ambient temperature, liquid volume, and heat dissipation conditions, making it difficult to maintain a rapid, stable, and precise temperature adjustment process.

[0003] Existing constant temperature control systems for fumigation and washing equipment mostly employ conventional proportional-integral-derivative (PI-DE) control algorithms or their variants for temperature regulation. For objects with large inertia and hysteresis, in the initial heating phase, due to the significant deviation between the set temperature and the actual temperature, the controller is prone to accumulating large integral errors during continuous heating, causing the output to rapidly reach the actuator's upper limit and resulting in integral saturation. Even as the actual temperature gradually approaches the set value, the controller may still continue to output high heating power due to the lag in the release of the integral term, leading to temperature overshoot and oscillation, reducing constant temperature stability and increasing operational risks. Existing anti-saturation strategies typically rely on passive correction based on the current state, lacking sufficient predictive ability for temperature change trends and potential overshoot risks, making it difficult to balance heating response speed with overshoot suppression. Therefore, it is necessary to propose a constant temperature control method for fumigation and washing equipment with predictive regulation capabilities and adaptive limiting capabilities to reduce the impact of integral saturation and temperature overshoot on the operational stability of the equipment. Summary of the Invention

[0004] To address the problems of integral saturation, temperature overshoot, and oscillation in the existing constant temperature control of fumigation and washing instruments, as well as the lack of predictive adjustment capabilities for temperature change trends and the difficulty in balancing heating response and constant temperature stability, this invention proposes an adaptive PID constant temperature control method and system for fumigation and washing instruments.

[0005] In a first aspect, the present invention proposes an adaptive PID constant temperature control method for a fumigation and washing device, comprising the following steps: Obtain the preset target temperature and the real-time acquired temperature, calculate the current temperature error and the rate of change of temperature error; based on the current temperature error, the integral accumulation of historical temperature errors, and the rate of change of temperature error, calculate the initial proportional quantity, the initial integral quantity, and the initial differential quantity; update the inertial parameters; The difference between the controller's maximum output value and the sum of the initial proportional and initial differential values ​​is used as the basic limiting space. The future peak temperature is predicted based on the real-time acquired temperature and the temperature error change rate, and the predicted overshoot is obtained based on the difference between the future peak temperature and the preset target temperature, set to zero when it is less than 0. A predictive suppression factor is constructed by combining the predicted overshoot and the inertial parameter. When the basic limiting space is greater than 0, the suppression factor is used to reduce the basic limiting space to obtain the integration upper limit value. When the basic limiting space is not greater than 0, the basic limiting space is used as the integration upper limit value. The lower limit of the integral is determined by the difference between the minimum output value of the controller and the sum of the initial proportional quantity and the initial differential quantity. If the upper limit of the integral is less than the lower limit, it is corrected to the lower limit. When overshoot occurs, the inertial parameters are updated. The initial integral quantity is subjected to upper and lower limit processing to obtain the final integral quantity. The initial proportional quantity, the final integral quantity and the initial differential quantity are added to obtain the final control output value, and the heating power of the fumigation device is adjusted accordingly.

[0006] Optionally, the step of obtaining the preset target temperature and the real-time acquired temperature, and calculating the current temperature error and the rate of change of temperature error, includes: Subtract the acquired real-time temperature from the acquired preset target temperature to generate a difference value, and set the difference value as the current temperature error; The current temperature error is subtracted from the historical temperature error of the control system in the previous sampling period to obtain the single-cycle error increment. The single-cycle error increment is then divided by the set sampling period duration, and the resulting quotient is used as the temperature error change rate.

[0007] Optionally, the step of calculating the initial proportional quantity, the initial integral quantity, and the initial differential quantity based on the current temperature error, the integral accumulation of historical temperature errors, and the rate of change of temperature error includes: Multiply the preset proportional control constant by the current temperature error, and output the product as the initial proportional value; The total cumulative error is obtained by summing the historical temperature error values ​​corresponding to the historical sampling periods within the preset integration window period of the calculation system. The total cumulative error is then added to the current temperature error and multiplied by the preset integration control constant. The result is used as the initial integration quantity. The preset differential control constant is multiplied by the temperature error change rate to obtain a value as the initial differential component.

[0008] Optionally, the step of using the difference between the controller's maximum output value and the sum of the initial proportional quantity and the initial differential quantity as the basic limiting space includes: The initial proportional quantity and the initial differential quantity are added together to obtain the current control basis summation; Retrieve the preset maximum output limit of the controller, and subtract the current basic sum of the controller's maximum output limit from the current basic sum of the controller's maximum output limit. Use the resulting difference as the basic limit space.

[0009] Optionally, the step of predicting the future peak temperature based on the real-time acquired temperature and the temperature error change rate, and obtaining the predicted overshoot based on the difference between the future peak temperature and the preset target temperature, setting it to zero when it is less than 0; combining the predicted overshoot with the inertia parameter, a predictive suppression factor is constructed, including: The future peak temperature is predicted based on the real-time acquired temperature and the temperature error change rate, and the predicted overshoot is obtained based on the difference between the future peak temperature and the preset target temperature. The predicted overshoot value is normalized by dividing the currently acquired predicted overshoot by a preset reference temperature, and the resulting value is multiplied by the value of the latest updated inertial parameter after normalization by dividing it by a preset reference inertial parameter to obtain the mixed state characteristic value. Using the natural constant as the base and the negative of the characteristic value of the mixed state as the exponent, an exponential calculation is performed, and the result is used as the predictive inhibition factor.

[0010] Optionally, when the basic limiting space is greater than 0, the inhibition factor is used to reduce the basic limiting space to obtain the integration upper limit value; when the basic limiting space is not greater than 0, the basic limiting space is used as the integration upper limit value, including: Determine whether the basic limiting space is greater than 0; If the basic limiting space is greater than 0, then the predictive suppression factor is multiplied by the basic limiting space, and the product is used as the final integral upper limit value adopted by the system. If the basic limiting space is not greater than 0, then the basic limiting space will be used as the final integration upper limit value adopted by the system.

[0011] Optionally, the step of applying upper and lower limits to the initial integral to obtain the final integral includes: Determine whether the initial integral is greater than the upper limit of integral; if so, use the upper limit of integral as the final integral. Determine whether the initial integral is less than the lower limit of integration; if so, use the lower limit of integration as the final integral. If the initial integral is not greater than the upper limit of integral and not less than the lower limit of integral, then the initial integral is taken as the final integral.

[0012] Optionally, the step of adding the initial proportional quantity, the final integral quantity, and the initial differential quantity to obtain the final control output value, and adjusting the heating power of the fumigation device accordingly, includes: The initial proportional value, the final integral value, and the initial differential value are summed to obtain the final control output value. Based on the final control output value, a power adjustment control signal with a corresponding duty cycle or time ratio is generated. The power adjustment control signal drives the on and off timing of the heating actuator, thereby changing the heating power of the heating actuator of the fumigation and washing instrument.

[0013] On the other hand, the present invention also proposes an adaptive PID constant temperature control system for a fumigation and washing device, comprising the following modules: The calculation module is used to obtain the preset target temperature and the real-time acquired temperature, calculate the current temperature error and the rate of change of temperature error; calculate the initial proportional quantity, the initial integral quantity and the initial differential quantity based on the current temperature error, the integral accumulation of historical temperature errors and the rate of change of temperature error; and update the inertial parameters. The module is configured to use the difference between the controller's maximum output value and the sum of the initial proportional and initial differential components as the basic limiting space; predict the future peak temperature based on the real-time acquired temperature and the temperature error change rate, and obtain the predicted overshoot based on the difference between the future peak temperature and the preset target temperature, setting it to zero when it is less than 0; construct a predictive suppression factor by combining the predicted overshoot and the inertial parameter; when the basic limiting space is greater than 0, reduce the basic limiting space using the suppression factor to obtain the integration upper limit value; when the basic limiting space is not greater than 0, use the basic limiting space as the integration upper limit value. The adjustment module is used to determine the lower limit of the integral by the difference between the minimum output value of the controller and the sum of the initial proportional quantity and the initial differential quantity; if the upper limit of the integral is less than the lower limit of the integral, it is corrected to the lower limit of the integral; when overshoot occurs, the inertial parameters are updated; the initial integral quantity is subjected to upper and lower limit processing to obtain the final integral quantity; the initial proportional quantity, the final integral quantity and the initial differential quantity are added to obtain the final control output value, and the heating power of the fumigation device is adjusted accordingly.

[0014] Preferably, the step of obtaining the preset target temperature and the real-time acquired temperature, and calculating the current temperature error and the rate of change of temperature error, includes: Subtract the acquired real-time temperature from the acquired preset target temperature to generate a difference value, and set the difference value as the current temperature error; The current temperature error is subtracted from the historical temperature error of the control system in the previous sampling period to obtain the single-cycle error increment. The single-cycle error increment is then divided by the set sampling period duration, and the resulting quotient is used as the temperature error change rate.

[0015] Preferably, the step of calculating the initial proportional quantity, the initial integral quantity, and the initial differential quantity based on the current temperature error, the integral accumulation of historical temperature errors, and the rate of change of temperature error includes: Multiply the preset proportional control constant by the current temperature error, and output the product as the initial proportional value; The total cumulative error is obtained by summing the historical temperature error values ​​corresponding to the historical sampling periods within the preset integration window period of the calculation system. The total cumulative error is then added to the current temperature error and multiplied by the preset integration control constant. The result is used as the initial integration quantity. The preset differential control constant is multiplied by the temperature error change rate to obtain a value as the initial differential component.

[0016] Preferably, the step of using the difference between the controller's maximum output value and the sum of the initial proportional quantity and the initial differential quantity as the basic limiting space includes: The initial proportional quantity and the initial differential quantity are added together to obtain the current control basis summation; Retrieve the preset maximum output limit of the controller, and subtract the current basic sum of the controller's maximum output limit from the current basic sum of the controller's maximum output limit. Use the resulting difference as the basic limit space.

[0017] Preferably, the step involves predicting the future peak temperature based on the real-time acquired temperature and the rate of change of temperature error, and obtaining a predicted overshoot based on the difference between the future peak temperature and the preset target temperature, setting it to zero when it is less than 0; combining the predicted overshoot with the inertial parameter to construct a predictive suppression factor, including: The future peak temperature is predicted based on the real-time acquired temperature and the temperature error change rate, and the predicted overshoot is obtained based on the difference between the future peak temperature and the preset target temperature. The predicted overshoot value is normalized by dividing the currently acquired predicted overshoot by a preset reference temperature, and the resulting value is multiplied by the value of the latest updated inertial parameter after normalization by dividing it by a preset reference inertial parameter to obtain the mixed state characteristic value. Using the natural constant as the base and the negative of the characteristic value of the mixed state as the exponent, an exponential calculation is performed, and the result is used as the predictive inhibition factor.

[0018] Preferably, when the basic limiting space is greater than 0, the inhibition factor is used to reduce the basic limiting space to obtain the integration upper limit value; when the basic limiting space is not greater than 0, the basic limiting space is used as the integration upper limit value, including: Determine whether the basic limiting space is greater than 0; If the basic limiting space is greater than 0, then the predictive suppression factor is multiplied by the basic limiting space, and the product is used as the final integral upper limit value adopted by the system. If the basic limiting space is not greater than 0, then the basic limiting space will be used as the final integration upper limit value adopted by the system.

[0019] Preferably, the step of applying upper and lower limits to the initial integral to obtain the final integral includes: Determine whether the initial integral is greater than the upper limit of integral; if so, use the upper limit of integral as the final integral. Determine whether the initial integral is less than the lower limit of integration; if so, use the lower limit of integration as the final integral. If the initial integral is not greater than the upper limit of integral and not less than the lower limit of integral, then the initial integral is taken as the final integral.

[0020] Preferably, the step of adding the initial proportional quantity, the final integral quantity, and the initial differential quantity to obtain the final control output value, and adjusting the heating power of the fumigation device accordingly, includes: The initial proportional value, the final integral value, and the initial differential value are summed to obtain the final control output value. Based on the final control output value, a power adjustment control signal with a corresponding duty cycle or time ratio is generated. The power adjustment control signal drives the on and off timing of the heating actuator, thereby changing the heating power of the heating actuator of the fumigation and washing instrument.

[0021] This invention obtains the initial proportional, integral, and derivative components by acquiring the target temperature and the real-time collected temperature, calculating the temperature error and the rate of change of error, and then constructing a predictive suppression factor based on the future peak temperature and predicted overshoot, combined with inertial parameters. The basic limiting space is determined by the difference between the controller's maximum output value and the sum of the proportional and derivative components. When there is a risk of overshoot, the suppression factor is used to reduce the upper limit of the integral, and the lower limit of the integral is used to limit the initial integral. This control method can reduce saturation caused by excessive integral accumulation, reduce temperature overshoot and oscillation during heating or disturbance processes, make the constant temperature control process of the fumigation and washing instrument more stable, and improve temperature control stability and operational safety. Attached Figure Description

[0022] Figure 1 A flowchart of the first embodiment; Figure 2 A schematic diagram showing the comparison of the initial control component values ​​for the PID controller; Figure 3 To control the output space occupancy distribution diagram; Figure 4 This is a curve showing the integral limiting characteristic. Detailed Implementation

[0023] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0024] In the first embodiment, the present invention proposes an adaptive PID constant temperature control method for a fumigation and washing device, such as... Figure 1 As shown, it includes the following steps: S1, acquire the preset target temperature and the real-time collected temperature, calculate the current temperature error and the rate of change of temperature error; based on the current temperature error, the integral accumulation of historical temperature errors and the rate of change of temperature error, calculate the initial proportional quantity, the initial integral quantity and the initial differential quantity; update the inertial parameters.

[0025] The microcontroller's communication interface calls a serial communication receiving function to read the user-defined target temperature and store it in a memory variable. A thermistor temperature sensor collects the temperature of the fumigation solution, and the real-time digital temperature is obtained through the microcontroller's built-in analog-to-digital converter and the analog-to-digital conversion reading function in the hardware abstraction layer library. Subsequently, a moving average filtering algorithm or a first-order hysteresis filtering algorithm is used to smooth and denoise the real-time temperature. The current temperature error is obtained by subtracting the smoothed real-time temperature from the target temperature. Then, the historical temperature error from the previous sampling period is subtracted from the current temperature error and divided by the sampling period duration to obtain the temperature error change rate.

[0026] Based on this, a discretized positional proportional-integral-derivative (PID) algorithm is used to calculate the control quantity. The proportional coefficient is multiplied by the current temperature error to obtain the initial proportional quantity; the discrete integral coefficient is multiplied by the current temperature error and the accumulated historical temperature error within the preset integration window to obtain the initial integral quantity; and the derivative coefficient is multiplied by the rate of change of the temperature error to obtain the initial derivative quantity.

[0027] When the control system is first started, the inertial parameters are initialized to preset initial inertial values, and minimum and maximum limits for the inertial parameters are set. The absolute value of the current temperature error and the absolute value of the historical temperature error of the previous sampling period are obtained, and the difference between the two is calculated to obtain the error change amplitude difference. When the error change amplitude difference is greater than 0, a target inertial adjustment value is generated according to the ratio of the error change amplitude difference to a preset reference error value, and the inertial parameters of the previous sampling period are updated to the target inertial adjustment value using an exponential smoothing method to obtain the current inertial parameters. When the error change amplitude difference is not greater than 0, the inertial parameters of the previous sampling period are attenuated and updated according to a preset attenuation coefficient to obtain the current inertial parameters. The updated current inertial parameters are subjected to amplitude limiting to keep them between the minimum and maximum limits, and the amplitude-limited value is used as the inertial parameters for subsequently constructing predictive suppression factors.

[0028] For example, the initial inertia value is set to 1.0, the minimum limit to 0.1, and the maximum limit to 3.0. The preset reference error is 1.0℃, the exponential smoothing coefficient is 0.8, and the preset attenuation coefficient is 0.95. If the historical temperature error of the previous sampling period is 1.2℃ and the current temperature error is 1.6℃, the difference in error variation is 0.4℃, indicating an increasing temperature error trend. The target inertia adjustment value is obtained by adding 1 to the ratio of 0.4℃ to 1.0℃, resulting in 1.4. The current inertia parameter is then calculated using exponential smoothing: 0.8 multiplied by the previous sampling period's inertia parameter of 1.0, plus 0.2 multiplied by the target inertia adjustment value of 1.4, resulting in the current inertia parameter of 1.08. If the current temperature error becomes 0.9℃, the difference in error variation is not greater than 0. The preset attenuation coefficient of 0.95 is used to attenuate the inertia parameter of the previous sampling period, resulting in an updated inertia parameter, which is then used for calculating the subsequent predictive suppression factor after amplitude limiting.

[0029] In an optional embodiment, the step of obtaining the preset target temperature and the real-time acquired temperature, and calculating the current temperature error and the rate of change of temperature error, includes: Subtract the acquired real-time temperature from the acquired preset target temperature to generate a difference value, and set the difference value as the current temperature error; The current temperature error is subtracted from the historical temperature error of the control system in the previous sampling period to obtain the single-cycle error increment. The single-cycle error increment is then divided by the set sampling period duration, and the resulting quotient is used as the temperature error change rate.

[0030] The preferred range for the target temperature of the fumigation device is set to 35.0℃ to 45.0℃, for example, 38.0℃. The real-time temperature is obtained via an NTC thermistor at 36.5℃. After low-pass filtering, a difference operation is performed to generate a difference value of 1.5℃, which is set as the current temperature error. By calling the historical temperature error recorded in the internal memory from the previous sampling period, for example, 1.8℃, the current temperature error is subtracted from this historical temperature error, resulting in a single-period error increment of -0.3℃.

[0031] The sampling period is preferably between 0.1 and 1.0 seconds to balance system response speed and anti-interference capability. Assuming a preset sampling period of 0.5 seconds, the single-cycle error increment of -0.3℃ is divided by 0.5 seconds to calculate the quotient -0.6℃ / s as the current temperature error change rate. This value indicates that the current temperature error is decreasing, corresponding to an upward trend in the real-time acquired temperature. The calculation result will be stored in the system's static random access memory as an input parameter for subsequent algorithm adjustments.

[0032] In an optional embodiment, the step of calculating the initial proportional quantity, the initial integral quantity, and the initial differential quantity based on the current temperature error, the integral accumulation of historical temperature errors, and the rate of change of temperature error includes: Multiply the preset proportional control constant by the current temperature error, and output the product as the initial proportional value; The total cumulative error is obtained by summing the historical temperature error values ​​corresponding to the historical sampling periods within the preset integration window period of the calculation system. The total cumulative error is then added to the current temperature error and multiplied by the preset integration control constant. The result is used as the initial integration quantity. The preset differential control constant is multiplied by the temperature error change rate to obtain a value as the initial differential component.

[0033] The control system integrates a PID algorithm. Control parameters are configured, with the proportional gain preferably ranging from 10 to 50, the integral gain being a discrete integral coefficient with a preferred range of 0.1 to 5.0, and the derivative gain preferably ranging from 1 to 20. For example, a proportional gain of 20, an integral gain of 1.5, and a derivative gain of 5 are set. The proportional gain of 20 is multiplied by the calculated current temperature error of 1.5℃, and the product 30.0 is output as the initial proportional gain.

[0034] Iterate through the historical temperature errors of the historical sampling periods within the set integration window. Assuming the sum of the historical temperature errors of the previous periods is 15.0℃, add the current temperature error of 1.5℃ to the sum of the historical temperature errors to get 16.5℃. Then multiply it by the integration coefficient of 1.5 to get the calculation result of 24.75 as the initial integration quantity.

[0035] Multiply the derivative coefficient 5 by the previously calculated temperature error change rate of -0.6℃ / s to obtain a value of -3.0 as the initial derivative. The above calculation process is completed within a single control cycle using an interrupt service function. A comparison of the initial PID control component values ​​is provided below. Figure 2 As shown.

[0036] S2, the difference between the controller's maximum output value and the sum of the initial proportional and initial differential components is used as the basic limiting space; the future peak temperature is predicted based on the real-time acquired temperature and the temperature error change rate, and the predicted overshoot is obtained according to the difference between the future peak temperature and the preset target temperature, which is set to zero when it is less than 0; a predictive suppression factor is constructed by combining the predicted overshoot and the inertial parameter; when the basic limiting space is greater than 0, the basic limiting space is reduced using the suppression factor to obtain the integration upper limit value; when the basic limiting space is not greater than 0, the basic limiting space is used as the integration upper limit value.

[0037] The controller's maximum output value is read from the system configuration file, and the sum of the initial proportional and differential values ​​is subtracted from this maximum output value to obtain the basic limiting space. Subsequently, based on real-time acquired temperature and temperature error change rate, multiple candidate predicted temperature values ​​are calculated within a preset prediction time window using first-order or second-order polynomial extrapolation, and the maximum value is taken as the future peak temperature. The preset target temperature is subtracted from the future peak temperature to obtain the predicted overshoot, which is set to 0 when it is less than 0. Next, the predicted overshoot and inertial parameters are dimensionlessly processed and multiplied to obtain a mixed-state characteristic value, which is then calculated using exponential decay to obtain the predictive suppression factor. When the basic limiting space is greater than 0, it is multiplied by the predictive suppression factor to obtain the integration upper limit; when the basic limiting space is not greater than 0, it is used as the integration upper limit.

[0038] In an optional embodiment, using the difference between the controller's maximum output value and the sum of the initial proportional quantity and the initial differential quantity as the basic limiting space includes: The initial proportional quantity and the initial differential quantity are added together to obtain the current control basis summation; Retrieve the preset maximum output limit of the controller, and subtract the current basic sum of the controller's maximum output limit from the current basic sum of the controller's maximum output limit. Use the resulting difference as the basic limit space.

[0039] The initial proportional value of 30.0 calculated above is added to the initial differential value of -3.0 to obtain the current control basis cumulative sum of 27.0. The maximum output value of the controller is preset in the non-volatile memory. This maximum output value of the controller corresponds to the duty cycle of the full-load power drive signal of the heating element of the fumigation device. It can be expressed as a percentage from 0 to 100, or as an 8-bit PWM counter from 0 to 255. In this embodiment, 100% represents 100% full-power heating.

[0040] The controller's maximum output value of 100 is retrieved. This maximum output value is then subtracted from the current control baseline sum of 27.0, yielding a difference of 73.0. This calculated result of 73.0 is set as the baseline limit space for the current control cycle. This parameter represents the system's remaining available heating drive capacity at the current moment, helping to reduce real-time temperature oscillations caused by integral saturation. The control output space distribution is as follows: Figure 3 As shown.

[0041] In an optional embodiment, the step involves predicting the future peak temperature based on the real-time acquired temperature and the rate of change of temperature error, and obtaining a predicted overshoot based on the difference between the future peak temperature and the preset target temperature, setting it to zero when it is less than 0; combining the predicted overshoot with the inertial parameter, a predictive suppression factor is constructed, including: The future peak temperature is predicted based on the real-time acquired temperature and the temperature error change rate, and the predicted overshoot is obtained based on the difference between the future peak temperature and the preset target temperature. The predicted overshoot value is normalized by dividing the currently acquired predicted overshoot by a preset reference temperature, and the resulting value is multiplied by the value of the latest updated inertial parameter after normalization by dividing it by a preset reference inertial parameter to obtain the mixed state characteristic value. Using the natural constant as the base and the negative of the characteristic value of the mixed state as the exponent, an exponential calculation is performed, and the result is used as the predictive inhibition factor.

[0042] The construction process of this predictive suppression factor integrates an exponential decay model and a dimensionless processing method. A preset reference temperature is set, preferably within the range of the highest protective water temperature during normal operation of the fumigation device, such as 50.0℃. A preset reference inertia parameter is also set, preferably within the range of 0.5 to 2.0; in this example, it is set to 1.0. Assuming the internal prediction model estimates the future overshoot corresponding to the current cycle to be 2.5℃, and the real-time update value of the inertia parameter is 0.8, the predicted overshoot of 2.5℃ is first divided by the reference temperature of 50.0℃ to obtain 0.05, which is then normalized. The inertia parameter 0.8 is divided by the reference inertia parameter 1.0 to obtain the value 0.8. Multiplying these two values ​​yields a mixed-state characteristic value of 0.04. Using the natural constant e, approximately 2.718, as the base, and the negative of the mixed-state characteristic value, -0.04, as the exponent, an exponential function operation is performed. The calculated predictive suppression factor is approximately 0.9608. This predictive suppressor can decay non-linearly exponentially when the system has an overshoot tendency, thus reducing the temperature overshoot amplitude.

[0043] In an optional embodiment, when the basic limiting space is greater than 0, the inhibition factor is used to reduce the basic limiting space to obtain the integration upper limit value; when the basic limiting space is not greater than 0, the basic limiting space is used as the integration upper limit value, including: Determine whether the basic limiting space is greater than 0; If the basic limiting space is greater than 0, then the predictive suppression factor is multiplied by the basic limiting space, and the product is used as the final integral upper limit value adopted by the system. If the basic limiting space is not greater than 0, then the basic limiting space will be used as the final integration upper limit value adopted by the system.

[0044] The value of the basic limiting space variable in memory is read, and it is determined whether the value is greater than 0. Referring to the previous example, if the obtained basic limiting space value is 73.0, it is determined that the value is greater than 0. The predictive suppression factor 0.9608 is multiplied by the basic limiting space value 73.0 to calculate the reduced upper limit of the integral, which is 70.1384. This value is then updated in the register to constrain the integral and prevent it from continuing to diverge.

[0045] In another heating scenario, if the initial proportional gain and initial differential gain increase, resulting in a calculated baseline limit of -5.0 (not greater than 0), it indicates that the current baseline control value has exceeded the system's maximum output capacity. In this case, this baseline limit of -5.0 is used as the upper limit of the system's integral. This segmented processing mechanism helps the system achieve integral convergence in the excess power range and also reduces the accumulation of positive integrals in the power saturation range.

[0046] S3, the lower limit of the integral is determined by the difference between the minimum output value of the controller and the sum of the initial proportional quantity and the initial differential quantity. If the upper limit of the integral is less than the lower limit of the integral, it is corrected to the lower limit of the integral. When overshoot occurs, the inertial parameters are updated. The initial integral quantity is subjected to upper and lower limit processing to obtain the final integral quantity. The initial proportional quantity, the final integral quantity and the initial differential quantity are added to obtain the final control output value, and the heating power of the fumigation device is adjusted accordingly.

[0047] The minimum output value of the controller is set to 0. The lower limit of integration is obtained by subtracting the sum of the initial proportional and initial differential values ​​from 0. The upper and lower limits of integration are compared. If the upper limit is smaller, the value of the upper limit is overwritten with the value of the lower limit, so that the integration limit range satisfies the constraint that the upper limit is not less than the lower limit.

[0048] When the real-time acquired temperature is greater than the preset target temperature, it is determined that overshoot has occurred in the current sampling period, and the difference between the real-time acquired temperature and the preset target temperature is calculated as the overshoot amplitude. The overshoot amplitude is divided by the preset reference temperature and squared to obtain the overshoot correction amount. The overshoot correction amount is superimposed on the inertial parameters that have been updated in the current sampling period, and the amplitude is limited to obtain the final inertial parameters of the current sampling period. The final inertial parameters are no longer used in the completed predictive suppression factor calculation in the current sampling period, but are stored as historical inertial parameters to be called in the next sampling period.

[0049] An interval saturation limiting algorithm is used to constrain the initial integral quantity. When the initial integral quantity is greater than the upper limit, it is modified to the upper limit; when it is less than the lower limit, it is modified to the lower limit; and when it falls between the two limits, it remains unchanged. This final integral quantity is the final integral quantity. The initial proportional quantity, the final integral quantity, and the initial derivative are summed to obtain the final control output value. This final control output value is then used as a duty cycle or time proportional parameter and fed into the power adjustment control function of the microcontroller to generate a corresponding power adjustment control signal. This signal, via a drive circuit, controls the on / off state of the heating actuator, adjusting the actual heating power of the fumigation device's heating element by changing the on / off ratio per unit time.

[0050] In an optional embodiment, the step of applying upper and lower limit processing to the initial integral to obtain the final integral includes: Determine whether the initial integral is greater than the upper limit of integral; if so, use the upper limit of integral as the final integral. Determine whether the initial integral is less than the lower limit of integration; if so, use the lower limit of integration as the final integral. If the initial integral is not greater than the upper limit of integral and not less than the lower limit of integral, then the initial integral is taken as the final integral.

[0051] Assuming the upper limit of integration is set to 70.1384, the lower limit of integration is calculated as -27.0 using the controller's minimum output value, which is usually set to 0 (i.e., turning off heating and subtracting the current basic sum of 27.0). The initial integral value calculated earlier is then retrieved; in this example, it is 24.75.

[0052] The first conditional branch is executed, evaluating whether 24.75 is greater than the upper integral limit of 70.1384. Since 24.75 is not greater than the upper integral limit, execution continues downwards, evaluating whether 24.75 is less than the lower integral limit of -27.0. After confirming that the lower limit has not been exceeded, the value 24.75 is assigned to the final integral variable. If the initial integral quantity increases to 85.0 due to accumulated temperature difference, triggering the first conditional condition, this initial integral quantity of 85.0 is assigned the upper integral limit of 70.1384; if the initial integral quantity is as low as -35.0, it is assigned the lower integral limit of -27.0. This process improves the anti-saturation capability of the isothermal control. The integral limiting characteristic curve is shown below. Figure 4 As shown.

[0053] In an optional embodiment, the step of adding the initial proportional quantity, the final integral quantity, and the initial differential quantity to obtain the final control output value, and adjusting the heating power of the fumigation device accordingly, includes: The initial proportional value, the final integral value, and the initial differential value are summed to obtain the final control output value. Based on the final control output value, a power adjustment control signal with a corresponding duty cycle or time ratio is generated. The power adjustment control signal drives the on and off timing of the heating actuator, thereby changing the heating power of the heating actuator of the fumigation and washing instrument.

[0054] The control components calculated above are integrated by summing the initial proportional value of 30.0, the final integral value after amplitude limiting of 24.75, and the initial differential value of -3.0, resulting in a final control output value of 51.75. Based on a linear mapping mechanism, this final control output value is converted into the corresponding pulse width modulation signal duty cycle, i.e., mapped to a duty cycle output of 51.75%.

[0055] The microcontroller's timer module generates a power adjustment control signal based on the duty cycle. If the heating actuator uses DC switching devices such as MOSFETs or IGBTs, the power adjustment control signal is a PWM square wave signal with a set duty cycle, preferably with a frequency of 1kHz to 10kHz, for example, 2kHz. The heating power is adjusted by changing the PWM duty cycle. If the heating actuator uses a thyristor or a zero-crossing solid-state relay, the power adjustment control signal is a zero-crossing trigger signal or a time-proportional control signal that matches the power frequency cycle. After isolating the power adjustment control signal through an optocoupler, it drives the corresponding heating actuator through a drive circuit. Within the PWM cycle or the preset time-proportional control cycle, the heating actuator performs on / off control according to the duty cycle or conduction ratio, thereby changing the actual heating power of the PTC ceramic heating plate or metal heating tube inside the fumigation device, so that the real-time acquired temperature gradually approaches and is maintained near the preset target temperature.

[0056] In the second embodiment, the present invention also proposes an adaptive PID constant temperature control system for a fumigation and washing device, comprising the following modules: The calculation module is used to obtain the preset target temperature and the real-time acquired temperature, calculate the current temperature error and the rate of change of temperature error; calculate the initial proportional quantity, the initial integral quantity and the initial differential quantity based on the current temperature error, the integral accumulation of historical temperature errors and the rate of change of temperature error; and update the inertial parameters. The module is configured to use the difference between the controller's maximum output value and the sum of the initial proportional and initial differential components as the basic limiting space; predict the future peak temperature based on the real-time acquired temperature and the temperature error change rate, and obtain the predicted overshoot based on the difference between the future peak temperature and the preset target temperature, setting it to zero when it is less than 0; construct a predictive suppression factor by combining the predicted overshoot and the inertial parameter; when the basic limiting space is greater than 0, reduce the basic limiting space using the suppression factor to obtain the integration upper limit value; when the basic limiting space is not greater than 0, use the basic limiting space as the integration upper limit value. The adjustment module is used to determine the lower limit of the integral by the difference between the minimum output value of the controller and the sum of the initial proportional quantity and the initial differential quantity; if the upper limit of the integral is less than the lower limit of the integral, it is corrected to the lower limit of the integral; when overshoot occurs, the inertial parameters are updated; the initial integral quantity is subjected to upper and lower limit processing to obtain the final integral quantity; the initial proportional quantity, the final integral quantity and the initial differential quantity are added to obtain the final control output value, and the heating power of the fumigation device is adjusted accordingly.

[0057] The above description represents the preferred embodiments of the present invention. It should be noted that, for those skilled in the art, various improvements and modifications can be made without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A self-adaptive PID constant temperature control method for a fumigation washing instrument, characterized in that, Includes the following steps: Obtain the preset target temperature and the real-time collected temperature, and calculate the current temperature error and the rate of change of temperature error; Based on the current temperature error, the integral accumulation of historical temperature errors, and the rate of change of temperature error, the initial proportional quantity, the initial integral quantity, and the initial differential quantity are calculated. Update inertial parameters; The difference between the controller's maximum output value and the sum of the initial proportional quantity and the initial differential quantity is used as the basic limiting space; The future peak temperature is predicted based on the real-time acquired temperature and the temperature error change rate, and the predicted overshoot is obtained based on the difference between the future peak temperature and the preset target temperature, which is set to zero when it is less than 0; a predictive suppression factor is constructed by combining the predicted overshoot and the inertial parameter. When the basic limiting space is greater than 0, the inhibition factor is used to reduce the basic limiting space to obtain the upper limit of integration. When the basic limiting space is not greater than 0, the basic limiting space is used as the upper limit value of integration; The lower limit of integration is determined by the difference between the minimum output value of the controller and the sum of the initial proportional and initial differential values. If the upper limit of integration is less than the lower limit of integration, it is corrected to the lower limit of integration. The inertial parameters are updated when overshoot occurs. The initial integral quantity is subjected to upper and lower limit processing to obtain the final integral quantity; the initial proportional quantity, the final integral quantity and the initial micro-quantity are added together to obtain the final control output value, and the heating power of the fumigation device is adjusted accordingly.

2. The method of claim 1, wherein, The process of obtaining the preset target temperature and the real-time acquired temperature, and calculating the current temperature error and the rate of change of temperature error, includes: Subtract the acquired real-time temperature from the acquired preset target temperature to generate a difference value, and set the difference value as the current temperature error; The current temperature error is subtracted from the historical temperature error of the control system in the previous sampling period to obtain the single-cycle error increment. The single-cycle error increment is then divided by the set sampling period duration, and the resulting quotient is used as the temperature error change rate.

3. The method of claim 2, wherein, The calculation of the initial proportional quantity, the initial integral quantity, and the initial differential quantity based on the current temperature error, the integral accumulation of historical temperature errors, and the rate of change of temperature error includes: Multiply the preset proportional control constant by the current temperature error, and output the product as the initial proportional value; The total cumulative error is obtained by summing the historical temperature error values ​​corresponding to the historical sampling periods within the preset integration window period of the calculation system. The total cumulative error is then added to the current temperature error and multiplied by the preset integration control constant. The result is used as the initial integral quantity. The preset differential control constant is multiplied by the temperature error change rate to obtain a value as the initial differential component.

4. The method of claim 1, wherein, The difference between the controller's maximum output value and the sum of the initial proportional quantity and the initial differential quantity is used as the basic limiting space, including: The initial proportional quantity and the initial differential quantity are added together to obtain the current control basis summation; Retrieve the preset maximum output limit of the controller, and subtract the current basic sum of the controller's maximum output limit from the current basic sum of the controller's maximum output limit. Use the resulting difference as the basic limit space.

5. The method of claim 1, wherein, The system predicts the future peak temperature based on the real-time acquired temperature and the rate of change of temperature error, and obtains the predicted overshoot based on the difference between the future peak temperature and the preset target temperature, setting it to zero when it is less than 0; combining the predicted overshoot with the inertia parameter, a predictive suppression factor is constructed, including: The future peak temperature is predicted based on the real-time acquired temperature and the temperature error change rate, and the predicted overshoot is obtained based on the difference between the future peak temperature and the preset target temperature. The predicted overshoot value is normalized by dividing the currently acquired predicted overshoot by a preset reference temperature, and the resulting value is multiplied by the value of the latest updated inertial parameter after normalization by dividing it by a preset reference inertial parameter to obtain the mixed state characteristic value. Using the natural constant as the base and the negative of the characteristic value of the mixed state as the exponent, an exponential calculation is performed, and the result is used as the predictive inhibition factor.

6. The method of claim 4, wherein, When the basic limiting space is greater than 0, the inhibition factor is used to reduce the basic limiting space to obtain the upper limit of integration. When the basic amplitude limiting space is not greater than 0, the basic amplitude limiting space is used as the upper limit value of integration, including: Determine whether the basic limiting space is greater than 0; If the basic limiting space is greater than 0, then the predictive suppression factor is multiplied by the basic limiting space, and the product is used as the final integral upper limit value adopted by the system. If the basic limiting space is not greater than 0, then the basic limiting space will be used as the final integration upper limit value adopted by the system.

7. The method of claim 1, wherein, The step of applying upper and lower limits to the initial integral to obtain the final integral includes: Determine whether the initial integral is greater than the upper limit of integral; if so, use the upper limit of integral as the final integral. Determine whether the initial integral is less than the lower limit of integration; if so, use the lower limit of integration as the final integral. If the initial integral is not greater than the upper limit of integral and not less than the lower limit of integral, then the initial integral is taken as the final integral.

8. The method of claim 1, wherein, The step of adding the initial proportional quantity, the final integral quantity, and the initial differential quantity to obtain the final control output value, and adjusting the heating power of the fumigation device accordingly, includes: The initial proportional value, the final integral value, and the initial differential value are summed to obtain the final control output value. Based on the final control output value, a power adjustment control signal with a corresponding duty cycle or time ratio is generated. The power adjustment control signal drives the on and off timing of the heating actuator, thereby changing the heating power of the heating actuator of the fumigation and washing instrument.

9. An adaptive PID constant temperature control system for a fumigation and washing device, characterized in that, Includes the following modules: The calculation module is used to obtain the preset target temperature and the real-time acquired temperature, and to calculate the current temperature error and the rate of change of temperature error; Based on the current temperature error, the integral accumulation of historical temperature errors, and the rate of change of temperature error, the initial proportional quantity, the initial integral quantity, and the initial differential quantity are calculated. Update inertial parameters; A construction module is used to use the difference between the controller's maximum output value and the sum of the initial proportional quantity and the initial differential quantity as the basic limiting space; The future peak temperature is predicted based on the real-time acquired temperature and the temperature error change rate, and the predicted overshoot is obtained based on the difference between the future peak temperature and the preset target temperature, which is set to zero when it is less than 0; a predictive suppression factor is constructed by combining the predicted overshoot and the inertial parameter. When the basic limiting space is greater than 0, the inhibition factor is used to reduce the basic limiting space to obtain the upper limit of integration. When the basic limiting space is not greater than 0, the basic limiting space is used as the upper limit value of integration; The adjustment module is used to determine the lower limit of integration by the difference between the minimum output value of the controller and the sum of the initial proportional quantity and the initial differential quantity; if the upper limit of integration is less than the lower limit of integration, it is corrected to the lower limit of integration; and the inertial parameters are updated when overshoot occurs. The initial integral quantity is subjected to upper and lower limit processing to obtain the final integral quantity; the initial proportional quantity, the final integral quantity and the initial micro-quantity are added together to obtain the final control output value, and the heating power of the fumigation device is adjusted accordingly.

10. The system according to claim 9, characterized in that, The process of obtaining the preset target temperature and the real-time acquired temperature, and calculating the current temperature error and the rate of change of temperature error, includes: Subtract the acquired real-time temperature from the acquired preset target temperature to generate a difference value, and set the difference value as the current temperature error; The current temperature error is subtracted from the historical temperature error of the control system in the previous sampling period to obtain the single-cycle error increment. The single-cycle error increment is then divided by the set sampling period duration, and the resulting quotient is used as the temperature error change rate.

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