Temperature control method for solution conductivity meter based on fuzzy PID (Proportion Integration Differentiation)

Abstract

The invention relates to the field of temperature control, in particular to a solution conductivity meter temperature control method based on fuzzy PID, and the method comprises the steps: collecting the temperature data of a measurement solution through a high-precision temperature sensor; acquiring temperature data of the measurement solution, and calculating a temperature deviation value and a temperature change rate of the measurement solution; inputting the temperature deviation value and the temperature change rate into a fuzzy PID (Proportion Integration Differentiation) control module; according to the input temperature deviation value and the temperature change rate, the input of the PID controller is corrected through a fuzzification and fuzzy rule table in the fuzzy PID control module and a corresponding variable quantity output by defuzzification; according to an algorithm, updated PID parameters are obtained, and then a pulse width control signal is obtained by an incremental PID control algorithm to control a driving circuit to dynamically adjust a TEC semiconductor cooler, so that the temperature of the measured liquid is controlled, the control speed is effectively improved, the robustness of the system is enhanced, and the temperature is stabilized near the target temperature.

Description

Technical Field

[0001] The invention relates to the field of temperature control, and in particular to a temperature control method of a solution conductivity meter based on fuzzy PID. Background Art

[0002] Temperature, as a physical quantity that characterizes the hotness or coldness of an object, plays a very important role in production activities and scientific experiments. To obtain ideal scientific experimental data or to carry out efficient production, it is necessary to effectively control temperature changes. In particular, in biochemical analysis experiments, temperature errors often affect experimental results.

[0003] With the continuous development and innovation of microelectronics technology, people have higher requirements for the accuracy of temperature control. How to speed up the control process and enhance the robustness of the system has become an urgent need. Most of the temperature controllers on the market currently use traditional PID algorithm control, which has the advantages of simplicity, stability, and adjustability. However, the traditional PID algorithm cannot make real-time corrections to the parameters during the control process. In the face of unknown interference and unknown performance of the controlled object, it is difficult to adjust the parameters and cannot adapt to the changing and complex environment. In addition, the traditional PID control algorithm cannot achieve excellent control effects in temperature control due to the characteristics of nonlinearity and hysteresis in the system. Summary of the invention

[0004] The object of the present invention is to provide a solution conductivity meter temperature control method based on fuzzy PID to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0006] A solution conductivity meter temperature control method based on fuzzy PID, the method comprising:

[0007] The temperature data of the measuring solution is collected through a high-precision temperature sensor;

[0008] Acquire temperature data of the measuring solution, and calculate the temperature deviation value and temperature change rate of the measuring solution;

[0009] Input the temperature deviation value and the temperature change rate into a fuzzy PID control module;

[0010] According to the input temperature deviation value and temperature change rate, the fuzzification and fuzzy rule table in the fuzzy PID control module and the defuzzification output K are p , K i , K d The corresponding change ΔK p , ΔK i , ΔK dThe input of the PID controller is corrected in this way; the updated PID parameters are obtained according to the algorithm, and then the pulse width control signal is obtained by the incremental PID control algorithm to control the drive circuit to dynamically adjust the TEC semiconductor cooler, thereby controlling the temperature of the measured liquid.

[0011] Preferably, calculating the temperature deviation value and the temperature change rate of the measured liquid includes:

[0012] Based on the temperature data of the measured solution, the actual solution temperature value T at time k is obtained. k , and use the subtractor to calculate the temperature deviation value E of the measured solution k :E k =set Tem -T k ;

[0013] Among them, E k Indicates the solution temperature deviation value at time k, set Tem Indicates the set temperature of semiconductor control mode;

[0014] The temperature deviation change rate ΔE of the measured solution is obtained based on two consecutive temperature deviation values ​​combined with the sampling time. k :

[0015]

[0016] Where, ΔE k represents the deviation change rate of the solution temperature at time k, E k-1 It represents the actual solution temperature deviation value at time k-1, and T is the sampling period.

[0017] Preferably, the fuzzification and fuzzy rule table in the fuzzy PID control module and the defuzzification output K p , K i , K d The corresponding change ΔK p , ΔK i , ΔK d This corrects the input to the PID controller, including:

[0018] The input of the fuzzy PID control module is the temperature deviation value E k And the temperature deviation change rate ΔEk, the output is the PID correction amount ΔK p , ΔK i , ΔK d ;

[0019] Among them, the temperature deviation value E k , Temperature deviation change rate ΔE k And the correction value ΔK of PID parameters p , ΔK i , ΔKd All adopt 7 - level fuzzy division, and the fuzzy domain is [-6, 6];

[0020] The said fuzzy rule table is obtained based on expert experience and experimental experience;

[0021] The said K p 、K i 、K d are the initial values of PID parameters, and they are obtained by trial - and - error method in the pre - tuning manner;

[0022] Then, according to the characteristics of the thermoelectric cooler, for different temperature deviation values E k and temperature deviation change rate ΔE k , the correction amounts ΔK p 、ΔK i 、ΔK d of PID are adjusted according to the following rules:

[0023] When the temperature deviation value E k >α, ΔK p >x, ΔK i =0, ΔK d <y; where α, x, and y all represent the intermediate values of fuzzy variables in the fuzzy rule table;

[0024] When the temperature deviation value E k =α and the temperature deviation change rate ΔE k =β, ΔK p <x, ΔK i =s, ΔK d =y; where β and s represent the intermediate values of fuzzy variables in the fuzzy rule table;

[0025] When the temperature deviation value E k <α, ΔK p >x, ΔK i >s, ΔK d <y;

[0026] When the temperature deviation change rate ΔE k <β, ΔK d =y;

[0027] When the temperature deviation change rate ΔE k >β, ΔK d <y;

[0028] And based on the above principles and the characteristics of the thermoelectric cooler, the fuzzy control rules of each PID parameter are summarized to obtain 49 fuzzy rules.

[0029] Preferably, the updated PID parameters are obtained according to the algorithm, and then the pulse width control signal is obtained by the incremental PID control algorithm to control the driving circuit to dynamically adjust the TEC semiconductor refrigerator, thereby controlling the temperature of the measured liquid, including:

[0030] The updated PID parameters include K PK , K IK , K DK , which are obtained by the initial PID parameters through the PID correction parameters and the proportional factor:

[0031] K PK =K p +0.6ΔK p ;

[0032] K IK =K i +0.45ΔK i ;

[0033] K DK =K d +0.3ΔK d ;

[0034] The formula of the incremental PID control algorithm is: k =K PK ΔE k +K IK E k +K DK (ΔE k -ΔE k-1 );

[0035] Where, ΔE k represents the deviation change rate of the solution temperature at time k, ΔE k-1 represents the deviation change rate of the solution temperature at time k-1; at this time, u k The PWM output is used to control the temperature of the liquid being measured.

[0036] Preferably, an electronic device is characterized by comprising:

[0037] at least one processor;

[0038] and, a memory communicatively coupled to the at least one processor;

[0039] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the above-mentioned control method.

[0040] Preferably, a computer-readable storage medium stores a computer program, wherein the computer program implements the above-mentioned control method when executed by a processor.

[0041] Compared with the prior art, the beneficial effects achieved by the present invention are:

[0042] The solution conductivity meter temperature control method based on fuzzy PID proposed by the present invention can effectively improve the control speed, enhance the robustness of the system, and stabilize the temperature near the target temperature. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0044] Figure 1 It is a system block diagram of a solution conductivity meter temperature control method based on fuzzy PID of the present invention;

[0045] Figure 2 This is a flow chart of a temperature control method of a solution conductivity meter based on fuzzy PID of the present invention;

[0046] Figure 3 is the membership function of the fuzzy PID of the present invention;

[0047] Figure 4 These are the experimental results of a temperature control method for a solution conductivity meter based on fuzzy PID. DETAILED DESCRIPTION

[0048] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0049] See also Figure 1-Figure 4 , the present invention provides a technical solution:

[0050] A solution conductivity meter temperature control method based on fuzzy PID, the method comprising:

[0051] S1, collecting temperature data of the measuring solution through a high-precision temperature sensor;

[0052] Preferably, the temperature data of the controlled object is sampled by a high-precision temperature sensor probe. The PT1000 is placed in the beaker solution to collect the temperature data of the measured solution. To ensure the accuracy and anti-interference of the temperature data, the temperature sensor is connected in a four-wire system to eliminate the influence of the excess lead resistance as much as possible.

[0053] Among them, the formula for the change of the resistance of the thermal resistor with temperature is:

[0054]

[0055] Where, t is temperature; R t is the resistance value at different temperatures; A = 3.90802 × 10-3, B = -5.8 × 10-7, C = 4.2735 × 10-12; R0 is the resistance value of the thermal resistor at 0 ° C, R0 = 1000Ω;

[0056] Since the resistance of the thermistor changes with temperature, the voltage divided by the thermistor in the voltage divider circuit changes and is converted into a voltage signal. The specific value of the collected temperature is calculated through digital-to-analog conversion.

[0057] S2. Obtain the temperature data of the measurement solution, and calculate the temperature deviation value and temperature change rate of the measurement solution;

[0058] Preferably, calculating the temperature deviation value and the temperature change rate of the measured liquid includes:

[0059] Based on the temperature data of the measured solution, the actual solution temperature value T at time k is obtained. k , and use the subtractor to calculate the temperature deviation value E of the measured solution k :E k =set Tem -T k ;

[0060] Among them, E k Indicates the solution temperature deviation value at time k, set Tem Indicates the set temperature of semiconductor control mode;

[0061] The temperature deviation change rate ΔE of the measured solution is obtained based on two consecutive temperature deviation values ​​combined with the sampling time. k :

[0062]

[0063] Where, ΔE k represents the deviation change rate of the solution temperature at time k, E k-1 It represents the actual solution temperature deviation value at time k-1, and T is the sampling period.

[0064] S3, inputting the temperature deviation value and the temperature change rate into a fuzzy PID control module;

[0065] S4, according to the input temperature deviation value and temperature change rate, through the fuzzification and fuzzy rule table in the fuzzy PID control module and the defuzzification output K p , K i , K d The corresponding change ΔK p , ΔK i , ΔK d The input of the PID controller is corrected in this way; the updated PID parameters are obtained according to the algorithm, and then the pulse width control signal is obtained by the incremental PID control algorithm to control the drive circuit to dynamically adjust the TEC semiconductor refrigerator, thereby controlling the temperature of the measured liquid;

[0066] Preferably, the fuzzification and fuzzy rule table in the fuzzy PID control module and the defuzzification output K p , K i , K d The corresponding change ΔK p , ΔK i , ΔK d This corrects the input to the PID controller, including:

[0067] The fuzzy PID control module calls the corresponding input membership function according to the input value to perform fuzzification, then performs fuzzy reasoning through the rule base, and finally defuzzifies through the output membership function, outputs the corresponding PID parameters, and obtains the pulse width control signal through the incremental PID algorithm and transmits it to the drive circuit. The drive circuit outputs voltage to control the TEC semiconductor to achieve control of the solution temperature measured by the conductivity meter;

[0068] like Figure 3 The figure shows a universal membership function diagram for two inputs and three outputs. The input in the fuzzy PID control module is the temperature deviation value E. k and temperature deviation change rate ΔE k , both inputs adopt 7-level fuzzy division, temperature deviation value E k The basic domain range is [-6,6], and the temperature deviation change rate ΔE k The basic domain range is [-6,6], and the three outputs in the fuzzy PID control module are the PID correction value ΔK p , ΔK i , ΔK d , and they all use 7-level fuzzy classification, namely negative large (NB), negative medium (NM), negative small (NS), zero (O), positive small (PS), positive medium (PM) and positive large (PB), and their fuzzy domains are all [-6,6];

[0069] Due to the very small thermal inertia of the semiconductor refrigerator, the cooling and heating times are very fast. The input of the fuzzy PID control module is the temperature deviation value E k and the temperature deviation change rate ΔE k , and the output is the correction amount ΔK p 、ΔK i 、ΔK d ;

[0070] Among them, the temperature deviation value E k 、the temperature deviation change rate ΔE k and the correction amount ΔK p 、ΔK i 、ΔK d of the PID parameters are all divided into 7 levels of fuzziness, and the fuzzy universe is [-6, 6];

[0071] The fuzzy rule table is obtained based on expert experience and experimental experience;

[0072] The K p 、K i 、K d are the initial values of the PID parameters, and they are obtained by trial and error in a pre-tuning manner;

[0073] Then, according to the characteristics of the semiconductor refrigerator, for different temperature deviation values E k and temperature deviation change rates ΔE k , the correction amounts ΔK p 、ΔK i 、ΔK d of the PID are adjusted according to the following rules:

[0074] When the temperature deviation value E k > α, ΔK p > x, ΔK i = 0, ΔK d < y; where α, x, and y all represent the intermediate quantities of the fuzzy variables in the fuzzy rule table;

[0075] When the temperature deviation value E k is relatively large, a relatively large ΔK p and a relatively small ΔK d are selected. The former quickly adjusts the system, and the latter prevents differential oversaturation caused by excessive short-term changes in the temperature deviation value E k . ΔK i is taken as 0 to prevent integral saturation and avoid excessive overshoot;

[0076] When the temperature deviation value E k = α and the temperature deviation change rate ΔE k = β, ΔK p < x, ΔK i=s,ΔK d =y; where β and s represent the intermediate quantities of fuzzy variables in the fuzzy rule table;

[0077] When E k and ΔE k When the value is in the middle, in order to reduce the overshoot, ΔK p The value should be small, ΔK i and ΔK d The value is taken in the middle, so that the system response speed adapts to the demand;

[0078] When the temperature deviation value E k <α, ΔK p >x,ΔK i >s,ΔK d <y;

[0079] When E k When the value of is small, ΔK p and ΔK i The value of is taken larger to ensure the stability of the control system. Considering the enhancement of robustness and the prevention of oscillation, ΔK d An appropriate smaller value should be taken;

[0080] When the temperature deviation change rate ΔE k <β, ΔK d =y;

[0081] When ΔE k When the value of is small, ΔK d Take the middle value;

[0082] When the temperature deviation change rate ΔE k >β, ΔK d <y;

[0083] When ΔE k When the value of is too large, ΔK d A smaller value should be taken;

[0084] According to the above principles and the characteristics of semiconductor refrigerators, the fuzzy control rules of PID parameters are summarized and 49 fuzzy rules are obtained.

[0085] For example, its reasoning logic can be expressed as ΔK p E k =PB, ΔE k =NS, then ΔK p=NM; In the process of converting analog quantity into precise quantity, this patent adopts the maximum membership method, and after conversion into precise quantity, numerical correction is required, and the precise quantity is multiplied by the proportional factor to obtain the final control quantity; the final control quantity is corrected on the basis of the initial PID parameter, and the correction quantity is substituted into the update PID parameter formula to obtain the corrected PID parameter value; the correction parameter is subjected to the incremental PID algorithm to obtain the output PWM;

[0086] The fuzzy PID control module contains the following rules:

[0087] Table 1 Assignment table of fuzzy variables

[0088]

[0089]

[0090] Table 2 △K p Fuzzy control rule table

[0091] <![CDATA[E k \△E k ]]> NB NM NS O PS PM PB NB PB PB PM PM PS O O NM PB PB PM PS PS O NS NS PM PM PS PS O NS NS O PM PM PS O NS NM NM PS PS PS O NS NS NM NM PM PS O NS NS NM NM NB PB O O NM NM NM NB NB

[0092] Table 3 △K i Fuzzy control rule table

[0093] <![CDATA[E k \△E k ]]> NB NM NS O PS PM PB NB NB NB NM NM NS O O NM NB NB NM NS NS O O NS NB NM NS NS O PS PS O NM NS NS O PS PM PM PS NM NS O PS PS PM PB PM O O PS PM PM PB PB PB O O PS PM PM PB PB

[0094] Table 4 △K d Fuzzy control rule table

[0095]

[0096]

[0097] Preferably, the updated PID parameters are obtained according to the algorithm, and then the pulse width control signal is obtained by the incremental PID control algorithm to control the driving circuit to dynamically adjust the TEC semiconductor refrigerator, thereby controlling the temperature of the measured liquid, including:

[0098] The updated PID parameters include K PK , K IK , K DK , which are obtained by the initial PID parameters through the PID correction parameters and the proportional factor:

[0099] K PK =K p +0.6ΔK p ;

[0100] K IK =K i +0.45ΔK i ;

[0101] KDK =K d +0.3ΔK d ;

[0102] The formula of the incremental PID control algorithm is: k =K PK ΔE k +K IK E K +K DK (ΔE k -ΔE k-1 );

[0103] Where, ΔE k represents the deviation change rate of the solution temperature at time k, ΔE k-1 represents the deviation change rate of the solution temperature at time k-1; at this time, u k The PWM output is used to control the temperature of the liquid being measured.

[0104] Preferably, an electronic device is characterized by comprising:

[0105] at least one processor;

[0106] and, a memory communicatively coupled to the at least one processor;

[0107] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the above-mentioned control method.

[0108] Preferably, a computer-readable storage medium stores a computer program, wherein the computer program implements the above-mentioned control method when executed by a processor.

[0109] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A solution conductivity meter temperature control method based on fuzzy PID, characterized in that: The method comprises: The temperature data of the measuring solution is collected through a high-precision temperature sensor; Acquire temperature data of the measuring solution, and calculate the temperature deviation value and temperature change rate of the measuring solution; Input the temperature deviation value and the temperature change rate into a fuzzy PID control module; According to the input temperature deviation value and temperature change rate, the fuzzification and fuzzy rule table in the fuzzy PID control module and the defuzzification output K are p , K i , K d The corresponding change ΔK p , ΔK i , ΔK d The input of the PID controller is corrected in this way; the updated PID parameters are obtained according to the algorithm, and then the pulse width control signal is obtained by the incremental PID control algorithm to control the drive circuit to dynamically adjust the TEC semiconductor cooler, thereby controlling the temperature of the measured liquid.

2. A solution conductivity meter temperature control method based on fuzzy PID as claimed in claim 1, characterized in that: The calculating and measuring the temperature deviation value and the temperature change rate of the liquid comprises: Based on the temperature data of the measured solution, the actual solution temperature value T at time k is obtained. k , and use the subtractor to calculate the temperature deviation value E of the measured solution k :E k =set Tem -T k ; Among them, E k Indicates the solution temperature deviation value at time k, set Tem Indicates the set temperature of semiconductor control mode; The temperature deviation change rate ΔE of the measured solution is obtained based on two consecutive temperature deviation values ​​combined with the sampling time. k : Where, ΔE k represents the deviation change rate of the solution temperature at time k, E k-1 It represents the actual solution temperature deviation value at time k-1, and T is the sampling period.

3. A solution conductivity meter temperature control method based on fuzzy PID as claimed in claim 1, characterized in that: The fuzzification and fuzzy rule table in the fuzzy PID control module and the defuzzification output K p , K i , K d The corresponding change ΔK p , ΔK i , ΔK d This corrects the input to the PID controller, including: The input of the fuzzy PID control module is the temperature deviation value E k and temperature deviation change rate ΔE k , the output is the PID correction value ΔK p , ΔK i , ΔK d ; Among them, the temperature deviation value E k , Temperature deviation change rate ΔE k And the correction value ΔK of PID parameters p , ΔK i , ΔK d All adopt 7-level fuzzy division, and the fuzzy domain is [-6,6]; The fuzzy rule table is obtained based on expert experience and experimental experience; The K p , K i , K d are the initial values ​​of the PID parameters, which are obtained by trial and error in pre-tuning; According to the characteristics of the semiconductor refrigerator, for different temperature deviation values ​​E k and temperature deviation change rate ΔE k , PID correction value ΔK p , ΔK i , ΔK d Adjust according to the following rules: When the temperature deviation value E k > α, ΔK p > x, ΔK i = 0, ΔK d < y; where α, x, and y all represent intermediate quantities of fuzzy variables in the fuzzy rule table; When the temperature deviation value E k =α, temperature deviation change rate ΔE k =β, ΔK p <x,ΔK i =s,ΔK d =y; where β and s represent the intermediate quantities of fuzzy variables in the fuzzy rule table; When the temperature deviation value E k <α, ΔK p >x,ΔK i >s,ΔK d <y; When the temperature deviation change rate ΔE k <β, ΔK d =y; When the temperature deviation change rate ΔE k >β, ΔK d <y; According to the above principles and the characteristics of semiconductor refrigerators, the fuzzy control rules of various PID parameters are summarized and 49 fuzzy rules are obtained.

4. A solution conductivity meter temperature control method based on fuzzy PID as claimed in claim 1, characterized in that: The updated PID parameters are obtained according to the algorithm, and then the pulse width control signal is obtained by the incremental PID control algorithm to control the driving circuit to dynamically adjust the TEC semiconductor refrigerator, thereby controlling the temperature of the measured liquid, including: The updated PID parameters include K PK , K IK , K DK , which are obtained by the initial PID parameters through the PID correction parameters and the proportional factor: K PK =K p +0.6ΔK p ; K IK =K i +0.45ΔK i ; K DK =K d +0.3ΔK d ; The formula of the incremental PID control algorithm is: k =K PK ΔE k +K IK E k +K DK (ΔE k -ΔE k-1 ); Where, ΔE k represents the deviation change rate of the solution temperature at time k, ΔE k-1 represents the deviation change rate of the solution temperature at time k-1; at this time, u k The PWM output is used to control the temperature of the liquid being measured.

5. An electronic device, characterized in that: include: at least one processor; and, a memory communicatively coupled to the at least one processor; The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the control method as described in any one of claims 1 to 4.

6. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the control method according to any one of claims 1 to 4 is implemented.

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