An environmental humidity control system and method for the tobacco leaf baking process of a tobacco leaf baking machine

Abstract

The present invention relates to an environmental humidity control system and method for the tobacco leaf baking process of a tobacco leaf baking machine, belonging to the technical field of tobacco leaf redrying; through the automatic control system for redrying humidity detection, it realizes the automatic adjustment of the internal environmental humidity of the tobacco leaf redrying drying area, enables the humidity state of the whole tobacco leaf drying process to be controlled, balances the internal air humidity control of 6 drying areas, meets the requirements of the process humidity control curve, realizes the processing requirement of "low-temperature slow baking" of tobacco leaves, can prevent the tobacco leaves from being "dried by high temperature", maintain the internal aroma components of the tobacco leaves, and improve the sensory quality of the tobacco leaves and the uniformity of moisture control.

Description

Technical Field

[0001] The present invention relates to an environmental humidity control system and method for the tobacco leaf baking process of a tobacco leaf baking machine, and belongs to the technical field of tobacco leaf redrying. Background Art

[0002] In the past, only the hot air temperature in the drying area was considered in tobacco leaf redrying, and the tobacco leaves were dried to the moisture process index of 9 - 11%. The key process index humidity of tobacco leaf dehydration in the 6 drying areas could not be controlled throughout the process. As a result, during the drying process of tobacco leaves, the baking temperature was high, and the aroma of tobacco leaves was lost, affecting the sensory quality of tobacco leaves.

[0003] When the tobacco leaves pass through the drying area of the tobacco leaf baking machine and are dried with circulating hot air, a large amount of moisture is released when the tobacco leaves exchange heat with the hot air and combines with the hot air to generate a large amount of humid hot air. The drying mechanism of tobacco leaves shows that the environmental humidity has an important impact on the drying and dehydration of tobacco leaves. The previous tobacco leaf redrying machines only had a temperature control system and did not automatically detect and control the humidity index, which has an important impact on the tobacco leaf dehydration process, resulting in poor drying effect of tobacco leaves. For example, although the drying temperature in the drying area is high, due to the large amount of moisture released after the dehydration of tobacco leaves, the environment in the drying area is very humid. According to the tobacco leaf dehydration mechanism, the internal moisture of tobacco leaves cannot be further released, affecting the aroma quality of tobacco leaves.

[0004] Therefore, an environmental humidity control system and method for the tobacco leaf baking process of a tobacco leaf baking machine are proposed to overcome the nonlinearity, time-variation, and uncertainty of the control model during the drying process, so as to accurately control the environmental humidity in each drying area, reduce the volatilization of tobacco leaf aroma due to high temperature, achieve the aroma preservation and moisture retention of tobacco leaves, and thus improve the sensory and smoking quality of redried tobacco leaves. Summary of the Invention

[0005] In order to overcome the problems in the background art, the present invention realizes the real-time monitoring of the humidity inside the drying area by comprehensively using hardware devices such as fans, actuators, temperature and humidity sensors, and air volume sensors, and adopts a fuzzy adaptive PID control algorithm to automatically adjust the exhaust air volume and the supply air volume of the air supply damper, so that the tobacco leaf baking can be realized according to the optimized process requirements, the humidity balance in each drying area is stable, the homogenization standard of redrying production is improved, the tobacco leaf redrying processing level is enhanced, the moisture of tobacco leaves is controlled within the standard range, the volatilization of tobacco leaf aroma due to high temperature is reduced, the aroma preservation and moisture retention of tobacco leaves are realized, and the sensory and smoking quality of redried tobacco leaves is improved.

[0006] In order to overcome the problems in the background art and solve the above problems, the present invention is realized through the following technical solutions:

[0007] An environmental humidity control method for the tobacco leaf baking process of a tobacco leaf baking machine includes the following steps:

[0008] Step 1: Summarize the theoretical basis and experience, and collect and file the real-time tobacco leaf baking humidity process parameters in the drying area.

[0009] Step 2: Establish a PID control function model, and write fuzzy control inference rules according to the humidity parameters in the drying area.

[0010] Step 3: Determine the membership function, retrieve the facts of the current system from the database, find the matching rules in the rule base, perform fuzzy inference, and give the estimated values of Kp, Ki, and Kd; Step 4: Perform fuzzy inference and defuzzification operations to obtain the precise control parameters of Kp, Ki, and Kd.

[0011] Preferably, the specific process of Step 1 is to summarize the optimal humidity of 6 drying areas according to daily production experience, and collect the humidity of 6 drying areas in real time and input it into the controller.

[0012] Preferably, the specific steps of Step 2 are to establish a PID control function model:

[0013]

[0014] In the formula, u(k) is the control output, kp is the proportional coefficient, ki is the integral coefficient, kd is the differential coefficient, u0 is the initial control value, and e(k) is the error.

[0015] Fuzzy self-tuning of PID parameters is to find the fuzzy relationship between the three PID parameters and, continuously detect during operation, and modify the three parameters online to meet different requirements for control parameters at different time periods. This system is a two-input and three-output fuzzy controller with the error e and the error change rate ec as the input language variables and Kp, Ki, and Kd as the output language variables. The absolute value of the error |e| and the absolute value of the error change rate |ec| are used to fully represent the response process of the entire system. The variation ranges of the system error e and the error change rate ec are defined as the universes of discourse on the fuzzy sets, and their fuzzy subsets are:

[0016] (e, ec) = {NB, NB, NM, 0, PS, PM, PB} (2)

[0017] In the subset, NB represents negative large, NM represents negative medium, NS represents negative small, PS represents positive small, PM represents positive medium, and PB represents positive large.

[0018] Assume that e, ec, and the three coefficients all follow a normal distribution, obtain the membership degrees of each fuzzy subset, and according to the membership degree assignment table of each fuzzy subset and each parameter fuzzy control model, apply fuzzy synthetic inference to design the fuzzy matrix table of PID parameters and find out the correction parameters.

[0019] Preferably, the process of determining the membership function in step 3 is as follows. Let the universes of discourse of the linguistic variables |e|, |ec|, Kp, Ki, and Kd of the fuzzy controller be:

[0020] |e|: X = {0, X1, X2, X3}

[0021] |ec|: Y = {0, Y1, Y2, Y3}

[0022] Kp: Zp = {0, Zp1, Zp2, Zp3} (3)

[0023] Ki: Zi = {0, Zi1, Zi2, Zi3}

[0024] Kd: Zd = {0, Zd1, Zd2, Zd3}

[0025] Among the above universes of discourse of the linguistic variables, the linguistic values of the input linguistic variables |e| and |ec| take four types: B, M, S, and Z; the linguistic values of the output linguistic variables Kp, Ki, and Kd also take four types: B, M, S, and Z; the definitions of each linguistic value are respectively described by the membership function curves, and the control rule tables of Kp, Ki, and Kd are shown in Table 1, Table 2, and Table 3 respectively:

[0026] Table 1 K P Control rule table

[0027]

[0028] Table 2 K I Control rule table

[0029]

[0030] Table 3 K d Control rule table

[0031]

[0032] After establishing the rule set, compile the fuzzy control inference engine program, retrieve the facts of the current system from the database, find the matching rules in the rule base, perform fuzzy inference, and give the estimated values of Kp, Ki, and Kd.

[0033] Preferably, the process of fuzzy inference and defuzzification operation is as follows. According to Table 1, Table 2, and Table 3, the membership degrees of all fuzzy values of the Kp, Ki, and Kd parameters under different deviations and deviation change rates can be obtained respectively. Then, based on the measured values of e and ec, and according to the defuzzification weighted average rule for judgment, the precise control parameter values of Kp, Ki, and Kd can be obtained, that is:

[0034]

[0035]

[0036]

[0037] In formulas (4), (5), and (6): μkpj(Zp) is the membership degree corresponding to the current measured values |e| and |ec|, Zpj is the central element value of each fuzzy value domain taken by parameter Kp, and the subsequent definitions of Ki and Kd are similar;

[0038] After obtaining the precise control parameters of Kp, Ki, and Kd, a control adjustment signal is obtained and converted into the opening degree of the air damper actuator and the exhaust air volume. These two signals are used as the set values of the make-up air controller and the exhaust air controller respectively. The make-up air controller uses the actual opening degree of the valve for feedback closed-loop control; the exhaust air controller uses the actual exhaust air volume for closed-loop control. The entire system constitutes a double closed-loop cascade control, and by adjusting the air volume entering and leaving the drying area, the stable balance of air humidity is achieved.

[0039] An environmental humidity control system for the tobacco leaf baking process of a tobacco leaf baking machine includes a main air duct, a steam pipe, a circulation fan, a temperature transmitter, a humidity sensor, an exhaust fan, a make-up air damper, a drying area, a controller, an air flow meter, a radiator, and a switch. The main air duct is a circulation heating duct. The make-up air damper is installed at the front end of the main air duct. The radiator is installed behind the make-up air damper. The steam pipe is installed on the radiator. The circulation fan is installed on the main air duct behind the radiator. The main air duct is installed at the upper and lower ends of the drying area. The temperature transmitter is installed in the drying area. An exhaust channel is provided on the main air duct behind the drying area, and an exhaust fan is installed on the exhaust channel. The air flow meter is installed at the air outlet of the exhaust fan. The humidity sensor is installed in the exhaust channel. The controller is connected to the circulation fan, the temperature transmitter, the humidity sensor, the exhaust fan, the make-up air damper, and the air flow meter through the switch.

[0040] Preferably, the controller is connected to an operation screen through the switch, and a communication module is connected to the controller.

[0041] The beneficial effects of the present invention are as follows:

[0042] By comprehensively using hardware devices such as fans, actuators, temperature and humidity sensors, and air flow sensors, and adopting a fuzzy adaptive PID control algorithm, the present invention realizes real-time monitoring of the humidity inside the drying area, automatically adjusts the exhaust air volume and the make-up air volume of the make-up air damper, enables the tobacco leaf baking to be realized according to the optimized process requirements, makes the humidity balance and stability of each drying area, improves the homogenization standard of the re-drying production, enhances the tobacco leaf re-drying processing level, controls the tobacco leaf moisture within the standard range, reduces the volatilization of tobacco leaf aroma due to high temperature, realizes the aroma and moisture preservation of tobacco leaves, and improves the sensory and smoking quality of the re-dried tobacco leaves. Description of the Drawings

[0043] Figure 1 is the schematic diagram of the humidity control of the baking machine of the present invention;

[0044] Figure 2 is the connection diagram of the control system of the present invention;

[0045] Figure 3 is the block diagram of the humidity closed-loop cascade control system of the present invention;

[0046] Figure 4 is the curve diagram of the humidity set value of each drying area of the present invention;

[0047] Figure 5 is the structure diagram of the fuzzy PID controller of the present invention;

[0048] Figure 6 is the working flow chart of the fuzzy control of the present invention;

[0049] Figure 7 is the curve diagram of the fuzzy control membership function of the present invention;

[0050] Figure 8 is the step response curve diagram of the fuzzy self-tuning PID control of the present invention.

[0051] The reference numerals in the figure are: 1 - main air duct, 2 - steam pipe, 3 - circulation fan, 4 - temperature transmitter, 5 - humidity sensor, 6 - exhaust fan, 7 - makeup air damper, 8 - drying area, 9 - controller, 10 - air flow meter, 11 - radiator, 12 - switch, 13 - operation screen. Detailed implementation manners

[0052] In order to make the objectives, technical solutions and beneficial effects of the present invention clearer, the preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings for the convenience of those skilled in the art to understand.

[0053] As Figure 1-2As shown in the figure, an environmental humidity control system for the tobacco leaf baking process of a tobacco leaf baking machine includes a main air duct 1, a steam duct 2, a circulation fan 3, a temperature transmitter 4, a humidity sensor 5, an exhaust fan 6, a makeup air damper 7, a drying area 8, a controller 9, an air flow meter 10, a radiator 11, a switch 12, and an operation screen 13. The main air duct 1 is a circulation heating duct, which is divided into an inlet air duct and a return air duct. The makeup air damper 7 is installed at the front end of the main air duct 1 to adjust the intake of fresh air. The radiator 11 is installed on the inlet air duct behind the makeup air damper 7, and the steam duct 2 is installed on the radiator 11. Fresh air and recycled hot air enter the drying area radiator together for heating to form hot air for drying tobacco leaves. The circulation fan 3 is installed on the inlet air duct of the main air duct 1 behind the radiator 11. The inlet air duct of the main air duct 1 is installed at the lower end of the drying area 8, and the return air duct of the main air duct 1 is installed at the upper end of the drying area 8. The temperature transmitter 4 is installed on the drying area 8 and connected to the controller 9. A moisture exhaust channel is provided on the return air duct of the main air duct 1, and an exhaust fan 6 is installed on the moisture exhaust channel. The air flow meter 10 is installed at the outlet of the exhaust fan 6, and the humidity sensor 5 is installed in the moisture exhaust channel. The temperature and humidity sensor 5 measures the ambient humidity of the circulating air in the moisture exhaust channel and inputs the detected digital signal into the controller 9.

[0054] The controller 9 is connected to the frequency converters of the circulation fan 3 and the exhaust fan 6 through the switch 12 to control the air intake and exhaust volume. The damper actuator is connected to the controller 9 through the field substation via Ethernet. Various sensors are installed nearby on-site and connected to the controller 9 through the substation to form a detection and control communication system. The controller 9 uses a PLC controller, and the switch 12 selects STRATIX6000 switches and STRATIX2000 switches. A communication module 1756-NE2T is connected to the controller 9. The controller 9 is connected to a field operation screen through the switch 12 for on-site operation and display of the humidity control system.

[0055] When the humidity control system for the tobacco leaf baking of the tobacco leaf baking machine of the present invention is running, the temperature and humidity sensor 5 measures the ambient humidity of the circulating air in the drying area and transmits the detected digital signal to the electric control system through the network. After comparing it with the optimized set value of the humidity curve, according to the deviation (e = set - actual), an adjustment signal is given in the control program. First, the electric control system sends a control signal to the makeup air damper (damper adjustment opening) to adjust the intake of fresh air (the fresh air entering the internal environment of each drying area, together with the recycled hot air, enters the drying area radiator for heating to form hot air for drying tobacco leaves). Secondly, the exhaust air volume at the top of the baking machine is adjusted accordingly (a large amount of water vapor is released during the tobacco leaf drying process), the discharge volume of the humid hot air passing through the heat exchange with the tobacco leaves is adjusted, and finally the steam volume entering the radiator is adjusted to maintain the temperature of the circulating air, so as to maintain the stable balance of the air volume and humidity inside the drying area.

[0056] A method for controlling the environmental humidity during the tobacco leaf baking process of a tobacco leaf baking machine. The design concept is as follows Figure 3 shown. First, the humidity deviation is compared, and PID control adjustment is performed according to the deviation to obtain a control adjustment signal. The control adjustment signal is respectively calculated and converted into the opening degree of the damper angle actuator and the frequency signal of the exhaust fan inverter. These two signals are respectively used as the set values of the makeup air controller and the exhaust air volume set value of the exhaust fan. The makeup air controller uses the actual opening degree of the valve for feedback closed-loop control; the exhaust controller uses the actual exhaust volume for closed-loop control. The entire system constitutes a double closed-loop cascade control. By adjusting the air volume entering and leaving the drying area, the stable balance of air humidity is achieved to meet the humidity control requirements. The humidity adjustment is the main loop, and the air volume adjustment is the secondary loop. The damper and the exhaust air volume controller quickly achieve air volume balance; while the humidity adjustment loop improves the control accuracy, stability, and anti-interference ability. The two-level controllers are coordinated and cooperate with each other. It is ensured that under the condition of changes in environmental conditions and loads, there is still a good control effect, and the control of the 6 drying areas is similar.

[0057] As Figure 3-8 shown, a method for controlling the humidity of tobacco leaves during baking by a tobacco leaf baking machine includes the following steps

[0058] Step 1: Summarize the theoretical basis and experience, and collect and file the real-time tobacco leaf baking humidity process parameters in the drying area.

[0059] Step 2: Establish a PID control function model, and write fuzzy control inference rules according to the humidity parameters in the drying area.

[0060] Step 3: Determine the membership function, extract the facts of the current system from the database, find the matching rules in the rule base, perform fuzzy inference, and give the estimated values of Kp, Ki, and Kd; Step 4: Perform fuzzy inference and defuzzification operations to obtain the precise control parameters of Kp, Ki, and Kd.

[0061] The specific process of the said Step 1 is to summarize the optimal humidity of the 6 drying areas according to daily production experience, and input the humidity values of the 6 drying areas collected in real time into the controller. Figure 4 is the humidity control diagram of the 6 drying areas, which meets the technological requirements of tobacco leaf redrying. In the first drying area, the tobacco leaves enter the baking machine, the exhaust is closed, the makeup air is reduced, and the temperature of the tobacco leaves is accelerated to rise for dehydration preheating. The air humidity is the lowest. By the fifth area, a large amount of water in the tobacco leaves is dehydrated, and the environmental humidity reaches the maximum. It is necessary to reduce the humidity and increase the exhaust and fresh air supplement. In the 2nd, 3rd, and 4th areas, the tobacco leaves are gradually dehydrated, and the environmental humidity is also higher. The humidity reaches the peak in the 5th area. The 6th area is about to enter the cooling and rehumidifying stage. In order to prevent a large amount of water vapor from entering the cooling and rehumidifying area, it is necessary to reduce the humidity in the 6th area (increase the fresh air intake and increase the exhaust volume) to form a new environmental humidity processing technology.

[0062] Preferably, the specific steps of step 2 are as follows: establish a PID control function model:

[0063]

[0064] In the formula, u(k) is the control output, kp is the proportional coefficient, ki is the integral coefficient, kd is the differential coefficient, u0 is the initial control value, and e(k) is the humidity error;

[0065] Fuzzy self-tuning of PID parameters is to find the fuzzy relationship between the three PID parameters, continuously detect during operation, and modify the three parameters online to meet different requirements for control parameters at different time periods. This system is a two-input three-output fuzzy controller with the absolute value of humidity error e and the absolute value of humidity error change rate ec as the input language variables and Kp, Ki, Kd as the output language variables. The absolute value of the humidity error |e| and the absolute value of the humidity error change rate |ec| completely represent the response process of the entire system. The change ranges of the system humidity error e and the humidity error change rate ec are defined as the universes of discourse on the fuzzy sets, and their fuzzy subsets are:

[0066] (e, ec) = {NB, NB, NM, 0, PS, PM, PB} (2)

[0067] In the subset, NB represents negative large, NM represents negative medium, NS represents negative small, PS represents positive small, PM represents positive medium, and PB represents positive large;

[0068] Assume that e, ec, and the three coefficients all follow a normal distribution, obtain the membership degrees of each fuzzy subset, and according to the membership degree assignment table of each fuzzy subset and the fuzzy control model of each parameter, apply fuzzy synthetic inference to design the fuzzy matrix table of PID parameters and find out the correction parameters.

[0069] During the online operation process, the control system completes the online self-correction of PID parameters through the result processing, table lookup, and calculation of fuzzy logic rules. Its working flow chart is as Figure 6 shown.

[0070] Based on the influence of the parameters Kp, Ki, and Kd on the system output characteristics, it can be summarized that in general, for different humidity errors |e| and the change rate of humidity error |ec|, the self-tuning requirements of the controlled process for the parameters Kp, Ki, and Kd are as follows: When |e| is relatively large, in order to accelerate the system response speed and avoid the instantaneous increase of the deviation of |e| at the beginning, which may cause the control action to exceed the allowable range, and at the same time to prevent integral saturation and avoid large overshoot in the system response, a larger Kp and a smaller Kd should be taken, and the integral action should be removed. When |e| and |ec| are of medium magnitude, to reduce the corresponding overshoot of the system, neither Kp, Ki, nor Kd should be large. A smaller Ki should be taken, and the magnitudes of Kp and Kd should be moderate to ensure the system response speed. When |e| is relatively small, to make the system have good steady-state performance, the values of Kp and Ki should be increased. At the same time, to avoid oscillations near the set value of the system and consider the anti-interference ability of the system, an appropriate value of Kd should be selected. The principle is: when |ec| is relatively small, Kd should be taken larger; when |ec| is relatively large, Kd should be taken smaller.

[0071] The process of determining the membership function in step 3 is as follows. Let the universes of discourse of the fuzzy controller's language variables |e|, |ec|, Kp, Ki, and Kd be:

[0072] |e|: X = {0, X1, X2, X3}

[0073] |ec|: Y = {0, Y1, Y2, Y3}

[0074] Kp: Zp = {0, Zp1, Zp2, Zp3} (3)

[0075] Ki: Zi = {0, Zi1, Zi2, Zi3}

[0076] Kd: Zd = {0, Zd1, Zd2, Zd3}

[0077] In the above universes of discourse of language variables, the universe of discourse language values of the input language variables |e| and |ec| take four kinds: B, M, S, Z; the universe of discourse language values of the output language variables Kp, Ki, and Kd also take four kinds: B, M, S, Z; the definitions of each language value are described by membership function curves respectively, as Figure 7 shown, and the control rule tables of Kp, Ki, and Kd are shown in Table 1, Table 2, and Table 3 respectively:

[0078] Table 1 K I Control rule table

[0079]

[0080] Table 2 K I Control rule table

[0081]

[0082] Table 3 K d Control rule table

[0083]

[0084] After establishing the rule set, compile the fuzzy control inference engine program, retrieve the facts of the current system from the database, find the matching rules in the rule base, perform fuzzy inference, and give the estimated values of Kp, Ki, and Kd.

[0085] The fuzzy inference and defuzzification operation process is as follows. According to Table 1, Table 2, and Table 3, the membership degrees of all fuzzy values of the KP, KI, and KD parameters under different deviations and deviation change rates can be obtained respectively. Then, based on the measured values of e and ec, and according to the defuzzification weighted average rule for judgment, the precise control parameters Kp, Ki, and Kd values of Kp, Ki, and Kd can be obtained, that is:

[0086]

[0087]

[0088]

[0089] In formulas (4), (5), and (6): μkpj(Zp) is the membership degree corresponding to the current measured values |e| and |ec|, Zpj is the central element value of each fuzzy value taken by the parameter Kp, and the definitions of Ki and Kd later are similar;

[0090] After obtaining the precise control parameters of Kp, Ki, and Kd, the control adjustment signal is obtained, which is converted into the opening degree of the air damper actuator and the exhaust air volume. The two signals are used as the set values of the make-up air controller and the exhaust air controller respectively. The make-up air controller uses the actual opening degree of the valve for feedback closed-loop control; the exhaust air controller uses the actual exhaust air volume for closed-loop control. The entire system constitutes a double closed-loop cascade control. By adjusting the air volume entering and leaving the drying area, the stable balance of air humidity is achieved. The step response curve of the control system is as Figure 8 shown.

[0091] Finally, it should be noted that the above preferred embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit. Although the present invention has been described in detail through the above preferred embodiments, those skilled in the art should understand that various changes can be made in form and details without departing from the scope defined by the claims of the present invention.

Claims

1. A method for controlling the humidity of tobacco leaves during baking in a tobacco leaf baking machine, characterized in that, It includes the following steps: Summarize the theoretical basis and experience, and determine the optimal humidity for each drying area; Collect the real-time tobacco leaf baking humidity value in the drying area as the input value of the fuzzy inference PID control model, and calculate the control adjustment signal; specifically, compare the error value between the optimal humidity and the real-time humidity in the drying area to be controlled, perform PID control adjustment according to the error value, the air supply controller uses the actual opening of the valve for feedback closed-loop control, and the moisture exhaust controller uses the actual moisture exhaust volume for closed-loop control. With humidity adjustment as the main loop and air volume adjustment as the secondary loop, a double closed-loop cascade control is formed; Convert the control adjustment signal into the opening degree of the air damper angle actuator and the frequency signal of the moisture exhaust fan inverter, and the two signals are respectively used as the set values of the air supply controller and the moisture exhaust fan controller; The fuzzy inference PID control model includes establishing a PID control function model and writing fuzzy control inference rules according to the humidity parameters in the drying area, including: fuzzy self-tuning of PID parameters is to find the proportional coefficient of PID Kp , integral coefficient Ki , and differential coefficient Kd among the three parameters and the error e and the error change rate ec The fuzzy relationship between them is continuously detected during operation, and the three parameters are modified in real time online to meet different requirements for control parameters in different time periods, adapt to changes in the controlled object or eliminate interference factors, and improve the control accuracy; Using the error e and the rate of change of error ec as the input linguistic variables, and Kp , Ki , Kd as the output linguistic variables, a two-input three-output fuzzy controller. The absolute value of the error | e | and the absolute value of the rate of change of error | ec | completely represent the response process of the entire system. Define the variation ranges of the system error e and the rate of change of error ec as the universes of discourse on the fuzzy sets; assume that e, ec, and the three parameters all follow a normal distribution, obtain the membership degrees of each fuzzy subset, and according to the membership degree assignment table of each fuzzy subset and the fuzzy control model of each parameter, apply fuzzy synthetic inference to design the fuzzy matrix table of PID parameters and find out the correction parameters; Determination of the membership function, retrieving the facts of the current system from the database, searching for matching rules in the rule base, performing fuzzy inference, and giving Kp , Ki and Kd estimated values; Fuzzy inference and defuzzification operations are performed to obtain Kp and Ki and Kd of the precise control parameters, including according to Kp and Ki and Kd control rules, respectively obtain Kp and Ki and Kd the membership degrees of all fuzzy values of the parameters under different errors and error change rates, and then according to e and ec measurement values, and judge according to the defuzzification weighted average rule to obtain Kp and Ki and Kd of the precise control parameters Kp and Ki and Kd values; after obtaining Kp and Ki and Kd of the precise control parameters, a control adjustment signal is obtained.

2. The method for controlling the humidity of tobacco leaves during baking by a baking machine according to claim 1, characterized in that, The determination of the membership function includes: Let the universe of discourse of each linguistic variable of the fuzzy controller be| e |,| ec |, Kp, Ki, Kd be| | e | :X = {0, X1, X2, X3} | ec | : Y = {0, Y1, Y2, Y3} Kp : Zp = {0 , Zp 1 , Zp 2 , Zp 3} （3） Ki : Zi = {0 , Zi 1 , Zi 2 , Zi 3} Kd : Zd = {0 , Zd 1 , Zd 2 , Zd 3} In the above-mentioned universe of discourse of linguistic variables, the universe of discourse language values of the input linguistic variables e | and ec | take four values: B, M, S, and Z; the universe of discourse language values of the output linguistic variables Kp , Ki and Kd also take four values: B, M, S, and Z; the definitions of each language value are respectively described by the membership function curves; After establishing the rule set, compile the fuzzy control inference engine program, retrieve the facts of the current system from the database, search for matching rules in the rule base, perform fuzzy inference, and give Kp, Ki and Kd estimated values.

3. A tobacco leaf baking humidity control system for a baking machine, which is used to execute the method for controlling the humidity of tobacco leaves during baking of a baking machine according to any one of claims 1-2, characterized in that, It includes: Main air duct (1), steam pipe (2), circulation fan (3), temperature transmitter (4), humidity sensor (5), moisture exhaust fan (6), air supply damper (7), drying area (8), main controller (9), air flow meter (10), radiator (11), switch (12); The main air duct (1) is a circulating heating duct, the air supply damper (7) is installed at the front end of the main air duct (1), the radiator (11) is installed behind the air supply damper (7), the steam pipe (2) is installed on the radiator (11), the circulation fan (3) is installed on the main air duct (1) behind the radiator (11), the main air duct (1) is installed at the upper and lower ends of the drying area (8), the temperature transmitter (4) is installed on the drying area (8), a moisture exhaust channel is provided on the main air duct (1) behind the drying area (8), a moisture exhaust fan (6) is installed on the moisture exhaust channel, the air flow meter (10) is installed at the air outlet of the moisture exhaust fan (6), the humidity sensor (5) is installed in the moisture exhaust channel, and the main controller (9) is connected to the circulation fan (3), temperature transmitter (4), humidity sensor (5), moisture exhaust fan (6), air supply damper (7) and air flow meter (10) through the switch (12).

4. According to the tobacco leaf baking humidity control system of a tobacco leaf baking machine described in claim 3, it is characterized in that: The main controller (9) is connected to an operation screen (13) through the switch (12), and a communication module is connected to the main controller (9).

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