CN108517711B - System and method for controlling drying cylinder inlet-outlet differential pressure based on fuzzy immune PID algorithm - Google Patents

System and method for controlling drying cylinder inlet-outlet differential pressure based on fuzzy immune PID algorithm Download PDF

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CN108517711B
CN108517711B CN201810291369.0A CN201810291369A CN108517711B CN 108517711 B CN108517711 B CN 108517711B CN 201810291369 A CN201810291369 A CN 201810291369A CN 108517711 B CN108517711 B CN 108517711B
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inlet
outlet
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CN108517711A (en
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汤伟
王帅
孙小乐
佟永亮
张越
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Shaanxi University of Science and Technology
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    • D—TEXTILES; PAPER
    • D21—PAPER-MAKING; PRODUCTION OF CELLULOSE
    • D21G—CALENDERS; ACCESSORIES FOR PAPER-MAKING MACHINES
    • D21G9/00—Other accessories for paper-making machines
    • D21G9/0009—Paper-making control systems
    • D21G9/0036—Paper-making control systems controlling the press or drying section
    • D—TEXTILES; PAPER
    • D21—PAPER-MAKING; PRODUCTION OF CELLULOSE
    • D21F—PAPER-MAKING MACHINES; METHODS OF PRODUCING PAPER THEREON
    • D21F5/00—Dryer section of machines for making continuous webs of paper
    • D21F5/02—Drying on cylinders
    • D21F5/022—Heating the cylinders
    • D21F5/028—Heating the cylinders using steam

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Abstract

The invention discloses control systems and methods of dryer inlet and outlet differential pressure based on fuzzy immune PID algorithm, including flow regulating heat pump for controlling dryer inlet and outlet differential pressure, inlet pressure transmitter and dryer outlet pressure transmitter for monitoring dryer inlet and outlet pressure arranged at inlet and outlet of dryer, exhaust valve arranged on secondary steam discharge pipeline between flash tank and flow regulating heat pump, control loop DPIC101 based on fuzzy immune PID algorithm, fuzzy immune PID control having fuzzy idea, dividing dryer inlet and outlet differential pressure into several different sections for fuzzification, combining immune feedback self adaptability and fuzzy control strong robustness, fuzzy immune on-line regulation for comparative coefficient, fuzzy on-line regulation for differential coefficient and integral coefficient to meet requirements of dryer inlet and outlet differential pressure fluctuation for different control parameters, stabilizing dryer inlet and outlet differential pressure within process allowable range by controlling opening degree of heat pump.

Description

System and method for controlling drying cylinder inlet-outlet differential pressure based on fuzzy immune PID algorithm
Technical Field
The invention belongs to the field of pulping and papermaking, and particularly relates to drying cylinder inlet and outlet differential pressure control systems and methods based on a fuzzy immune PID algorithm.
Background
In the paper production process, after a wet paper web is squeezed and dewatered, the dryness range is between 40% and 50%, and the dryness range of finished paper is required to be between 92% and 95%, so that the wet paper web must pass through the rear part of a drying part to meet the requirement.
Disclosure of Invention
In order to solve the problems in the prior art, the invention discloses a system and a method for controlling the inlet-outlet differential pressure of a drying cylinder based on a fuzzy immune PID algorithm, so that the inlet-outlet differential pressure of the drying cylinder is stabilized within a process allowable range, the drying cylinder is ensured to be in a water accumulation-free state for a long time, the papermaking energy consumption is reduced, and the paper quality is improved.
In order to achieve the purpose, the technical scheme adopted by the invention is that the control system of the inlet-outlet differential pressure of the drying cylinder based on the fuzzy immune PID algorithm comprises a flow regulating heat pump for controlling the inlet-outlet differential pressure of the drying cylinder, an inlet pressure transmitter and a drying cylinder outlet pressure transmitter which are arranged at the inlet and the outlet of the drying cylinder and used for monitoring the inlet-outlet pressure of the drying cylinder, and an exhaust valve arranged on a secondary steam discharge pipeline between a flash tank and the flow regulating heat pump; the device also comprises a control loop DPIC101 of the pressure difference between the inlet and the outlet of the drying cylinder; the control loop DPIC101 comprises a fuzzy immune PID controller based on a fuzzy immune PID control algorithm
Figure BDA0001617614940000021
Wherein e (K) represents deviation amount, u (K) represents output of the controller, Δ u (K) represents output variation of the controller, K represents response speed of the immune feedback, η represents stabilization effect of the immune feedback, and K represents response speed of the immune feedbackI0、KD0Respectively, the initial integral value, differential value, delta K of the fuzzy controllerI、ΔKDRespectively, the output integral increment and the differential increment of the fuzzy controller.
A drying cylinder inlet and outlet differential pressure control loop DPIC101 detects a differential pressure value delta P and a process set differential pressure range delta P according to a drying cylinder inlet pressure transmitter and a drying cylinder outlet pressure transmitter0～ΔP1And controlling the flow to regulate the pressure difference between the inlet and the outlet of the drying cylinder.
The differential pressure of the inlet and the outlet of the drying cylinder is used as a controlled parameter, the differential pressure of the inlet and the outlet of the drying cylinder is respectively detected and fed back by a drying cylinder inlet pressure transmitter and a drying cylinder outlet pressure transmitter, a drying cylinder inlet and outlet differential pressure control loop DPIC101 adopts a fuzzy immune PID controller, the opening of a heat pump is adjusted according to a deviation value, and the steam quantity is adjusted to realize the control of the differential pressure of the inlet and the outlet of the drying cylinder.
Using the inlet-outlet differential pressure delta P of the drying cylinder as a controlled parameter, if delta P is<ΔP0The fuzzy immune PID controller increases the opening of the heat pump according to the deviation to stabilize the pressure difference between the inlet and the outlet of the drying cylinder at delta P0～ΔP1(ii) a If the opening degree of the heat pump reaches 100%, the delta P is still smaller than the delta P0The exhaust valve is opened to release steam so as to increase the differential pressure in step ;
if Δ P>ΔP1The fuzzy immune PID controller reduces the opening of the heat pump according to the deviation to stabilize the pressure difference between the inlet and the outlet of the drying cylinder at delta P0～ΔP1In the meantime.
The design process of the fuzzy immune PID controller comprises the following steps:
step 1, obtaining an immune feedback basic model according to a biological specificity immune mechanism, wherein the immune feedback basic model comprises a nonlinear function;
step 2, approximating a nonlinear function in the immune feedback mathematical model obtained in the step 1 by using a fuzzy controller to obtain a fuzzy immune proportion algorithm for adjusting a proportion coefficient, wherein the input of the fuzzy controller is the output and the output variable quantity of a fuzzy immune PID controller, and the output is the value of the nonlinear function;
step 3, a fuzzy controller is adopted to adjust a differential coefficient and a differential coefficient, the input of the fuzzy controller is deviation and deviation variable quantity, and the output is integral increment and differential increment;
and 4, listing the discrete form of the conventional PID algorithm, and combining the step 1, the step 2 and the step 3 to obtain an expression of the fuzzy immune PID algorithm.
The basic model for immune feedback in step 1 is u (K) ═ K (1- η f (u (K), Δ u (K)) e (K).
In the step 2, a two-dimensional fuzzy controller is adopted to approximate the nonlinear function f (u (k), delta u (k)) in the step 1, input variables of the fuzzy controller are output u and output deviation amount delta u of the PID controller, three fuzzy sets of negative, zero and positive fuzzify the input variable u, and two fuzzy sets of negative and positive fuzzify the input variable delta u; and determining the universe of discourse of the fuzzy set according to the values of the fuzzification functions f (u, delta u)) of the negative fuzzy set, the zero fuzzy set and the positive fuzzy set, and obtaining a fuzzy immune model for adjusting the proportionality coefficient in the PID controller.
In step 3, the integral coefficient and the differential coefficient are adjusted by adopting fuzzy control, the input of the fuzzy controller is deviation e and deviation variable quantity delta e, and the output variable is integral coefficient increment delta KIAnd the differential coefficient increment Δ KD(ii) a The input variables e and delta e are fuzzified by seven fuzzy sets, namely negative large, negative middle, negative small, zero, positive small, positive middle and positive large, and the discourse domain of the input variables e and delta e is determined; output variable Δ KIAnd Δ KDAre all fuzzified by seven fuzzy sets, namely negative large, negative middle, negative small, zero, positive small, positive middle and positive large, and determine an output variable delta KIAnd Δ KDThe domain of discourse of (a).
The final expression of the fuzzy immune PID control algorithm obtained in the step 4 is as follows:
Figure BDA0001617614940000031
wherein e (K) represents deviation amount, u (K) represents output of the controller, Δ u (K) represents output variation of the controller, K represents response speed of the immune feedback, η represents stabilization effect of the immune feedback, and K represents response speed of the immune feedbackI0、KD0Respectively, the initial integral value, differential value, delta K of the fuzzy controllerI、ΔKDRespectively, the output integral increment and the differential increment of the fuzzy controller.
Compared with the prior art, the invention has at least the following beneficial effects: the fuzzy immune PID control has the 'fuzzy' idea, divides the pressure difference of the inlet and the outlet of the drying cylinder into a plurality of different sections for fuzzification, combines the stronger self-adaptability of immune feedback and the strong robustness of fuzzy control, carries out fuzzy immune on-line adjustment on a proportional coefficient, carries out fuzzy on-line adjustment on a differential coefficient and an integral coefficient so as to meet the requirements of pressure difference fluctuation of the inlet and the outlet of the drying cylinder on different control parameters, and stabilizes the pressure difference of the inlet and the outlet of the drying cylinder within the process allowable range by controlling the opening degree of a heat pump.
Drawings
FIG. 1 is a process flow chart of the differential pressure control of the inlet and outlet of a drying cylinder with a measurement and control point according to the invention;
FIG. 2 is a schematic diagram of the humoral immune modulation of the present invention;
FIGS. 3a, 3b, 3c are graphs of membership functions for input variables u and Δ u and output variable f of the nonlinear function of the fuzzy immune algorithm of the present invention;
FIGS. 4a and 4b show the input variables e, Δ e and the output variable Δ K of the fuzzy controller of the present inventionI、ΔKDA membership function graph;
FIG. 5 is a diagram of the fuzzy immune PID control of the present invention.
1-a steam supplementing valve, 2-a drying cylinder, 3-a flash tank, 4-an exhaust valve, 5-a flow regulating heat pump, 6-an inlet pressure transmitter, 7-an outlet pressure transmitter, 8-a fresh steam pipeline, 9-a steam inlet pipeline, 10-a condensed water outlet pipeline, 11-a secondary steam pipeline and 12-a secondary steam discharge pipeline.
Detailed Description
The invention is further illustrated in with reference to the drawings, but is not intended to be limiting.
The invention relates to a part for controlling the pressure difference between an inlet and an outlet of a drying cylinder 2 of a paper machine and a connection relation thereof, as shown in figure 1, the part comprises the drying cylinder 2 and a flow regulating heat pump 5 for controlling the pressure difference between the inlet and the outlet of the drying cylinder 2, wherein a steam inlet pipeline 9 and a condensed water outlet pipeline 10 of the drying cylinder 2 are correspondingly provided with a drying cylinder inlet pressure transmitter 6 and a drying cylinder outlet pressure transmitter 7; the working steam inlet of the flow regulating heat pump 5 is connected with a fresh steam pipeline 8, the injection steam inlet is connected with a secondary steam pipeline 11 of the outlet of the flash tank 3, the mixed steam outlet of the flow regulating heat pump 5 is communicated with a steam inlet pipeline 9 of the drying cylinder 2, a steam exhaust valve 4 is further arranged on a secondary steam discharge pipeline 12 between the flash tank 3 and the flow regulating heat pump 5, and a condensate water outlet pipeline 10 of the drying cylinder 2 is communicated with the flash tank 3.
Fresh steam enters the drying cylinder 2 through a steam supplementing valve 1 arranged on a steam inlet pipeline 9 and a drying cylinder inlet pressure transmitter 6, and wet paper is heated by contacting with the drying cylinder 2; most of steam is changed into condensed water after entering the drying cylinder 2 through heat exchange, part of uncondensed steam and the condensed water form a steam-water mixture, the steam is discharged into the flash tank 3 under the action of the inlet-outlet differential pressure of the drying cylinder, fresh steam is used as a power source of the flow regulating heat pump 5, the fresh steam and secondary steam in the flash tank 3 are mixed to improve the quality and then enter the drying cylinder 2, the cyclic utilization of the steam is realized, and the condensed water in the flash tank 3 is sent to a boiler room through a flash tank condensed water outlet pipeline 13.
The control system of the drying cylinder inlet and outlet differential pressure based on the fuzzy immune PID algorithm comprises a flow regulating heat pump 5 for controlling the inlet and outlet differential pressure of the drying cylinder 2, an inlet pressure transmitter 6 and a drying cylinder outlet pressure transmitter 7 which are arranged at the inlet and outlet of the drying cylinder 2 and used for monitoring the inlet and outlet pressure of the drying cylinder, and an exhaust valve 4 arranged on a secondary steam discharge pipeline 12 between a flash tank 3 and the flow regulating heat pump 5; the dryer is characterized by further comprising a control loop DPIC101 of the pressure difference between the inlet and the outlet of the dryer, wherein the control loop DPIC101 comprises a fuzzy immune PID controller, and the fuzzy immune PID controller is based on a fuzzy immune PID control algorithm
Figure BDA0001617614940000051
Wherein e (K) represents deviation amount, u (K) represents output of the controller, Δ u (K) represents output variation of the controller, K represents response speed of the immune feedback, η represents stabilization effect of the immune feedback, and K represents response speed of the immune feedbackI0、KD0Respectively, the initial integral value, differential value, delta K of the fuzzy controllerI、ΔKDRespectively, the output integral increment and the differential increment of the fuzzy controller.
A drying cylinder inlet and outlet differential pressure control loop DPIC101 sets a differential pressure range delta P according to a differential pressure delta P detected by a drying cylinder inlet pressure transmitter 6 and a drying cylinder outlet pressure transmitter 7 and a process0～ΔP1And in comparison, the pressure difference of the inlet and the outlet of the drying cylinder is controlled by controlling the flow to adjust the opening of the heat pump 5.
Fuzzy immune PID control method for drying cylinder inlet and outlet differential pressure control system of paper machine, the drying cylinder inlet and outlet differential pressure should be stabilized in the range delta P allowed by the technology0～ΔP1Within the device, a pressure transmitter 6 at the inlet of the drying cylinder and a pressure transmitter 7 at the outlet of the drying cylinder are used for detecting differential pressure values delta P and delta P0～ΔP1For comparison, a drying cylinder inlet-outlet differential pressure control loop DPIC101 of the flow regulating heat pump 5 is set in a control mode, and a loop controller is a fuzzy immune PID controller.
If Δ P<ΔP0The fuzzy immune PID controller increases the opening of the heat pump 5 according to the deviation to stabilize the differential pressure between the inlet and the outlet of the drying cylinder at delta P0～ΔP1(ii) a If the opening degree of the flow-regulating heat pump reaches 100%, the delta P is still smaller than the delta P0The steam exhaust valve 4 is opened to release steam so as to increase the differential pressure in step ;
if Δ P>ΔP1The fuzzy immune PID controller reduces the opening of the flow adjusting heat pump 5 according to the deviation, so that the pressure difference of the inlet and the outlet of the drying cylinder is stabilized at delta P0～ΔP1。
The specific design steps of the fuzzy immune PID controller are as follows:
, deducing an immune feedback basic model according to the biospecific immune mechanism, and developing a humoral immune regulation diagram as shown in FIG. 2, wherein the antigen concentration is higher in the initial stage of the reaction, and the antigen presenting cells present the antigen to the T cells including helper T cellsHCellular and suppressor TSCell, activated THCells and a small amount of TSCells, THThe cell stimulates B cell to proliferate and differentiate, the step of producing antibody, which binds to antigen to form cell mass or precipitate, which is then digested by phagocytesSCytosis, of THCell and B cell production inhibition is a simplified model, where inhibition is only shown on B cells, and antibody concentration is further reduced to stabilize the organismHCells stimulated by antigen, the effect on B cells is denoted as TH(k) The following can be obtained:
TH(k)＝K1ε(k) (1)
in formula (1): k1Is THPromotion of cellsAnd (4) carrying out factor correction.
B cells are simultaneously subjected to THCells and TSStimulation of cells, denoted as s (k), gives:
S(k)＝TH(k)-TS(k) (2)
when the antibody concentration increased to constant value, TSThe cells will inhibit B cells, considering the feedback effect, will TSStimulation of cells was denoted as TS(k) The following can be obtained:
TS(k)＝K2f(S(k),ΔS(k))ε(k) (3)
in the formula (3), K2Is TSThe cell inhibitory factor, f (s (k), Δ s (k)), is a nonlinear function and indicates the magnitude of the amount of T cell inhibition. Combining expressions (1), (2) and (3), it can be seen that the total stimulation received by B cells is:
S(k)＝K(1-ηf(S(k),ΔS(k)))ε(k) (4)
wherein K is K1Denotes the response speed, η ═ K1/K2Expression 4 is the basic model of immune feedback, indicating a stabilizing effect. Comparing the control system, and equating the given deviation e (k) at the k-th sampling time to the k-th generation antigen concentration epsilon (k), and the k-th sampling time controller outputting u (k) to be equative to the total stimulation S (k) received by the k-th generation B cells, then the expression (4) can be expressed as:
u(k)＝KP1e(k) (5)
wherein, KP1K (1- η f (u (K), Δ u (K)), it follows that the substantially non-linear scaling algorithm from which the model is derived from the immune feedback mechanism, the scaling factor varying with the output, can be used to adjust the scaling factor of the PID controller.
Step two, approximating a nonlinear function f (u (k), delta u (k)) in the immune feedback mathematical model by using a two-dimensional fuzzy controller; as shown in fig. 3a, 3b and 3c, the input of the fuzzy controller is the output u (k) and the output variation Δ u (k) of the PID controller, and as shown in fig. 3a, u (k) is fuzzified by three fuzzy sets, negative N, zero Z and positive P, respectively, and the domain of discourse is [ -1,1 ]; as shown in fig. 3b, Δ u (k) is blurred by two blur sets, negative N and positive P, respectively, with a range of argument of [ -1,1], the output of the blur controller being the value of the non-linear function f (u (k), Δ u (k)), as shown in fig. 3c, f (u (k), Δ u (k)) is blurred by three blur sets, negative N, zero Z and positive P, respectively, with a range of argument of [ -1,1 ];
according to the expression that the stronger the stimulation the cells receive, the weaker the inhibition capacity; the principle that the weaker the stimulus the cells receive, the stronger the inhibitory capacity "determines the fuzzy control rule as follows:
1If u is P andΔu is P then f(u,Δu)is N
2If u is Z andΔu is P then f(u,Δu)is N
3If u is N andΔu is P then f(u,Δu)is Z
4If u is P andΔu isN then f(u,Δu)is Z
5If u is Z andΔu is N then f(u,Δu)is P
6If u is N andΔu is N then f(u,Δu)is P
the fuzzy controller selects a Mamdani reasoning method through fuzzy reasoning and selects a centroid gravity center method through fuzzy solution.
Step three, adopting a fuzzy controller to adjust an integral coefficient and a differential coefficient;
referring to fig. 4a, 4b, graphs of membership functions of input variables and output variables of a fuzzy controller, the input variables of the fuzzy controller are a deviation e and a deviation change Δ e, and the output variables are increments of integral coefficients Δ KIAnd the increment of the differential coefficient Δ KD；KI0And KD0For fuzzy controller initial parameters, KIAnd KDFor real-time adjustment of the parameters, it is thus possible to:
KI＝KI0+ΔKI(6)
KD＝KD0+ΔKD(7)
as shown in FIG. 4a, the argument of two input variables is [ -3, depending on the actual variation of the error e and the error variation Δ e]The fuzzy subset comprises seven fuzzy subsets of negative large NB, negative middle NM, negative small NS, zero Z, positive small PS, positive PM and positive large PB; according to Δ K, as shown in FIG. 4bIAnd Δ KDIs set to [ -0.06,0.06 ] respectively]Is divided intoSeven fuzzy subsets are negative large NB, negative middle NM, negative small NS, zero Z, positive small PS, positive middle PM and positive large PB, and delta K is obtained according to experienceIControl rule table and Δ KDControl rule table:
ΔKIcontrol rule table
ΔKDControl rule table
Figure BDA0001617614940000082
Figure BDA0001617614940000091
In each rule, Zadeh fuzzy logic AND operation is used, a Mamdani inference method is selected by fuzzy inference, AND a centroid gravity center method is selected by deblurring.
And step four, deducing a fuzzy immune PID algorithm expression and a control structure chart according to the discrete form of the conventional PID control algorithm.
The fuzzy immune PID control structure related to the invention is shown in FIG. 5, and the discrete expression of the conventional PID control algorithm is as follows:
Figure BDA0001617614940000092
the fuzzy immune PID algorithm expression can be obtained according to the formulas 5, 6, 7 and 8:
Figure BDA0001617614940000093
wherein, KP1＝K(1-ηf(u(k),Δu(k)))，KI＝KI0+ΔKI，KD＝KD0+ΔKD。

Claims (3)

1, dryer inlet and outlet differential pressure control methods based on fuzzy immune PID algorithm, characterized in that the method is based on a control system, the control system comprises a flow regulating heat pump (5) for controlling the inlet and outlet differential pressure of a dryer (2), an inlet pressure transmitter (6) and a dryer outlet pressure transmitter (7) which are arranged at the inlet and outlet of the dryer (2) and used for monitoring the inlet and outlet pressure of the dryer, an exhaust valve (4) arranged on a secondary steam discharge pipeline (12) between a flash tank (3) and the flow regulating heat pump (5), and a control loop DPIC101 of the inlet and outlet differential pressure of the dryer, the control loop DPIC101 comprises a fuzzy immune PID controller based on the fuzzy immune PID control algorithm, and the fuzzy immune PID controller is based on the fuzzy immune PID control algorithm
Figure FDA0002259728810000011
Wherein e (K) represents deviation amount, u (K) represents output of the controller, Δ u (K) represents output variation of the controller, K represents response speed of the immune feedback, η represents stabilization effect of the immune feedback, and K represents response speed of the immune feedbackI0、KD0Respectively, the initial integral value, differential value, delta K of the fuzzy controllerI、ΔKDRespectively output integral increment and differential increment of the fuzzy controller; a drying cylinder inlet and outlet differential pressure control loop DPIC101 sets a differential pressure range delta P according to a differential pressure delta P detected by a drying cylinder inlet pressure transmitter (6) and a drying cylinder outlet pressure transmitter (7) and a process setting differential pressure range delta P0～ΔP1In contrast, the drying cylinder inlet and outlet differential pressure control method for controlling the opening of the flow adjusting heat pump (5) takes the inlet and outlet differential pressure of the drying cylinder (2) as a controlled parameter, respectively detects and feeds back the pressure difference between the inlet and the outlet of the drying cylinder through a drying cylinder inlet pressure transmitter (6) and a drying cylinder outlet pressure transmitter (7), and a drying cylinder inlet and outlet differential pressure control loop DPIC101 adopts a fuzzy immune PID controller to adjust the opening of the heat pump (5) according to a deviation value and adjust the steam quantity to realize the control of the drying cylinder inlet and outlet differential pressure; the design process of the fuzzy immune PID controller comprises the following steps:
step 1, obtaining an immune feedback basic model according to a biological specificity immune mechanism, wherein the immune feedback basic model comprises a nonlinear function, and the immune feedback basic model in the step 1 is u (K) ═ K (1- η f (u (K), delta u (K))) e (K);
step 2, approximating a nonlinear function in the immune feedback mathematical model obtained in the step 1 by using a fuzzy controller to obtain a fuzzy immune proportion algorithm for adjusting a proportion coefficient, wherein the input of the fuzzy controller is the output and the output variable quantity of a fuzzy immune PID controller, and the output is the value of the nonlinear function;
step 3, a fuzzy controller is adopted to adjust a differential coefficient and a differential coefficient, the input of the fuzzy controller is deviation and deviation variable quantity, and the output is integral increment and differential increment;
step 4, listing discrete forms of the conventional PID algorithm, and combining the step 1, the step 2 and the step 3 to obtain an expression of the fuzzy immune PID algorithm;
in step 2, the input of the fuzzy controller is the output u (k) and the output variable quantity delta u (k) of the PID controller; u (k) is blurred by three fuzzy sets, negative N, zero Z and positive P, with a domain of discourse of [ -1,1 ]; Δ u (k) is blurred by two blur sets, negative N and positive P, respectively, with a domain of discourse of [ -1,1], the output of the fuzzy controller being the value of the nonlinear function f (u (k), Δ u (k)), f (u (k), Δ u (k)) is blurred by three blur subsets, negative N, zero Z and positive P, respectively, with a domain of discourse of [ -1,1 ];
and 3, a membership function curve chart of input variables and output variables of the fuzzy controller, wherein the input variables of the fuzzy controller are deviation e and deviation variable quantity delta e, and the output variables are increment delta K of integral coefficientsIAnd the increment of the differential coefficient Δ KD；KI0And KD0For fuzzy controller initial parameters, KIAnd KDIn order to adjust the parameters in real time,
KI＝KI0+ΔKI
KD＝KD0+ΔKD
according to the actual change situation of the error e and the error change quantity delta e, the discourse range of the two input variables is [ -3,3]The fuzzy subset comprises seven fuzzy subsets of negative large NB, negative middle NM, negative small NS, zero Z, positive small PS, positive PM and positive large PB; according to Δ K, as shown in FIG. 4bIAnd Δ KDIs set to [ -0.06,0.06 ] respectively]Seven fuzzy subsets divided are negative large NB, negative middle NM and negative small NBNS, zero Z, positive small PS, positive middle PM and positive large PB to obtain Delta KIControl rule table and Δ KDA control rule table; Δ KIControl rule table
Figure FDA0002259728810000021
ΔKDControl rule table
Figure FDA0002259728810000032
2. The control method of the dryer inlet-outlet differential pressure based on the fuzzy immune PID algorithm as claimed in claim 1, characterized in that: the inlet-outlet differential pressure delta P of the drying cylinder (2) is taken as a controlled parameter, if delta P is less than delta P0The fuzzy immune PID controller increases the opening of the heat pump (5) according to the deviation to stabilize the pressure difference between the inlet and the outlet of the drying cylinder at delta P0～ΔP1(ii) a If the opening degree of the heat pump reaches 100%, the delta P is still smaller than the delta P0Opening a steam exhaust valve (4) to release steam so as to increase the differential pressure in step ;
if Δ P>ΔP1The fuzzy immune PID controller reduces the opening of the heat pump (5) according to the deviation to stabilize the pressure difference between the inlet and the outlet of the drying cylinder at delta P0～ΔP1In the meantime.
3. The control method of the dryer inlet-outlet differential pressure based on the fuzzy immune PID algorithm as claimed in claim 1, characterized in that: the final expression of the fuzzy immune PID control algorithm obtained in the step 4 is as follows:
Figure FDA0002259728810000033
wherein e (k) represents the deviation, u (k) represents the controller output, and Δ u (k) represents the controller outputThe variation is shown, K represents the response speed of the immune feedback, η represents the stable effect of the immune feedback, and KI0、KD0Respectively, the initial integral value, differential value, delta K of the fuzzy controllerI、ΔKDRespectively, the output integral increment and the differential increment of the fuzzy controller.
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