CN114838460A - Textile enterprise air conditioning system control method based on dynamic adjustment algorithm - Google Patents
Textile enterprise air conditioning system control method based on dynamic adjustment algorithm Download PDFInfo
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
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- F24F11/62—Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
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- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/70—Control systems characterised by their outputs; Constructional details thereof
- F24F11/80—Control systems characterised by their outputs; Constructional details thereof for controlling the temperature of the supplied air
- F24F11/83—Control systems characterised by their outputs; Constructional details thereof for controlling the temperature of the supplied air by controlling the supply of heat-exchange fluids to heat-exchangers
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
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Abstract
The invention discloses a textile enterprise air conditioning system control method based on a dynamic regulation algorithm, which specifically comprises the following steps: step 1, collecting temperature and humidity data of a workshop; step 2, using humidity as a primary adjustment object, using the deviation between the collected humidity data of the textile workshop and the set humidity as an input quantity, and calculating an output quantity through a dynamic adjustment formula to adjust the operation equipment group a; step 3, selecting temperature deviation amount and deviation change rate obtained by mutual coupling of temperature and humidity of a workshop as input quantities, performing decoupling compensation and establishing a fuzzy decoupling compensation control rule table to obtain output quantity of a fuzzy decoupling compensator; step 4, combining the output quantity of the fuzzy decoupling compensator with a dynamic regulation formula, and calculating the input quantity of the operating equipment group b; and 5, adjusting the operation equipment group b according to the obtained actual control input quantity. The invention is beneficial to the accurate regulation of the temperature and the humidity of the air conditioning system of the textile mill and reduces the energy consumption of the system.
Description
Technical Field
The invention belongs to the technical field of control engineering, and particularly relates to a textile enterprise air conditioning system control method based on a dynamic adjustment algorithm.
Background
The textile air conditioning system is one of the important components of the modern textile industry, and environmental factors such as temperature, humidity and the like in a textile production workshop controlled by the textile air conditioning system have decisive influence on the quality and the production efficiency of textile products. The temperature and humidity control of the existing textile air conditioning system can be divided into two categories of manual control and automatic control. The traditional manual control is performed by workers according to experience essentially, so that the problems of serious dependence on skilled workers, insufficient adjustment precision, long action time of an adjustment process, energy waste and the like exist. In order to make up for various defects in manual control, a computer controller is introduced in the industry to monitor and process environmental state parameters of the production process, so that the control effect is improved, and the labor cost is reduced. With the progress of textile materials and the advance of green development strategies in recent years, the requirements on temperature and humidity precision and energy consumption ratio in the textile industry are higher and higher, so that the complexity of the adjusting process of the air conditioning control system is higher and higher, the change of object structures and parameters is more and more complex, and a single automatic control algorithm is not suitable for the textile air conditioning control system. With the popularization of novel intelligent algorithms such as fuzzy control, neural network control and expert control algorithms, how to effectively combine advanced intelligent control algorithms with traditional application scenes better serves the practical production of the textile industry, and becomes a hotspot of algorithm research.
Disclosure of Invention
The invention provides a textile enterprise air conditioning system control method based on a dynamic regulation algorithm, which is beneficial to accurately regulating the temperature and humidity of an air conditioning system of a textile factory and reducing the energy consumption of the system.
The technical scheme adopted by the invention is that the textile enterprise air conditioning system control method based on the dynamic regulation algorithm specifically comprises the following steps:
step 1, collecting temperature and humidity data of a textile workshop;
step 2, taking the humidity of the textile workshop as a primary regulation object, taking the deviation between the humidity data of the textile workshop collected in the step 1 and the set humidity as an input quantity, and calculating an output quantity through a dynamic regulation formula to regulate the operation equipment group a;
step 3, selecting temperature deviation amount and deviation change rate obtained by mutual coupling of temperature and humidity of a workshop as input quantities, performing decoupling compensation and establishing a fuzzy decoupling compensation control rule table to obtain output quantity of a fuzzy decoupling compensator;
step 4, combining the output quantity of the fuzzy decoupling compensator obtained in the step 3 with a dynamic regulation formula, and calculating the actual control input quantity of the operating equipment group b;
and 5, adjusting the operation equipment group b according to the actual control input quantity obtained in the step 4.
The present invention is also characterized in that,
the operation equipment group a in the step 2 comprises the following steps: fresh air windows, ground return air windows and circulating water spray pumps;
the dynamic regulation formula in the step 2 is specifically shown as the formula (1) and the formula (2):
in the formula (1), the reaction mixture is,
if Y (t) is the control output of the circulating water spray pump, Y (t-1) is the control output of the spray pump at the last moment; k is a correction coefficient and has a value range of 0-1; f max The upper limit of the output of the spray pump is set; f min The lower limit of the output of the spray pump; b is max Setting an upper humidity limit for the workshop; b is min Setting a lower humidity limit for the workshop; d is actually measured humidity of the workshop;
if Y (t) is the fresh air window control quantity, Y (t-1) is the fresh air window opening at the last moment; k is a correction coefficient and has a value range of 0-1; f max The opening upper limit of the fresh air window; f min The lower limit of the opening of the fresh air window; b is max The maximum enthalpy value of the dew point of the machine; b is min The minimum enthalpy value of the dew point of the machine; d is the enthalpy value of the mixing point;
Y(t) D ＝100％-Y(t) O (2)
in the formula (2), Y (t) D : the control output quantity of the ground return air window; y (t) O : and controlling output quantity of the fresh air window.
The adjustment of the step 2 is specifically as follows:
when the humidity of the workshop is lower than a set standard, the production requirement is met by increasing the frequency of the equipment with lower power consumption in sequence for adjustment;
when the humidity of the workshop is higher than the set standard, the production requirement is met by reducing the frequency of the equipment with larger power consumption in turn for adjustment.
The sequence of step 2 is shown in formula (3) and formula (4):
increasing the humidity of the workshop:
and (3) reducing the humidity of the workshop:
in the formulae (3) and (4), F 1 (t): the input amount of the equipment group a is operated.
The input quantity of the fuzzy decoupling compensator in the step 3 is determined by the deviation quantity and the deviation change rate of the workshop temperature caused by regulating the humidity of the workshop, the relation of the deviation change rate and the deviation quantity is shown as the formula (5), and the relation of the deviation change rate and the deviation quantity is shown as the formula (6):
ΔT＝(Δt,Δtc) (5)
in formula (5), Δ T: the input quantity of the fuzzy decoupling compensator; Δ t: subtracting the required temperature from the measured temperature; Δ tc: a rate of change of deviation;
in formula (6), Δ tc: a rate of change of deviation; Δ t: subtracting the required temperature from the measured temperature; Δ (t-1): subtracting the difference value of the required temperature from the actual measured temperature at the last moment; t: system-adjusted delay time;
the method for obtaining the output quantity of the fuzzy decoupling compensator in the step 3 specifically comprises the following steps: selecting the increment delta beta of the first 7 times of adjustment of the operating equipment group a according to a fuzzy decoupling compensation control rule table and sequencing the increment delta beta from small to large, wherein the increment delta beta is delta beta 1 To Δ β 7 Then the output quantity U corresponds to the domain of discourse:
U＝{Δβ 1 、Δβ 2 、Δβ 3 、Δβ 4 、Δβ 5 、Δβ 6 、Δβ 7 }
u: the output of the fuzzy decoupling compensator.
Step 4, the operation equipment group b comprises a blower and a process air window, and the dynamic regulation formula of the step 4 is shown as a formula (7) and a formula (8):
in formula (7): o (t): controlling the output opening degree of the current process air window; o (t-1): opening degree of a process air window at the previous moment; k i : correcting the coefficient, wherein the value range is 0-1, and the initial value is 0.5; o is max : the upper limit of the opening degree of the process air window; o is min : the lower limit of the opening degree of the process air window; RT (reverse transcription) max : setting an upper temperature limit in a workshop; RT (reverse transcription) min : setting a lower temperature limit in a workshop; RT (reverse transcription) SP : a target workshop temperature; RT (reverse transcription) PV : actually measuring the temperature of a workshop;
in formula (8), Y (t): blower control amount, Y (t-1): controlling the output quantity at the last moment; k: the correction coefficient is a function of the number of pixels,the value range is 0-1; f max : an upper limit of the output of the blower; f min : the lower limit of the output quantity of the blower; b max : setting an upper temperature limit in a workshop; b is min : setting a lower limit of humidity in a workshop; d: actually measuring the temperature of a workshop;
the actual control input amount calculation method of the operating equipment group b in the step 4 is shown as the formula (9):
F 2 (t)＝Y air blower (t)+U (9)
In the formula (9), F 2 (t): the input amount of the operating equipment group b; y is Air blower (t): blower control amount; u: the output of the fuzzy decoupling compensator.
The beneficial effects of the invention are:
the invention is based on a dynamic regulation algorithm, introduces a fuzzy control algorithm aiming at the strong temperature and humidity coupling action in a special production environment of a textile mill, can better treat the temperature and humidity coupling problem of a system by a finally formed fuzzy dynamic decoupling algorithm, can realize the accurate temperature and humidity regulation of an air conditioning system of the textile mill along with the long-term operation of the system, reduces the design target of system energy consumption, reasonably optimizes and adjusts the control algorithm according to the structure of the air conditioning system of the existing textile enterprise, so that the control algorithm is more in line with the control requirement, and has more excellent performance.
Drawings
Fig. 1 is a structural diagram of an enterprise air conditioning system in the textile enterprise air conditioning system control method based on a dynamic regulation algorithm of the present invention;
FIG. 2 is a decoupling structure diagram of the textile enterprise air conditioning system control method based on the dynamic adjustment algorithm;
FIG. 3 is a schematic diagram of a novel algorithm control structure of the textile enterprise air conditioning system control method based on a dynamic adjustment algorithm.
Detailed Description
The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.
The structure of the air conditioning system of the textile enterprise in the control method of the air conditioning system based on the dynamic regulation algorithm of the textile enterprise is shown in figure 1, and the air conditioning system mainly comprises a fresh air window, a blower, a return air window, a return air fan, a process air window, a process fan, a spray room, an indoor spray water pump and other equipment. In the textile air-conditioning control system, the temperature and the humidity of a production workshop are adjusted by controlling the operating frequency of a blower, a ground return air fan, a process fan and a circulating water spray pump and the opening of a fresh air window, a ground return air window and a process air window.
As shown in fig. 2 and 3, the textile enterprise air conditioning system control method based on the dynamic adjustment algorithm specifically includes the following steps:
step 1, collecting temperature and humidity data of a textile workshop by a sensor and uploading the data to a controller;
the operating equipment in fig. 1 is controlled to output by a dynamic regulation algorithm, wherein the specific algorithm of the blower, the circulating water spray pump and the fresh air window is shown as formula (1):
the corresponding meanings of the parameters in formula (1) are shown in table 1:
TABLE 1 dynamic adjustment algorithm parameter meaning correspondence table
The dew point of the machine refers to an air monitoring point before passing through the air feeder after being sprayed by the circulating water spray pump. The enthalpy value of the point is obtained according to the maximum temperature and humidity and the minimum temperature and humidity set by a production workshop, and then the upper limit and the lower limit of the enthalpy value are obtained according to the relative humidity RH which is 90 percent. And the upper and lower limit parameters of the temperature and the humidity of the workshop are set according to the actual production requirements.
K in the formula (1) represents a correction coefficient, and the value range is 0-1. By changing the value of K, the system can be adjusted to control and output the frequency of the fan and the spray water pump and the increment of the opening degree of the air window every time, and the default value is 0.5.
The effect of the correction factor is: when the initial adjustment is carried out, if the difference between the required temperature and humidity value and the actual temperature and humidity value of the production workshop is too large, the overshoot exists in the system adjustment process, namely, the overshoot phenomenon occurs in the system adjustment process, the actual temperature and humidity of the initial adjustment can be enabled to float up and down outside the range value of the required temperature and humidity, and therefore the time for the system to reach the stable state can be prolonged. By setting the size of K, the overshoot phenomenon can be prevented, the adjusting efficiency is improved, and unnecessary energy waste is reduced.
The process fan is a main heat dissipation device for discharging the heat generated by workshop production equipment. In order to ensure that the textile production plant is operating properly, the heat generated must be removed in time, so that the process fan is generally operated at a fixed maximum power. The secondary return air regulation in the air conditioning system is carried out by utilizing heat discharged by a process fan through a process air window. When outdoor temperature is higher in summer, the process air window is in a closed state, and the process fan discharges heat of the production workshop machine to the outside. In winter, the outdoor temperature is lower, the opening degree of the process air window is controlled through a dynamic process air window adjusting algorithm, and at the moment, the process fan discharges part of heat emitted by a workshop machine to an air conditioning room for secondary return air adjustment, so that unnecessary waste of energy can be greatly reduced.
The process window adjusting algorithm is shown as formula (2):
in formula (2): o (t) is the opening degree of the control output of the current process window; o (t-1) is the opening degree of the process window at the previous moment; k i The value range is 0-1 for the correction coefficient, and the initial value is 0.5; o is max Is the upper limit of the opening of the process air window; o is min The lower limit of the opening degree of the process air window; RT (reverse transcription) max Setting an upper temperature limit for the workshop; RT (reverse transcription) min Setting a lower temperature limit for the workshop; RT (reverse transcription) SP Is the target temperature of the workshop; RT (reverse transcription) PV And measuring the temperature for the workshop.
In the air conditioning system of the textile mill, the air temperature and humidity are regulated, and meanwhile, the air pressure in the workshop is required to be ensured to be in a micro-positive pressure state, so that when textile products are produced, the produced flying cotton is uniformly scattered to the boundary of the production workshop under the micro-positive pressure of the air in the workshop, and the cleanliness of the air is ensured. The relation between a blower and a ground return fan and a process fan in an air conditioning system of a textile mill is shown in formula (3):
P D +P G ≤P S (3)
p in formula (3) D The maximum power of the ground return fan; p is G The maximum power of the process fan; p S The maximum power of the blower. And knowing the control frequency when the equipment runs according to the running power of the equipment. Because the process fan runs at the maximum power and the running frequency of the air feeder is obtained according to the dynamic regulation algorithm of the air feeder, the running frequency of the ground return fan can be obtained only by knowing the difference delta F between the frequency of the air feeder and the frequency of the ground return fan to ensure that the air in a workshop is in a micro-positive pressure state. Through the size of adjusting difference value delta F, the atmospheric pressure size of steerable workshop air because the power parameter of each fan equipment is different among the air conditioning control system of different textile mills, therefore delta F's value can carry out special setting to different operational environment in this design, can satisfy the demand that will reach the pressure-fired in the workshop air pressure among the air conditioning system of different textile mills from this.
In the control of the air conditioning system of the textile mill, the ground return air window and the fresh air window have a linkage relation. The linkage relation between the ground return air window and the fresh air window is shown as the formula (4):
Y(t) D ＝100％-Y(t) O (4)
y (t) in the formula (4) D Is the control output of the ground return air window; y (t) O Is the control output of the fresh air window. And obtaining the control quantity of the fresh air window according to the dynamic adjustment algorithm of the fresh air window, namely obtaining the control output quantity of the ground return air window.
Step 2, the controller adjusts the humidity of the textile workshop as a primary object according to a humidity priority principle; the controller calculates an output quantity through a dynamic regulation formula to regulate the running frequency of the running equipment group a according to the deviation between the humidity data of the textile workshop acquired by the sensor in the step 1 and the set humidity as an input quantity; the operation equipment group a in the step 2 comprises the following steps: fresh air windows, ground return air windows and circulating water spray pumps;
in the temperature and humidity regulation process, as the humidity priority principle is followed, namely the humidity regulation is taken as the main target, the temperature regulation is carried out after the humidity regulation reaches the set range.
When the operation equipment is mediated, in order to furthest waste construction energy, the design follows the principle of increasing and reducing. Namely, during temperature and humidity adjustment, according to the operation energy consumption of the temperature and humidity adjustment equipment, the small energy consumption equipment is started firstly when the humidity is increased, the large energy consumption equipment is shut down correspondingly and preferentially when the humidity is reduced, and in the operation equipment of the air conditioning system of the known weaving plant, the fan energy consumption, the water pump energy consumption and the air window energy consumption are sequenced according to the energy consumption
When the humidity of the workshop is lower than a set standard, the production requirement is met by increasing the frequency of the equipment with lower power consumption in sequence for adjustment;
when the humidity of the workshop is higher than the set standard, the production requirement is met by reducing the frequency of the equipment with larger power consumption in turn for adjustment.
According to the principle of increasing and decreasing, the operation equipment is adjusted in sequence, namely F 1 The control value of (t) is determined by equations (5) and (6).
Increasing the humidity of the workshop:
and (3) reducing the humidity of the workshop:
in formulae (5) and (6), F 1 (t): the input amount of the equipment group a is operated.
Expressions (5) and (6) show that the control quantity F is being controlled according to the principle of increasing and decreasing 1 (t) when the algorithm is outputted, the equipment with low energy consumption is preferentially controlledAnd outputting, namely controlling and outputting and adjusting the equipment with higher energy consumption when the equipment with low energy consumption is adjusted to the maximum control quantity.
However, since the change of humidity has an influence on the temperature, i.e. the single set b of control operation devices cannot achieve a good temperature adjustment effect, the temperature change caused by the humidity change needs to be considered when adjusting the temperature. For the coupling effect, a common solution is to convert a multi-input multi-output system into a single-input single-output system as much as possible for adjustment, i.e., generalized decoupling. The scheme aims at the characteristics of time-varying nonlinearity, large hysteresis and multivariable of the system, and the decoupling compensation is carried out on the coupling effect of the system by adopting a control theory. Fuzzy control can quantize the control experience of human experts on a specific control object by using a fuzzy set theory, and convert the control experience into a controller which can be realized mathematically for control, so that a fuzzy decoupling compensator designed for the system compensates for the loss of control quantity generated by humidity change.
Step 3, selecting temperature deviation amount and deviation change rate obtained by mutual coupling of temperature and humidity of a workshop as input amounts, performing decoupling compensation by adopting a fuzzy decoupling compensator and establishing a fuzzy decoupling compensation control rule to obtain output amount of the fuzzy decoupling compensator;
the fuzzy decoupling compensator selects a temperature deviation amount delta t and a deviation change rate delta tc which are obtained by mutually coupling temperature and humidity as input quantities, and an output quantity U is an increment delta beta of each operation device corresponding to the current temperature deviation amount in current adjustment. According to the principle of humidity priority, in the current adjustment process, the temperature deviation amount delta t and deviation change rate delta tc of temperature change caused by temperature and humidity coupling during humidity adjustment and the increment delta beta of current adjustment of each running device can be obtained. The relationship between the deviation change rate and the deviation amount is:
in formula (7), Δ tc: a rate of change of deviation; delta t is the measured temperature minus the required temperature; delta (t-1) is the difference value of the actual measured temperature minus the required temperature at the last moment; and T is the delay time of system regulation.
The fuzzy decoupling compensator is characterized in that the quantization domains of the temperature deviation amount delta t, the deviation change rate delta tc and the output amount U of the previous 7 times of adjustment are uniformly set to be [ -3,3] by taking the current time of adjustment as a reference. The fuzzy variables are described by using 7 language variables of 'positive big', 'positive middle', 'positive small', 'zero', 'negative small', 'negative middle' and 'negative big', namely { PB, PM, PS, ZO, NS, NM and NB }. The fuzzy decoupling compensation control rule for establishing the air conditioning control system of the textile mill is shown in the table 2:
TABLE 2 fuzzy decoupling rule control table
The increment delta beta of the current adjustment of each operation device of the first 7 times is sorted from small to large into delta beta 1 To delta beta 7 Then, the output quantity U corresponds to the discourse domain:
U＝{Δβ 1 、Δβ 2 、Δβ 3 、Δβ 4 、Δβ 5 、Δβ 6 、Δβ 7 }
u: the output of the fuzzy decoupling compensator.
The decoupling compensation control rule of the fuzzy compensator is based on the current time every time, so that the data of the fuzzy decoupling rule control table is updated after each adjustment, and the output quantity U of the fuzzy decoupling compensator is continuously close to the optimal control output quantity every time of adjustment.
Step 4, combining the output quantity of the fuzzy decoupling compensator obtained in the step 3 with a dynamic regulation formula, and calculating the actual control input quantity of the operating equipment group b;
the system decoupling structure is shown in fig. 2, and the coupled part in the air conditioning control system of the textile mill mainly causes the deviation of the temperature of the workshop when the humidity of the workshop is adjusted through operating equipment, and causes the deviation of the humidity of the workshop when the temperature of the workshop is adjusted. The design is that a fuzzy decoupling compensator is added after a dynamic regulation algorithm, and in the regulation process, according to the principle that humidity is prior, the humidity value is taken as a main index, namely the temperature deviation caused by prior humidity regulation is used for reverse compensation regulation of the temperature.
Wherein the input quantity X 1 And X 2 The corresponding input quantity when the corresponding dynamic adjustment algorithm is operated; the equipment corresponding to the operating equipment a is a fresh air window, a ground return air window and a circulating water spray pump, and is the main adjusting equipment for the humidity of the production workshop.
The equipment corresponding to the operating equipment group b is a blower and the process air window adjustment when secondary air return adjustment is needed in winter, and is the main adjusting equipment for the temperature of the production workshop. After the dynamic regulation algorithm is used for calculating and outputting the air feeder and the process air window, the output quantity U of the fuzzy decoupling compensator is added on the basis. The value of the output quantity U is then derived from the input Δ T of the fuzzy decoupling compensator.
The input Δ T of the fuzzy decoupling compensator in fig. 2 is determined by the deviation Δ T and the deviation rate of change Δ tc of the plant temperature caused when the plant humidity is adjusted, i.e.:
ΔT＝(Δt,Δtc) (8)
in formula (8), Δ T: the input quantity of the fuzzy decoupling compensator; Δ t: subtracting the required temperature from the measured temperature; Δ tc: rate of change of deviation.
And 5, adjusting the opening degree of the operating equipment group b according to the actual control input quantity obtained in the step 4. The output of the fuzzy decoupling compensator is U, the running equipment group b is the main control of the workshop temperature, and the input quantity F of the fuzzy decoupling compensator 2 (t) is:
F 2 (t)＝Y air blower (t)+U (9)
In the formula (9), F 2 (t): the input quantity of the running equipment group b; y is Air blower (t): blower control amount; u: the output of the fuzzy decoupling compensator.
The schematic diagram of the algorithm control structure is shown in fig. 3, and the invention specifically controls the environment temperature and the environment humidity for a special system of a textile air-conditioning control system. After the system starts to operate, each device operates according to an initial set value, and temperature and humidity data collected by the sensor are uploaded to the controller to be subjected to temperature and humidity regulation after the device operates for a period of time. The system firstly adjusts the operation equipment group a according to the deviation of the environmental humidity and the set humidity, so that the environmental humidity parameter meets the set target. The temperature loss caused by the absorption of indoor sensible heat by air due to the increase of humidity is creatively compensated by adopting a fuzzy decoupling compensator, the output value of the fuzzy decoupling compensator is obtained by utilizing the temperature deviation amount and the deviation change rate of the current production workshop through the established fuzzy decoupling compensation control rule table of the air conditioning system, and finally the calculated compensation amount is combined with the dynamic air window regulation formula to calculate the actual control input amount of each controlled device.
Claims (8)
1. The textile enterprise air conditioning system control method based on the dynamic regulation algorithm is characterized by comprising the following steps:
step 1, collecting temperature and humidity data of a textile workshop;
step 2, taking the humidity of the textile workshop as a primary regulation object, taking the deviation between the humidity data of the textile workshop collected in the step 1 and the set humidity as an input quantity, and calculating an output quantity through a dynamic regulation formula to regulate the operation equipment group a;
step 3, selecting temperature deviation amount and deviation change rate obtained by mutual coupling of temperature and humidity of a workshop as input quantities, performing decoupling compensation and establishing a fuzzy decoupling compensation control rule table to obtain output quantity of a fuzzy decoupling compensator;
step 4, combining the output quantity of the fuzzy decoupling compensator obtained in the step 3 with a dynamic regulation formula, and calculating the actual control input quantity of the operating equipment group b;
and 5, adjusting the operation equipment group b according to the actual control input quantity obtained in the step 4.
2. The textile enterprise air conditioning system control method based on the dynamic adjustment algorithm according to claim 1, wherein the operating equipment group a in step 2 comprises: fresh air windows, ground return air windows and circulating water spray pumps;
in the step 2, the dynamic regulation formula is specifically shown as formula (1) and formula (2):
in the formula (1), the reaction mixture is,
if Y (t) is the control output of the circulating water spray pump, Y (t-1) is the control output of the spray pump at the last moment; k is a correction coefficient and has a value range of 0-1; f max The upper limit of the output of the spray pump is set; f min The lower limit of the output of the spray pump; b is max Setting an upper humidity limit for the workshop; b is min Setting a lower humidity limit for the workshop; d is actually measured humidity of the workshop;
if Y (t) is the fresh air window control quantity, Y (t-1) is the fresh air window opening at the last moment; k is a correction coefficient and has a value range of 0-1; f max The opening upper limit of the fresh air window; f min The lower limit of the opening of the fresh air window; b is max The maximum enthalpy value of the dew point of the machine; b is min The minimum enthalpy value of the dew point of the machine; d is the enthalpy value of the mixing point;
Y(t) D ＝100％-Y(t) O (2)
in the formula (2), Y (t) D : the control output quantity of the ground return air window; y (t) O : and controlling output quantity of the fresh air window.
3. The textile enterprise air conditioning system control method based on the dynamic adjustment algorithm according to claim 1, wherein the adjustment in the step 2 is specifically:
when the humidity of the workshop is lower than a set standard, the production requirement is met by increasing the frequency of the equipment with lower power consumption in sequence for adjustment;
when the humidity of the workshop is higher than the set standard, the production requirement is met by reducing the frequency of the equipment with larger power consumption in turn for adjustment.
4. The textile enterprise air conditioning system control method based on the dynamic adjustment algorithm as claimed in claim 1, wherein the adjustment sequence of step 2 is as shown in formula (3) and formula (4):
increasing the humidity of the workshop:
and (3) reducing the humidity of the workshop:
in formulae (3) and (4), F 1 (t): the input amount of the equipment group a is operated.
5. The textile enterprise air conditioning system control method based on the dynamic adjustment algorithm according to claim 1, wherein the input amount of the fuzzy decoupling compensator in step 3 is determined by a deviation amount and a deviation change rate which cause a workshop temperature when the workshop humidity is adjusted, and the relation of the deviation change rate and the deviation amount is shown as formula (5), and the relation of the deviation change rate and the deviation amount is shown as formula (6):
ΔT＝(Δt，Δtc) (5)
in formula (5), Δ T: the input quantity of the fuzzy decoupling compensator; Δ t: subtracting the required temperature from the measured temperature; Δ tc: a rate of change of deviation;
in formula (6), Δ tc: a rate of change of deviation; Δ t: subtracting the required temperature from the measured temperature; Δ (t-1): subtracting the difference value of the required temperature from the actual measured temperature at the last moment; t: system adjusted delay time.
6. Textile enterprise air conditioning system control method based on dynamic adjustment algorithm according to claim 1The method is characterized in that the method for obtaining the output quantity of the fuzzy decoupling compensator in the step 3 specifically comprises the following steps: selecting the increment delta beta of the first 7 times of adjustment of the operating equipment group a according to a fuzzy decoupling compensation control rule table and sequencing the increment delta beta from small to large, wherein the increment delta beta is delta beta 1 To delta beta 7 Then the output quantity U corresponds to the domain of discourse:
U＝{Δβ 1 、Δβ 2 、Δβ 3 、Δβ 4 、Δβ 5 、Δβ 6 、Δβ 7 }
u: the output of the fuzzy decoupling compensator.
7. The textile enterprise air conditioning system control method based on the dynamic adjustment algorithm according to claim 1, wherein the operation equipment group b in the step 4 comprises a blower and a process air window, and the dynamic adjustment formula in the step 4 is represented by the following formulas (7) and (8):
in formula (7), O (t): controlling the opening degree of the output by the current process air window; o (t-1): opening degree of a process air window at the previous moment; k i : the value range of the correction coefficient is 0-1, and the initial value is 0.5; o is max : the upper limit of the opening degree of the process air window; o is min : the lower limit of the opening degree of the process air window; RT (reverse transcription) max : setting an upper temperature limit in a workshop; RT (reverse transcription) min : setting a lower temperature limit in a workshop; RT (reverse transcription) SP : a target workshop temperature; RT (reverse transcription) PV : actually measuring the temperature of a workshop;
in formula (8), Y (t): blower control amount, Y (t-1): controlling the output quantity at the last moment; k: the value range of the correction coefficient is 0-1; f max : an upper limit of the output of the blower; f min : the lower limit of the output quantity of the blower; b is max : setting an upper temperature limit in a workshop;B min : setting a lower limit of humidity in a workshop; d: and actually measuring the temperature in the workshop.
8. The textile enterprise air conditioning system control method based on the dynamic adjustment algorithm according to claim 1, wherein the actual control input amount calculation method for the operating equipment group b in the step 4 is represented by formula (9):
F 2 (t)＝Y air blower (t)+U (9)
In the formula (9), F 2 (t): the input quantity of the running equipment group b; y is Air blower (t): blower control amount; u: the output of the fuzzy decoupling compensator.
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