CN117128609A - Self-adaptive nonlinear control method for temperature and humidity of air conditioner - Google Patents

Self-adaptive nonlinear control method for temperature and humidity of air conditioner Download PDF

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Publication number
CN117128609A
CN117128609A CN202311032050.3A CN202311032050A CN117128609A CN 117128609 A CN117128609 A CN 117128609A CN 202311032050 A CN202311032050 A CN 202311032050A CN 117128609 A CN117128609 A CN 117128609A
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Prior art keywords
humidity
temperature
source intensity
control method
adaptive
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Chinese (zh)
Inventor
刘存根
刘吉华
刘晓平
王焕清
孙钰龙
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Shandong Jianzhu University
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Shandong Jianzhu University
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Priority to CN202311032050.3A priority Critical patent/CN117128609A/en
Publication of CN117128609A publication Critical patent/CN117128609A/en
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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
    • F24F11/30—Control or safety arrangements for purposes related to the operation of the system, e.g. for safety or monitoring
    • 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
    • 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
    • F24F11/63—Electronic processing
    • F24F11/64—Electronic processing using pre-stored data
    • 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
    • F24F11/70—Control systems characterised by their outputs; Constructional details thereof
    • 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
    • F24F11/88—Electrical aspects, e.g. circuits
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F2110/00—Control inputs relating to air properties
    • F24F2110/10—Temperature
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F2110/00—Control inputs relating to air properties
    • F24F2110/20—Humidity
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B30/00—Energy efficient heating, ventilation or air conditioning [HVAC]
    • Y02B30/70—Efficient control or regulation technologies, e.g. for control of refrigerant flow, motor or heating

Abstract

The invention relates to a self-adaptive nonlinear control method for temperature and humidity of an air conditioner, which comprises the following steps: step 1: the method comprises the steps of establishing a nonlinear dynamic model of a temperature and humidity control system of an air handling unit by taking humidity source intensity, heat load, outdoor humidity ratio and outdoor temperature as unknowns, and then carrying out system transformation; step 2: constructing a serial-parallel estimation model to obtain a humidity source intensity estimated value and a heat load estimated value; step 3: establishing a humidity control signal to control indoor humidity to reach an expected value, and designing a first humidity source intensity self-adaptive law to process a humidity source intensity estimated value; step 4: constructing a virtual control signal and a heat load self-adaptive law to process the heat load, and designing a first poplar inequality and a second humidity source intensity self-adaptive law to process a humidity source intensity estimated value; step 5: designing a second poplar inequality to handle the unknown varying humidity ratio and the unknown varying temperature; step 6: establishing a temperature control signal to control the indoor temperature to reach a desired value; the technical scheme has high control precision.

Description

Self-adaptive nonlinear control method for temperature and humidity of air conditioner
Technical Field
The invention belongs to the technical field of air conditioner temperature and humidity control, and particularly relates to an air conditioner temperature and humidity self-adaptive nonlinear control method.
Background
A typical heating ventilation air conditioning system consists of a plurality of loops, each loop has a plurality of mutual variables, each link has high nonlinearity, and a plurality of uncertain factors such as time-varying characteristics, coupling, time lags, disturbance and the like lead the whole heating ventilation air conditioning system to form a typical complex nonlinear multivariable system.
The Chinese patent publication CN116336617A discloses a nonlinear control method of an air handling unit, which is designed directly for a nonlinear mathematical model of the air handling unit, and the influence degree of disturbance on the output of the system is attenuated to a given degree by a nearly disturbance decoupling technology.
The nonlinear mathematical model of the air handling unit proposed in the above patent publication has the following drawbacks: the humidity source intensity, the heat load, the outdoor humidity ratio and the outdoor temperature are regarded as disturbance, the disturbance is divided into a known constant and a bounded function to carry out almost disturbance decoupling treatment, and the treatment mode has limitation. Because the problem of system balance shift is unavoidable when treating the humidity source intensity, heat load, outdoor humidity ratio and outdoor temperature as unknown. Because the processing with almost disturbance decoupling requires that the fluctuation of the bounded function be kept small, it does not lead to a shift in the equilibrium point of the system: if the fluctuation of the bounded function is large, the balance point of the system is shifted, and the problem is not solved fundamentally.
Disclosure of Invention
The invention aims to solve the technical problem of overcoming the defects of the prior art and providing a self-adaptive nonlinear control method for temperature and humidity of an air conditioner.
The technical scheme of the invention is as follows:
an adaptive nonlinear control method for temperature and humidity of an air conditioner comprises the following steps:
step 1: establishing a nonlinear dynamic model of a temperature and humidity control system of the air processing unit by taking humidity source intensity, heat load, outdoor humidity ratio and outdoor temperature as unknowns, wherein the outdoor humidity ratio comprises a known humidity ratio and an unknown change humidity ratio, and the outdoor temperature comprises a known temperature and an unknown change temperature; then, carrying out system transformation on a nonlinear dynamic model of a temperature and humidity control system of the air handling unit;
step 2: constructing a serial-parallel estimation model, and estimating unknown humidity source intensity and thermal load by adopting the serial-parallel estimation model to obtain a humidity source intensity estimated value and a thermal load estimated value;
step 3: establishing a humidity control signal to control indoor humidity to reach an expected value, and designing a first humidity source intensity self-adaptive law to process the humidity source intensity estimated value in the step 2;
step 4: constructing a virtual control signal and a heat load self-adaptive law to process the heat load in the step 1, and designing a first poplar inequality and a second humidity source intensity self-adaptive law to process the humidity source intensity estimated value in the step 2;
step 5: designing a second poplar inequality to handle the unknown varying humidity ratio and the unknown varying temperature in step 1;
step 6: a temperature control signal is established to control the indoor temperature to a desired value.
Further, in step 1, the nonlinear dynamic model of the temperature and humidity control system of the air handling unit is:
（1）
wherein,is the indoor humidity ratio>Is the air supply humidity ratio->Is the indoor temperature->For the air supply temperature->For the temperature gradient of the heat exchanger,/->For unknown humidity source intensity, +.>For unknown heat load, +.>Is the volume of the indoor space>For the volume of the cooling device->Air flow rate of blower,/>In order to control the flow of cooling water to the valve,for outdoor temperature->For a known temperature +.>For unknown change temperature, +.>Is the outdoor humidity ratio->For a known humidity ratio, +.>For unknown change of humidity ratio, +.>Specific heat of air->Specific heat of water->Is saturated water enthalpy->For vaporization enthalpy->For air density->Is water density, is->The fresh air ratio in the air supply is +.>Is the air return duty ratio in the air supply, and +.>。
Further, in step 1, the system transforms into:
（2）
wherein,is humidity control signal, ">In the form of a temperature control signal,
，/>，/>，/>，/>；
parameters (parameters)，/>，/>The expression is as follows:
,/>,/>,
,/>,
,/>。
further, in step 2, the serial-parallel estimation model is:
（3）
wherein, for observing errors +.>And->Is of normal number>And->Respectively->And->Estimated value of ∈10->Is a humidity control signal.
Further, in step 3, the humidity control signal is:
（4）
wherein,is a positive design parameter, +.>，/>Is the target humidity.
Further, in step 3, the first humidity source intensity adaptive law is:
（5）
wherein,and->Is a positive constant.
Further, in step 4, the virtual control signal is，
（6）
Wherein,is a positive design parameter, +.>，/>Is the target temperature;
the thermal load adaptation law is:
（7）
wherein,and->Is a positive constant.
Further, in step 4, the first poplar inequality is:
（8）
wherein,is positive constant, +.>，/>，/>Is->Is a function of the estimated value of (2);
the second humidity source intensity adaptation law is:
（9）
wherein,and->Is a positive constant.
Further, in step 5, the second poplar inequality is:
（10）
wherein,and->Is a positive design parameter, +.>，/>，/>And->Respectively areAnd->And is a normal number.
Further, in step 6, the temperature control signal is：
（11）
Wherein,is a positive design parameter, +.>。
The invention has the following beneficial effects: the invention applies the serial-parallel estimation model to the existing model for the first time, solves the problem of system balance point deviation generated when the humidity source intensity, the heat load, the outdoor humidity ratio and the outdoor temperature are used as unknown variable quantity, and improves the control precision of the system.
Drawings
Fig. 1 is a flowchart of a control method provided in an embodiment of the present invention.
FIG. 2 is a graph showing the humidity change in an air treatment unit room when the target temperature and humidity are constant, according to an embodiment of the present invention.
FIG. 3 is a graph of air handling unit humidity control signal provided by an embodiment of the present invention when target temperature and humidity are constant.
FIG. 4 is a graph of indoor temperature of an air treatment unit when target temperature and humidity are constant, as provided by an embodiment of the present invention.
FIG. 5 is a graph of air handling unit temperature control signals provided by an embodiment of the present invention when target temperature and humidity are constant.
FIG. 6 is a graph of air handling unit supply air temperature when target temperature and humidity are constant, provided by an embodiment of the present invention.
FIG. 7 is a graph showing the humidity change in an air treatment unit room when the target temperature and humidity change, according to an embodiment of the present invention.
FIG. 8 is a graph of the humidity error in an air handling unit room as the target temperature and humidity change, provided by an embodiment of the present invention.
FIG. 9 is a graph of air handling unit humidity control signals as target temperature and humidity vary, provided by an embodiment of the present invention.
FIG. 10 is a graph of indoor temperature of an air treatment unit as target temperature and humidity change, provided by an embodiment of the present invention.
FIG. 11 is a graph illustrating temperature error in an air handling unit room when a target temperature and humidity change, according to an embodiment of the present invention.
FIG. 12 is a graph of air handling unit temperature control signals as target temperature and humidity change provided by an embodiment of the present invention.
FIG. 13 is a graph showing the adaptation of the humidity source intensity of an air treatment unit as the target temperature and humidity change, according to an embodiment of the present invention.
FIG. 14 is a graph showing the adaptation of the thermal load of an air treatment unit as target temperature and humidity change, provided by an embodiment of the present invention.
FIG. 15 is a schematic illustration of an air handling unit according to an embodiment of the present invention when the target temperature and humidity are variedIs a self-adaptive curve of (2).
Detailed Description
The invention will be described in further detail with reference to the drawings and the detailed description.
The embodiment is an improved design based on the prior art, and the prior art specifically refers to: a nonlinear control method of an air handling unit is disclosed in Chinese patent publication CN 116336617A.
The construction principle of the air handling unit in this embodiment is exactly the same as that of fig. 1 of chinese patent publication CN116336617 a.
An adaptive nonlinear control method for temperature and humidity of an air conditioner comprises the following steps:
step 1: establishing a nonlinear dynamic model of a temperature and humidity control system of the air processing unit by taking humidity source intensity, heat load, outdoor humidity ratio and outdoor temperature as unknowns, wherein the outdoor humidity ratio comprises a known humidity ratio and an unknown change humidity ratio, and the outdoor temperature comprises a known temperature and an unknown change temperature; and then carrying out system transformation on a nonlinear dynamic model of the temperature and humidity control system of the air handling unit.
The nonlinear dynamic model of the temperature and humidity control system of the air handling unit is as follows:
（1）
wherein,is the indoor humidity ratio>Is the air supply humidity ratio->Is the indoor temperature->For the air supply temperature->For the temperature gradient of the heat exchanger,/->For unknown humidity source intensity, +.>For unknown heat load, +.>Is the volume of the indoor space>For the volume of the cooling device->Air flow rate of blower,/>In order to control the flow of cooling water to the valve,for outdoor temperature->For a known temperature +.>For unknown change temperature, +.>Is the outdoor humidity ratio->For a known humidity ratio, +.>For unknown change of humidity ratio, +.>Specific heat of air->Specific heat of water->Is saturated water enthalpy->For vaporization enthalpy->For air density->Is water density, is->The fresh air ratio in the air supply is +.>Is the air return duty ratio in the air supply, and +.>In this embodiment +.>︰/>=1︰4。
The system is transformed into:
（2）
wherein,is humidity control signal, ">In the form of a temperature control signal,
，/>，/>，/>，/>；
parameters (parameters)，/>，/>The expression is as follows:
,/>,/>,
,/>,
,/>。
step 2: in order to avoid the offset of the balance point of the system, a serial-parallel estimation model is constructed, and the serial-parallel estimation model is adopted to estimate unknown humidity source intensity and thermal load, so as to obtain a humidity source intensity estimated value and a thermal load estimated value.
The serial-parallel estimation model is as follows:
（3）
wherein, for observing errors +.>And->Is of normal number>And->Respectively->And->Estimated value of ∈10->Is a humidity control signal.
Step 3: and (3) establishing a humidity control signal to control the indoor humidity to reach a desired value, and designing a first humidity source intensity adaptive law to process the humidity source intensity estimated value in the step (2).
The humidity control signal is:
（4）
wherein,is a positive design parameter, +.>，/>Is the target humidity.
Remarks: due toIs determined by the volume of the room, so +.>Is a positive constant. The precondition of the system model is that: the actual humidity of the air supply system is always greater than the actual humidity of the room, therefore +.>Is not zero, ensure->The denominator of (2) is not zero, so +.>Is reasonable.
The first humidity source intensity adaptation law is:
（5）
wherein,and->Is a positive constant.
Step 4: constructing a virtual control signal and a heat load self-adaptive law to process the heat load in the step 1, and designing a first poplar inequality and a second humidity source intensity self-adaptive law to process the humidity source intensity estimated value in the step 2.
Virtual control signalThe method comprises the following steps:
（6）
wherein,is a positive design parameter, +.>，/>Is the target temperature.
Remarks: air flow rateSince humidity exchange exists between the inside and outside of the room, the humidity in the room cannot be constant, so the air conditioner always blows humid air to the room. Thus (S)>Is a positive constant, ensuring +.>The denominator of (2) is not zero, so +.>Is reasonable.
The thermal load adaptation law is:
（7）
wherein,and->Is a positive constant.
The first poplar inequality is:
（8）
wherein,is positive constant, +.>，/>，/>Is->Is a function of the estimated value of (2);
the second humidity source intensity adaptation law is:
（9）
wherein,and->Is a positive constant.
Step 5: the second poplar inequality is designed to handle the unknown varying humidity ratio and unknown varying temperature in step 1.
The second poplar inequality is:
（10）
wherein,and->Is a positive design parameter, +.>，/>，/>And->Respectively areAnd->And is a normal number.
Step 6: a temperature control signal is established to control the indoor temperature to a desired value.
The temperature control signal is：
（11）
Wherein,is a positive design parameter, +.>。
The following is a system stability demonstration:
construction of first Lyapunov function candidateThe stability of the system is proved,
（12）
for the first Lyapunov function candidateDeriving and obtaining
（13）
Substituting formula (4) into formula (13)
（14）
Substitution of formula (5) into formula (14) yields
（15）
Construction of a second Liapunov function candidateThe method comprises the following steps:
（16）
wherein,for->Can obtain the derivation
（17）
Substituting formula (6) into formula (17)
（18）
Substituting the formulas (7) and (8) into the formula (18) to obtain
（19）
Substituting formula (9) into formula (19)
（20）
Construction of a third Lyapunov function candidateThe method comprises the following steps:
for a pair ofCan obtain the derivation
（21）
Substituting formula (10) into formula (21) to obtain
（22）
Substituting formula (11) into formula (22) to obtain
（23）
The third poplar inequality is:
（24）
substituting formula (24) into formula (23) to obtain
（25）
Wherein,，
lemma 1: for the air conditioning system (1), under the controllers (4), (6), (11), the serial-parallel estimation model (3) and the adaptive laws (5), (7), (9), the control errors of temperature and humidity are bounded, and the unknown parameters can converge to actual values.
By the formula (25), the control method provided by the invention can ensure the stability of a closed loop system by combining the Lyapunov stability theory and the primer 1.
The following were simulated:
in order to verify the effectiveness of the control method provided by the invention, the control method provided by the invention is compared with feedback linearization and PID through Matlab simulation. The following two cases are discussed:
the scheme one is as follows: this embodiment
The scheme II is as follows: feedback linearization technique
The scheme III is as follows: PID technology
(1) Constant target temperature and humidity
The initial conditions were selected as follows:，and->. The design parameters of the control signal are as follows: />，/>And. The target humidity and temperature were set as: />And。
simulation pairs such as shown in fig. 2-6.
The humidity and ideal humidity curves of the output are shown in fig. 2, and it can be seen from the graph that there is a significant overshoot in all three schemes, but in contrast to the controller proposed by scheme one (this embodiment) which has the highest convergence rate.
Humidity control signalAs shown in fig. 3, the humidity control performance of the first scheme (this example) is better than that of the second scheme (feedback linearization technique) and the third scheme (PID technique) as compared to the humidity control performance of the first scheme (this example).
Fig. 4 shows the indoor temperature profile, wherein the convergence rate is the fastest as soon as the recipe (this embodiment) reaches a steady state value of 100 s.
FIG. 5 is a graph of temperature control signals, wherein scheme one (this embodiment) and scheme three (PID technique) controlRelatively stable, while scheme two (feedback linearization technique) controlled +.>Eventually converging into a small area.
The supply air temperature is shown in FIG. 6, from which it can be seen that the temperature first risesThen descend again and finally stabilize at。
(2) Target temperature and humidity change
The initial conditions were selected as follows:(abbreviated as->），And->. The input parameters of the controllers (7), (12) and (23) are: />，And->. Humidity source intensity, heat load and +.>The initial value of (2) is set as follows: />，/>And->。
The simulation results are shown in fig. 7-15.
Tracking performance on humidity as shown in fig. 7, the tracking performance of the first embodiment (this embodiment) is the best regardless of whether the desired humidity is constant or variable.
Fig. 8 shows humidity error curves for three schemes, the root mean square of the three humidity error curves being respectively,，/>and->。
FIG. 9 is a humidity control signal, as can be seenThe saturation value of the humidity control signal isThe humidity control signals of the three schemes are all bounded and larger than zero, which accords with the practice; the root mean square of the humidity control signals of the three schemes are respectively,/>And->。
Fig. 10 plots the actual and desired temperature curves, and it is easy to see that the temperature error of scheme one (this embodiment) is minimal.
The temperature errors are shown in FIG. 11, and the root mean square of the temperature errors in the three schemes are respectively，And->。
FIG. 12 shows a temperature control signalIts saturation value is set to->Within a reasonable range, the root mean square of the temperature control signals of the three schemes is +.>，/>And。
FIG. 13 depicts humidity source intensityIs respectively the average steady state value of the two adaptive curvesAnd->Can converge to around the desired value.
FIG. 14 is a heat loadIs a steady state average value of +.>But may also converge to a desired value.
FIG. 15 is a diagram ofIs the steady state average value of +.>。
From fig. 8-9, fig. 11-13 and the calculated root mean square, it can be seen that the performance of scheme one (this embodiment) is better than that of scheme two (feedback linearization technique) and scheme three (PID technique).
From the view of fig. 13, fig. 14 and the calculated steady state values, after the serial-parallel estimation model is adopted in the first scheme (this embodiment), not only can the unknown humidity source intensity and the thermal load be ensured to converge to the actual values, but also the problem of the offset of the balance point of the system is solved.

Claims (10)

1. An adaptive nonlinear control method for temperature and humidity of an air conditioner is characterized by comprising the following steps: the method comprises the following steps:
step 1: establishing a nonlinear dynamic model of a temperature and humidity control system of the air processing unit by taking humidity source intensity, heat load, outdoor humidity ratio and outdoor temperature as unknowns, wherein the outdoor humidity ratio comprises a known humidity ratio and an unknown change humidity ratio, and the outdoor temperature comprises a known temperature and an unknown change temperature; then, carrying out system transformation on a nonlinear dynamic model of a temperature and humidity control system of the air handling unit;
step 2: constructing a serial-parallel estimation model, and estimating unknown humidity source intensity and thermal load by adopting the serial-parallel estimation model to obtain a humidity source intensity estimated value and a thermal load estimated value;
step 3: establishing a humidity control signal to control indoor humidity to reach an expected value, and designing a first humidity source intensity self-adaptive law to process the humidity source intensity estimated value in the step 2;
step 4: constructing a virtual control signal and a heat load self-adaptive law to process the heat load in the step 1, and designing a first poplar inequality and a second humidity source intensity self-adaptive law to process the humidity source intensity estimated value in the step 2;
step 5: designing a second poplar inequality to handle the unknown varying humidity ratio and the unknown varying temperature in step 1;
step 6: a temperature control signal is established to control the indoor temperature to a desired value.
2. The adaptive nonlinear control method of the temperature and humidity of the air conditioner according to claim 1, which is characterized in that: in step 1, a nonlinear dynamic model of a temperature and humidity control system of an air handling unit is as follows:
（1）
wherein,is the indoor humidity ratio>Is the air supply humidity ratio->Is the indoor temperatureDegree (f)>For the air supply temperature->For the temperature gradient of the heat exchanger,/->For unknown humidity source intensity, +.>For unknown heat load, +.>Is the volume of the indoor space>For the volume of the cooling device->Air flow rate of blower,/>In order to control the flow of cooling water to the valve,for outdoor temperature->For a known temperature +.>For unknown change temperature, +.>Is the outdoor humidity ratio->For a known humidity ratio, +.>For unknown change of humidity ratio, +.>Specific heat of air->Specific heat of water->Is saturated water enthalpy->For vaporization enthalpy->For air density->Is water density, is->The fresh air ratio in the air supply is +.>Is the air return duty ratio in the air supply, and +.>。
3. The adaptive nonlinear control method of the temperature and humidity of the air conditioner according to claim 2, which is characterized in that: in step 1, the system transforms into:
（2）
wherein,is humidity control signal, ">In the form of a temperature control signal,
，/>，/>，/>，/>；
parameters (parameters)，/>，/>The expression is as follows:
,/>,/>,
,/>,
,/>。
4. the adaptive nonlinear control method for temperature and humidity of the air conditioner according to claim 3, wherein the method comprises the following steps: in step 2, the serial-parallel estimation model is:
（3）
wherein, for observing errors +.>And->Is of normal number>And->Respectively->And->Estimated value of ∈10->Is a humidity control signal.
5. The adaptive nonlinear control method for temperature and humidity of the air conditioner according to claim 4, wherein the adaptive nonlinear control method is characterized in that: in step 3, the humidity control signal is:
（4）
wherein,is a positive design parameter, +.>，/>Is the target humidity.
6. The adaptive nonlinear control method for temperature and humidity of the air conditioner according to claim 5, wherein the adaptive nonlinear control method is characterized in that: in step 3, the first humidity source intensity adaptive law is:
（5）
wherein,and->Is a positive constant.
7. The adaptive nonlinear control method of the temperature and humidity of the air conditioner according to claim 6, wherein the adaptive nonlinear control method is characterized in that: in step 4, the virtual control signal is，
（6）
Wherein,is a positive design parameter, +.>，/>Is the target temperature;
the thermal load adaptation law is:
（7）
wherein,and->Is a positive constant.
8. The adaptive nonlinear control method of the temperature and humidity of the air conditioner according to claim 7, wherein the adaptive nonlinear control method is characterized in that: in step 4, the first poplar inequality is:
（8）
wherein,is positive constant, +.>，/>，/>Is->Is a function of the estimated value of (2);
the second humidity source intensity adaptation law is:
（9）
wherein,and->Is a positive constant.
9. The adaptive nonlinear control method of the temperature and humidity of the air conditioner according to claim 8, wherein the adaptive nonlinear control method is characterized in that: in step 5, the second poplar inequality is:
（10）
wherein,and->Is a positive design parameter, +.>，/>，/>And->Are respectively->Andand is a normal number.
10. The adaptive nonlinear control method of the temperature and humidity of the air conditioner according to claim 9, wherein the adaptive nonlinear control method is characterized in that: in step 6, the temperature control signal is：
（11）
Wherein,is a positive design parameter, +.>。
CN202311032050.3A 2023-08-16 2023-08-16 Self-adaptive nonlinear control method for temperature and humidity of air conditioner Pending CN117128609A (en)

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Application Number Priority Date Filing Date Title
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