CN107883529A - A kind of central air conditioner system temprature control method based on fuzzy technology - Google Patents
A kind of central air conditioner system temprature control method based on fuzzy technology Download PDFInfo
- Publication number
- CN107883529A CN107883529A CN201711051782.1A CN201711051782A CN107883529A CN 107883529 A CN107883529 A CN 107883529A CN 201711051782 A CN201711051782 A CN 201711051782A CN 107883529 A CN107883529 A CN 107883529A
- Authority
- CN
- China
- Prior art keywords
- fuzzy
- indoor temperature
- formula
- mrow
- central air
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Landscapes
- Air Conditioning Control Device (AREA)
Abstract
The invention discloses a kind of central air conditioner system temprature control method based on fuzzy technology, Indoor Temperature angle value e is obtained by temperature sensor, try to achieve Indoor Temperature angle value error e (k) and error rate ec (k), the Indoor Temperature angle value error e (k) and error rate ec (k) are subjected to Fuzzy processing and obtain fuzzy quantity, fuzzy reasoning and decision-making are carried out by fuzzy control rule again, fuzzy output amount Y corresponding to obtaining, the fuzzy output amount Y defuzzifications are obtained to control output quantity, central air-conditioning blowing mouth valve positioner is according to the control output quantity, blowing open area is controlled, so as to reach the effect of control indoor temperature.
Description
Technical field
The present invention relates to central air conditioning system field, in particular to a kind of central hollow based on fuzzy technology
Adjusting system temprature control method.
Background technology
With the rise and the improvement of people's living standards of intelligent building, largely employ under construction air-conditioning system and
Relevant device, scale is increasingly huge, and air-conditioning system turns into a very important composition portion of building automatic in intelligent building
Point.In recent years, air-conditioning technique is widely applied in the various aspects of national economy every field and people's lives, right
The improvement of the energy-conservation of air-conditioning has great importance for mitigating network load.Therefore the control of central air-conditioning is directed to, it is comprehensive
The intelligent temperature regulation of air-conditioning is considered, to reach energy-saving and environmental protection, economically and reasonably require.
For the control method of central air-conditioning frequently with traditional PID control method, this algorithm is relatively simple, but by
It is nonlinear complication system in central air conditioner system, has when with the PID controller for having mixed up parameter applied to another
When having the system of different model parameters, the performance of system will be deteriorated, or even unstable.And fuzzy control and traditional PID control
Compare, its incomplete or mathematical models independent of controlled device, while have from optimizing feature, and entirely controlling
During system, computer obtains information and handles in real time and provide control decision online, passes through continuous Optimal Parameters and searching
The optimum structure form of controller, to obtain total optimization control performance.
The content of the invention
It is an object of the invention to provide a kind of central air conditioner system temprature control method based on fuzzy technology, to solve
The problem of being proposed in above-mentioned background technology.
The present invention is achieved by the following technical solutions：
A kind of central air conditioner system temprature control method based on fuzzy technology, comprises the following steps,
Step a：Gather indoor temperature e；
Step b：Central processing unit, according to default indoor temperature r, obtains interior on the basis of indoor temperature e is obtained
Temperature error e (k) and indoor temperature error rate ec (k)；
Step c：Indoor temperature error e (k) and indoor temperature error rate ec (k) are mapped to input by central processing unit
Domain, obtain the fuzzy quantity E and Ec of indoor temperature error e (k) and indoor temperature error rate ec (k)；
Step d：Central controller enters according to indoor temperature error ambiguity amount E and indoor temperature error rate fuzzy quantity Ec
Row fuzzy reasoning, obtain fuzzy output amount Y；
Step e：Central controller carries out defuzzification processing to the fuzzy output amount, obtains controlling output quantity；
Step f：The control output quantity is exported to central air-conditioning executing agency, the central air-conditioning executing agency according to
Control output quantity is controlled to controlled device；
Step g：The central controller is according to the indoor temperature error e (k) and indoor temperature error rate ec
(k) output quantity, is controlled, obtains the dynamic response curve figure of control process..
Further, the indoor temperature e is gathered by temperature sensor, and the temperature sensor is multiple, and is placed in
Not in chummery.
Further, the indoor temperature error e (k) described in step b is achieved in the following ways：
If temperature sensor quantity is n, n temperature sensor at a time carries out not chummery indoor temperature survey
Amount, obtains n data, arranges from small to large ord, if temperature sensor measurement value is EniIf intermediate value EM, upper quartile
EOn, lower quartile EUnder, difference dE, the intermediate value EMObtained by formula 1 and formula 2：
EM=E(n+1)/2 (2)
In formula 1, n is even number, and in formula 2, n is odd number.
The upper quartile EOnObtained by formula 3 and formula 4：
EOn=E(n+3)/2 (4)
In formula 3, n is even number, and in formula 4, n is odd number.
The lower quartile EUnderObtained by formula 5 and formula 6：
EUnder=E(n-1)/2 (6)
In formula 5, n is even number, and in formula 6, n is odd number.
The difference dE is obtained by formula 7：
DE=EOn-EUnder (7)
By temperature sensor measurement value EniWith intermediate value EMDifference absolute value compared with difference dE absolute value, be more than
Difference dE for invalid data, after rejecting invalid data, arithmetic mean of instantaneous value is asked for remaining data, obtains the environment temperature
Error e (k).
Further, fuzzy rule base is provided with the central controller, the fuzzy rule base is used to deposit
Put whole fuzzy control rules.
Further, the fuzzy rule base can freely add fuzzy control rule as needed.
Further, the fuzzy control rule added is rule 1：When the indoor temperature e is less than wind pushing temperature es
When, make indoor temperature close to wind pushing temperature, rule 2 by reducing indoor air output：When the indoor temperature e is more than air-supply temperature
Spend esWhen, make indoor temperature close to wind pushing temperature by increasing indoor air output.
Further, the fuzzy output amount Y includes and indoor temperature error e (k), indoor temperature error rate ec
(k) membership function corresponding to fuzzy language value corresponding to output quantity and the fuzzy language value, is controlled.
Further, the central air-conditioning executing agency is central hollow temperature adjustment blowing mouth valve positioner.
Further, controlled device described in step f is blowing open area.
Compared with prior art, the beneficial effects of the invention are as follows：
A kind of central air conditioner system temprature control method based on fuzzy technology provided by the invention, by using Fuzzy Control
The method of technology processed, indoor temperature error e (k) and indoor temperature error rate ec (k) are converted into fuzzy quantity, according to fuzzy
Control rule carries out fuzzy reasoning to the fuzzy quantity, and the control output quantity after being controlled according to ambiguity solution is carried out to controlled device
Control, controlled not caused by overcoming non-linear, time-varying and hysteresis characteristic in existing central air-conditioning PID temperature control process of knowing clearly
The problem of accurate.
Brief description of the drawings
Fig. 1 is a kind of central air conditioner system temprature control method flow based on fuzzy technology provided in an embodiment of the present invention
Figure.
Fig. 2 is fuzzy quantity E and EC membership function image.
Fig. 3 is fuzzy output amount Y membership function image.
Embodiment
Technical scheme in order to illustrate the embodiments of the present invention more clearly, make required in being described below to embodiment
Accompanying drawing is briefly described, it should be apparent that, drawings in the following description are only the preferred embodiments of the present invention, for
For those of ordinary skill in the art, without having to pay creative labor, it can also be obtained according to these accompanying drawings
His accompanying drawing.
As described in Figure 1, a kind of central air conditioner system temprature control method based on fuzzy technology provided by the invention, including
Following steps,
Step a：Gather indoor temperature e；
Step b：On the basis of central processing unit obtains indoor temperature e, according to default indoor temperature r, Indoor Temperature is obtained
Spend error e (k) and indoor temperature error rate ec (k)；
Step c：Indoor temperature error e (k) and indoor temperature error rate ec (k) are mapped to input by central processing unit
Domain, obtain the fuzzy quantity E and Ec of indoor temperature error e (k) and indoor temperature error rate ec (k)；
Step d：Central controller enters according to indoor temperature error ambiguity amount E and indoor temperature error rate fuzzy quantity Ec
Row fuzzy reasoning, obtain fuzzy output amount Y；
Step e：Central controller carries out defuzzification processing to the fuzzy output amount Y, obtains controlling output quantity；
Step f：The control output quantity is exported to central air-conditioning executing agency, the central air-conditioning executing agency according to
Control output quantity is controlled to controlled device；
Step g：The central controller is according to the indoor temperature error e (k) and indoor temperature error rate ec
(k) output quantity, is controlled, obtains the dynamic response curve figure of control process.
Specifically, the indoor temperature e is gathered by temperature sensor, the temperature sensor is located at multiple rooms, and
There was only one in each room.
Specifically, the method that indoor temperature error e (k) is obtained described in step b is：
If temperature sensor quantity is n, n temperature sensor at a time carries out not chummery indoor temperature survey
Amount, obtains n data, arranges from small to large ord, if temperature sensor measurement value is EniIf intermediate value EM, upper quartile
EOn, lower quartile EUnder, difference dE, the intermediate value EMObtained by formula 1 and formula 2：
EM=E(n+1)/2 (2)
In formula 1, n is even number, and in formula 2, n is odd number.
The upper quartile EOnObtained by formula 3 and formula 4：
EOn=E(n+3)/2 (4)
In formula 3, n is even number, and in formula 4, n is odd number.
The lower quartile EUnderObtained by formula 5 and formula 6：
EUnder=E(n-1)/2 (6)
In formula 5, n is even number, and in formula 6, n is odd number.
The difference dE is obtained by formula 7：
DE=EOn-EUnder (7)
By temperature sensor measurement value EniWith intermediate value EMDifference absolute value compared with difference dE absolute value, be more than
Difference dE for invalid data, after rejecting invalid data, arithmetic mean of instantaneous value is asked for remaining data, obtains the environment temperature
Error e (k).
Specifically, the central processing unit is provided with fuzzy rule base, the fuzzy rule base is fuzzy control
The set of rule, in the present embodiment, the fuzzy control rule is added by technical staff, and the rule of addition is as follows：
Rule 1：When the indoor temperature e is less than wind pushing temperature esWhen, make the temperature of interior by reducing indoor air output
Close to wind pushing temperature；
Rule 2：When the indoor temperature e is more than wind pushing temperature esWhen, make the temperature of interior by increasing indoor air output
Close to wind pushing temperature.
Specifically, the step c is obtaining the fuzzy of indoor temperature error e (k) and indoor temperature error rate ec (k)
When measuring E and Ec, comprise the following steps：
1. setting the domain of indoor temperature error e (k) as [- 5,5], scale factor K e is 1.2, and the domain is indoor temperature
The actual change scope of error e (k) error；
2. setting indoor temperature error rate ec (k) domain as [- 10,10], scale factor K ec is 0.6, the domain
For indoor temperature error rate ec (k) actual change scope；
3. determining minimum supply air rate according to air flow rate formula, the air flow rate formula is：In formula：L is
Air flow rate；ρ is air-supply density, and in the present embodiment, the scope of air flow rate is [165,550] m3/ h, set air flow rate
Actual domain be [- 550,550], scale factor K y is 0.011；
4. in the present embodiment, by indoor temperature error ambiguity amount E and indoor temperature error rate fuzzy quantity Ec, fuzzy
Output quantity Y fuzzy domain is set to [- 6,6], form containing 13 integer elements fuzzy domain -6, -5, -4, -3, -2, -1,
0,1,2,3,4,5,6 }, the fuzzy domain is divided into the fuzzy subset { NB, NS, ZR, PS, PB } of 5 grades.
Fuzzy subset's inner language implication is as follows：
NB- is negative big
NS- bears small
ZR- zero
PS- is just small
PB- is honest
5. according to Indistinct Input amount temperature error ambiguity amount E, indoor temperature error rate fuzzy quantity Ec and fuzzy output
Y relation is measured, the fuzzy control rule is write as a form, is shown in Table 1
The fuzzy control rule table of table 1
Specifically, in the simulation input amount input central controller that step c is obtained, central controller passes through Mamdani
The fuzzy control rule of algorithm and the table 1 carries out fuzzy reasoning computing, obtains fuzzy output amount Y.
Specifically, the fuzzy output amount Y include with indoor temperature error e (k), indoor temperature error rate ec (k),
Membership function corresponding to controlling fuzzy language value corresponding to output quantity and the fuzzy language value, consider the convenience calculated, this
Embodiment is corresponding with indoor temperature error rate ec (k) as the indoor temperature error e (k) using triangular membership
Membership function, using trapezoidal membership function as it is described control output quantity corresponding to membership function, membership function image such as Fig. 2
Shown in Fig. 3.
Specifically, central controller is carried out at defuzzification to the fuzzy output amount Y according to the fuzzy control rule of table 1
Reason, obtain controlling output quantity, executing agency is controlled controlled device according to the control output quantity, in the present embodiment, should
Executing agency is central hollow temperature adjustment blowing mouth valve positioner, and controlled device is blowing open area.
Specifically, central processing unit can be according to the indoor temperature error e (k) and indoor temperature error rate ec of input
(k), the control output quantity of output obtains the dynamic response curve of control process.
By the description of above-described embodiment, the fuzzy control method of the present embodiment is not required to know the number of controlled device or process
Learn model, it is easy to accomplish the object with probabilistic object and with strong nonlinearity is controlled, for control system
Interference there is stronger rejection ability, improve the adjustability, intelligent of system temperature, make control process more accurate.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all essences in the present invention
God any modification, equivalent substitution and improvements made etc., should be included in the scope of the protection with principle.
Claims (9)
- A kind of 1. central air conditioner system temprature control method based on fuzzy technology, it is characterised in that comprise the following steps,Step a：Gather indoor temperature e；Step b：On the basis of central processing unit obtains indoor temperature e, according to default indoor temperature r, indoor temperature mistake is obtained Poor e (k) and indoor temperature error rate ec (k)；Step c：Indoor temperature error e (k) and indoor temperature error rate ec (k) are mapped to input opinion by central processing unit Domain, obtain the fuzzy quantity E and Ec of indoor temperature error e (k) and indoor temperature error rate ec (k)；Step d：Central controller carries out mould according to indoor temperature error ambiguity amount E and indoor temperature error rate fuzzy quantity Ec Reasoning is pasted, obtains fuzzy output amount Y；Step e：Central controller carries out defuzzification processing to the fuzzy output amount Y, obtains controlling output quantity；Step f：The control output quantity is exported to central air-conditioning executing agency, the central air-conditioning executing agency is according to control Output quantity is controlled to controlled device；Step g：The central controller is according to the indoor temperature error e (k) and indoor temperature error rate ec (k), control Output quantity processed, obtain the dynamic response curve figure of control process.
- 2. a kind of central air conditioner system temprature control method based on fuzzy technology according to claim 1, its feature exist In the indoor temperature e is gathered by temperature sensor, and the temperature sensor is multiple, and is placed in not in chummery.
- 3. a kind of central air conditioner system temprature control method based on fuzzy technology according to claim 2, its feature exist In the indoor temperature error e (k) described in step b obtains in the following manner：If temperature sensor quantity is n, n temperature sensor at a time carries out not chummery indoor temperature measurement, obtains To n data, arrange from small to large ord, if temperature sensor measurement value is EniIf intermediate value EM, upper quartile EOn, under Quartile EUnder, difference dE, the intermediate value EMObtained by formula 1 or formula 2：<mrow> <msub> <mi>E</mi> <mi>M</mi> </msub> <mo>=</mo> <mfrac> <mrow> <msub> <mi>E</mi> <mrow> <mi>n</mi> <mo>/</mo> <mn>2</mn> </mrow> </msub> <mo>+</mo> <msub> <mi>E</mi> <mrow> <mrow> <mo>(</mo> <mrow> <mi>n</mi> <mo>+</mo> <mn>2</mn> </mrow> <mo>)</mo> </mrow> <mo>/</mo> <mn>2</mn> </mrow> </msub> </mrow> <mn>2</mn> </mfrac> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> </mrow>EM=E(n+1)/2 (2)In formula 1, n is even number, and in formula 2, n is odd number.The upper quartile EOnObtained by formula 3 or formula 4：EOn=E(n+3）/2 (4)In formula 3, n is even number, and in formula 4, n is odd number.The lower quartile EUnderObtained by formula 5 or formula 6：EUnder=E(n-1)/2 (6)In formula 5, n is even number, and in formula 6, n is odd number.The difference dE is obtained by formula 7：DE=EOn-EUnder (7)By temperature sensor measurement value EniWith intermediate value EMDifference absolute value compared with difference dE absolute value, more than difference DE for invalid data, after rejecting invalid data, arithmetic mean of instantaneous value is asked for remaining data, obtains the environment temperature error e(k)。
- 4. a kind of central air conditioner system temprature control method based on fuzzy technology according to claim 1, its feature exist In the central controller is interior to be provided with fuzzy rule base, and the fuzzy rule base is used to deposit whole fuzzy controls Rule.
- 5. a kind of central air conditioner system temprature control method based on fuzzy technology according to claim 4, its feature exist In the fuzzy rule base can freely add fuzzy control rule as needed.
- 6. a kind of central air conditioner system temprature control method based on fuzzy technology according to claim 4, its feature exist In the fuzzy control rule added is rule 1：When the indoor temperature e is less than wind pushing temperature esWhen, it is indoor by reducing Air output makes indoor temperature close to wind pushing temperature, rule 2：When the indoor temperature e is more than wind pushing temperature esWhen, pass through increase Indoor air output makes indoor temperature close to wind pushing temperature.
- 7. a kind of central air conditioner system temprature control method based on fuzzy technology according to claim 1, its feature exist In fuzzy output amount Y described in step d includes defeated with indoor temperature error e (k), indoor temperature error rate ec (k), control Membership function corresponding to fuzzy language value corresponding to output and the fuzzy language value.
- 8. a kind of central air conditioner system temprature control method based on fuzzy technology according to claim 1, its feature exist In central air-conditioning executing agency described in step f is central hollow temperature adjustment blowing mouth valve positioner.
- 9. a kind of central air conditioner system temprature control method based on fuzzy technology according to claim 1, its feature exist In controlled device described in step f is blowing open area.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711051782.1A CN107883529A (en) | 2017-10-30 | 2017-10-30 | A kind of central air conditioner system temprature control method based on fuzzy technology |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711051782.1A CN107883529A (en) | 2017-10-30 | 2017-10-30 | A kind of central air conditioner system temprature control method based on fuzzy technology |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN107883529A true CN107883529A (en) | 2018-04-06 |
Family
ID=61783299
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201711051782.1A Pending CN107883529A (en) | 2017-10-30 | 2017-10-30 | A kind of central air conditioner system temprature control method based on fuzzy technology |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107883529A (en) |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109269027A (en) * | 2018-06-20 | 2019-01-25 | 广东海悟科技有限公司 | A kind of air conditioner refrigerating control method, system and the device of automatic optimal |
| CN110262421A (en) * | 2019-06-21 | 2019-09-20 | 深圳市美兆环境股份有限公司 | The control method and device of production equipment |
| CN110567092A (en) * | 2019-09-26 | 2019-12-13 | 上海朗绿建筑科技股份有限公司 | temperature control method and system applied to air handling unit |
| CN112130502A (en) * | 2020-09-24 | 2020-12-25 | 中石油西北联合管道有限责任公司 | Three-axis data acquisition system and method for pipeline magnetic flux leakage internal detector |
| CN112484260A (en) * | 2020-12-07 | 2021-03-12 | 格力电器（武汉）有限公司 | Humidity control method, humidity control device, electronic equipment and storage medium |
| CN114711033A (en) * | 2022-04-27 | 2022-07-08 | 北京良安科技有限公司 | Circulation system in granary |
| CN117193019A (en) * | 2023-10-13 | 2023-12-08 | 武城县建筑设计院 | Intelligent building control system for building design |
| CN117603809A (en) * | 2023-12-06 | 2024-02-27 | 威海紫光科技园有限公司 | Temperature control method and system applied to resuscitation in NK cell preparation process |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR100225637B1 (en) * | 1997-05-23 | 1999-10-15 | 윤종용 | Temperature control apparatus for air conditioner |
| CN101561661A (en) * | 2009-05-25 | 2009-10-21 | 中国农业大学 | Fuzzy control method and fuzzy controller |
| CN101893851A (en) * | 2010-07-12 | 2010-11-24 | 郭栋才 | Indoor temperature fuzzy control system and method thereof |
| US20130158722A1 (en) * | 2011-12-14 | 2013-06-20 | Industrial Technology Research Institute | Air conditioning control device and method thereof |
| CN203350635U (en) * | 2013-06-09 | 2013-12-18 | 苏州经贸职业技术学院 | Dynamic fuzzy control system |
| KR101438901B1 (en) * | 2012-08-23 | 2014-09-16 | 현대자동차주식회사 | Blower control device and method for high voltage battery |
| CN105260861A (en) * | 2015-11-25 | 2016-01-20 | 海南电网有限责任公司 | Comprehensive risk assessment method for electric vehicle battery replacement station |
| WO2016170005A1 (en) * | 2015-04-20 | 2016-10-27 | Resmed Sensor Technologies Limited | Detection and identification of a human from characteristic signals |
| CN106604496A (en) * | 2016-11-24 | 2017-04-26 | 海南电力技术研究院 | Parking lot illumination system control method based on fuzzy technology |
-
2017
- 2017-10-30 CN CN201711051782.1A patent/CN107883529A/en active Pending
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR100225637B1 (en) * | 1997-05-23 | 1999-10-15 | 윤종용 | Temperature control apparatus for air conditioner |
| CN101561661A (en) * | 2009-05-25 | 2009-10-21 | 中国农业大学 | Fuzzy control method and fuzzy controller |
| CN101893851A (en) * | 2010-07-12 | 2010-11-24 | 郭栋才 | Indoor temperature fuzzy control system and method thereof |
| US20130158722A1 (en) * | 2011-12-14 | 2013-06-20 | Industrial Technology Research Institute | Air conditioning control device and method thereof |
| KR101438901B1 (en) * | 2012-08-23 | 2014-09-16 | 현대자동차주식회사 | Blower control device and method for high voltage battery |
| CN203350635U (en) * | 2013-06-09 | 2013-12-18 | 苏州经贸职业技术学院 | Dynamic fuzzy control system |
| WO2016170005A1 (en) * | 2015-04-20 | 2016-10-27 | Resmed Sensor Technologies Limited | Detection and identification of a human from characteristic signals |
| CN105260861A (en) * | 2015-11-25 | 2016-01-20 | 海南电网有限责任公司 | Comprehensive risk assessment method for electric vehicle battery replacement station |
| CN106604496A (en) * | 2016-11-24 | 2017-04-26 | 海南电力技术研究院 | Parking lot illumination system control method based on fuzzy technology |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109269027A (en) * | 2018-06-20 | 2019-01-25 | 广东海悟科技有限公司 | A kind of air conditioner refrigerating control method, system and the device of automatic optimal |
| CN109269027B (en) * | 2018-06-20 | 2023-04-07 | 广东海悟科技有限公司 | Automatic optimization air conditioner refrigeration control method, system and device |
| CN110262421A (en) * | 2019-06-21 | 2019-09-20 | 深圳市美兆环境股份有限公司 | The control method and device of production equipment |
| CN110567092A (en) * | 2019-09-26 | 2019-12-13 | 上海朗绿建筑科技股份有限公司 | temperature control method and system applied to air handling unit |
| CN112130502A (en) * | 2020-09-24 | 2020-12-25 | 中石油西北联合管道有限责任公司 | Three-axis data acquisition system and method for pipeline magnetic flux leakage internal detector |
| CN112484260A (en) * | 2020-12-07 | 2021-03-12 | 格力电器（武汉）有限公司 | Humidity control method, humidity control device, electronic equipment and storage medium |
| CN112484260B (en) * | 2020-12-07 | 2022-04-15 | 格力电器（武汉）有限公司 | Humidity control method, humidity control device, electronic equipment and storage medium |
| CN114711033A (en) * | 2022-04-27 | 2022-07-08 | 北京良安科技有限公司 | Circulation system in granary |
| CN114711033B (en) * | 2022-04-27 | 2023-03-14 | 北京良安科技有限公司 | Circulation system in granary |
| CN117193019A (en) * | 2023-10-13 | 2023-12-08 | 武城县建筑设计院 | Intelligent building control system for building design |
| CN117603809A (en) * | 2023-12-06 | 2024-02-27 | 威海紫光科技园有限公司 | Temperature control method and system applied to resuscitation in NK cell preparation process |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107883529A (en) | A kind of central air conditioner system temprature control method based on fuzzy technology | |
| CN110059801B (en) | Air conditioner energy efficiency control method based on neural network | |
| CN110057045B (en) | Control method for air conditioner | |
| US12130603B2 (en) | Method and apparatus for controlling smart home | |
| Liang et al. | Design of intelligent comfort control system with human learning and minimum power control strategies | |
| CN110186170B (en) | Thermal comfort index PMV control method and equipment | |
| CN105588274B (en) | A kind of natural wind control method and device | |
| CN106920006A (en) | A kind of subway station air conditioning energy consumption Forecasting Methodology based on ISOA LSSVM | |
| CN109827292A (en) | Construction method and control method of self-adaptive energy-saving control model of household appliance and household appliance | |
| CN111520878A (en) | Air conditioner temperature control system based on RBF neural network and control method thereof | |
| CN101672509A (en) | Air-conditioning control technique with variable air quantity based on enthalpy value control | |
| CN105117770A (en) | Surface cooler control method based on improved fuzzy neural network | |
| CN110440385A (en) | A kind of mechanical constructing device and method of comfortable natural-wind-imitating | |
| CN111457571A (en) | Method, equipment and system for controlling indoor relative temperature and humidity | |
| Xu et al. | The study of the dynamic load forecasting model about air-conditioning system based on the terminal user load | |
| CN107368940A (en) | Count and respond uncertain temperature control Load aggregation response potential evaluation method and system | |
| CN111623498A (en) | Automatic air conditioner temperature determination method and system | |
| CN111288610A (en) | Variable static pressure self-adaptive fuzzy control method for variable air volume air conditioning system | |
| CN110094838A (en) | A kind of variable element MFA control method based on air-conditioning system | |
| CN112180733B (en) | Fuzzy logic-based building energy consumption system prediction control parameter setting method | |
| Eftekhari et al. | Design and performance of a rule-based controller in a naturally ventilated room | |
| CN118259595A (en) | Optimization control method of variable air volume air conditioning system based on fuzzy control and model predictive control | |
| CN114838452B (en) | Intelligent air valve applied to variable air volume system, system and control method | |
| CN116746697A (en) | Environmental humidity control system and method for tobacco leaf baking process of sheet baking machine | |
| Cui et al. | An Online Reinforcement Learning Method for Multi-Zone Ventilation Control With Pre-Training |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20180406 |
|
| RJ01 | Rejection of invention patent application after publication |