CN108443958A - The adjusting method and system of heating system - Google Patents
The adjusting method and system of heating system Download PDFInfo
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- CN108443958A CN108443958A CN201810271763.8A CN201810271763A CN108443958A CN 108443958 A CN108443958 A CN 108443958A CN 201810271763 A CN201810271763 A CN 201810271763A CN 108443958 A CN108443958 A CN 108443958A
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24D—DOMESTIC- OR SPACE-HEATING SYSTEMS, e.g. CENTRAL HEATING SYSTEMS; DOMESTIC HOT-WATER SUPPLY SYSTEMS; ELEMENTS OR COMPONENTS THEREFOR
- F24D19/00—Details
- F24D19/10—Arrangement or mounting of control or safety devices
- F24D19/1003—Arrangement or mounting of control or safety devices for steam heating systems
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24D—DOMESTIC- OR SPACE-HEATING SYSTEMS, e.g. CENTRAL HEATING SYSTEMS; DOMESTIC HOT-WATER SUPPLY SYSTEMS; ELEMENTS OR COMPONENTS THEREFOR
- F24D19/00—Details
- F24D19/10—Arrangement or mounting of control or safety devices
- F24D19/1006—Arrangement or mounting of control or safety devices for water heating systems
Abstract
The present invention relates to a kind of adjusting methods of heating system to include：The floor data of current system is obtained in real time；Present input data error and present input data change rate is calculated according to the floor data；Fuzzy processing is carried out to present input data error and present input data change rate, the fuzzy subset of corresponding current output data is searched by fuzzy control rule；Ambiguity solution operation is carried out according to the fuzzy subset of present input data error, present input data change rate and current output data, obtains current output data；The heating system is adjusted according to the current output data.The present invention makes the adjustment process of heating system simplify using the method for fuzzy control, meets the regulatory demand of Correction for Large Dead Time System, further make system response much sooner, control it is more accurate, also solve system output concussion the problem of.
Description
Technical field
The present invention relates to accurate field of intelligent control technology, a kind of adjusting method more particularly to heating system and are
System.
Background technology
Heating system is that steam or hot water are supplied to all resident families of Lou Dongzhong by pipeline, and by steam or hot water
The effective cycle in pipeline between heat source and Lou Dong, the purpose is to provide to stablize comfortable heat for the resident family of Lou Dongzhong
Amount.Stablize comfortable heat to provide the user with, therefore is just needed to heating system in the cyclic process of steam or hot water
It is constantly adjusted, to ensure comfortably stable temperature.
In current traditional technology, the adjusting method of usually used heating system is divided into two kinds, and one is PID control sides
Method, the artificial control targe (water pump frequency or valve opening) for setting heating system, control system use the method that error is cut down
Constantly approach operation control targe.Another kind is CFD emulation modes, and environmental data and system data are carried out to heating system
Sampling, CFD model is established based on sampled data, and the model of foundation is recycled to carry out system control.
In two kinds of adjusting methods of above-mentioned traditional technology, PID control method exists due to the feedback of status of heating system
Larger time lag, thus the method exist response not in time, the problems such as control is inaccurate and output concussion.CFD emulation modes
Due to the environmental condition and appointed condition of heating system, different engineering and it is different when it is interim there are larger differences, make
Simulation model is difficult to cover all situations, therefore this control method is also inaccurate.
Invention content
Based on this, it is necessary to for response not in time, the problems such as control is inaccurate and output concussion, a kind of heat supply is provided
The adjusting method and system of system.
The present invention provides a kind of adjusting methods of heating system to include：The floor data of current system is obtained in real time；Root
Present input data error and present input data change rate is calculated according to the floor data；Present input data is missed
Difference and present input data change rate carry out Fuzzy processing, and corresponding current output data is searched by fuzzy control rule
Fuzzy subset；According to present input data error, the fuzzy subset of present input data change rate and current output data
Ambiguity solution operation is carried out, current output data is obtained；The heating system is adjusted according to the current output data.
It is further, described that Fuzzy processing is carried out to present input data error and present input data change rate,
The step of searching the fuzzy subset of corresponding current output data by fuzzy control rule include：It is missed according to present input data
Difference searches the fuzzy subset of corresponding present input data error；It is searched according to present input data change rate corresponding current defeated
Enter the fuzzy subset of data variation rate；According to the fuzzy subset of present input data error and present input data change rate
Fuzzy subset searches the fuzzy subset of corresponding current output data by fuzzy control rule.
Further, described according to present input data error, present input data change rate and current output data
Fuzzy subset carry out ambiguity solution operation, the step of obtaining current output data includes：Present input data error is substituted into and is subordinate to
Category degree function, obtain present input data is subordinate to angle value；Present input data change rate is substituted into membership function, is worked as
Preceding input data change rate is subordinate to angle value；To present input data be subordinate to angle value, present input data change rate is subordinate to
The fuzzy subset of angle value and current output data is weighted averagely, obtains current output data.
Further, the fuzzy control rule is：According to the value range of error of input data, input data change rate
Value range and output data value range constructed by fuzzy control rule.
Further, the fuzzy control rule includes：The input number divided according to the value range of error of input data
According to the fuzzy subset of error；According to the fuzzy subset for the input data change rate that the value range of input data change rate divides；
According to the fuzzy subset for the output data that the value range of output data divides；And the fuzzy subset of error of input data and defeated
Enter the correspondence between all combinations of the fuzzy subset of data variation rate and the fuzzy subset of output data.
Further, the fuzzy subset of the error of input data, the fuzzy subset of input data change rate and output
The number of the fuzzy subset of data is seven；Wherein seven fuzzy subsets are respectively：In negative big, negative, it is negative it is small, zero, it is just small, just
In, it is honest.
Further, if the fuzzy subset of error of input data is negative big, the fuzzy subset of input data change rate is negative
Greatly, then the fuzzy subset of output data is negative big；During if the fuzzy subset of error of input data is negative, input data change rate
During fuzzy subset is negative, then during the fuzzy subset of output data is negative；If the fuzzy subset of error of input data is negative small, input
The fuzzy subset of data variation rate is negative small, then the fuzzy subset of output data is negative small；If the fuzzy son of error of input data
Collection is zero, and the fuzzy subset of input data change rate is zero, then the fuzzy subset of output data is zero；If error of input data
Fuzzy subset is just small, and the fuzzy subset of input data change rate is just small, then the fuzzy subset of output data is just small；If defeated
The fuzzy subset for entering data error is center, and the fuzzy subset of input data change rate is center, then the fuzzy son of output data
Collection is center；If the fuzzy subset of error of input data is honest, the fuzzy subset of input data change rate is honest, then exports
The fuzzy subset of data is honest.
Further, the floor data includes：Inflow temperature, return water temperature, flow system flow, system flow rate, regulating valve
Aperture and water pump frequency；The input data is return water temperature；The output data is control valve opening.
Further, it is also wrapped after the described the step of heating system is adjusted according to the current output data
It includes：According to the adjusting of heating system as a result, correcting the fuzzy control rule.
Example of the present invention additionally provides a kind of regulating system of heating system：Acquisition module, it is current for obtaining in real time
The floor data of system；Computing module, for present input data error and current to be calculated according to the floor data
Input data change rate；It is blurred module, for searching corresponding present input data error according to present input data error
Fuzzy subset；It is additionally operable to search the fuzzy son of corresponding present input data change rate according to present input data change rate
Collection；Fuzzy rule module, for according to the fuzzy subset of present input data error and the mould of present input data change rate
Paste subset searches the fuzzy subset of corresponding current output data by fuzzy control rule；Ambiguity solution module is worked as basis
The fuzzy subset of preceding error of input data, present input data change rate and current output data carries out ambiguity solution operation, obtains
To current output data；Adjustment module, for the heating system to be adjusted according to the current output data.
Current input number is calculated according to floor data by acquiring the floor data of current system in real time in the present invention
According to error and present input data change rate, using present input data error and present input data change rate as fuzzy
The input of algorithm, and output data is finally obtained by blurring, fuzzy reasoning and ambiguity solution, and according to output data to supplying
Hot systems are adjusted.The present invention makes the adjustment process of heating system simplify using the method for fuzzy control, meets large dead time system
The regulatory demand of system, further make system response much sooner, control it is more accurate, also solve system output concussion ask
Topic.
Description of the drawings
Fig. 1 is a kind of flow chart of the adjusting method of heating system provided in an embodiment of the present invention；
Fig. 2 is the membership function image of error of input data provided in an embodiment of the present invention；
Fig. 3 is the membership function image of input data change rate provided in an embodiment of the present invention；
Fig. 4 is the membership function image of output data provided in an embodiment of the present invention；
Fig. 5 is the flow chart of ambiguity solution in a kind of adjusting method of heating system provided in an embodiment of the present invention；
Fig. 6 is a kind of structural schematic diagram of the regulating system of heating system provided in an embodiment of the present invention.
Reference numeral：100 be acquisition module, and 200 be computing module, and 300 be blurring module, and 400 be fuzzy rule mould
Block, 500 be ambiguity solution module, and 600 be adjustment module.
Specific implementation mode
In order to make the object, technical solution and advantage of the embodiment of the present invention be more clearly understood, below in conjunction with attached drawing and reality
Example is applied, the embodiment of the present invention is further elaborated.It should be appreciated that specific embodiment described herein is only used to
It explains the embodiment of the present invention, is not intended to limit the present invention embodiment.
The embodiment of the invention discloses a kind of adjusting methods of heating system, by pre-establishing FUZZY ALGORITHMS FOR CONTROL.
When needing that heating system is adjusted, current floor data is obtained in real time first, and be calculated according to floor data
Present input data error and present input data change rate.Current error originated from input and current error originated from input change rate are made
FUZZY ALGORITHMS FOR CONTROL is substituted into for input, current output data is calculated, heating system is carried out further according to current output data
It adjusts, to achieve the purpose that real-time control.
The embodiment of the present invention pre-establishes fuzzy control rule, and wherein fuzzy control rule is：According to error of input data
Value range, the fuzzy control rule constructed by the value range of input data change rate and the value range of output data
Then.Fuzzy control rule includes：According to the fuzzy subset for the error of input data that the value range of error of input data divides；Root
According to the fuzzy subset for the input data change rate that the value range of input data change rate divides；According to the value model of output data
Enclose the fuzzy subset of the output data of division；And the fuzzy subset of error of input data and the fuzzy son of input data change rate
Correspondence between all combinations and the fuzzy subset of output data of collection.
Specifically, according to the value range of error of input data e, the value range of input data change rate de and output
The value range of error of input data e is divided into the fuzzy son of seven error of input data e by the value range of data z respectively
The value range of input data change rate de is divided into the fuzzy subset of seven input data change rate de, will export number by collection
The fuzzy subset of seven output data z is divided into according to the value range of z.
The fuzzy subset of wherein seven error of input data e respectively includes：During e is negative big, e is negative, e bear that small, e zero, e be just small, e
Center, e are honest.When error of input data e is negative, indicate it is expected that return water temperature is less than current return water temperature；Work as input data
Error e is timing, indicates it is expected that return water temperature is higher than current return water temperature.More specifically, when the value model of error of input data e
Enclose for [- 2,2] when, be [- 2, -0.65] during e negative greatly [- 2, -1.4], e are negative, e bear it is small be [- 1.4,0], e zero for [- 0.65,
0.65] it is [0,1.4] that, e is just small, the centers e are [0.65,2], e just greatly [1.4,2], and determine being subordinate to for error of input data e
Spend function.
The fuzzy subset of wherein seven input data change rate de respectively includes：During de is negative big, de is negative, de bear small, de zero,
De is just small, de is hit exactly, de is honest.When input data change rate de is negative, indicate that previous moment return water temperature is returned less than current
Coolant-temperature gage；When input data change rate de is timing, expression previous moment return water temperature is higher than current return water temperature.More specifically
, when the value range of input data change rate de is [- 1.5,1.5], be during de negative greatly [- 1.5, -1], de are negative [-
1.5, -0.5], de bear it is small be [- 1,0], de zero be [- 0.5,0.5], de it is just small be [0,1], de center be [0.5,1.5], de
Just greatly [1,1.5], and determine the membership function of input data change rate de.
The fuzzy subset of wherein seven output data z respectively includes：During z is negative big, z is negative, z bear small, z zero, z be just small, z just
In, z it is honest.When output data z is negative, expression needs to reduce control valve opening；When output data z is timing, expression needs
Increase control valve opening.More specifically, when the value range of output data z is [- 6,6], during z negative greatly [- 6, -3], z are negative
For [- 6, -1], z bear it is small be [- 3,0], z zero be [- 1,1], z it is just small be [0,3], the centers z are [1,6], z just greatly [3,6], and
Determine the membership function of output data z.
When the value range and output data respectively to the value range of error of input data, input data change rate
After value range has divided fuzzy subset, according to the fuzzy subset of error of input data e, input data change rate de it is fuzzy
The fuzzy subset of subset and output data z establish correspondence；Specifically, if the fuzzy subset of error of input data e is negative
Greatly, the fuzzy subset of input data change rate de is negative big, then the fuzzy subset of output data z is negative big；If input data is missed
During the fuzzy subset of poor e is negative, the fuzzy subset of input data change rate de is in bearing, then the fuzzy subset of output data z is
In negative；If the fuzzy subset of error of input data e is negative small, the fuzzy subset of input data change rate de is negative small, then exports
The fuzzy subset of data z is negative small；If the fuzzy subset of error of input data e is zero, the fuzzy son of input data change rate de
Collection is zero, then the fuzzy subset of output data z is zero；If the fuzzy subset of error of input data e is just small, input data variation
The fuzzy subset of rate de is just small, then the fuzzy subset of output data z is just small；If the fuzzy subset of error of input data e is
The fuzzy subset of center, input data change rate de is center, then the fuzzy subset of output data z is center；If input data
The fuzzy subset of error e is honest, and the fuzzy subset of input data change rate de is honest, the then fuzzy subset of output data z
It is honest.Preferably, all combinations of the fuzzy subset of the fuzzy subset of error of input data e and input data change rate de with
Correspondence such as following table between the fuzzy subset of output data z：
The fuzzy subset corresponding to present input data error can be found according to present input data error, according to working as
Preceding error of input data change rate can find the fuzzy subset corresponding to current input slew rate, further according to current input number
Fuzzy control rule is searched according to the fuzzy subset corresponding to error and the fuzzy subset corresponding to current input slew rate to search
The fuzzy subset of output data.
It is a kind of flow chart of the adjusting method of heating system provided in an embodiment of the present invention, Fig. 2 to please refer to Fig.1-4, Fig. 1
For the membership function image of error of input data provided in an embodiment of the present invention, Fig. 3 is input provided in an embodiment of the present invention
The membership function image of data variation rate, Fig. 4 are the membership function image of output data provided in an embodiment of the present invention.
As shown in Figs 1-4, a kind of adjusting method of heating system may comprise steps of S100 to step S500：
Step S100：The floor data of current system is obtained in real time.
Specifically, using in the real-time acquiring heat supply system of sensor inflow temperature, return water temperature, flow system flow and
System flow rate.Collector obtains control valve opening and water pump frequency in real time.Wherein sensor includes temperature sensor, flow
Sensor and water flow sensor.Floor data includes inflow temperature, return water temperature, flow system flow, system flow rate, regulating valve
Aperture and water pump frequency.
Step S200：Present input data error and present input data variation is calculated according to the floor data
Rate.
Specifically, according to current working data and pre-set heating system expectation operating mode number in floor data
According to present input data error and present input data change rate is calculated.Preferably, it is expected that floor data subtracts currently
Present input data error is calculated in floor data.Present input data error subtracts the calculating of previous moment error of input data
Obtain present input data change rate.Error of input data is calculated in the present embodiment and the method for input data change rate is
It is illustrated, it is not limited to the method for the present embodiment.Wherein input data is return water temperature, present input data error
For current return water temperature error, present input data change rate is current return water temperature change rate.
Step S300：Fuzzy processing is carried out to present input data error and present input data change rate, is passed through
Fuzzy control rule searches the fuzzy subset of corresponding current output data.
Specifically, searching the fuzzy subset of corresponding present input data error according to present input data error.It is preferred that
, the range that the fuzzy subset for corresponding to return water temperature error in fuzzy control rule according to current return water temperature error is identified into
Row is searched, and determines the fuzzy subset corresponding to current return water temperature error.It is searched according to present input data change rate corresponding
The fuzzy subset of present input data change rate.Preferably, it is corresponded in fuzzy control rule according to current return water temperature change rate
The range that the fuzzy subset of return water temperature change rate is identified is searched, and determines the mould corresponding to current return water temperature change rate
Paste subset.It is fuzzy corresponding to fuzzy subset and current return water temperature change rate corresponding to current return water temperature error
The correspondence of subset lookup fuzzy control rule determines the fuzzy subset of current output data.Wherein output data is regulating valve
Aperture.
Step S400：According to present input data error, the mould of present input data change rate and current output data
It pastes subset and carries out ambiguity solution operation, obtain current output data.
Specifically, according to the membership function of present input data error and error of input data, current input is calculated
Data error is subordinate to angle value with the fuzzy subset's of corresponding error of input data.According to present input data change rate and
The membership function of input data change rate calculates the mould of present input data change rate and corresponding input data change rate
Paste subset is subordinate to angle value.Again by the degree of membership of present input data error and the fuzzy subset of corresponding error of input data
Value, present input data change rate and the fuzzy subset of corresponding input data change rate are subordinate to angle value, currently export number
According to fuzzy subset be weighted average, obtain current output data.
Step S500：The heating system is adjusted according to the current output data.
Specifically, after current output data is calculated, heating system is exchanged according to obtained current output data
Section valve opening is adjusted, the further temperature for adjusting whole system.According to the adjusting of heating system as a result, correcting the mould
Paste control rule.
Referring to Fig. 5, Fig. 5 is the flow of ambiguity solution in a kind of adjusting method of heating system provided in an embodiment of the present invention
Figure.
As shown in figure 5, ambiguity solution may comprise steps of S410 to step in a kind of adjusting method of heating system
S430：
Step S410：Present input data error is substituted into membership function, obtain present input data is subordinate to angle value.
Specifically, present input data error is substituted into the membership function of the fuzzy subset of each error of input data,
Calculate the angle value that is subordinate to of the fuzzy subset of present input data error and each error of input data, wherein error of input data
Membership function is：
Wherein, s is to be subordinate to angle value, and x is present input data error.Work as a=-2, when b=-2, c=-1.4；It is calculated
S be error of input data e it is negative big be subordinate to angle value；Work as a=-2, when b=-1.4, c=-0.65；The s being calculated is input
It is subordinate to angle value during data error e is negative；Work as a=-1.4, when b=-0.65, c=0；The s being calculated is error of input data e
It is negative small to be subordinate to angle value；Work as a=-0.65, when b=0, c=0.65；The s being calculated is the degree of membership of error of input data e zero
Value；Work as a=0, when b=0.65, c=1.4；The s being calculated be error of input data e it is just small be subordinate to angle value；Work as a=
When 0.65, b=1.4, c=2；The s being calculated is subordinate to angle value for the centers error of input data e；Work as a=1.4, b=2, c=
When 2；The s being calculated be error of input data e it is honest be subordinate to angle value.
Step S420：Present input data change rate is substituted into membership function, obtains present input data change rate
It is subordinate to angle value.
Specifically, present input data change rate to be substituted into the degree of membership letter of the fuzzy subset of each input data change rate
Number, calculate the fuzzy subset of present input data change rate and each input data change rate is subordinate to angle value, wherein inputting number
It is according to the membership function of change rate：
Wherein, s is to be subordinate to angle value, and x is present input data change rate.Work as a=-1.5, when b=-1.5, c=-1；It calculates
Obtained s be input data change rate de it is negative big be subordinate to angle value；Work as a=-1.5, when b=-1, c=-0.5；The s being calculated
It is subordinate to angle value in negative for input data change rate de；Work as a=-1, when b=-0.5, c=0；The s being calculated is input data
Change rate de, which is born, small is subordinate to angle value；Work as a=-0.5, when b=0, c=0.5；The s being calculated is input data change rate de
Zero is subordinate to angle value；Work as a=0, when b=0.5, c=1；The s being calculated is the just small degrees of membership of input data change rate de
Value；Work as a=0.5, when b=1, c=1.5；The s being calculated is subordinate to angle value for the centers input data change rate de；Work as a=1,
When b=1.5, c=1.5；The s being calculated be input data change rate de it is honest be subordinate to angle value.
Step S430：To present input data be subordinate to angle value, present input data change rate is subordinate to angle value and works as
The fuzzy subset of preceding output data is weighted averagely, obtains current output data.
Specifically, by present input data error and the fuzzy subset of corresponding error of input data be subordinate to angle value,
Present input data change rate and the fuzzy subset's of corresponding input data change rate is subordinate to angle value, current output data
Fuzzy subset is weighted averagely, obtains current output data.Wherein Weighted Average Algorithm is：
Wherein, y is current output data, and n indicates that the effective fuzzy subset's sum of error of input data, m indicate input data
The effective fuzzy subset's sum of change rate, wherein fuzzy subset's sum that effective fuzzy subset's sum, which is degree of membership, to be not zero.I is indicated
It is subordinate to fuzzy subset's title that angle value is not zero in all fuzzy subsets of error of input data,Indicate that data error is all fuzzy
It is subordinate to the fuzzy subset that angle value is not zero in subset and is subordinate to angle value accordingly.J indicates all fuzzy subsets of input data change rate
In be subordinate to fuzzy subset's title that angle value is not zero,Indicate that being subordinate to angle value in all fuzzy subsets of data variation rate is not zero
Fuzzy subset be subordinate to angle value accordingly.ZijIndicate the fuzzy subset of current output data.
Referring to Fig. 6, Fig. 6 is a kind of structural schematic diagram of the regulating system of heating system provided in an embodiment of the present invention.
As shown in fig. 6, a kind of regulating system of heating system includes：Acquisition module 100, for obtaining current system in real time
Floor data；Computing module 200, for present input data error and current defeated to be calculated according to the floor data
Enter data variation rate；It is blurred module 300, for searching corresponding present input data error according to present input data error
Fuzzy subset；It is additionally operable to search the fuzzy son of corresponding present input data change rate according to present input data change rate
Collection；Fuzzy rule module 400, for according to the fuzzy subset of present input data error and present input data change rate
Fuzzy subset searches the fuzzy subset of corresponding current output data by fuzzy control rule；Ambiguity solution module 500 is used for root
Ambiguity solution fortune is carried out according to the fuzzy subset of present input data error, present input data change rate and current output data
It calculates, obtains current output data；Adjustment module 600, for being adjusted to the heating system according to the current output data
Section.
Specifically, acquisition module 100 includes sensor and collector.Using in the real-time acquiring heat supply system of sensor
Inflow temperature, return water temperature, flow system flow and system flow rate.Collector obtains control valve opening and water pump frequency in real time
Rate.Wherein sensor includes temperature sensor, water flow sensing unit and water flow sensor.Floor data include inflow temperature,
Return water temperature, flow system flow, system flow rate, control valve opening and water pump frequency.Acquisition module 100 is by the floor data of acquisition
It is transferred to computing module 200.
Computing module 200 is according to the current working data and pre-set heating system expectation operating mode in floor data
Present input data error and present input data change rate is calculated in data.Preferably, it is expected that floor data subtracts works as
Present input data error is calculated in preceding floor data.Present input data error subtracts previous moment error of input data meter
Calculation obtains present input data change rate.Error of input data and the method for input data change rate are calculated in the present embodiment
It is to be illustrated, it is not limited to the method for the present embodiment.Wherein input data is return water temperature, and present input data misses
Difference is current return water temperature error, and present input data change rate is current return water temperature change rate.Computing module 200 will be current
Error of input data and present input data change rate are transferred to blurring module 300.
Blurring module 300 searches the fuzzy son of corresponding present input data error according to present input data error
Collection.Preferably, the fuzzy subset for corresponding to return water temperature error in fuzzy control rule according to current return water temperature error is identified
Range searched, determine the fuzzy subset corresponding to current return water temperature error.It is looked into according to present input data change rate
Look for the fuzzy subset of corresponding present input data change rate.Preferably, Fuzzy Control is corresponded to according to current return water temperature change rate
The range that the fuzzy subset of return water temperature change rate is identified in system rule is searched, and determines current return water temperature change rate institute
Corresponding fuzzy subset.Module 300 is blurred to change the fuzzy subset of present input data error and present input data
The fuzzy subset of rate is transferred to fuzzy rule module 400.
Fuzzy subset and current return water temperature of the fuzzy rule module 400 corresponding to current return water temperature error become
The correspondence of fuzzy subset's lookup fuzzy control rule corresponding to rate determines the fuzzy subset of current output data.Wherein
Output data is control valve opening.The fuzzy subset of current output data is transmitted to ambiguity solution module by fuzzy rule module 400
500。
Ambiguity solution module 500 is worked as according to the membership function of present input data error and error of input data, calculating
Preceding error of input data is subordinate to angle value with the fuzzy subset's of corresponding error of input data.Changed according to present input data
The membership function of rate and input data change rate calculates present input data change rate and changes with corresponding input data
The fuzzy subset's of rate is subordinate to angle value.Again by present input data error with the fuzzy subset's of corresponding error of input data
It is subordinate to angle value, present input data change rate and the fuzzy subset of corresponding input data change rate are subordinate to angle value, current
The fuzzy subset of output data is weighted averagely, obtains current output data.Ambiguity solution module 500 passes current output data
Transport to adjustment module 600.
Adjustment module 600 is adjusted control valve opening according to obtained current output data, further adjusts whole
The temperature of a system.According to the adjusting of heating system as a result, correcting the fuzzy control rule.
The embodiment of the present invention is calculated currently by acquiring the floor data of current system in real time according to floor data
Error of input data and present input data change rate make present input data error and present input data change rate
For the input of fuzzy algorithmic approach, and output data is finally obtained by blurring, fuzzy reasoning and ambiguity solution, and according to output number
It is adjusted according to heating system.The embodiment of the present invention makes the adjustment process of heating system simplify using the method for fuzzy control,
Meet the regulatory demand of Correction for Large Dead Time System, further make system response much sooner, control it is more accurate, also solve system
The problem of output concussion.
Each technical characteristic of embodiment described above can be combined arbitrarily, to keep description succinct, not to above-mentioned reality
It applies all possible combination of each technical characteristic in example to be all described, as long as however, the combination of these technical characteristics is not deposited
In contradiction, it is all considered to be the range of this specification record.
Several embodiments of the invention above described embodiment only expresses, the description thereof is more specific and detailed, but simultaneously
It cannot therefore be construed as limiting the scope of the patent.It should be pointed out that coming for those of ordinary skill in the art
It says, without departing from the inventive concept of the premise, various modifications and improvements can be made, these belong to the protection of the present invention
Range.Therefore, the protection domain of patent of the present invention should be determined by the appended claims.
Claims (10)
1. a kind of adjusting method of heating system, which is characterized in that including：
The floor data of current system is obtained in real time；
Present input data error and present input data change rate is calculated according to the floor data；
Fuzzy processing is carried out to present input data error and present input data change rate, is looked by fuzzy control rule
Look for the fuzzy subset of corresponding current output data；
Solution mould is carried out according to the fuzzy subset of present input data error, present input data change rate and current output data
Operation is pasted, current output data is obtained；
The heating system is adjusted according to the current output data.
2. the adjusting method of heating system according to claim 1, which is characterized in that described to present input data error
And present input data change rate carries out Fuzzy processing, and corresponding current output data is searched by fuzzy control rule
The step of fuzzy subset includes：
The fuzzy subset of corresponding present input data error is searched according to present input data error；
The fuzzy subset of corresponding present input data change rate is searched according to present input data change rate；
Pass through Fuzzy Control according to the fuzzy subset of the fuzzy subset of present input data error and present input data change rate
The fuzzy subset of the corresponding current output data of rule searching processed.
3. the adjusting method of heating system according to claim 1, which is characterized in that described to be missed according to present input data
The fuzzy subset of difference, present input data change rate and current output data carries out ambiguity solution operation, obtains currently exporting number
According to the step of include：
Present input data error is substituted into membership function, obtain present input data is subordinate to angle value；
Present input data change rate is substituted into membership function, obtain present input data change rate is subordinate to angle value；
To present input data be subordinate to angle value, present input data change rate the mould for being subordinate to angle value and current output data
Paste subset is weighted averagely, obtains current output data.
4. the adjusting method of heating system according to claim 1, which is characterized in that
The fuzzy control rule is：According to the value range of error of input data, the value range of input data change rate with
And the fuzzy control rule constructed by the value range of output data.
5. the adjusting method of heating system according to claim 4, which is characterized in that
The fuzzy control rule includes：
According to the fuzzy subset for the error of input data that the value range of error of input data divides；
According to the fuzzy subset for the input data change rate that the value range of input data change rate divides；
According to the fuzzy subset for the output data that the value range of output data divides；And
The mould of all combinations and output data of the fuzzy subset of error of input data and the fuzzy subset of input data change rate
Paste the correspondence between subset.
6. the adjusting method of heating system according to claim 5, which is characterized in that
Fuzzy subset, the fuzzy subset of input data change rate and the fuzzy subset of output data of the error of input data
Number be seven；
Wherein seven fuzzy subsets are respectively：In negative big, negative, it is negative it is small, zero, it is just small, center, honest.
7. the adjusting method of heating system according to claim 6, which is characterized in that the correspondence includes：
If the fuzzy subset of error of input data is negative big, the fuzzy subset of input data change rate is big to bear, then output data
Fuzzy subset be negative big；
If during the fuzzy subset of error of input data is negative, during the fuzzy subset of input data change rate is negative, then output data
Fuzzy subset be negative；
If the fuzzy subset of error of input data is negative small, the fuzzy subset of input data change rate is small to bear, then output data
Fuzzy subset be negative small；
If the fuzzy subset of error of input data is zero, the fuzzy subset of input data change rate is zero, then the mould of output data
It is zero to paste subset；
If the fuzzy subset of error of input data is just small, the fuzzy subset of input data change rate is just small, then output data
Fuzzy subset be it is just small；
If the fuzzy subset of error of input data is center, the fuzzy subset of input data change rate is center, then output data
Fuzzy subset be center；
If the fuzzy subset of error of input data is honest, the fuzzy subset of input data change rate is honest, then output data
Fuzzy subset be it is honest.
8. the adjusting method of heating system according to claim 1, which is characterized in that
The floor data includes：Inflow temperature, return water temperature, flow system flow, system flow rate, control valve opening and water pump frequency
Rate；
The input data is return water temperature；
The output data is control valve opening.
9. the adjusting method of heating system according to claim 1, which is characterized in that described according to the current output number
Further include later according to the step of heating system is adjusted：
According to the adjusting of heating system as a result, correcting the fuzzy control rule.
10. a kind of regulating system of heating system, which is characterized in that including：
Acquisition module, the floor data for obtaining current system in real time；
Computing module, for present input data error and present input data variation to be calculated according to the floor data
Rate；
It is blurred module, the fuzzy subset for searching corresponding present input data error according to present input data error；
It is additionally operable to search the fuzzy subset of corresponding present input data change rate according to present input data change rate；
Fuzzy rule module, for according to the fuzzy subset of present input data error and the mould of present input data change rate
Paste subset searches the fuzzy subset of corresponding current output data by fuzzy control rule；
Ambiguity solution module, for according to present input data error, present input data change rate and current output data
Fuzzy subset carries out ambiguity solution operation, obtains current output data；
Adjustment module, for the heating system to be adjusted according to the current output data.
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