CN115302630B - Concrete mortar stirring control method - Google Patents
Concrete mortar stirring control method Download PDFInfo
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- CN115302630B CN115302630B CN202211219362.0A CN202211219362A CN115302630B CN 115302630 B CN115302630 B CN 115302630B CN 202211219362 A CN202211219362 A CN 202211219362A CN 115302630 B CN115302630 B CN 115302630B
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B28—WORKING CEMENT, CLAY, OR STONE
- B28C—PREPARING CLAY; PRODUCING MIXTURES CONTAINING CLAY OR CEMENTITIOUS MATERIAL, e.g. PLASTER
- B28C7/00—Controlling the operation of apparatus for producing mixtures of clay or cement with other substances; Supplying or proportioning the ingredients for mixing clay or cement with other substances; Discharging the mixture
- B28C7/02—Controlling the operation of the mixing
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B28—WORKING CEMENT, CLAY, OR STONE
- B28C—PREPARING CLAY; PRODUCING MIXTURES CONTAINING CLAY OR CEMENTITIOUS MATERIAL, e.g. PLASTER
- B28C7/00—Controlling the operation of apparatus for producing mixtures of clay or cement with other substances; Supplying or proportioning the ingredients for mixing clay or cement with other substances; Discharging the mixture
- B28C7/04—Supplying or proportioning the ingredients
- B28C7/0404—Proportioning
- B28C7/0418—Proportioning control systems therefor
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- 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
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
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Abstract
The invention relates to the field of mixing, and provides a concrete mortar stirring control method, which comprises the following steps: acquiring an input value and a signal deviation of a signal at each moment in a historical time period of the stirring equipment; obtaining a predicted signal deviation at each moment; acquiring the chaos degree of signal deviation in each sub-time period; obtaining the effect value of the signal deviation of each sub-time period; determining a boundary value of a signal deviation membership function; determining a signal deviation membership function; determining a boundary value of a signal deviation adjustment quantity membership function; determining a signal deviation adjustment quantity membership function; obtaining a signal adjustment quantity corresponding to the signal deviation at the current moment; and adjusting the input value of the current time signal of the stirring equipment according to the signal adjustment amount corresponding to the current time signal deviation. The invention has high adjusting efficiency and is easy to realize.
Description
Technical Field
The invention relates to the field of mixing, in particular to a concrete mortar stirring control method.
Background
With the development of the construction industry in China, the demand on concrete is continuously increased, and the development of the concrete industry is stimulated. The production quality of concrete is extremely important to the quality of concrete engineering, the production quality of concrete mainly depends on the proportion of raw materials and the control of a mortar stirring process, and the proportion of the raw materials is generally obtained through strict experimental data, so the quality of the concrete is mainly influenced by the stirring quality of the concrete mortar in production.
In modern mechanized production, the stirring equipment is controlled by a main control system, but in the actual production process, a deviation exists between a target signal of the equipment and an actual output signal of the equipment, so that the control parameters of the equipment are changed, and the stirring quality of the concrete mortar is influenced. In order to better control the concrete mortar mixing, the signal deviation needs to be corrected in the actual production, namely, the actual signal deviation is corrected by adjusting the input signal of the main control system. The existing deviation signal adjustment is mainly PID controller adjustment, but the PID controller adjustment is an iterative adjustment and needs to manually set adjustment parameters, so that the adjustment efficiency is not high. Therefore, the invention provides a concrete mortar stirring control method.
Disclosure of Invention
The invention provides a concrete mortar mixing control method, which aims to solve the problem of low signal adjustment efficiency in the prior art.
The invention relates to a concrete mortar stirring control method, which adopts the following technical scheme:
acquiring an input value, an actual output value and a target value of a signal at each moment in a historical time period of the stirring equipment; acquiring the signal deviation of each moment according to the actual output value and the target value of the signal at each moment; obtaining a predicted signal deviation at each moment;
acquiring sub-time periods with different lengths in a historical time period, and acquiring the chaos degree of the signal deviation in each sub-time period according to the signal deviation at each moment in each sub-time period and the predicted signal deviation at each moment;
obtaining the effect value of the signal deviation of each sub-time period according to the length of each sub-time period and the chaos degree of the signal deviation in the sub-time period;
selecting a sub-time period corresponding to the maximum effect value from all the obtained effect values as an optimal sub-time period, taking the maximum absolute value of the signal deviation in the optimal sub-time period as the maximum degree of the signal deviation, and determining the boundary value of the signal deviation membership function according to the maximum degree of the signal deviation;
determining a signal deviation membership function according to the boundary value of the signal deviation membership function and a standard membership function model;
determining a boundary value of a signal deviation adjustment quantity membership function according to the input value of the signal in the optimal sub-time period, the actual output value of the signal at all moments and the signal deviation maximum degree; the number of the boundary values of the signal deviation adjustment quantity membership function is equal to the number of the boundary values of the signal deviation membership function;
determining a signal deviation adjustment quantity membership function according to the demarcation value of the signal deviation adjustment quantity membership function and the standard membership function model;
acquiring the current time signal deviation by using the actual output value and the target value of the current time signal, calculating the membership degree of the current time signal deviation in the signal deviation membership function, and calculating the signal adjustment quantity corresponding to the current time signal deviation in the signal deviation adjustment quantity membership function according to the acquired membership degree of the current time signal deviation;
and adjusting the input value of the current time signal of the stirring equipment according to the signal adjustment amount corresponding to the current time signal deviation.
Further, in the concrete mortar mixing control method, the boundary values of the signal deviation membership function are respectively the maximum degree of signal deviation, the maximum degree of signal deviation which is one-half times, zero, the opposite number of the maximum degree of signal deviation which is one-half times and the opposite number of the maximum degree of signal deviation.
Furthermore, in the concrete mortar mixing control method, the number of the boundary values of the signal deviation adjustment quantity membership function is 5, and the number of the boundary values comprises a first boundary value, a second boundary value, a third boundary value, a fourth boundary value and a fifth boundary value;
the first, second, third, fourth and fifth boundary values are obtained according to the following steps:
obtaining the difference value between the signal input value in the optimal sub-time period and the average value of the actual output values of the signals at all moments, and calculating the ratio of the difference value to the average value of the actual output values of the signals at all moments in the optimal sub-time period;
calculating the product of the sum of the obtained ratio and 1 and the maximum degree of the signal deviation, wherein the product is a fifth boundary value of the membership function of the signal deviation adjustment quantity;
the fourth threshold is one half of the fifth threshold;
the third boundary value is zero;
the second boundary value is the inverse of the fourth boundary value;
the first cut-off value is the inverse of the fifth cut-off value.
Further, in the concrete mortar mixing control method, the expression of the effect value of the signal deviation of each sub-period is as follows:
in the formula (I), the compound is shown in the specification,
represents a time length of
The effect value of the sub-period signal deviation of (a),
indicates the time length of the sub-period,
represents a time length of
The degree of misordering of the signal deviations within the sub-periods of time.
Further, the method for controlling the mixing of the concrete mortar to obtain the degree of disorder of the signal deviation in each sub-period comprises the following steps:
acquiring a difference value of signal deviation between each moment and the previous moment in each sub-time period, and taking the difference value as a first difference value;
acquiring a difference value between the signal deviation of each moment and the predicted signal deviation of the moment in each sub-time period, and taking the difference value as a second difference value; and obtaining the chaos degree of the signal deviation in each sub-period through all the first difference values and all the second difference values in each sub-period.
Further, in the concrete mortar mixing control method, the expression of the degree of disorder of the signal deviation in each sub-period is as follows:
in the formula (I), the compound is shown in the specification,
represents a time length of
The standard deviation of the signal deviation in the sub-period of time,
represents a time length of
Within a sub-period of time
At the time of day, the user may,
represents a time length of
Within a sub-period of time
Time and first
The difference in the deviation of the time of day signals,
represents a time length of
Within a sub-period of time
Deviation of time signal from first
The time of day predicts the difference in signal deviation.
Further, in the concrete mortar mixing control method, the signal deviation at each moment is the difference between the actual output value and the target value of the signal at each moment.
Further, the method for controlling the mixing of the concrete mortar, after the signal adjustment amount corresponding to the signal deviation at the current time is obtained, further includes:
and the signal adjustment quantity corresponding to the signal deviation at the current moment is refined to obtain the precise adjustment quantity corresponding to the signal deviation at the current moment.
Further, in the concrete mortar mixing control method, the prediction signal deviation at each moment is obtained by a kalman filter algorithm.
The invention has the beneficial effects that: the method determines the optimal time length so as to obtain the maximum degree of signal deviation and obtain a membership function of the signal deviation; the method has the advantages that the membership function of the signal deviation adjustment quantity is obtained through the signal information in the optimal time length time period, and then the adjustment quantity of the signal input is obtained through the membership function of the signal deviation and the membership function of the signal deviation adjustment quantity; meanwhile, in the fuzzy control process, the influence of various interferences and parameter changes on the control effect is weakened, the stability is high, and the method is simple and easy to implement.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a schematic flow chart illustrating an embodiment of a concrete mortar mixing control method according to the present invention;
FIG. 2 is a schematic diagram of a deviation signal membership function;
FIG. 3 is a schematic diagram of a membership function of a signal offset adjustment.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1
An embodiment of a concrete mortar mixing control method according to the present invention, as shown in fig. 1, includes:
the main purposes of the invention are: and performing fuzzy control on the deviation of the signal by using a fuzzy control method, determining different membership degrees according to the characteristics of data, and finally, performing precision on the fuzzy control to obtain the final adjustment quantity of the signal.
The present invention is directed to the following scenarios: in the concrete mortar stirring process, the main control system inputs control parameters of equipment so as to control the equipment. However, in the actual process, the actual output signal of the device deviates from the required target signal, and the existence of the signal deviation has a great influence on the operation of the device, so that the deviation signal needs to be corrected according to the actual requirement, namely, the input signal needs to be adjusted. Therefore, in the invention, the signal deviation is adjusted by a fuzzy control method, and the accuracy of the parameters of the concrete mortar stirring equipment is ensured.
101. Acquiring an input value, an actual output value and a target value of a signal at each moment in a historical time period of the stirring equipment; acquiring the signal deviation of each moment according to the actual output value and the target value of the signal at each moment; the predicted signal deviation at each time instant is obtained.
For mortar mixing of concrete, the parameters for mixing production are generally obtained by rigorous experiments. And inputting the parameters obtained by the experiment by a main control system of the stirring equipment to control the stirring equipment.
However, the actual output signal of the general equipment always has a deviation from the target signal, and in order to adjust the deviation, when the equipment runs, the actual output signal of the equipment running, the input signal of the main control system and the target signal are collected, the signal deviation at each moment is obtained according to the actual output value and the target value of the signal at each moment, the predicted signal deviation at each moment is obtained, and the signal deviation is adjusted through subsequent analysis. In this embodiment, the input and output signals are the rotation speed of the stirring device.
During operation of the concrete mixing equipment, deviation always exists between an input signal of the main control system and an actual output signal of the equipment, and the larger the signal deviation is, the more the control parameter of the actual equipment deviates, the more the mixing of concrete mortar is influenced, namely the quality of concrete is influenced. According to the embodiment, the deviation between the actual output signal and the target signal of the equipment is adjusted through a fuzzy control principle, so that the concrete mortar is stirred more according with actual requirements.
For the stirring control of concrete mortar, the current production parameters are all that raw materials are detected firstly, then relevant parameters are determined through experiments, and then the relevant parameters of the stirring equipment are controlled in real time through the main control equipment.
The target signal set by the current master control system is known as
When the actual output signal of the device is
The difference between the actual output signal of the device and the target signal of the device, which is expressed as the deviation of the actual output signal of the device from the target signal set by the system, is due to the transmission of the signal and the corresponding delay of the device
I.e. by
At this time, according to the deviation of the signal
Conditioning the input signal to make the output signal more connectedClose to the target signal.
For differences between the device output signal and the target signal, adjustments need to be made to the input of the original signal, for differences between the device output signal and the target signal
Indicating that the current signal input is too high, the input signal needs to be reduced, an
The larger the input signal is, the larger the degree of reduction of the input signal is;
indicating that the current input signal is too low, that an increase in the input signal is required, an
The smaller the input signal, the greater the degree of increase. At this time, adjusting the current deviation signal according to the magnitude of the deviation signal may cause too slow response time or over-adjustment, so that the signal may oscillate.
In this embodiment, the deviation of the current signal is adjusted by fuzzy control. For general fuzzy control, firstly, a regulating basis value, namely a signal deviation, needs to be obtained; fuzzification is carried out on the deviation of the signals, and the membership function of the deviation signals is determined mainly through the characteristics of the deviation signals and the target signals, so that the membership relation of the deviation signals is obtained; then, reasoning the adjusting mode of the deviation signal according to the membership of the deviation signal; and finally, carrying out fuzzy control on the adjustment of the deviation signal according to the membership and the adjustment mode, and further realizing the precise adjustment of the deviation signal, namely the precise control of the input signal.
Various variables in the fuzzy control system do not need accurate mathematical models, so the fuzzy control system is simple to operate and easy to realize, and meanwhile, the control system has strong adaptability; in the control process, the influence of various interferences and parameter changes on the control effect is greatly weakened, so that the stability of the control effect is high.
Based on the deviation signal
Determines the adjustment of the input signal, so that first of all the deviation signal is adjusted
Fuzzification processing is carried out, namely the degree of the deviation signal is judged, at this moment, the general deviation signal is considered to be divided into { negative large, negative small, zero, positive small, positive large }, and the corresponding numerical value is represented as { -B, -A,0, A, B }.
Then, the membership relationship of different deviation signals is determined, and in this embodiment, the deviation signals are fuzzified by using the membership function shown in fig. 2: the horizontal axis in fig. 2 represents signal deviation
And the vertical axis represents the degree of membership.
At this time, the signal deviation for each time
There may be a certain difference, so for the membership degree boundary value { -B, -a,0, a, B } of the deviation signal, the deviation of the signal at different time is different, and different deviation signals need to calculate their membership degree in the same membership degree function, so it is necessary to obtain the most accurate membership degree function in a time period, i.e. calculate the membership degree function boundary value.
At this time, the following relationship exists: the statistical time period of the deviation signal is too short, the data is too unilateral, the time period is too long, the response time of the system is too long, and the signal is not timely adjusted, so that the optimal time period needs to be determined according to the characteristics of the deviation signal value.
102. And acquiring sub-time periods with different lengths in the historical time period, and acquiring the chaos degree of the signal deviation in each sub-time period according to the signal deviation at each moment in each sub-time period and the predicted signal deviation at each moment.
The signal deviation at different time instants is expressed as
Setting the maximum adjustment time of the system at the same time
In a length of
In a time period of time, obtaining a corresponding signal deviation
Analysis of
Within a period of time
Obtaining the predicted value of the signal deviation at each moment by using Kalman filtering algorithm
Determining the chaos degree of the signal deviation in the current time period through the relationship between the predicted value and the actual value:
in the formula (I), the compound is shown in the specification,
the length of the current time period is indicated,
is less than
，
Denotes the first
Deviation of time signal from first
The difference in the deviation of the time of day signals,
the greater the value of the difference mean, which represents the signal deviation at all times, the more unstable the value representing the current signal deviation,
indicating a period of time
Inner first
The difference between the actual value of the time signal deviation and the predicted value,
the larger the signal deviation is, the more chaotic the current signal deviation is, the more unstable the difference of the deviation signal is, the Kalman filtering can realize the functions of estimating and predicting the real-time running state, and has strong anti-noise interference capability, thereby accurately predicting the signal.
Indicating a period of time
The standard deviation of the internal signal,
the larger the float representing the current signal deviation, the more chaotic the current signal deviation is reflected.
Indicating the degree of misordering of the signal deviations in the current time segment. For deviation informationIn the membership degree judgment of the number, the larger the disorder degree of the signal deviation is, the lower the reliability of judging the membership relation boundary according to the value of the signal deviation is.
103. And obtaining the effect value of the signal deviation of each sub-time period through the length of each sub-time period and the chaos degree of the signal deviation in the sub-time period.
Generally, in the determination of the degree of signal deviation, the result is more reliable as the amount of data to be acquired increases, but the time taken to react to the system increases as the amount of data increases, and therefore, it is necessary to maximally reflect the desired signal deviation in the acquisition of the degree of signal deviation in as little time as possible. At this time, for time periods with different lengths, the shorter the time period is, the smaller the degree of confusion of the signal deviation is, it means that the judgment effect of the current time period length on the signal deviation value is better, that is, the membership grade boundary value of the signal deviation is better, and the effect of the signal deviation of the time periods with different lengths at this time is represented as:
in the formula (I), the compound is shown in the specification,
indicating the degree of misordering of the signal deviations in the current time period,
the greater the degree of disorder representing the signal deviation, the lower the confidence of the currently obtained signal deviation value, and therefore the lower the accuracy of the obtained membership grade boundary value,
indicating the length of the time period during which signal deviation data is currently obtained,
the larger, the longer the period of data acquisition, the lower the response time of the system,reducing the control efficiency of the system.
Indicating the effect of the signal deviation of the current time segment, i.e. the effect of the signal deviation of the judgment of the current time segment,
the larger, the greater the degree of misordering of the data obtained,
the smaller and the same time
The larger, the longer the response time,
the smaller.
104. And selecting a sub-time period corresponding to the maximum effect value from all the obtained effect values as an optimal sub-time period, taking the maximum absolute value of the signal deviation in the optimal sub-time period as the maximum degree of the signal deviation, and determining the boundary value of the signal deviation membership function according to the maximum degree of the signal deviation.
The effect of judging the signal deviation is obtained in time periods with different lengths, and the time period is
At maximum, the signal deviation value obtained is most accurate. So in case of changing the length of the time period, it is calculated
Thereby obtaining an optimal time period within which the signal deviation value is obtained.
The most accurate signal deviation value is obtained according to the method, and the maximum value and the minimum value of the signal deviation value are respectively expressed as
，
From this, the maximum degree of signal deviation is obtained, expressed as:
in the formula (I), the compound is shown in the specification,
which is indicative of the maximum extent of the signal deviation,
reflecting the most stable signal deviation range obtained in the shortest possible time period
The range of the signal deviation can be reflected most accurately, and the boundary value of the membership relation of the signal deviation is judged according to the range of the signal deviation, namely
Determining membership degree boundary values of signal deviations
And determining the signal deviation membership grade boundary value as follows:
determining the membership grade boundary value of the signal deviation according to the range of the signal deviation, namely the signal deviation reaches the maximum degree of the currently judged signal deviation
At this time, the signal deviation is considered to be large, so that the membership grade boundary value with large signal deviation is set as
I.e. by
(ii) a Then setting up
For membership degree scores with small deviation, i.e.
. Since the direction of the signal deviation is random, the membership degree boundary value of the signal deviation is determined
，
。
105. And determining the signal deviation membership function according to the boundary value of the signal deviation membership function and the standard membership function model.
And determining the membership grade boundary value of the signal deviation through the steps so as to determine the membership function of the signal deviation and obtain the membership of different signal deviations. And then adjusting different signal deviations through different membership degrees.
106. Determining a boundary value of a signal deviation adjustment quantity membership function according to the input value of the signal in the optimal sub-time period, the actual output value of the signal at all moments and the signal deviation maximum degree; and the number of the boundary values of the signal deviation adjustment quantity membership function is equal to the number of the boundary values of the signal deviation membership function.
When adjusting the deviation of the signal, the required input value is the deviation of the signal
The output value is the adjustment amount to the input value of the original signal. It is known that signal deviation is fuzzified to obtain different membership degrees of the deviation signal, and when the deviation signal is adjusted, the adjustment quantity also needs to be fuzzified, and a membership function in the same form is selected, as shown in fig. 3, to determine the membership degree of the adjustment quantity of the original input signal.
In fig. 3, the horizontal axis represents the adjustment amount of the signal, or referred to as the adjustment amount of the signal, and the vertical axis represents the membership degree of the adjustment amount. At this time, the boundary value of the adjustment quantity membership function needs to be obtained
Since there is a difference between the input to the signal and the actual signal output, the adjustment amount generally set differs from the deviation amount of the signal. Determining a membership grade boundary value of the signal regulating quantity according to the relation between the input signal and the output signal and the deviation of the signal:
in the formula (I), the compound is shown in the specification,
indicating the input value of the signal, which is a fixed value when the input signal is not adjusted, and which is set directly according to the actual valueOnly the actual output value of the signal is varied,
which represents the actual output value of the signal,
indicates the length of the optimal sub-period of time,
representing the maximum deviation value of the signal within the optimal sub-period,
to represent
The mean value of the actual output signal over the corresponding time period.
Representing the loss of the signal from the input to the output,
the greater the degree of adjustment to the signal deviation. For the adjustment amount of the signal, the loss of the signal needs to be considered, that is, the adjustment amount is generally larger than the actual deviation value of the current signal, when the adjustment amount is larger than the actual deviation value
Indicating the degree of signal loss during transmission, i.e.
Indicating the relationship between the deviation of the signal and the amount of signal adjustment required, again because
The range of the signal deviation is reflected to the maximum extent,
corresponding adjustment amount is
So as to set the membership grade boundary value of the signal adjustment quantity
，
At the same time, because of the randomness of the signal deviation direction, the direction of the signal deviation adjustment quantity also has a random direction, and the membership degree boundary value of the negative direction adjustment quantity is
。
107. And determining the signal deviation adjustment quantity membership function according to the boundary value of the signal deviation adjustment quantity membership function and the standard membership function model.
Through the steps, the membership function of the signal deviation adjustment quantity can be obtained, and then the membership of the signal deviation adjustment quantity is obtained.
108. And obtaining the current time signal deviation by using the actual output value and the target value of the current time signal, calculating the membership degree of the current time signal deviation in the signal deviation membership function, and calculating the signal adjustment quantity corresponding to the current time signal deviation in the signal deviation adjustment quantity membership function according to the obtained membership degree of the current time signal deviation.
The membership grade boundary values of the signal deviation and the signal deviation adjustment quantity are determined according to the actual signal deviation value, so that the self-adaptive acquisition of the membership grade between different signal deviations is realized, the membership grade of all deviation signals can more accurately correspond to the membership grade of the deviation signal adjustment quantity, and the fuzzification control of corresponding variables is more accurately realized.
After the membership degree of the adjustment quantity is obtained, the membership relation of the adjustment quantity needs to be inferred according to the membership relation of the signal deviation.
When the signal deviation is-B, the signal adjustment amount is-B, namely the input of the signal is greatly reduced;
when the signal deviation is-A, the signal adjustment amount is-a, namely the input of the signal is reduced slightly;
when the signal deviation is 0, the signal adjustment amount is 0, namely the signal is not adjusted;
when the signal deviation is A, the signal adjustment amount is a, namely the input of the signal is slightly increased;
when the signal deviation is B, the signal adjustment amount is B, namely the input of the signal is greatly increased;
by the method, signal adjustment modes corresponding to different signal deviations are obtained.
109. And adjusting the input value of the current time signal of the stirring equipment according to the signal adjustment amount corresponding to the current time signal deviation.
The above steps obtain signal adjustment modes corresponding to different signal deviations, but the adjustment quantity is fuzzified, so that a specific adjustment quantity value cannot be determined, and therefore, the adjustment quantity needs to be refined to obtain the refined fuzzy output corresponding to different signal deviations.
For the precise fuzzy output in the fuzzy control, the output can be completed by adopting the existing precise fuzzy output tool such as MATLAB fuzzy control box.
During the concrete mortar mixing process, the loss of signals is real-time and can be changed continuously, so that the adjustment of the signal deviation needs to be carried out in real time.
And in the running process of the equipment, obtaining the signal deviation in real time, and obtaining the signal input adjustment quantity of the main control system in real time according to the fuzzy control method, thereby ensuring the accuracy of the running parameters of the equipment to the maximum extent and realizing the control of concrete mortar stirring.
The method determines the optimal time length so as to obtain the maximum degree of signal deviation and obtain a membership function of the signal deviation; the method has the advantages that the membership function of the signal deviation adjustment quantity is obtained through the signal information in the optimal time length time period, and then the adjustment quantity of the signal input is obtained through the membership function of the signal deviation and the membership function of the signal deviation adjustment quantity; meanwhile, in the fuzzy control process, the influence of various interferences and parameter changes on the control effect is weakened, the stability is high, and the method is simple and easy to implement.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and should not be taken as limiting the scope of the present invention, which is intended to cover any modifications, equivalents, improvements, etc. within the spirit and scope of the present invention.
Claims (4)
1. A concrete mortar mixing control method is characterized by comprising the following steps:
acquiring an input value, an actual output value and a target value of a signal at each moment in a historical time period of the stirring equipment; acquiring the signal deviation of each moment according to the actual output value and the target value of the signal at each moment; obtaining a predicted signal deviation at each moment;
acquiring sub-time periods with different lengths in a historical time period, and acquiring the chaos degree of the signal deviation in each sub-time period according to the signal deviation at each moment in each sub-time period and the predicted signal deviation at each moment;
obtaining the effect value of the signal deviation of each sub-time period according to the length of each sub-time period and the chaos degree of the signal deviation in the sub-time period;
selecting a sub-time period corresponding to the maximum effect value from all the obtained effect values as an optimal sub-time period, taking the maximum absolute value of the signal deviation in the optimal sub-time period as the maximum degree of the signal deviation, and determining the boundary value of the signal deviation membership function according to the maximum degree of the signal deviation;
determining a signal deviation membership function according to the boundary value of the signal deviation membership function and a standard membership function model;
determining a boundary value of a signal deviation adjustment quantity membership function according to the input value of the signal in the optimal sub-time period, the actual output value of the signal at all moments and the signal deviation maximum degree; the number of the boundary values of the signal deviation adjustment quantity membership function is equal to the number of the boundary values of the signal deviation membership function;
determining a signal deviation adjustment quantity membership function according to the boundary value of the signal deviation adjustment quantity membership function and the standard membership function model;
acquiring the current time signal deviation by using the actual output value and the target value of the current time signal, calculating the membership degree of the current time signal deviation in the signal deviation membership function, and calculating the signal adjustment quantity corresponding to the current time signal deviation in the signal deviation adjustment quantity membership function according to the acquired membership degree of the current time signal deviation;
adjusting the input value of the current moment signal of the stirring equipment according to the signal adjustment amount corresponding to the current moment signal deviation; the expression of the effect value of the signal deviation per sub-period is:
in the formula (I), the compound is shown in the specification,
represents a time length of
The effect value of the sub-period signal deviation of (a),
indicates the time length of the sub-period,
represents a time length of
The degree of disorder of the signal deviation within the sub-period of time;
the method for obtaining the chaos degree of the signal deviation in each sub-time period comprises the following steps:
acquiring a difference value of signal deviation of each moment and the previous moment in each sub-time period, and taking the difference value as a first difference value;
acquiring a difference value between the signal deviation of each moment and the predicted signal deviation of the moment in each sub-time period, and taking the difference value as a second difference value; obtaining the chaos degree of the signal deviation in each sub-time period through all the first difference values and all the second difference values in each sub-time period;
the expression for the degree of misordering of the signal deviation in each sub-period is:
in the formula (I), the compound is shown in the specification,
represents a time length of
The standard deviation of the signal deviation within the sub-period of time,
represents a time length of
Within a sub-period of time of
At the time of day, the user may,
represents a time length of
Within a sub-period of time of
Time of day and
the difference in the deviation of the time of day signals,
represents a time length of
Within a sub-period of time of
Deviation of time signal from first
A difference in time prediction signal deviation;
the boundary values of the signal deviation membership function are respectively the maximum degree of signal deviation, the maximum degree of signal deviation which is one half times, the inverse number of the maximum degree of signal deviation which is zero and one half times and the inverse number of the maximum degree of signal deviation;
the number of the boundary values of the membership function of the signal deviation adjustment quantity is 5, and the number of the boundary values comprises a first boundary value, a second boundary value, a third boundary value, a fourth boundary value and a fifth boundary value;
the first, second, third, fourth and fifth boundary values are obtained according to the following steps:
obtaining the difference value between the signal input value in the optimal sub-time period and the average value of the actual output values of the signals at all moments, and calculating the ratio of the difference value to the average value of the actual output values of the signals at all moments in the optimal sub-time period;
calculating the product of the sum of the obtained ratio and 1 and the maximum degree of the signal deviation, wherein the product is a fifth boundary value of the membership function of the signal deviation adjustment quantity;
the fourth threshold is one half of the fifth threshold;
the third boundary value is zero;
the second boundary value is the inverse of the fourth boundary value;
the first boundary value is the inverse of the fifth boundary value;
the standard membership function model is a triangular membership function.
2. The method for controlling mixing of concrete mortar according to claim 1, wherein the signal deviation at each time is a difference between an actual output value of the signal at each time and a target value.
3. The method for controlling mixing of concrete mortar according to claim 1, wherein after the signal adjustment amount corresponding to the signal deviation at the current time is obtained, the method further comprises:
and the signal adjustment quantity corresponding to the signal deviation at the current moment is refined to obtain the precise adjustment quantity corresponding to the signal deviation at the current moment.
4. The method according to claim 1, wherein the predicted signal deviation at each time is obtained by a kalman filter algorithm.
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