CN111459033A - Grey prediction fuzzy PID control method and equipment for water and fertilizer irrigation - Google Patents
Grey prediction fuzzy PID control method and equipment for water and fertilizer irrigation Download PDFInfo
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- 239000003337 fertilizer Substances 0.000 title claims abstract description 82
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- A01C—PLANTING; SOWING; FERTILISING
- A01C23/00—Distributing devices specially adapted for liquid manure or other fertilising liquid, including ammonia, e.g. transport tanks or sprinkling wagons
- A01C23/04—Distributing under pressure; Distributing mud; Adaptation of watering systems for fertilising-liquids
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Abstract
The invention relates to the technical field of water and fertilizer irrigation control methods, and discloses a gray prediction fuzzy PID control method for water and fertilizer precision irrigation, which comprises the following steps: s1, combining a gray prediction control method, a fuzzy logic control method and a PID control method; s2, developing a series automatic irrigation control system aiming at different irrigation modes and control objects; s3, the precise control irrigation of water and fertilizer is realized by the serial automatic irrigation control system aiming at different irrigation modes adopted by different plots and different crops. The gray prediction fuzzy PID control method for water and fertilizer precision irrigation provided by the technical scheme of the invention can realize precision control of water and fertilizer irrigation.
Description
Technical Field
The invention relates to the technical field of water and fertilizer irrigation control methods, in particular to a gray prediction fuzzy PID control method and device for water and fertilizer irrigation.
Background
In order to ensure the normal growth of crops and obtain high and stable yield, the crops must be supplied with sufficient moisture. Under natural conditions, the water requirement of crops cannot be met due to insufficient precipitation or uneven distribution. Therefore, irrigation must be done manually to compensate for the lack of natural rainfall. With the rapid development of science and technology, many places begin to implement automatic irrigation of water and fertilizer in order to reduce manpower.
In the process of carrying out automatic water and fertilizer irrigation, in order to realize automatic irrigation, a power source is generally required to be controlled so as to open a control object, and then water and fertilizer are sprayed out to realize water and fertilizer irrigation.
However, since the irrigation methods are different, different irrigation methods and control objects are controlled by the same control method, which easily causes deviation between the actually sprayed water and fertilizer and the theoretically sprayed water and fertilizer, and thus, the water and fertilizer irrigation cannot be precisely controlled.
Disclosure of Invention
The invention aims to provide a gray prediction fuzzy PID control method for water and fertilizer precision irrigation, and aims to solve the problem that water and fertilizer irrigation cannot be precisely controlled in the prior art.
The invention is realized in this way, a grey prediction fuzzy PID control method for irrigation of water and fertilizer quality, comprising the following steps:
s1, combining a gray prediction control method, a fuzzy logic control method and a PID control method;
s2, developing a series automatic irrigation control system aiming at different irrigation modes and control objects;
s3, the precise control irrigation of water and fertilizer is realized by the serial automatic irrigation control system aiming at different irrigation modes adopted by different plots and different crops.
Optionally, in the gray prediction control method:
the grey model is a dynamic model consisting of a set of grey differential equations, and a GM (1,1) model of the grey model is established by the following modeling process:
1)X(0)for the original non-negative data sequence: x(0)＝[x(0)(1),x(0)(2),...,x(0)(n)]To X(0)Performing an accumulation generation operation to obtain X(0)1-AGO sequence of (A), X(1)＝[x(1)(1),x(1)(2),...,x(1)(n)]Wherein
2) For sequence X(1)Performing adjacent mean value generation operation to obtain X(1)Is generated by the adjacent mean generation sequence Z(1)Wherein z is(1)(k)＝0.5[x(1)(k)+x(1)(k-1)],k＝1,2,...,n；
3) The gray differential equation for GM (1,1) can be obtained: x is the number of(0)(k)+az(1)(k) U, and the corresponding whitening equation:
wherein a is called a development coefficient, and u is a gray effect amount;
4) solving a and u: using minimumTwo multiplication
Wherein
Yn＝[x(0)(2) x(0)(3) … x(0)(n)]T(ii) a The solution of the whitening equation is
The time response sequence of the corresponding gray differential equation is: i.e. the value at time k
5) To the sequence
Performing an accumulation and subtraction operation, i.e. performing the inverse operation of the accumulation and generation, and recording the operation as IAGO, to obtain a prediction sequence
Wherein
The predicted value at the time k + d is:
d is the system delay (lag) time, which can be measured according to field experiments.
Optionally, on the basis of a common PID controller, a gray prediction control function and a fuzzy logic control function are added, and a self-adaptive adjustment factor x is introduced at the output end of the gray prediction controller, i.e., at the prediction error, to form a new self-adaptive gray prediction fuzzy PID controller.
Optionally, a gray prediction fuzzy controller established by combining a gray prediction control method and a fuzzy logic control method is adopted, the soil humidity signal input by the multi-channel sensor is subjected to data processing to obtain data reflecting the soil humidity as input, and the input value is compared with a standard value to obtain an input deviation e; if e is greater than 0, the soil humidity is greater than the optimal humidity, namely the soil is not lack of water, and the system does not output irrigation signals; and if e is less than 0, carrying out fuzzy decision by using the deviation e and the fuzzy control rule R according to the inferred synthesis rule to obtain a fuzzy control quantity u, namely u is e R, and then converting the fuzzy control quantity u into an accurate value to control the execution mechanism.
Optionally, the irrigation mode comprises drip irrigation, sprinkling irrigation and ground irrigation.
Optionally, the control object includes an electromagnetic valve, a variable frequency motor, and an electric gate.
The invention also provides grey prediction fuzzy PID control equipment for water and fertilizer irrigation, which operates according to the grey prediction fuzzy PID control method for water and fertilizer irrigation, and comprises the following steps:
an automatic irrigation control system;
the irrigation system is used for carrying out water and fertilizer irrigation on different plots and different crops; the serial automatic irrigation control system controls the irrigation system to realize precise control irrigation of water and fertilizer.
Compared with the prior art, the gray prediction fuzzy PID control method for water and fertilizer precision irrigation provided by the invention can meet the control requirements in different occasions by adopting a specific automatic irrigation control system according to different irrigation modes adopted by different plots and different crops, and realizes precision control irrigation of water and fertilizer. The problem of among the prior art, can't the smart volume control water, fertile irrigation is solved.
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FIG. 1 is a flow chart diagram of a gray prediction fuzzy PID control method for irrigation of water and fertilizer concentrate provided by the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The following describes the implementation of the present invention in detail with reference to specific embodiments.
The same or similar reference numerals in the drawings of the present embodiment correspond to the same or similar components; in the description of the present invention, it should be understood that if there is an orientation or positional relationship indicated by the terms "upper", "lower", "left", "right", etc. based on the orientation or positional relationship shown in the drawings, it is only for convenience of describing the present invention and simplifying the description, but it is not intended to indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation, and be operated, and therefore, the terms describing the positional relationship in the drawings are only used for illustrative purposes and are not to be construed as limiting the present patent, and the specific meaning of the terms may be understood by those skilled in the art according to specific circumstances.
The gray prediction fuzzy PID control method for water and fertilizer precision irrigation can realize precision control of water and fertilizer irrigation.
Referring to fig. 1, a preferred embodiment of the present invention is shown.
In the embodiment of the invention, the gray prediction fuzzy PID control method for irrigation of water and fertilizer quality comprises the following steps:
s1, combining a gray prediction control method, a fuzzy logic control method and a PID control method;
s2, developing a series automatic irrigation control system aiming at different irrigation modes and control objects;
s3, the precise control irrigation of water and fertilizer is realized by the serial automatic irrigation control system aiming at different irrigation modes adopted by different plots and different crops.
The gray prediction control method, the fuzzy logic control method and the PID control method can be combined in pairs or combined in a unified way according to requirements.
The PID control method has the characteristics of good robustness, simple structure, easy realization and the like; the gray prediction control method is a novel control method combining a control theory and a gray system theory, and has the advantages of low requirement on model precision, less online estimation parameters, convenience in calculation, good control comprehensive effect and the like; because the establishment of the crop irrigation model is influenced by a series of factors such as different crop growth laws, seasons, climatic environments and the like, the establishment of the irrigation model adapting to the crop growth laws is difficult, the fuzzy control does not depend on a mathematical model accurate to the system, and the model is based on the summary of long-term irrigation experience and is continuously updated through learning, so that the model has intelligence and self-learning.
In the embodiment, the specific automatic irrigation control system is adopted according to different irrigation modes adopted by different plots and different crops, so that the control requirements of different occasions can be met, the precise control irrigation of water and fertilizer is realized, and the excellent growth of the crops is ensured. In addition, the frequency conversion control technology is applied to realize centralized or decentralized control of regional and multi-path frequency conversion, and realize the control functions of manual (remote telephone, wireless remote control, remote network), automatic and the like of the irrigation system.
Referring to fig. 1, in an embodiment of the invention, the gray prediction control method includes:
the grey model is a dynamic model consisting of a group of grey differential equations, and a grey model GM (1,1) model is established, wherein the modeling process is as follows:
1)X(0)for the original non-negative data sequence: x(0)＝[x(0)(1),x(0)(2),...,x(0)(n)]To X(0)Performing an accumulation generation operation to obtain X(0)1-AGO sequence of (A), X(1)＝[x(1)(1),x(1)(2),...,x(1)(n)]Wherein
2) For sequence X(1)Performing adjacent mean value generation operation to obtain X(1)Is generated by the adjacent mean generation sequence Z(1)Wherein z is(1)(k)＝0.5[x(1)(k)+x(1)(k-1)],k＝1,2,...,n；
3) The gray differential equation for GM (1,1) can be obtained: x is the number of(0)(k)+az(1)(k) U, and the corresponding whitening equation:
wherein a is called a development coefficient, and u is a gray effect amount;
4) solving a and u: using least squares
Wherein
Yn＝[x(0)(2) x(0)(3) … x(0)(n)]T(ii) a The solution of the whitening equation is
The time response sequence of the corresponding gray differential equation is: i.e. the value at time k
5) To the sequence
Performing an accumulation and subtraction operation, i.e. performing the inverse operation of the accumulation and generation, and recording the operation as IAGO, to obtain a prediction sequence
Wherein
The predicted value at the time k + d is:
d is the system delay (lag) time, which can be measured according to field experiments.
The gray model is a dynamic model consisting of a set of gray differential equations, denoted as GM (n, h), where: n is the order of the differential equation, and h is the number of variables. In the embodiment of the invention, the GM (1,1) model which is most widely applied in the gray model is adopted.
The gray prediction control method combining the gray system theory and the control theory is adopted, the system development rule is sought through the extraction of the system behavior data series, the future behavior of the system is predicted according to the rule, and the corresponding control decision is determined according to the future behavior trend of the system for pre-control, so that the prevention in the bud and the timely control can be realized. In addition, the system output error predicted in advance and the current output error of the system can be combined to form a system comprehensive error, an actual error item in the traditional feedback control method is replaced, and accurate and precise control of water and fertilizer is realized.
Referring to fig. 1, in an embodiment of the present invention, a gray prediction control function and a fuzzy logic control function are added on the basis of a general PID controller, and an adaptive adjustment factor x is introduced into an output end of the gray prediction controller, i.e., a prediction error, to form a new self-adjusting gray prediction fuzzy PID controller.
That is, the three methods are combined together, and the introduced adaptive adjustment factor x can reduce the weight (proportion) of the prediction error value in the controller when the prediction accuracy of the gray prediction GM model is not high, and increase the weight (proportion) of the prediction error value in the controller when the prediction accuracy of the gray prediction GM model is high, so as to reduce the influence of the error caused by prediction on the system and improve the accuracy of control.
Referring to fig. 1, in an embodiment of the present invention, a gray prediction fuzzy controller is established by combining a gray prediction control method and a fuzzy logic control method, soil humidity signals input by multiple sensors are subjected to data processing to obtain data reflecting soil humidity as input, and an input value is compared with a standard value to obtain an input deviation e; if e is greater than 0, the soil humidity is greater than the optimal humidity, namely the soil is not lack of water, and the system does not output irrigation signals; and if e is less than 0, carrying out fuzzy decision by using the deviation e and the fuzzy control rule R according to the inferred synthesis rule to obtain a fuzzy control quantity u, namely u is e R, and then converting the fuzzy control quantity u into an accurate value to control the execution mechanism.
The grey prediction fuzzy controller provided by the method has high control efficiency and quick operation.
Referring to fig. 1, in addition, a gray predictive control method may be combined with a PID control method to obtain a gray predictive PID control method, so as to achieve accurate and precise control of water and fertilizer.
In addition, a PID control method can be combined with a fuzzy logic control method to obtain a fuzzy PID control method, and the control method has stronger intelligence and higher running speed.
Referring to fig. 1, in an embodiment of the present invention, the irrigation method includes drip irrigation, sprinkling irrigation and ground irrigation.
Drip irrigation, namely, water is sent to the roots of crops through orifices or drippers by using a plastic pipeline for local irrigation, the water utilization rate is high, and uniform irrigation at all positions can be ensured for the land of block areas; the sprinkling irrigation is an irrigation mode that water with certain pressure is sprayed into the air by means of a water pump and a pipeline system or by utilizing the fall of a natural water source, and the water is scattered into small water drops or forms mist to fall onto plants and the ground, and the mode is not limited by the terrain; ground irrigation, namely a method for irrigating by using ground irrigation ditches, ridges or check fields, wherein the irrigation mode can be more matched with land divided into blocks.
In addition, the control objects comprise an electromagnetic valve, a variable frequency motor and an electric gate.
Therefore, aiming at different control objects and irrigation modes, the precise control of water and fertilizer can be realized through the combination of different control methods, and the excellent growth of crops is ensured.
The invention also provides an intelligent irrigation control method, which comprises the following steps:
s4, collecting the agricultural condition information of the crops; because the water and fertilizer requirement information of the crops is closely related to the agricultural condition information around the crops and the crops, the agricultural condition information needs to be comprehensively known in order to accurately acquire the water and fertilizer requirement information.
S5, calling data information of crop growth requirements; the data information is stored in a database system and contains the most suitable information of the crop surrounding and the crop itself for each growth stage of the crop, which is obtained by the past expert experience.
S6, analyzing the agricultural condition information and the data information, and diagnosing the water and fertilizer demand information of the crops; the agricultural condition information and the data information crop are compared, and further the water and fertilizer demand information can be obtained.
And S7, controlling an irrigation system to irrigate according to the water and fertilizer demand information of the crops. After the water and fertilizer requirement information of the crops is obtained, irrigation is carried out, so that the crops can meet the corresponding growth requirements.
Like this, through gathering the farming feelings information of crop, then compare with the data information of the growth demand of crop, and then reach the required water of crop, fertile information, irrigate according to water demand, fertile information afterwards, make the crop reach corresponding growth demand, so that the healthy growth of crop, this automatic irrigation method need not artifical watering, and the watering is accurate, can just reach the growth demand of crop, compare in artifical watering, more cultivate healthy, good crop, and very big reduction the manpower.
In an embodiment of the present invention, the agricultural condition information includes crop information, soil information, weather information, and environmental information.
The crop information here is the variety and growth stage of the crop, the soil information includes the PH value of the soil and nutrients contained in the soil, the weather information includes the weather conditions in the collection period, and the environmental information includes the air humidity and the air oxygen concentration around the crop.
And connecting the database system with the Internet, adding the agricultural information into the database system, and updating the data information.
Therefore, the data in the database system can be updated in time to realize automatic irrigation of new variety crops or optimize the existing data information to improve the quality of the cultivated crops.
In one embodiment of the present invention, in step S6:
dividing the land into a plurality of blocks;
analyzing the agricultural condition information and the data information of each block;
and diagnosing the water and fertilizer requirement information of the crops in each block.
That is, because the land area is wide, the agricultural condition information of different blocks has a large difference, so that each block needs to be separately collected and respectively diagnosed to obtain the water and fertilizer requirement information of each block.
In this embodiment, the block is divided into rectangular blocks, specifically, the block may be arranged in a square block, so that the block is regular in shape, and is convenient for subsequent watering with water or fertilizer.
In an embodiment of the present invention, the formula for diagnosing the crop water demand information of each block is as follows:
ETm＝Kc·ET0
in the formula, KcDifferent crops can be selected from the crop coefficient knowledge base according to the development stages of the different crops as the crop coefficients; ET0Is the reference crop evapotranspiration, in units (mm/d). Wherein the content of the first and second substances,
ET0＝[0.408Δ(Rn-G)+γ*900/(T+273)U2VPD]/[Δ+γ(1+0.34U2)]
wherein Rn is the net radiation of the surface of the crop, and the unit is (MJ.m)-2·d-1) (ii) a G is the soil heat flux in units of (MJ.m)-2·d-1) (ii) a T is the average air temperature at a height of 2m, in degrees centigrade; u2 is the average wind speed of 24h at 2m height in units (m/s); VPD is the vapor pressure difference at 2m height, in units (kPa); Δ is the slope of saturated water vapor pressure in units (kPa/. degree. C.); γ is the dry-wet bulb constant in kPa/deg.C.
In this embodiment, the water demand of the crops is obtained through the above formula, the numerical value in the above formula can be obtained through the collected agricultural condition information, and of course, in other embodiments, the water demand can be further obtained through comparison between the agricultural condition information and each data of the data information.
In addition, the agricultural condition information also comprises nutrient information of crops, the data information also comprises nutrient demand information of the crops, and the step of diagnosing the crop fertilizer demand information of each block comprises the following steps:
calling out the acquired expert decisions about nutrient information, nutrient demand information and fertilizer demand in the knowledge base;
and determining the crop fertilizer requirement information of each block according to the expert decision, the nutrient information and the nutrient requirement information.
The obtained expert decision about the nutrient information, the nutrient demand information and the fertilizer demand is that data obtained through experience in the past is a ternary function, namely the nutrient demand information-nutrient information-k fertilizer demand, a constant k is obtained, and then the nutrient information and the nutrient demand information obtained at present are combined, so that the fertilizer demand information of each block can be obtained.
Further, step S7 includes:
determining the irrigation time and flow according to the irrigation modes and the water and fertilizer requirements of different blocks;
and controlling an irrigation system according to the determined time and flow to carry out water and fertilizer irrigation.
Because its spun time of different irrigation methods is different, consequently need confirm time and the flow of irrigating respectively according to the irrigation method of difference to carry out accurate liquid manure and irrigate.
In the embodiment of the invention, when the agricultural condition information of the crops is collected, the method comprises the following steps:
monitoring crops to obtain agricultural condition information;
transmitting the agricultural information to the collector
The agricultural condition information is sorted and packaged;
the collector transmits the agricultural condition information to the server in a wired or wireless mode.
The crop monitoring method includes monitoring the crop and the crop surrounding environment, and obtaining comprehensive agricultural condition information to facilitate understanding of the growth condition of the crop. The server is a local server and is connected to the network. The server is internally provided with a database system which contains the most suitable crop surrounding and crop self information of each growth stage of crops, the information is obtained through the past expert experience, and the water and fertilizer requirement information of the crops can be obtained by comparing the crop condition information with the data information. The server is connected to the network, so that the data in the database system can be updated in time to realize automatic irrigation of new variety crops or optimization of existing data information to improve the quality of cultivated crops.
In this embodiment, the agricultural condition information obtained by monitoring the crops is transmitted to the collector in a centralized manner, then is sorted and packed by the collector, and is transmitted to the server in a centralized manner, so that the agricultural condition information obtained by monitoring is regular and uniform, and the subsequent diagnosis and analysis of the irrigation amount of water and fertilizer according to the condition of the agricultural condition information of the crops are facilitated.
In one embodiment of the invention, the agricultural condition information is sorted and packaged:
dividing a plurality of time nodes, and recording agricultural condition information of each time node;
averaging the agricultural condition information recorded by the plurality of time nodes to serve as the agricultural condition information;
and (5) sorting and packaging the agricultural condition information.
In order to avoid the inaccuracy of the measured agricultural condition information caused by accidental conditions, in the embodiment, the average value of the agricultural condition information of a plurality of time nodes is taken, further, during specific calculation, a maximum value and a minimum value can be removed, and the average value between the maximum value and the minimum value is taken, so that the accuracy of the agricultural condition information obtained through monitoring is ensured, and the water and fertilizer amount obtained through subsequent diagnosis and analysis is more accurate.
Furthermore, the interval between the divided time nodes is short, in this embodiment, the time interval is 10s, and the time interval is divided into 7 time nodes within one minute, so as to avoid the situation that the difference of the agricultural condition information is large due to the overlong time interval.
In addition, in this embodiment, it is set that the agricultural condition information is collected and transmitted at a specific time, that is, it can be preset to 7 am every day, so that the agricultural condition information is automatically collected, the water and fertilizer demand is diagnosed and analyzed, and the automatic irrigation of water and fertilizer is realized.
In an embodiment of the invention, after the step of transmitting the agricultural condition information to the server by the collector in a wired or wireless manner:
the server receives the agricultural condition information and generates feedback information;
and the server sends the feedback information to the collector.
Namely, the server and the collector are in wired or wireless bidirectional transmission, so that the accuracy of data transmission of the server and the collector is ensured.
Specifically, the step of sending the feedback information to the collector by the server includes:
and when the collector does not receive the feedback information within the preset time, monitoring the crops to obtain the agricultural condition information.
And when the collector receives the feedback information within the preset time, the collector exits the process.
Thus, the predetermined time takes into account delays in the transmission of information and the fact that the speed is too slow. The collector does not receive the feedback information within the preset time, and the transmission of the agricultural condition information is lost possibly, so that the server needs to collect and transmit the agricultural condition information again to ensure the subsequent water and fertilizer irrigation.
The invention also provides an intelligent irrigation control system which operates according to the intelligent irrigation control method and comprises the following steps:
the collection system is used for collecting the agricultural condition information of the crops;
the database system calls out data information of crop growth requirements;
the decision system analyzes the agricultural condition information and the data information and diagnoses the water and fertilizer demand information of the crops;
and the control system controls the irrigation system to irrigate according to the water and fertilizer demand information of the crops.
The collecting system comprises various monitors and a collector, the various monitors are used for collecting the agricultural condition information and transmitting the agricultural condition information to the collector, the collector and the database system are connected in a wired or wireless mode, the collector can transmit the agricultural condition information to the database system, then the water and fertilizer information is calculated through the decision-making system, finally crops are irrigated through the control system, and automatic irrigation of the water and fertilizer is achieved.
And a power supply is arranged in the collector and is a storage battery. Through the power in the collector, realize for collector and various detectors realization power supply, as required, this power can be connected in the commercial power, certainly, because the power that this embodiment provided is the battery, it can place in optional position, is convenient for remove.
In addition, the top of collector is equipped with the photovoltaic board, photovoltaic board and battery electric connection. Like this, can realize the charging to the interior power of collector through this photovoltaic board, guarantee that the collector uses in open air for a long time.
The monitor comprises a conductivity meter, an optical fiber PH meter and a plant nutrition collecting system.
The agricultural condition information which can be measured by the conductivity measuring instrument is the conductivity of the land, the optical fiber PH meter is used for measuring the agricultural condition information which is the PH value of the land, and the plant nutrition collecting system is used for measuring the agricultural condition information which is the nutrient information of the crops.
Of course, the types of the monitors of the various layers in this embodiment are not limited to the above, that is, the humidity of the air can be measured by the hygrometer, the oxygen content around the crops can be measured by the oxygen concentration meter, and in addition, the weather information can be directly obtained by connecting the server with the network, so as to obtain the subsequent water and fertilizer demand information.
In one embodiment, the monitor further comprises a camera, the camera is used for taking pictures of a farmland, the pictures are transmitted into the server through the collector, the server obtains the types of crops through retrieval and comparison, and therefore the server can carry out corresponding water and fertilizer demand diagnosis according to the types of the crops. Of course, the type of crop to be diagnosed can also be input into the server manually and actively.
And, according to needs, can select corresponding monitor to carry out corresponding monitoring through the server, like this, the collection of reducible unnecessary agricultural information.
Referring to fig. 1, the present invention further provides a gray prediction fuzzy PID control device for irrigation of water and fertilizer, that is, the control system, which operates according to the gray prediction fuzzy PID control method for irrigation of water and fertilizer, and includes:
an automatic irrigation control system;
the irrigation system is used for irrigating water and fertilizer in different plots and different crops; the irrigation system is controlled by a series of automatic irrigation control systems, and precise control irrigation of water and fertilizer is realized.
The irrigation system comprises the different irrigation modes and control objects, the series automatic irrigation control system is a combination of two or more control methods, and the control requirements of different occasions can be met by adopting the specific automatic irrigation control system according to the different irrigation modes adopted by different plots and different crops, so that the precise control irrigation of water and fertilizer is realized, and the excellent growth of the crops is ensured.
In this embodiment, the irrigation system includes:
the water pump is arranged at one end of the main pipeline, the water pump is arranged at the other end of the main pipeline, the main pipeline is provided with a first valve and a second valve, the first valve is arranged at one end, close to the water pump, of the main pipeline, and the second valve is arranged at one end, close to the water drainage area, of the main pipeline;
the number of the branch pipelines is multiple, one end of each branch pipeline is connected to the main pipeline, and the other end of each branch pipeline is connected to the farmland; the branch pipeline is provided with a third valve;
when irrigation is needed, the second valve is closed, the first valve is opened, and then the third valve is opened to realize irrigation; when irrigation is stopped, the third valve is closed, and then the first valve is closed; when the third valve is closed and the first valve and the second valve are opened, the main pipeline is cleaned.
In addition, still be equipped with first manometer on the trunk line, when first manometer surpassed preset pressure, the second valve was opened. The branch pipeline is provided with a second pressure gauge, and when the second pressure gauge reaches a preset pressure, a third valve is opened.
In this embodiment, the control system further includes a control chassis, the control chassis is electrically connected to the first valve, the second valve, and the third valve, and the control chassis has a radio frequency card controller therein, and the radio frequency card controller is used to manually control the first valve, the second valve, and the third valve.
The radio frequency IC card can unlock the radio frequency card controller, and the water and fertilizer irrigation can be manually realized by controlling the opening degree and the opening time of the first valve, the second valve and the third valve. In addition, the radio frequency card controller can also inquire statistical information such as water demand, fertilizer demand and the like.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (7)
1. A grey prediction fuzzy PID control method for irrigation of water and fertilizer quality is characterized by comprising the following steps:
s1, combining a gray prediction control method, a fuzzy logic control method and a PID control method;
s2, developing a series automatic irrigation control system aiming at different irrigation modes and control objects;
s3, the precise control irrigation of water and fertilizer is realized by the serial automatic irrigation control system aiming at different irrigation modes adopted by different plots and different crops.
2. The fuzzy PID control method for gray prediction of irrigation of water and fertilizer quality as claimed in claim 1, wherein the fuzzy PID control method for gray prediction comprises:
the grey model is a dynamic model consisting of a set of grey differential equations, and a GM (1,1) model of the grey model is established by the following modeling process:
1)X(0)for the original non-negative data sequence: x(0)＝[x(0)(1),x(0)(2),...,x(0)(n)]To X(0)Perform a tirednessAddition of a generation operation to give X(0)1-AGO sequence of (A), X(1)＝[x(1)(1),x(1)(2),...,x(1)(n)]Wherein
2) For sequence X(1)Performing adjacent mean value generation operation to obtain X(1)Is generated by the adjacent mean generation sequence Z(1)Wherein z is(1)(k)＝0.5[x(1)(k)+x(1)(k-1)],k＝1,2,...,n；
3) The gray differential equation for GM (1,1) can be obtained: x is the number of(0)(k)+az(1)(k) U, and the corresponding whitening equation:
wherein a is called a development coefficient, and u is a gray effect amount;
4) solving a and u: using least squares
Wherein
Yn＝[x(0)(2)x(0)(3) ... x(0)(n)]T(ii) a The solution of the whitening equation is
The time response sequence of the corresponding gray differential equation is: i.e. the value at time k
5) To the sequence
Performing an accumulation and subtraction operation, i.e. performing the inverse operation of the accumulation and generation, and recording the operation as IAGO, to obtain a prediction sequence
Wherein
The predicted value at the time k + d is:
d is the system delay (lag) time, which can be measured according to field experiments.
3. The grey prediction fuzzy PID control method for irrigation of water and fertilizer quality according to claim 1 or 2, characterized in that, the grey prediction control and fuzzy logic control function is added on the basis of the ordinary PID controller, and an adaptive adjustment factor x is introduced at the output end of the grey prediction controller, namely the prediction error, to form a new self-adjusting grey prediction fuzzy PID controller.
4. The grey prediction fuzzy PID control method for irrigation of water and fertilizer essence quantity according to claim 1 or 2, characterized in that a grey prediction fuzzy controller established by combining the grey prediction control method and a fuzzy logic control method is adopted, a soil humidity signal input by a multi-channel sensor is subjected to data processing to obtain a data reflecting soil humidity as an input, and the input value is compared with a standard value to obtain an input deviation e; if e is greater than 0, the soil humidity is greater than the optimal humidity, namely the soil is not lack of water, and the system does not output irrigation signals; and if e is less than 0, carrying out fuzzy decision by using the deviation e and the fuzzy control rule R according to the inferred synthesis rule to obtain a fuzzy control quantity u, namely u is e R, and then converting the fuzzy control quantity u into an accurate value to control the execution mechanism.
5. The fuzzy PID control method of gray prediction for irrigation of water and fertilizer according to claim 1 or 2, wherein the irrigation mode comprises drip irrigation, sprinkling irrigation and ground irrigation.
6. The grey prediction fuzzy PID control method for water and fertilizer irrigation according to claim 1 or 2, wherein the control objects comprise electromagnetic valves, variable frequency motors and electric gates.
7. A grey prediction fuzzy PID control device for water and fertilizer irrigation, comprising a grey prediction fuzzy PID control method for water and fertilizer irrigation according to any one of claims 1 to 6, characterized by comprising:
an automatic irrigation control system;
the irrigation system is used for carrying out water and fertilizer irrigation on different plots and different crops; the serial automatic irrigation control system controls the irrigation system to realize precise control irrigation of water and fertilizer.
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