CN118011782B - THGS-PID-based vegetable hydroponic nutrition self-adaptive regulation and control method - Google Patents
THGS-PID-based vegetable hydroponic nutrition self-adaptive regulation and control method Download PDFInfo
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Abstract
The invention provides a THGS-PID-based vegetable hydroponic nutrition self-adaptive regulation and control method, which relates to the field of hydroponic vegetables and comprises a nondestructive weight measurement method, a growth target setting method, a nutrient solution concentration control method and a control parameter setting method; the nutrient solution concentration control method is used for controlling the current nutrient solution concentration by adopting a PID controller according to the weight of the single plant of the hydroponic vegetable obtained in the nondestructive weight measurement method and the growth target curve of each stage of the hydroponic vegetable obtained in the growth target setting method; the control parameter setting method adopts THGS algorithm to adjust and optimize parameters in the PID controller in each control stage of the nutrient solution concentration control method. The method solves the problems that the concentration of the nutrient solution of the hydroponic vegetables cannot be effectively and adaptively regulated, the regulation and control efficiency is low, the regulation and control error is large and the like in the prior art, and realizes the efficient and high-yield planting of the hydroponic vegetables.
Description
Technical Field
The invention relates to the technical field of hydroponic vegetables, in particular to a THGS-PID-based vegetable hydroponic nutrition self-adaptive regulation and control method.
Background
The water-cultivated vegetable belongs to one of soilless cultivation, has short growth cycle and early marketing time, and is rich in various microorganisms and mineral substances necessary for human bodies; most root systems of the hydroponic vegetables grow in the nutrient solution layer, and the nutrient solution provides moisture, nutrients, oxygen and other components necessary for plant growth. Therefore, the nutrient solution plays a vital role in the growth of the hydroponic vegetables, and is prepared by dissolving a certain amount of fertilizer into water according to the nutrient requirement of plant growth and proper arm strength, namely the concentration of the nutrient solution is directly related to the fertility state of the hydroponic system; in different stages of vegetable growth, the demands on the concentration of the hydroponic nutrient solution (namely, the vegetable absorptivity) are different, and the concentration of the nutrient solution is too low, so that the problems of unbalanced nutrition of the vegetables, blocked growth of root systems of the vegetables, even death of plants and the like are easily caused; the concentration of the nutrient solution is too high, so that waste of raw materials is easily caused, the planting cost of the whole water planting system is increased, and the nutrient solution with too high concentration is easily caused to be too rich for plants with lower tolerance, so that the subsequent growth of the plants is influenced. At present, the regulation of the nutrient solution of the hydroponic vegetables mainly comprises two modes of manual intervention regulation and automatic system regulation: the manual intervention and adjustment has high requirement on experience of operators, large artificial influence factor, poor adjustment instantaneity, large adjustment error and low precision, and simultaneously wastes a large amount of manpower and material resources; the automatic body system adjustment is usually carried out by adopting a PID control system, but the PID control system has the problems of long adjustment time, time delay, time lag and the like, so that the adjustment of the system has the defects of time variation, lag, nonlinearity and the like, the instability of the system is increased, and the normal growth of the hydroponic vegetables is further influenced.
Disclosure of Invention
Aiming at the problems existing in the prior art, the invention aims to provide a THGS-PID-based vegetable hydroponic nutrient self-adaptive regulation and control method, so as to solve the problems that the concentration of hydroponic vegetable nutrient solution in the prior art cannot be effectively and adaptively regulated, the regulation and control efficiency is low, the regulation and control error is large and the like.
The aim of the invention is achieved by the following technical scheme:
a THGS-PID-based vegetable hydroponic nutrition self-adaptive regulation and control method comprises a nondestructive weight measurement method, a growth target setting method, a nutrient solution concentration control method and a control parameter setting method;
The nondestructive weight measurement method comprises the following steps: the method comprises the steps of carrying out nondestructive weight measurement on vegetables in a water culture system, and outputting the weight of a single plant of water culture vegetables;
the method for setting the growth target comprises the following steps: through historical data of the hydroponic vegetables, generating a growth target curve of each stage of the hydroponic vegetables in a statistics way, wherein the growth target curve of each stage is used for describing the growth condition of the hydroponic vegetables; the method comprises the steps of historical data acquisition and growth target curve statistics;
The nutrient solution concentration control method comprises the following steps: according to the weight of the single plant of the hydroponic vegetable obtained in the nondestructive weight measurement method and the growth target curve of each stage of the hydroponic vegetable obtained in the growth target setting method, controlling the concentration of the current nutrient solution by adopting a PID controller;
the control parameter setting method comprises the following steps: and in each control stage of the nutrient solution concentration control method, parameters in the PID controller are optimized by adopting THGS algorithm.
Based on the further optimization of the scheme, the nondestructive weight measurement method comprises the following steps:
Firstly, randomly selecting M groups of water-cultured vegetables from the whole water-culture system at uniform intervals, wherein each group comprises N plants; then, taking out each group of hydroponic vegetables from the hydroponic liquid, draining for a fixed period of time, and weighing after draining to obtain the weight W i (i=1, 2, …, M) of each group of hydroponic vegetables; finally, the weight w of the single hydroponic vegetable is output:
。
Based on the further optimization of the scheme, the historical data acquisition is specifically as follows: recording historical data of single hydroponic vegetables aiming at each batch of hydroponic vegetables in the hydroponic system in the same growing environment, wherein the historical data comprise historical growing weight and picking weight;
The method comprises the steps of monitoring the whole growth process of the hydroponic vegetables according to the historical growth weight in a sampling period to obtain historical growth weight data of each sampling period; the historical growth weight comprises a planting time and a weight value, wherein the planting time is a time interval from the planting start of a corresponding batch, and the weight value is the weight of a single plant of hydroponic vegetables obtained from the batch of hydroponic vegetables according to a nondestructive weight measurement method in the corresponding planting time;
The picking weight is the weight of the single plant of the water-cultivated vegetables which are picked according to the picking flow after the corresponding batch of the water-cultivated vegetables are ripe, and reflects the harvest state of the batch of the vegetables.
Based on the further optimization of the scheme, the growth target curve statistics specifically comprise:
Step S11, sequencing: firstly, sequencing all batches of hydroponic vegetables according to picking weights obtained in historical data acquisition from large to small, and selecting historical data of the first Y batches;
step S12, fitting: fitting is carried out on the historical data of the first Y batches, namely the historical growth weight of each sampling period, and the fitting weight of the corresponding sampling period is output, specifically:
；
Wherein: w j represents the fitting weight of the hydroponic vegetable in the j-th sampling period, namely the growth target weight; representing picking weights, i.e., fitting weights, in historical data of the selected y-th batch of hydroponic vegetables; Representing the weight value of the selected y-th batch of hydroponic vegetables in the j-th sampling period;
step S13, curve generation: and obtaining fitting weights in all sampling periods through the step S12, and forming a growth target curve by using the fitting weights and the corresponding sampling periods.
Based on the further optimization of the scheme, the PID controller comprises a proportional unit, an integral unit and a differential unit, and control parameters corresponding to each unit are Kp, ki and Kd respectively; the PID controller controls the current nutrient solution concentration by utilizing a PID control algorithm according to the weight w of the single hydroponic vegetable output in the nondestructive weight measurement method and a growth target curve obtained by a growth target setting method;
the regulation and control period of the PID controller is consistent with the period in the nondestructive weight measurement method; the PID controller input signals are: the method comprises the steps that the difference value between the weight w of the single plant of the hydroponic vegetable obtained by a nondestructive weight measurement method of the hydroponic vegetable in the current sampling period and the fitting weight obtained by a growth target curve in a growth target setting method in the corresponding sampling period is obtained; the output signal of the PID controller is the nutrient solution regulating quantity and the unit quantity for changing (mainly adding) the concentration of the nutrient solution in the water planting vegetable planting system.
Based on the further optimization of the scheme, the control parameter setting method specifically comprises the following steps: the method comprises the steps that Z parameter regulation and control systems independent of the water culture system are arranged outside the water culture system, the water culture system is a main system for cultivating water-cultured vegetables, the parameter regulation and control systems are reduced in version according to the same proportion of the water culture system, the parameters for the water culture system are regulated and controlled, namely, the number of the water-cultured vegetables, the dosage of nutrient solution and the like are reduced in proportion, and environmental factors such as illumination, temperature and humidity are kept unchanged;
The parameter regulation and control system adopts THGS algorithm to control parameters and regulate the PID controller in each regulation and control period (the regulation and control period is a fixed time period);
Wherein, THGS algorithm specifically comprises:
Wherein: x best represents the current optimal individual position, i.e. the optimal control parameter; x (t) represents the position of each individual in the population, t represents the current iteration number; randn (1) and r 1、r2 are random numbers, and randn (1) obeys positive distribution; l is a system constant;
The parameter R is specifically as follows:
Wherein: t represents the maximum number of iterations, randn (2) is a random number, and has the same properties as randn (1);
the weights W 1 and W 2 are specifically:
Wherein: g represents the number of the set population; r 3、r4、r5 are random numbers; sum H represents the Sum of the hunger levels of all individuals, obtained by summing H (i); h (i) represents the hunger level of each individual, specifically:
；
wherein: AF (i) represents the fitness of all individuals, BF represents the best fitness in the current iteration process; the parameter h is specifically:
Wherein: r represents a random number; LH represents the lower bound of parameter h; the parameter TH is specifically:
Wherein: WF represents the optimal fitness in the current iteration process; r 6 is a random number; f (i) is each individual fitness saved in AF (i), ; UB and LB represent the upper and lower bounds of the search, respectively;
the parameter E is specifically:
Wherein: Representation of Is the reciprocal of (2);
the specific steps of the parameter regulation and control system for controlling the parameters are as follows:
Step S21, firstly initializing parameters, setting maximum iteration times T and system constant l, initializing random parameters r, r 1、r2、r3、r4、r5、r6, randn (1) and randn (2), and simultaneously setting upper and lower boundaries of control parameters, namely 、、；
Step S22, initializing values of Z parameter regulation and control systems, and obtaining Z group control parameters according to a chaotic mapping mode, wherein the Z group control parameters specifically comprise:
Wherein: 、、 representing an initialization parameter value; representing a random diffusion factor;
The control parameters x s of the Z parameter regulation and control systems are as follows:
s=1,2,…,Z；
Step S23, using the Z-group control parameters x s(t) obtained in step S22, and regulating and controlling the corresponding Z parameter regulating and controlling systems; then waiting for a regulation period, and measuring the hydroponic vegetables in each parameter regulation system by adopting a nondestructive weight measurement method to obtain the weight w s of the single hydroponic vegetable in each parameter regulation system;
Step S24, acquiring a control parameter x s(t+1) in the next regulation and control period by adopting an iterative algorithm: if the iteration number T is smaller than the maximum iteration number T, repeating the steps S23 to S24; if the iteration times T is not smaller than the maximum iteration times T, stopping iteration, and outputting the optimal parameter control parameter x best after iteration to the hydroponic system (namely the PID controller of the hydroponic system) to realize the tuning of the hydroponic system parameters.
Based on further optimization of the scheme, the regulation period is 24h.
Based on a further optimization of the above scheme, the random parameters r, r 1、r2、r3、r4、r5、r6 both belong to (0, 1).
Based on a further optimization of the above scheme, the system constant l=0.08.
Based on the further optimization of the scheme, the iterative algorithm specifically comprises the following steps:
step S241, firstly, obtaining the individual fitness F (i) in each parameter control system:
wherein: e (t) represents the error between the input and the output in the parameter regulation system; representing a control value; the concentration value of the nutrient solution of the water planting system is represented; g 1、g2、g3 respectively represents corresponding influence weight values;
Step S242, updating THGS the optimal fitness BF, the worst fitness WF and the optimal control parameter x best in the algorithm by the individual fitness in step S241; obtaining the hunger degree H (i) of each parameter regulation and control system, weights W 1 and W 2, and parameters E and R;
And step S243, substituting the parameters acquired in the step S243 into an iteration process of the THGS algorithm to realize iteration.
The following technical effects are achieved by the technical scheme of the invention:
According to the application, the PID controller is regulated and controlled in each regulation and control period by adopting THGS algorithm, so that the optimal value of the parameter of the PID controller is adaptively found, the concentration regulation and control of the PID controller on the hydroponic vegetable nutrient solution is optimal, and the problems of time varying, lag, nonlinearity, long regulation time and the like in the regulation and control process of the PID controller are effectively avoided. Meanwhile, by means of the repeated iteration of THGS, the problems of low precision of manual parameter adjustment, poor instantaneity, large artificial influence factors, low degree of automation and the like are effectively avoided, the self-updating of a system can be realized, the adjustment of parameters of the PID controller and the matching of different growth stages of the hydroponic vegetables are ensured, a proper amount of nutrients are provided for the hydroponic vegetables, the normal growth of the hydroponic vegetables is ensured, and the yield and quality of the hydroponic vegetables are further ensured. In addition, the nondestructive weight measurement and the growth target measurement parameters of the hydroponic vegetables are used as the input of the PID controller, so that the characteristics of the hydroponic vegetables in the normal growth stage can be effectively reflected, and the precise regulation and the supplementation of the hydroponic nutrient solution are further completed.
Drawings
FIG. 1 is a system frame diagram of an adaptive modulation method according to an embodiment of the present invention.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth such as the particular system architecture, techniques, etc., in order to provide a thorough understanding of the embodiments of the present invention. .
Example 1:
a THGS-PID-based vegetable hydroponic nutrition self-adaptive regulation and control method comprises a nondestructive weight measurement method, a growth target setting method, a nutrient solution concentration control method and a control parameter setting method;
The nondestructive weight measurement method comprises the following steps: the method comprises the steps of carrying out nondestructive weight measurement on vegetables in a water culture system, and outputting the weight of a single plant of water culture vegetables; the method comprises the following steps:
Firstly, randomly selecting M groups of water-cultured vegetables from the whole water-culture system at uniform intervals, wherein each group comprises N plants; then, taking out each group of hydroponic vegetables from the hydroponic liquid, draining for a fixed period of time, and weighing after draining to obtain the weight W i (i=1, 2, …, M) of each group of hydroponic vegetables; finally, the weight w of the single hydroponic vegetable is output:
the method for setting the growth target comprises the following steps: through historical data of the hydroponic vegetables, generating a growth target curve of each stage of the hydroponic vegetables in a statistics way, wherein the growth target curve of each stage is used for describing the growth condition of the hydroponic vegetables; the method comprises the steps of historical data acquisition and growth target curve statistics;
The historical data collection is specifically as follows: recording historical data of single hydroponic vegetables aiming at each batch of hydroponic vegetables in the hydroponic system in the same growing environment, wherein the historical data comprise historical growing weight and picking weight;
The method comprises the steps of monitoring the whole growth process of the hydroponic vegetables according to the historical growth weight in a sampling period to obtain historical growth weight data of each sampling period; the historical growth weight comprises a planting time and a weight value, wherein the planting time is a time interval from the planting start of a corresponding batch, and the weight value is the weight of a single plant of hydroponic vegetables obtained from the batch of hydroponic vegetables according to a nondestructive weight measurement method in the corresponding planting time;
The picking weight is the weight of the single plant of the water-cultivated vegetables which are picked according to the picking flow after the corresponding batch of the water-cultivated vegetables are ripe, and reflects the harvest state of the batch of the vegetables.
The growth target curve statistics specifically comprise:
Step S11, sequencing: firstly, sequencing all batches of hydroponic vegetables according to picking weights obtained in historical data acquisition from large to small, and selecting historical data of the first Y batches;
step S12, fitting: fitting is carried out on the historical data of the first Y batches, namely the historical growth weight of each sampling period, and the fitting weight of the corresponding sampling period is output, specifically:
Wherein: w j represents the fitting weight of the hydroponic vegetable in the j-th sampling period, namely the growth target weight; representing picking weights, i.e., fitting weights, in historical data of the selected y-th batch of hydroponic vegetables; Representing the weight value of the selected y-th batch of hydroponic vegetables in the j-th sampling period;
Step S13, curve generation: the fitting weight in all sampling periods is obtained through step S12, and a growth target curve is formed by using the fitting weight and the corresponding sampling period (the fitting curve is only required by adopting a conventional curve fitting method in the art, and the embodiment is not particularly limited).
The nutrient solution concentration control method comprises the following steps: according to the weight of the single plant of the hydroponic vegetable obtained in the nondestructive weight measurement method and the growth target curve of each stage of the hydroponic vegetable obtained in the growth target setting method, controlling the concentration of the current nutrient solution by adopting a PID controller;
The PID controller comprises a proportion unit, an integration unit and a differentiation unit, and control parameters corresponding to each unit are Kp, ki and Kd respectively; proportion unit: the proportional unit is also called a P-controller and is mainly used for controlling the current, and giving an output proportional to the current error; when the P-controller is applied, a value is firstly set, and then a set value or an expected value is compared with an actual value obtained in the use process, wherein the actual value can also be a feedback value obtained in the control process; multiplying the error by a proportionality constant to obtain the output of the P-controller; when the P-controller output is 0, it is indicated that the current error value is 0. An integration unit: the integration unit is also called an I-controller and is mainly used for controlling the past; when the P-controller is in control, an offset is necessarily generated between a process variable and a set value, and the offset is controlled by the I-controller, so that steady-state errors are eliminated as much as possible; the I-controller mainly integrates the error to control the error, and when the error value is 0, the I-controller can save the parameter value of the controller in the current state. And a differentiation unit: the differentiating unit is also called D-controller, mainly used for controlling future; the two controllers do not predict future functions, so in actual control, even if the set point is changed, the two controllers can only normally correspond to each other and cannot make corresponding changes; and the D-controller can solve this problem by predicting the future.
The PID controller controls the current nutrient solution concentration by utilizing a PID control algorithm according to the weight w of the single hydroponic vegetable output in the nondestructive weight measurement method and a growth target curve obtained by a growth target setting method; the regulation and control period of the PID controller is consistent with the period in the nondestructive weight measurement method; the PID controller input signals are: the method comprises the steps that the difference value between the weight w of the single plant of the hydroponic vegetable obtained by a nondestructive weight measurement method of the hydroponic vegetable in the current sampling period and the fitting weight obtained by a growth target curve in a growth target setting method in the corresponding sampling period is obtained; the output signal of the PID controller is the nutrient solution regulating quantity and the unit quantity for changing (mainly adding) the concentration of the nutrient solution in the water planting vegetable planting system.
The control parameter setting method comprises the following steps: in each control stage of the nutrient solution concentration control method, parameters in the PID controller are optimized by adopting THGS algorithm; the method comprises the following steps: the method comprises the steps that Z parameter regulation and control systems independent of the water culture system are arranged outside the water culture system, the water culture system is a main system for cultivating water-cultured vegetables, the parameter regulation and control systems are in a scaled-down version (the scaled-down version is determined according to actual conditions) according to the water culture system, and the parameter regulation and control systems are used for the water culture system, namely, the number of the water-cultured vegetables, the dosage of nutrient solution and the like are reduced in proportion, and environmental factors such as illumination, temperature and humidity are kept unchanged;
The parameter regulation and control system adopts THGS algorithm to carry out control parameter regulation and control on the PID controller in each regulation and control period (the regulation and control period is a fixed time period), and the regulation and control period is 24h in the embodiment;
Wherein, THGS algorithm specifically comprises:
Wherein: x best represents the current optimal individual position, i.e. the optimal control parameter; x (t) represents the position of each individual in the population, t represents the current iteration number; randn (1) and r 1、r2 are random numbers, and randn (1) obeys positive distribution; l is a system constant;
The parameter R is specifically as follows:
Wherein: t represents the maximum number of iterations, randn (2) is a random number, and has the same properties as randn (1);
the weights W 1 and W 2 are specifically:
Wherein: g represents the number of the set population; r 3、r4、r5 are random numbers; sum H represents the Sum of the hunger levels of all individuals, obtained by summing H (i); h (i) represents the hunger level of each individual, specifically:
wherein: AF (i) represents the fitness of all individuals, BF represents the best fitness in the current iteration process; the parameter h is specifically:
Wherein: r represents a random number; LH represents the lower bound of parameter h; the parameter TH is specifically:
Wherein: WF represents the optimal fitness in the current iteration process; r 6 is a random number; f (i) is each individual fitness saved in AF (i), ; UB and LB represent the upper and lower bounds of the search, respectively;
the parameter E is specifically:
Wherein: Representation of Is the reciprocal of (2);
the specific steps of the parameter regulation and control system for controlling the parameters are as follows:
step S21, initializing parameters, setting maximum iteration times T and system constant l (l=0.08 in this embodiment), initializing random parameters r, r 1、r2、r3、r4、r5、r6, randn (1), randn (2) (r and r 1、r2、r3、r4、r5、r6 in this embodiment are all (0, 1; randn (1) and randn (2) are set according to practical situations), and setting upper and lower boundaries of control parameters, namely 、、；
Step S22, initializing values of Z parameter regulation and control systems, and obtaining Z group control parameters according to a chaotic mapping mode, wherein the Z group control parameters specifically comprise:
Wherein: 、、 representing an initialization parameter value; representing random diffusion factor, the value in this example is [0, 1);
The control parameters x s of the Z parameter regulation and control systems are as follows:
s=1,2,…,Z；
Step S23, using the Z-group control parameters x s(t) obtained in step S22, and regulating and controlling the corresponding Z parameter regulating and controlling systems; then waiting for a regulation period, and measuring the hydroponic vegetables in each parameter regulation system by adopting a nondestructive weight measurement method to obtain the weight w s of the single hydroponic vegetable in each parameter regulation system;
Step S24, acquiring a control parameter x s(t+1) in a next regulation period by adopting an iterative algorithm, which specifically includes:
step S241, firstly, obtaining the individual fitness F (i) in each parameter control system:
Wherein: e (t) represents the error between input and output in the parameter regulation system (in this embodiment, i.e. the same point in time, the difference between the weight of the single hydroponic vegetable obtained by the non-destructive weight measurement method and the fitted weight obtained by the growth target curve in the growth target setting method); Representing a control value (namely, a nutrient solution regulating quantity output by a PID controller); the concentration value of the nutrient solution of the water planting system is represented; g 1、g2、g3 represents the corresponding influence weight value, in this embodiment g 1=0.8、g2=0.01、g3 =0.09;
Step S242, updating THGS the optimal fitness BF, the worst fitness WF and the optimal control parameter x best in the algorithm by the individual fitness in step S241; obtaining the hunger degree H (i) of each parameter regulation and control system, weights W 1 and W 2, and parameters E and R;
step S243, substituting the parameters acquired in step S243 into the iterative process of THGS algorithm, namely:
and (5) iteration is realized.
If the iteration number T is smaller than the maximum iteration number T, repeating the steps S23 to S24; if the iteration times T is not smaller than the maximum iteration times T, stopping iteration, and outputting the optimal parameter control parameter x best after iteration to the hydroponic system (namely the PID controller of the hydroponic system) to realize the tuning of the hydroponic system parameters.
Example 2:
As a further optimization of the solution of the present application, on the basis of the solution of embodiment 1, since the concentration of the nutrient solution changes dynamically in the unit regulation period, that is, the PID controller changes (mainly adds) while the hydroponic vegetables are also absorbing, in order to further realize the precise control of the concentration of the nutrient solution in the hydroponic system, a nutrient solution transmission model is set in the hydroponic system to reflect the change of the concentration of the nutrient solution with time, specifically:
Wherein: c represents the concentration of nutrient solution which can be absorbed by the water-cultivated vegetables in the water-cultivated system; v c represents the nutrient solution utilization rate, namely the absorption rate of the hydroponic vegetables to the nutrient solution, and is obtained through a large amount of test data; Indicating the regulating quantity of nutrient solution.
Presetting transmission model fluctuation threshold [ C L,CH ] when dynamically changingWhen the fluctuation threshold value is within the range, regulating and controlling according to the normal regulating and controlling parameters; when dynamically changingAnd when the fluctuation threshold value is out of the range, outputting errors and performing readjustment.
Claims (5)
1. A THGS-PID-based vegetable hydroponic nutrition self-adaptive regulation and control method is characterized in that: the method comprises a nondestructive weight measurement method, a growth target setting method, a nutrient solution concentration control method and a control parameter setting method;
The nondestructive weight measurement method comprises the following steps: the method comprises the steps of carrying out nondestructive weight measurement on vegetables in a water culture system, and outputting the weight of a single plant of water culture vegetables;
the method for setting the growth target comprises the following steps: through historical data of the hydroponic vegetables, generating a growth target curve of each stage of the hydroponic vegetables in a statistics way, wherein the growth target curve of each stage is used for describing the growth condition of the hydroponic vegetables; the method comprises the steps of historical data acquisition and growth target curve statistics;
The nutrient solution concentration control method comprises the following steps: according to the weight of the single plant of the hydroponic vegetable obtained in the nondestructive weight measurement method and the growth target curve of each stage of the hydroponic vegetable obtained in the growth target setting method, controlling the concentration of the current nutrient solution by adopting a PID controller;
the control parameter setting method comprises the following steps: in each control stage of the nutrient solution concentration control method, parameters in the PID controller are optimized by adopting THGS algorithm;
the PID controller comprises a proportion unit, an integration unit and a differentiation unit, and control parameters corresponding to each unit are Kp, ki and Kd respectively; the PID controller controls the current nutrient solution concentration by utilizing a PID control algorithm according to the weight w of the single hydroponic vegetable output in the nondestructive weight measurement method and a growth target curve obtained by a growth target setting method;
The regulation and control period of the PID controller is consistent with the period in the nondestructive weight measurement method; the PID controller input signals are: the method comprises the steps that the difference value between the weight w of the single plant of the hydroponic vegetable obtained by a nondestructive weight measurement method of the hydroponic vegetable in the current sampling period and the fitting weight obtained by a growth target curve in a growth target setting method in the corresponding sampling period is obtained; the PID controller outputs signals which are nutrient solution regulating and controlling amounts and unit amounts for changing the concentration of the nutrient solution in the hydroponic vegetable planting system;
The control parameter setting method specifically comprises the following steps: the method comprises the steps that Z parameter regulation and control systems independent of the water culture system are arranged outside the water culture system, the water culture system is a main system for cultivating water-cultured vegetables, the parameter regulation and control systems are reduced in version according to the same proportion of the water culture system, the parameters for the water culture system are regulated and controlled, namely, the number of the water-cultured vegetables, the dosage of nutrient solution and the like are reduced in proportion, and environmental factors such as illumination, temperature and humidity are kept unchanged;
The parameter regulation and control system adopts THGS algorithm to control parameters and regulate the PID controller in each regulation and control period;
Wherein, THGS algorithm specifically comprises:
Wherein: x best represents the current optimal individual position, i.e. the optimal control parameter; x (t) represents the position of each individual in the population, t represents the current iteration number; randn (1) and r 1、r2 are random numbers, and randn (1) obeys positive distribution; l is a system constant;
The parameter R is specifically as follows:
Wherein: t represents the maximum number of iterations, randn (2) is a random number, and has the same properties as randn (1);
the weights W 1 and W 2 are specifically:
Wherein: g represents the number of the set population; r 3、r4、r5 are random numbers; sum H represents the Sum of the hunger levels of all individuals, obtained by summing H (i); h (i) represents the hunger level of each individual, specifically:
wherein: AF (i) represents the fitness of all individuals, BF represents the best fitness in the current iteration process; the parameter h is specifically:
Wherein: r represents a random number; LH represents the lower bound of parameter h; the parameter TH is specifically:
Wherein: WF represents the optimal fitness in the current iteration process; r 6 is a random number; f (i) is each individual fitness saved in AF (i), ; UB and LB represent the upper and lower bounds of the search, respectively;
the parameter E is specifically:
Wherein: Representation of Is the reciprocal of (2);
the specific steps of the parameter regulation and control system for controlling the parameters are as follows:
Step S21, firstly initializing parameters, setting maximum iteration times T and system constant l, initializing random parameters r, r 1、r2、r3、r4、r5、r6, randn (1) and randn (2), and simultaneously setting upper and lower boundaries of control parameters, namely 、、；
Step S22, initializing values of Z parameter regulation and control systems, and obtaining Z group control parameters according to a chaotic mapping mode, wherein the Z group control parameters specifically comprise:
Wherein: 、、 representing an initialization parameter value; representing a random diffusion factor;
The control parameters x s of the Z parameter regulation and control systems are as follows:
s=1,2,…,Z；
Step S23, using the Z-group control parameters x s(t) obtained in step S22, and regulating and controlling the corresponding Z parameter regulating and controlling systems; then waiting for a regulation period, and measuring the hydroponic vegetables in each parameter regulation system by adopting a nondestructive weight measurement method to obtain the weight w s of the single hydroponic vegetable in each parameter regulation system;
Step S24, acquiring a control parameter x s(t+1) in the next regulation and control period by adopting an iterative algorithm: if the iteration number T is smaller than the maximum iteration number T, repeating the steps S23 to S24; if the iteration times T is not smaller than the maximum iteration times T, stopping iteration, and outputting the optimal parameter control parameter x best after iteration to the hydroponic system to realize the optimization of the hydroponic system parameters.
2. The THGS-PID-based vegetable hydroponic nutrition adaptive regulation and control method according to claim 1, wherein the method is characterized in that: the nondestructive weighing method comprises the following steps:
Firstly, randomly selecting M groups of water-cultured vegetables from the whole water-culture system at uniform intervals, wherein each group comprises N plants; then, taking out each group of hydroponic vegetables from the hydroponic liquid, draining for a fixed period of time, and weighing after draining to obtain the weight W i (i=1, 2, …, M) of each group of hydroponic vegetables; finally, the weight w of the single hydroponic vegetable is output:
3. The THGS-PID-based vegetable hydroponic nutrition adaptive regulation and control method according to claim 1 or 2, wherein the method is characterized in that: the historical data acquisition specifically comprises the following steps: recording historical data of single hydroponic vegetables aiming at each batch of hydroponic vegetables in the hydroponic system in the same growing environment, wherein the historical data comprise historical growing weight and picking weight;
The method comprises the steps of monitoring the whole growth process of the hydroponic vegetables according to the historical growth weight in a sampling period to obtain historical growth weight data of each sampling period; the historical growth weight comprises a planting time and a weight value, wherein the planting time is a time interval from the planting start of a corresponding batch, and the weight value is the weight of a single plant of hydroponic vegetables obtained from the batch of hydroponic vegetables according to a nondestructive weight measurement method in the corresponding planting time;
The picking weight is the weight of the single plant of the water-cultivated vegetables which are picked according to the picking flow after the corresponding batch of the water-cultivated vegetables are ripe, and reflects the harvest state of the batch of the water-cultivated vegetables.
4. The THGS-PID-based vegetable hydroponic nutrition adaptive regulation and control method according to claim 3, wherein the method comprises the following steps: the growth target curve statistics specifically comprise:
Step S11, sequencing: firstly, sequencing all batches of hydroponic vegetables according to picking weights obtained in historical data acquisition from large to small, and selecting historical data of the first Y batches;
step S12, fitting: fitting is carried out on the historical data of the first Y batches, namely the historical growth weight of each sampling period, and the fitting weight of the corresponding sampling period is output, specifically:
Wherein: w j represents the fitting weight of the hydroponic vegetable in the j-th sampling period, namely the growth target weight; representing picking weights, i.e., fitting weights, in historical data of the selected y-th batch of hydroponic vegetables; Representing the weight value of the selected y-th batch of hydroponic vegetables in the j-th sampling period;
step S13, curve generation: and obtaining fitting weights in all sampling periods through the step S12, and forming a growth target curve by using the fitting weights and the corresponding sampling periods.
5. The THGS-PID-based vegetable hydroponic nutrition adaptive regulation and control method according to claim 1, wherein the method is characterized in that: the iterative algorithm specifically comprises the following steps:
step S241, firstly, obtaining the individual fitness F (i) in each parameter control system:
wherein: e (t) represents the error between the input and the output in the parameter regulation system; representing a control value; the concentration value of the nutrient solution of the water planting system is represented; g 1、g2、g3 respectively represents corresponding influence weight values;
Step S242, updating THGS the optimal fitness BF, the worst fitness WF and the optimal control parameter x best in the algorithm by the individual fitness in step S241; obtaining the hunger degree H (i) of each parameter regulation and control system, weights W 1 and W 2, and parameters E and R;
And step S243, substituting the parameters acquired in the step S243 into an iteration process of the THGS algorithm to realize iteration.
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