CN109634101B - Photosynthesis PID control method based on chlorophyll fluorescence as feedback signal - Google Patents
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Abstract
The invention discloses a photosynthesis PID control method based on chlorophyll fluorescence as a feedback signal. The invention relates to a photosynthesis PID closed-loop control method using chlorophyll fluorescence as a feedback signal. It is important to control plant growth in view of limited land and water resources. The current greenhouse control strategy mainly depends on the experience of farmers, does not consider the actual needs of photosynthesis of plants, and therefore cannot achieve the best crop yield and the most effective and reasonable utilization of resources. In this invention, the main process of photosynthesis is represented by an overall mathematical model with chlorophyll fluorescence (ChlF) as output from measurable photosystem ii (psii). The parameters of the model, i.e. the rate constants of the reactions, were further determined by example fitting of experimental data.
Description
Technical Field
The invention relates to the field of plant growth control, in particular to a photosynthesis PID control method based on chlorophyll fluorescence as a feedback signal.
Background
Plants can use solar energy to provide energy and food for organisms. Controlling plant growth is a trend in the future of botany and automatic control, considering limited resources and land. This is one of the 125 global problems promulgated by the "science" journal. Greenhouse control strategies based on plant photosynthesis can reduce waste of resources and increase crop yield. Therefore, it is of great importance to develop plant growth control strategies based on the photosynthetic requirements of plants. According to modern control theory, models covering the main photosynthetic response are crucial for the development of plant growth control strategies. Therefore, it is necessary to design a feasible photosynthesis kinetic model system for achieving the maximized photosynthetic efficiency.
There are three energy pathways for the light energy absorbed by the photosystem ii (psii) of plants, which are involved in photosynthetic chemical reactions, lost as heat energy and dissipated as chlorophyll fluorescence (ChlF). The three pathways are in a trade-off and mutual constraint relation, so that ChlF has very rich photosynthetic information. The process of ChlF loss is complex, but it provides information about the structure and physiology of plant photosynthesis and can be measured by portable instruments. The measurement of ChlF is not invasive to plants and has therefore been widely used as a probe to study photosynthetic energy transfer, physiological processes and intrinsic mechanisms of photosynthesis.
The traditional technology has the following technical problems:
there is a relative lack in the literature of control strategies based on plant physiology to modulate photosynthesis. Although chlorophyll fluorescence can be easily measured, the objective of controlling plant growth is not to obtain the desired fluorescence profile, but to modulate photosynthesis activity, e.g., increase carbohydrate production, etc., by using ChlF as a feedback signal for different purposes. However, a real problem is that in a short time (on the order of seconds) of real-time control, the state quantity of the system, such as the amount of sugars, cannot be measured, and thus the sugars themselves cannot be used as a feedback signal for controlling photosynthesis.
Disclosure of Invention
The invention aims to provide a photosynthesis PID control method based on chlorophyll fluorescence as a feedback signal, and particularly relates to acquisition of chlorophyll fluorescence experimental data, establishment of a photosynthesis model, fitting of the experimental data and a mathematical model, estimation of state quantity by using an extended Kalman filtering technology and regulation of photosynthesis by using a PID control technology.
In order to solve the above technical problems, the present invention provides a photosynthesis PID control method based on chlorophyll fluorescence as a feedback signal, comprising:
acquiring a fluorescence curve;
establishing a mathematical model of the whole process of photosynthesis;
fitting a mathematical model and a fluorescence curve obtained by an experiment, and determining a series of reaction rate constants;
estimating a state variable according to the fluorescence value output by the model and by utilizing an extended Kalman filtering technology;
the photosynthetic activity is regulated using PID control techniques.
In one embodiment, "a fluorescence curve is acquired; "in (1), the chlorophyll fluorometer test is used to obtain the fluorescence curve.
In one embodiment, "a mathematical model of the overall process of photosynthesis is established; "in, establish the photosynthesis mathematical model according to the light reaction electron transfer mechanism, regulation mechanism and dark reaction process of photosynthesis.
In one embodiment, a mathematical model and experimentally derived fluorescence curve are "fitted to determine a series of reaction rate constants; and fitting the experimental data and the established mathematical model by using a Levenberg-Marquardt method to determine the reaction rate constant of the system.
In one embodiment, an extended Kalman filter technique is used to estimate the system's unmeasured state variables from the system's output chlorophyll fluorescence signal.
In one embodiment, the undetectable state variable is the amount of carbohydrate production, electron acceptor QA redox, electron acceptor QB redox, Plastoquinone (PQ).
In one embodiment, "PID control techniques are used to regulate photosynthesis activity. "the plant photosynthesis is regulated using a PID control algorithm using the estimated state variables as feedback signals.
A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of any of the methods when executing the program.
A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of any of the methods.
A processor for running a program, wherein the program when running performs any of the methods.
The invention has the beneficial effects that:
the method for estimating the photosynthesis state variable by using the extended Kalman filtering technology and adjusting the plant photosynthesis by using the most extensive PID control technology in the current industry has important significance for plant growth control.
Drawings
FIG. 1 is a graph of the fitting effect of experimental data and a mathematical model in the photosynthesis PID control method based on chlorophyll fluorescence as a feedback signal.
FIG. 2 is a flow chart of the extended Kalman filtering technique in the photosynthesis PID control method based on chlorophyll fluorescence as a feedback signal.
FIG. 3 is a comparison graph of the state estimator in the photosynthesis PID control method based on chlorophyll fluorescence as the feedback signal and the results obtained from computer simulation.
FIG. 4 is a block diagram of a closed loop system for regulating plant photosynthesis by the PID control technology in the photosynthesis PID control method based on chlorophyll fluorescence as a feedback signal.
FIG. 5 is an example of a light intensity variation curve (a) and corresponding PQ reduction efficiency (b) obtained by using PID control technique in the photosynthesis PID control method based on chlorophyll fluorescence as a feedback signal according to the present invention.
Detailed Description
The present invention is further described below in conjunction with the following figures and specific examples so that those skilled in the art may better understand the present invention and practice it, but the examples are not intended to limit the present invention.
The ChlF output of the system is measurable, the fluorescence curve can reflect the important characteristics of plant growth, and the ChlF is widely applied to the fields of fault diagnosis, automation, radar systems, missile tracking and the like, and the extended Kalman filtering technology can estimate the state quantity by utilizing the output quantity. The method for estimating the photosynthesis state variable by using the extended Kalman filtering technology provided by the invention adjusts the plant photosynthesis by using the most extensive PID control technology in the industry at present, and has important significance for plant growth control.
Step 1: testing of chlorophyll fluorescence curves using chlorophyll fluorometer
Chlorophyll fluorescence data was obtained from tea leaves collected from university campus (Wuxi, China). The leaves were picked in the morning of 2018, 7 months, and then quickly taken to a laboratory for testing. 12 leaves were used in the experiment, which were floated in water for two hours in order to prevent evaporation of water from the leaves; they were then dark-adapted for at least 15 minutes while consistently held in the clamp before the start of the ChlF measurement. ChlF was measured with FluorPen PSI (Photon Systems Instruments, Czech Reublic) and its OJIP protocol was selected. The intensity of illumination light was set to 750. mu. molphosons m-2s-1(the wavelength of light is in the range of 400-700 nm).
Step 2: and establishing a mathematical model according to the physiological process of plant photosynthesis.
1) Photoreaction stage and electron transfer
Photoreaction and subsequent electron transfer, from light absorption to the formation of NAPDH, also include a photoprotective mechanism when the illumination intensity is relatively strong.
2) Dark reaction stage
The carbon cycle is part of the "dark response" in photosynthesis, with the site of response being the chloroplast stroma. The cycle has three main phases: by CO2Carboxylated RuBP, CO2And reduction of ribulose 1, 5-bisphosphate (RuBP). Most plants incorporate immobilized CO by binding them to the second carbon of 5-carbon RuBP using Rubisco (RuBP carboxylase oxygenase)2A molecule. Thus CO2Is reduced. The six carbon compound thus formed is extremely unstable and immediately decomposes into two molecules of three carbon compound: 3-phosphoglycerate. The latter is then phosphorylated by ATP (formed by ATP synthase) to 1, 3-Diphosphoglycerate (DPGA) and then reduced by NADPH produced by two photoreactions. One of the triosephosphate molecules leaving the cycle is then used to synthesize glucose after a complex series of biochemical reactions. In general, 6 cycles produce one molecule of hexose. In addition, the cycle includes the formed ribulose-1, 5-bisphosphate molecule restarting the cycle. The chemical equation can be expressed as:
TABLE 1 notation of equations (1) - (22), corresponding substance concentrations and initializations
From equations (1) - (22), the following set of differential equations can be established:
and step 3: the experimental chlorophyll fluorescence curve was fitted to the mathematical model using the levenberg-marquardt algorithm.
The Levenberg-Marquardt method is one of the most common methods for system identification, and the fitting result of model simulation and experimental data is shown in the attached drawing 1, so that the model output can be well matched with the experimental data, and the photosynthesis model has good practical significance. Table 2 lists the values of the rate constants used for the model simulations.
Table 2 rate constant values for model simulations
| FIG. 1 of the drawings | FIG. 1 of the drawings | FIG. 1 of the drawings | |||
| k1u | 0.04 | k14 | 0.09 | k27 | 8.183 |
| k2 | 28.34 | k15 | 796.5 | k28 | 2.812 |
| k3 | 95.37 | k16 | 27.17 | k29 | 1.878 |
| k4 | 1310.2 | k17 | 15.795 | k30 | 8.88 |
| k5 | 0.012 | k18 | 38.41 | k31 | 6.13 |
| k6 | 144.3 | k19 | 5.514 | PQ0 | 5.25 |
| k7 | 0.02 | k20 | 10.53 | PC0 | 1.203 |
| k8 | 19299 | k21 | 17.33 | Fd0 | 1.499 |
| k9 | 21.31 | k22 | 24.68 | ATP0 | 18.14 |
| k10 | 325.7 | k23 | 0.0036 | NADPH0 | 7.5 |
| k11 | 481.1 | k24 | 0.227 | PGA0 | 0.024 |
| k12 | 590.9 | k25 | 1.23×10-5 | G | 0.75 |
| k13 | 8259.1 | k26 | 30.06 |
And 4, step 4: the state quantity is estimated from the chlorophyll fluorescence output of the system using extended kalman filtering techniques.
The Extended Kalman Filter (EKF) flow diagram is shown in fig. 2, and in the present invention, the actual output of the system is chlorophyll fluorescence. In fig. 2, the function f is the established photosynthesis model. The function h is F ═ Gk2x1。xkRepresenting model-based state variables (i.e., predicted values). y iskWhich may include process and measurement noise, corresponds to the actual fluorescence output value. Q and R are the covariance of the process noise and measurement noise possible during the chlorophyll fluorescence measurement (commonly known as gaussian noise). A and H can be calculated from the Jacobian matrix of the mathematical model. P is the chlorophyll fluorescence error estimation covariance matrix, and P0It can be arbitrarily initialized to a matrix of appropriate size because it will converge after a certain number of steps.
And 5: PID control techniques are used to regulate plant photosynthesis.
Reaction amount v ═ k15x7x8Is related to the reduction efficiency of PQ at a certain time. It can reflect the amount of photoelectrons used for forward photochemical reactions, which is positively correlated with the final sugar production. X can also be estimated using EKF based on measured ChlF7And x8The amount of (c). The dynamics of v are then controlled here using the most common PID (proportional, integral and derivative) closed loop control system. FIG. 4 shows a block diagram of a closed loop system for regulating plant photosynthesis using EKF-based PID control techniques. The controllable input is the light intensity u. The "controller" submodule in the system refers to the PID controller in this operation. By "power supply" sub-module is meant a light energy source such as a Light Emitting Diode (LED) or a high pressure sodium lamp (HPS). "execution unit" refers to a light regulator based on the controller output. The sub-module of the controlled plant refers to the established mathematical model. The "converter" submodule refers to the corresponding photosensor, which is replaced by a gain factor in the simulation. The reduction efficiency (v) of PQ is controlled to a desired reduction efficiency (v ^) using PID control as shown in FIG. 4. For example, we keep the light intensity constant under current greenhouse conditions, the reduction efficiency (v) of PQ will not be kept at a constant level because of the photoprotective mechanisms and other reaction kinetics reactions. However, by setting the PID control to a constant value to achieve the required PQ reduction efficiency (v ^), we can keep v constant using the controller in FIG. 4. Figure 5a shows the controlled post-autotuned lighting dynamics, generating control signals based on the deviation of the set desired PQ recovery efficiency (v ^) from the actual PQ recovery efficiency (v) of the system, automatically adjusting the voltage level of the power supply and gradually reaching the dynamic equilibrium, thus producing the illumination intensity shown in figure 5 (a). As can be seen from FIG. 5(b), the PQ reduction efficiency can be maintained constant in a PID controller in a short time, which is equivalent to artificially regulating the photosynthesis activity of plants, and is significant for the generation of plant photosynthesis efficiency and biomass, and the PQ reduction efficiency can be obtained according to the photosynthesis efficiency requiredThe control system is reasonably designed and the illumination resources are reasonably utilized. Constant levels of lighting intensity are commonly applied in greenhouse production, but too much light can lead to wasted energy, even affecting the photosynthesis mechanism and even damaging the plants due to photoprotection. This example illustrates how the photosynthesis-related quantity can be controlled to the desired dynamics, although it cannot be measured directly. The invention successfully applies the most common extended Kalman filtering technology and PID control technology in industrial application to the regulation of plant photosynthesis, has obvious regulation effect and has important significance for plant growth control.
The above-mentioned embodiments are merely preferred embodiments for fully illustrating the present invention, and the scope of the present invention is not limited thereto. The equivalent substitution or change made by the technical personnel in the technical field on the basis of the invention is all within the protection scope of the invention. The protection scope of the invention is subject to the claims.
Claims (4)
1. A photosynthesis PID control method based on chlorophyll fluorescence as a feedback signal is characterized by comprising the following steps:
step 1, acquiring a fluorescence curve by using a chlorophyll fluorescence instrument;
step 2, establishing a mathematical model of the whole process of photosynthesis;
step 3, fitting a mathematical model and a fluorescence curve obtained by an experiment, and determining a series of reaction rate constants;
step 4, estimating a state variable according to the fluorescence value output by the model and by utilizing an extended Kalman filtering technology;
step 5, regulating the photosynthesis activity by using a PID control technology;
step 2, establishing a mathematical model of the whole process of photosynthesis; the method specifically comprises the following steps:
1) photoreaction stage and electron transfer
Photoreaction and subsequent electron transfer, from light absorption to formation of NAPDH, and photoprotection mechanisms when the illumination intensity is relatively strong;
TABLE 1 notation of equations (1) - (16), corresponding substance concentrations and initializations
2) Dark reaction stage
The carbon cycle is part of the "dark response" in photosynthesis, with the site of response being the chloroplast stroma; the cycle has three main phases: by CO2Carboxylated RuBP, CO2Reduction of (3) and reduction of RuBP; most of themPlants incorporate immobilized CO by binding them to the second carbon of the 5-carbon RuBP using RuBP carboxylase oxygenase2A molecule; thus CO2Is reduced; the six carbon compound thus formed is extremely unstable and immediately decomposes into two molecules of three carbon compound: 3-phosphoglyceric acid; the latter is then phosphorylated by ATP to 1, 3-diphosphoglycerate, and then reduced by NADPH produced by two photoreactions to produce 3-triosephosphate; then, after a series of complex biochemical reactions, one of the triose-3-phosphate molecules is recycled off carbon for the synthesis of glucose; according to the light reaction and dark reaction processes, the following differential equation sets are established:
and step 3: fitting a mathematical model and a fluorescence curve obtained by an experiment to determine a series of reaction rate constants; "in, fit the chlorophyll fluorescence curve and mathematical model using Levenberg-Marquardt algorithm;
the following table lists the values of the rate constants used for the model simulation;
Step 4, estimating the state quantity of chlorophyll fluorescence from the output quantity of the system by using an extended Kalman filtering technology; the method specifically comprises the following steps:
first, setting
And P0Then according to the formula
Computing
And
then according to
Calculating KkAnd then calculate
Simultaneous calculation
The actual output of the system is chlorophyll fluorescence; the function f is the established photosynthesis model; the function h is F ═ Gk2x1；xkRepresenting model-based state variables; y iskCorresponding to the actual fluorescence output value, which may include process and measurement noise; q and R are the covariance of the possible process noise and measurement noise during chlorophyll fluorescence measurement; a and H can be calculated from the Jacobian matrix of the mathematical model; p is the chlorophyll fluorescence error estimation covariance matrix, and P0Can be arbitrarily initiatedTo a matrix of appropriate size, since it will converge after a certain number of steps;
step 5, regulating the photosynthesis of the plant by using a PID control technology; "specifically includes
Reaction amount v ═ k15x7x8Relating to the reduction efficiency of PQ at a certain moment; it may reflect the amount of photoelectrons used for the forward photochemical reaction, which is positively correlated with the final sugar production; x can also be estimated using EKF based on measured ChlF7And x8The amount of (c); then the most common PID closed loop control system is adopted to control the dynamics of v; firstly, the difference value between a set value v ^ and the actual output v of a control system is used as the input of a controller, the controller feeds back a control result to an execution unit after generating a control action, so that the execution unit can automatically adjust the power of a power supply to generate different illumination intensities u, the different illumination intensities act on a controlled plant, the blade of the controlled plant scatters out a fluorescence value, meanwhile, the actual output v of the control system is estimated through EKF according to the fluorescence value, and finally, the difference value between the set value and an experimental value is used as the input of a controller of the next sampling time; the controllable input is the light intensity u; the 'controller' submodule in the system refers to a PID controller in the work; the "power supply" submodule refers to a light energy source; "execution unit" refers to a light regulator based on the controller output; the sub-module of the controlled plant refers to an established mathematical model; the "converter" submodule refers to the corresponding photosensor, which is replaced by a gain factor in the simulation.
2. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the steps of the method of claim 1 are performed when the program is executed by the processor.
3. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method as claimed in claim 1.
4. A processor, characterized in that the processor is configured to run a program, wherein the program when running performs the method of claim 1.
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