Multi-wavelength collaborative LED plant light source real-time dynamic regulation and control method and system

Abstract

The invention discloses a multi-wavelength collaborative LED plant light source real-time dynamic regulation and control method and system, and the method comprises the steps: S1, obtaining basic data; s2, constructing a light source real-time dynamic regulation and control model; s3, a Levenberg-Marquardt algorithm is adopted to carry out iterative optimization training, and an optimized light source real-time dynamic regulation and control model is obtained; s4, adopting combined modulation to obtain a multi-wavelength collaborative LED plant light source real-time dynamic regulation and control model; s5, calculating an optimal PWM dimming signal of each waveband channel based on the multi-wavelength collaborative LED plant light source real-time dynamic regulation and control model; and S6, obtaining a regulation and control strategy of the plant light environment according to the optimal PWM dimming signal of each waveband channel, and realizing multi-wavelength cooperative intelligent regulation and control in the plant growth light environment. The system can effectively solve the problems of low light source utilization efficiency and high energy consumption of plants due to the fact that spectrum regulation and control are static, the adaptability is insufficient, and the regulation and control real-time performance and precision are poor in an existing plant light source system.

Description

Technical Field

[0001] The present invention relates to the technical field of plant lighting regulation, and in particular to a real-time dynamic regulation method and system for a multi-wavelength coordinated LED plant light source. Background Art

[0002] As the core support of modern agriculture, LED plant lighting technology has developed from single spectrum regulation to multi-wavelength coordination and intelligent control. Its core advantages lie in single and adjustable spectrum and dynamic light environment management combined with machine learning. In recent years, with the popularization of vertical agriculture and plant factories, LED light sources have been effective in increasing crop yields and shortening growth cycles. However, the existing technology still has the following key problems:

[0003] 1. Insufficient staticity and adaptability of spectrum regulation

[0004] Currently, most LED plant light sources use preset spectral ratios and lack dynamic response to plant growth stages and environmental parameters. For example, most LED plant light sources can only provide a fixed red-blue ratio, making it difficult to adjust the spectrum according to the real-time needs of plants, and the light energy utilization rate is low. In addition, full-spectrum simulation technology still has problems such as incomplete wavelength coverage and uneven light intensity distribution, which affect plant photosynthesis.

[0005] 2. Real-time and precision limitations of intelligent control

[0006] Most existing control models are based on empirical thresholds or offline data and cannot provide real-time feedback. For example, some systems rely on timers to control the light cycle and ignore changes in plant growth requirements. Although intelligent control systems have introduced environmental sensors, dynamic optimization algorithms under multi-parameter coupling are still immature, making it difficult to balance energy consumption and crop quality.

[0007] In summary, there is an urgent need for a dynamic adjustment method with multi-parameter coupling, real-time feedback and low energy consumption. Summary of the invention

[0008] The purpose of the present invention is to overcome the shortcomings of the prior art and provide a real-time dynamic control method for a multi-wavelength collaborative LED plant light source, which can effectively solve the problems of static spectral control and insufficient adaptability of the existing plant light source system, poor control real-time and accuracy, resulting in low efficiency of light source utilization and high energy consumption of plants.

[0009] Another object of the present invention is to provide a multi-wavelength coordinated LED plant light source real-time dynamic control system.

[0010] The purpose of the present invention is achieved through the following technical solutions:

[0011] A method for real-time dynamic control of a multi-wavelength coordinated LED plant light source, comprising the steps of:

[0012] S1. Obtain the basic data required for photosynthetically active radiation per unit area on the illuminated surface of the plant canopy;

[0013] S2. Based on the acquired basic data, a real-time dynamic control model of light source is constructed using the Ploy2D method;

[0014] S3. According to the light source real-time dynamic control model, the Levenberg-Marquardt algorithm is used to perform iterative optimization training based on basic data to obtain an optimized light source real-time dynamic control model;

[0015] S4. According to the optimized light source real-time dynamic control model, a multi-wavelength collaborative LED plant light source real-time dynamic control model is obtained by using combined modulation;

[0016] S5. According to the set target spectrum ratio, target light intensity and the height from the light source to the illuminated surface of the plant canopy during the plant growth process, the optimal PWM dimming signal of each band channel is calculated based on the real-time dynamic control model of multi-wavelength collaborative LED plant light source;

[0017] S6. Obtain a control strategy for the plant light environment based on the optimal PWM dimming signal of each band channel to achieve multi-wavelength coordinated intelligent control of the plant growth light environment.

[0018] Further, in step S1, the following operations are specifically performed:

[0019] The wide spectrum light source white LED that simulates the full spectrum of natural light is the basic band, and the two main absorption peaks of the plant photosynthetic pigment absorption spectrum, the 660nm band red LED and the 440nm band blue LED, are the adjustment bands. The multi-wavelength collaborative LED lamp bead module is composed of white LED, red LED and blue LED;

[0020] The linear light source array formed by the multi-wavelength coordinated LED lamp bead module is optimized and designed to obtain the array arrangement with the best light intensity uniformity and color mixing uniformity, and obtain the multi-wavelength coordinated LED light source module;

[0021] By adopting the constant current mode and PWM dimming input signal, the driving current duty cycle of the white wavelength W channel, red wavelength R channel and blue wavelength B channel of the multi-wavelength collaborative LED light source module is changed respectively to realize the regulation of the light intensity of the three bands, thereby obtaining the basic data of light intensity at different heights and different band ratios of the plant canopy.

[0022] Furthermore, the real-time dynamic control model of the light source is specifically:

[0023] P t =P0+ah+by t +ch2 +dy t 2 +fhy t 2

[0024] Among them, P t is the dependent variable, which represents the light intensity of each wavelength channel on the illuminated surface of the plant canopy, y t is the independent variable, representing the duty cycle of the driving current at each wavelength, h represents the height from the light source to the illuminated surface of the plant canopy, and P0, a, b, c, d, and f are the corresponding control parameters.

[0025] Further, in step S3, the following operations are specifically performed:

[0026] Based on the basic data, the root mean square error is used as the evaluation function, and the Levenberg-Marquardt algorithm is used to iteratively optimize the light source real-time dynamic control model to obtain the optimized light source real-time dynamic control model, including the single-channel band real-time dynamic control model of white wavelength W, red wavelength R and blue wavelength B, as follows:

[0027] P w =11.31-0.088h+154.88y w +0.000169h 2 -19.16y w 2 -0.21hy w 2

[0028] P R =11.24-0.1h+187.16y R +0.00021h 2 -5.29y R 2 -0.28hy R 2

[0029] P B =10.56-0.09h+159.9y B +0.00018h 2 -12.32y B 2 -0.24hy B 2

[0030] Where h represents the height from the light source to the illuminated surface of the plant canopy, y W ,y R and Bare independent variables, representing the duty cycle of white wavelength W, red wavelength R and blue wavelength B, respectively. w , P R and P B are dependent variables, representing the light intensity of the white wavelength channel, the red wavelength channel, and the blue wavelength channel on the illuminated surface of the plant canopy, respectively.

[0031] Further, in step S4, the following operations are specifically performed:

[0032] The optimized light source real-time dynamic control model is combined and modulated to obtain a multi-wavelength collaborative LED plant light source real-time dynamic control model, as follows:

[0033] P f =33.11-0.278h+0.000589h2+187.16y R +159.91y B +154.88y W -5.29y R 2 -12.32y B 2 -19.16y W 2 -0.28hy R -0.24hy B -0.21hy W

[0034] Among them, P f is the optimized value of the total light intensity of the illuminated surface of the plant canopy, h represents the height from the light source to the illuminated surface of the plant canopy, and y W ,y R and B are independent variables, representing the duty cycle of white wavelength W, red wavelength R and blue wavelength B respectively.

[0035] Further, in step S5, the following operations are specifically performed:

[0036] The height from the light source to the illuminated surface of the plant canopy during the plant growth process is collected, and the target spectral ratio data, target light intensity and collected height set in the plant growth stage are sent to the multi-wavelength collaborative LED plant light source real-time dynamic control model for inversion to obtain the optimal PWM dimming signal corresponding to each channel.

[0037] Further, in step S6, the following operations are specifically performed:

[0038] S6.1. According to the plant growth requirements, input the set target total light intensity of the plant canopy and the spectrum ratio of each band, and calculate the target light intensity of each band of the LED plant light source;

[0039] S6.2. Based on the height from the light source to the plant canopy and the target light intensity of each band, the target duty cycle of each wavelength band is calculated using the optimized light source real-time dynamic control model;

[0040] S6.3, calculating the actual light intensity of each band based on the actual total light intensity of the plant canopy measured by the real-time light sensor, and then calculating the difference between the actual light intensity of each band and the target light intensity;

[0041] S6.4. Based on the difference between the actual light intensity of each band and the target light intensity, a multi-wavelength collaborative LED plant light source real-time dynamic control model is used to calculate the adjustment duty cycle of each band;

[0042] S6.5. Calculate the actual duty cycle of each wavelength band of the plant light source system according to the target duty cycle and adjustment duty cycle of each wavelength band, and output it to the control system of the plant light source system for adjustment;

[0043] S6.6. According to the adjusted light source, the actual total light intensity of the plant canopy measured by the real-time light sensor is compared with the optimized value of the total light intensity of the illuminated surface of the plant canopy. If the accuracy is less than the preset ratio, the adjustment is ended, otherwise return to step S6.3.

[0044] Furthermore, in the process of real-time dynamic control of the light source, a multi-wavelength collaborative LED plant light source real-time dynamic control model is used to optimize the calculation of the optimal value of the total light intensity of the illuminated surface of the plant canopy according to the height and the duty cycle of each channel.

[0045] Another object of the present invention is achieved by the following technical solutions:

[0046] A multi-wavelength coordinated LED plant light source real-time dynamic control system is applied to the multi-wavelength coordinated LED plant light source real-time dynamic control method described above, comprising:

[0047] A data acquisition module is used to obtain the basic data required for photosynthetically active radiation per unit area on the illuminated surface of the plant canopy;

[0048] The light source real-time dynamic control model construction module is used to construct the light source real-time dynamic control model using the Ploy2D method based on the acquired basic data;

[0049] The model optimization module is used to dynamically adjust the model according to the light source in real time, and perform iterative optimization training using the Levenberg-Marquardt algorithm based on basic data to obtain an optimized light source real-time dynamic adjustment model;

[0050] A multi-wavelength collaborative LED plant light source real-time dynamic control model modulation module is used to obtain a multi-wavelength collaborative LED plant light source real-time dynamic control model by combined modulation according to the optimized light source real-time dynamic control model;

[0051] The calculation module is used to calculate the optimal PWM dimming signal of each band channel based on the real-time dynamic control model of multi-wavelength collaborative LED plant light source according to the set target spectrum ratio, target light intensity and the height from the light source to the illuminated surface of the plant canopy during the plant growth process;

[0052] The control module is used to obtain the control strategy of the plant light environment according to the optimal PWM dimming signal of each band channel, and realize the coordinated intelligent control of multiple wavelengths in the plant growth light environment.

[0053] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0054] The present invention determines efficient spectral combinations based on the physiological needs of plant light quality, and develops a real-time dynamic control model for multi-wavelength collaborative LED plant light sources. It can accurately and dynamically adjust the spectral ratio and light intensity of the light source according to the real-time changes in the plant growth height during the plant growth process, ensuring that the plant canopy maintains a stable lighting environment. On the one hand, it improves the utilization rate of the light source efficiency of plants, and on the other hand, it significantly reduces the consumption of electrical energy. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 This is a flow chart of the method of Example 1.

[0056] Figure 2 This is an implementation flow chart of Example 1.

[0057] Figure 3 This is the main view of the control system of the plant light source system.

[0058] Figure 4 A side view of the control system of the plant light source system.

[0059] Figure 5 This is a structural diagram of the data acquisition system.

[0060] Figure 6 is the target parameter of Example 1.

[0061] Figure 7 are the actual parameters of Example 1.

[0062] Figure 8 These are the adjustment parameters obtained in Example 1.

[0063] Fig. 9 The actual output light intensity and error of Example 1. DETAILED DESCRIPTION

[0064] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0065] Embodiment 1:

[0066] like Figure 1 , Figure 2 As shown, this embodiment provides a method for real-time dynamic control of a multi-wavelength coordinated LED plant light source, including the steps of:

[0067] S1, such as Figure 3 As shown, the data acquisition system is used to obtain the basic data required for photosynthetically active radiation per unit area on the illuminated surface of the plant canopy; the following operations are performed specifically:

[0068] The wide spectrum light source white LED that simulates the full spectrum of natural light is the basic band, and the two main absorption peaks of the plant photosynthetic pigment absorption spectrum, the 660nm band red LED and the 440nm band blue LED, are the adjustment bands. The multi-wavelength collaborative LED lamp bead module is composed of white LED, red LED and blue LED;

[0069] The linear light source array formed by the multi-wavelength coordinated LED lamp bead module is optimized and designed to obtain the array arrangement with the best light intensity uniformity and color mixing uniformity, and obtain the multi-wavelength coordinated LED light source module;

[0070] By adopting the constant current mode and PWM dimming input signal, the driving current duty cycle of the white wavelength W channel, red wavelength R channel and blue wavelength B channel of the multi-wavelength collaborative LED light source module is changed respectively to realize the regulation of the light intensity of the three bands, thereby obtaining the basic data of light intensity at different heights and different band ratios of the plant canopy.

[0071] S2. Based on the acquired basic data, a real-time dynamic control model of light source is constructed using the Ploy2D method;

[0072] The real-time dynamic control model of the light source is specifically:

[0073] P t =P0+ah+by t +ch 2 +dy t 2 +fhy t 2

[0074] Among them, P t is the dependent variable, which represents the light intensity of each wavelength channel on the illuminated surface of the plant canopy, y t is the independent variable, representing the duty cycle of the driving current at each wavelength, h represents the height from the light source to the illuminated surface of the plant canopy, and P0, a, b, c, d, and f are the corresponding control parameters.

[0075] S3. According to the real-time dynamic control model of the light source, the Levenberg-Marquardt algorithm is used to perform iterative optimization training based on basic data to obtain an optimized real-time dynamic control model of the light source; specifically, the following operations are performed:

[0076] Based on the basic data, the root mean square error is used as the evaluation function, and the Levenberg-Marquardt algorithm is used to iteratively optimize the light source real-time dynamic control model to obtain the optimized light source real-time dynamic control model, including the single-channel band real-time dynamic control model of white wavelength W, red wavelength R and blue wavelength B, as follows:

[0077] P w =11.31-0.088h+154.88y w +0.000169h 2 -19.16y w 2 -0.21hy w 2

[0078] P R =11.24-0.1h+187.16y R +0.00021h 2 -5.29y R 2 -0.28hy R 2

[0079] P B =10.56-0.09h+159.9y B +0.00018h 2 -12.32y B 2 -0.24hy B 2

[0080] Where h represents the height from the light source to the illuminated surface of the plant canopy, y W ,y R and B are independent variables, representing the duty cycle of white wavelength W, red wavelength R and blue wavelength B, respectively.w , P R and P B are dependent variables, representing the light intensity of the white wavelength channel, the red wavelength channel, and the blue wavelength channel on the illuminated surface of the plant canopy, respectively.

[0081] S4. According to the optimized light source real-time dynamic control model, a multi-wavelength collaborative LED plant light source real-time dynamic control model is obtained by using combined modulation; the following operations are specifically performed:

[0082] The optimized light source real-time dynamic control model is combined and modulated to obtain a multi-wavelength collaborative LED plant light source real-time dynamic control model, as follows:

[0083] P f =33.11-0.278h+0.000589h2+187.16y R +159.91y B +154.88y W -5.29y R 2 -12.32y B 2 -19.16y W 2 -0.28hy R -0.24hy B -0.21hy W

[0084] Among them, P f is the optimized value of the total light intensity of the illuminated surface of the plant canopy, h represents the height from the light source to the illuminated surface of the plant canopy, and y W ,y R and B are independent variables, representing the duty cycle of white wavelength W, red wavelength R and blue wavelength B respectively.

[0085] S5. According to the set target spectrum ratio, target light intensity and the height from the light source to the illuminated surface of the plant canopy during the plant growth process, the optimal PWM dimming signal of each band channel is calculated based on the real-time dynamic control model of multi-wavelength collaborative LED plant light source; the following operations are performed specifically:

[0086] The height from the light source to the illuminated surface of the plant canopy during the plant growth process is collected, and the target spectral ratio data, target light intensity and collected height set in the plant growth stage are sent to the multi-wavelength collaborative LED plant light source real-time dynamic control model for inversion to obtain the optimal PWM dimming signal corresponding to each channel.

[0087] S6. Obtain the control strategy of the plant light environment according to the optimal PWM dimming signal of each band channel to realize the multi-wavelength coordinated intelligent control of the plant growth light environment; specifically perform the following operations:

[0088] S6.1, if Figure 6 As shown in the figure, according to the plant growth requirements, the set plant canopy target total light intensity and the spectrum ratio of each band are input, and the target light intensity of each band of the LED plant light source is calculated.

[0089]

[0090] Among them, P w,aim , P R,aim and P B,aim are dependent variables, representing the target white wavelength channel light intensity, target red wavelength channel light intensity, and target blue wavelength channel light intensity on the illuminated surface of the plant canopy; P f,aim Indicates the set total light intensity of the plant canopy target; x w、 x R and x B They represent the target light quality ratio of white light W, the target light quality ratio of red light R, and the target light quality ratio of blue light B respectively;

[0091] S6.2. Based on the height from the light source to the plant canopy and the target light intensity of each band, the target duty cycle of each wavelength band is calculated using the optimized light source real-time dynamic control model.

[0092]

[0093] Among them, P w,aim , P R,aim and P B,aim They represent the target white wavelength channel light intensity, target red wavelength channel light intensity and target blue wavelength channel light intensity of the illuminated surface of the plant canopy respectively; h represents the height from the light source to the illuminated surface of the plant canopy; y w,aim、 y R,aim and B,aim There is a unique solution for the dependent variable, which represents the target duty cycle of white wavelength W, red wavelength R and blue wavelength B respectively, and the target duty cycle is between 0 and 1;

[0094] S6.3, if Figure 7 As shown in the figure, the actual total light intensity P of the plant canopy measured by the real-time light sensor L , calculate the actual light intensity of each band, and then calculate the difference between the actual light intensity of each band and the target light intensity.

[0095] △P w =P w,aim -PLw

[0096] △P R =P R,aim -P LR

[0097] △P B =P B,aim -P LB

[0098] Among them, △P w , △P R and △P B They represent the difference between the target white wavelength channel light intensity and the actual white wavelength channel light intensity, the difference between the target red wavelength channel light intensity and the actual red wavelength channel light intensity, and the difference between the target blue wavelength channel light intensity and the actual blue wavelength channel light intensity on the illuminated surface of the plant canopy, respectively. Lw , P LR and P LB Respectively represent the actual white wavelength channel light intensity, the actual red wavelength channel light intensity and the actual blue wavelength channel light intensity;

[0099] S6.4, if Figure 8 As shown in the figure, based on the difference between the actual light intensity of each band and the target light intensity, the multi-wavelength collaborative LED plant light source real-time dynamic control model is used to calculate the adjustment duty cycle of each band.

[0100]

[0101] Among them, △yf W、 △yf R and △yf B are dependent variables, representing the duty cycle of white wavelength W adjustment, red wavelength R adjustment, and blue wavelength B adjustment;

[0102] S6.5. The actual duty cycle of each wavelength band of the plant light source system is calculated based on the target duty cycle and the adjusted duty cycle of each wavelength band, and output to the control system of the plant light source system for adjustment. The control system implementation platform is as follows: Figure 4 , Figure 5 As shown,

[0103] y LW =y w,aim +△yf W

[0104] y LR =y R,aim +△yf R

[0105] y LB =yB,aim +△yf B ;

[0106] S6.6, if Fig. 9 As shown in the figure, according to the adjusted light source, the actual total light intensity P of the plant canopy measured by the real-time light sensor is L The optimal value of total light intensity P of the illuminated surface of the plant canopy f Perform a comparison, if the accuracy is less than 5%, end the adjustment, otherwise return to step S6.3.

[0107] In the process of real-time dynamic control of light sources, the multi-wavelength collaborative LED plant light source real-time dynamic control model is used to optimize the calculation of the optimal value P of the total light intensity of the illuminated surface of the plant canopy according to the height and the duty cycle of each channel. f .

[0108] Embodiment 2:

[0109] This embodiment provides a multi-wavelength coordinated LED plant light source real-time dynamic control system, which is applied to the multi-wavelength coordinated LED plant light source real-time dynamic control method of embodiment 1, including:

[0110] A data acquisition module is used to obtain the basic data required for photosynthetically active radiation per unit area on the illuminated surface of the plant canopy;

[0111] The light source real-time dynamic control model construction module is used to construct the light source real-time dynamic control model using the Ploy2D method based on the acquired basic data;

[0112] The model optimization module is used to dynamically adjust the model according to the light source in real time, and perform iterative optimization training using the Levenberg-Marquardt algorithm based on basic data to obtain an optimized light source real-time dynamic adjustment model;

[0113] A multi-wavelength collaborative LED plant light source real-time dynamic control model modulation module is used to obtain a multi-wavelength collaborative LED plant light source real-time dynamic control model by combined modulation according to the optimized light source real-time dynamic control model;

[0114] The calculation module is used to calculate the optimal PWM dimming signal of each band channel based on the real-time dynamic control model of multi-wavelength collaborative LED plant light source according to the set target spectrum ratio, target light intensity and the height from the light source to the illuminated surface of the plant canopy during the plant growth process;

[0115] The control module is used to obtain the control strategy of the plant light environment according to the optimal PWM dimming signal of each band channel, and realize the coordinated intelligent control of multiple wavelengths in the plant growth light environment.

[0116] The above is only a preferred embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical solution and invention concept of the present invention within the scope disclosed by the present invention, which shall fall within the protection scope of the present invention.

Claims

1. A method for real-time dynamic control of multi-wavelength coordinated LED plant light sources, characterized in that: Including steps, S1. Obtain the basic data required for photosynthetically active radiation per unit area on the illuminated surface of the plant canopy; S2. Based on the acquired basic data, a real-time dynamic control model of light source is constructed using the Ploy2D method; S3. According to the light source real-time dynamic control model, the Levenberg-Marquardt algorithm is used to perform iterative optimization training based on basic data to obtain an optimized light source real-time dynamic control model; S4. According to the optimized light source real-time dynamic control model, a multi-wavelength collaborative LED plant light source real-time dynamic control model is obtained by using combined modulation; S5. According to the set target spectrum ratio, target light intensity and the height from the light source to the illuminated surface of the plant canopy during the plant growth process, the optimal PWM dimming signal of each band channel is calculated based on the real-time dynamic control model of multi-wavelength collaborative LED plant light source; S6. Obtain a control strategy for the plant light environment based on the optimal PWM dimming signal of each band channel to achieve multi-wavelength coordinated intelligent control of the plant growth light environment.

2. The multi-wavelength coordinated LED plant light source real-time dynamic control method according to claim 1 is characterized in that: In step S1, the following operations are specifically performed: The wide spectrum light source white LED that simulates the full spectrum of natural light is the basic band, and the two main absorption peaks of the plant photosynthetic pigment absorption spectrum, the 660nm band red LED and the 440nm band blue LED, are the adjustment bands. The multi-wavelength collaborative LED lamp bead module is composed of white LED, red LED and blue LED; The linear light source array formed by the multi-wavelength coordinated LED lamp bead module is optimized and designed to obtain the array arrangement with the best light intensity uniformity and color mixing uniformity, and obtain the multi-wavelength coordinated LED light source module; By adopting the constant current mode and PWM dimming input signal, the driving current duty cycle of the white wavelength W channel, red wavelength R channel and blue wavelength B channel of the multi-wavelength collaborative LED light source module is changed respectively to realize the regulation of the light intensity of the three bands, thereby obtaining the basic data of light intensity at different heights and different band ratios of the plant canopy.

3. The multi-wavelength coordinated LED plant light source real-time dynamic control method according to claim 1 is characterized in that: The real-time dynamic control model of the light source is specifically: P t =P0+ah+by t +ch 2 +to t 2 +fhy t 2 Among them, P t is the dependent variable, which represents the light intensity of each wavelength channel on the illuminated surface of the plant canopy, y t is the independent variable, representing the duty cycle of the driving current at each wavelength, h represents the height from the light source to the illuminated surface of the plant canopy, and P0, a, b, c, d, and f are the corresponding control parameters.

4. The multi-wavelength coordinated LED plant light source real-time dynamic control method according to claim 1 is characterized in that: In step S3, the following operations are specifically performed: Based on the basic data, the root mean square error is used as the evaluation function, and the Levenberg-Marquardt algorithm is used to iteratively optimize the light source real-time dynamic control model to obtain the optimized light source real-time dynamic control model, including the single-channel band real-time dynamic control model of white wavelength W, red wavelength R and blue wavelength B, as follows: P w =11.31-0.088h+154.88y w +0.000169h 2 -19.16y w 2 -0.21hy w 2 P R =11.24-0.1h+187.16y R +0.00021h 2 -5.29y R 2 -0.28hy R 2 P B =10.56-0.09h+159.9y B +0.00018h 2 -12.32y B 2 -0.24hy B 2 Where h represents the height from the light source to the illuminated surface of the plant canopy, y W ,y R and B are independent variables, representing the duty cycle of white wavelength W, red wavelength R and blue wavelength B, respectively. w , P R and P B are dependent variables, representing the light intensity of the white wavelength channel, the red wavelength channel, and the blue wavelength channel on the illuminated surface of the plant canopy, respectively.

5. The multi-wavelength coordinated LED plant light source real-time dynamic control method according to claim 1 is characterized in that: In step S4, the following operations are specifically performed: The optimized light source real-time dynamic control model is combined and modulated to obtain a multi-wavelength collaborative LED plant light source real-time dynamic control model, as follows: P f =33.11-0.278h+0.000589h2+187.16y R +159.91y B +154.88y W -5.29y R 2 -12.32y B 2 -19.16y W 2 -0.28hy R -0.24hy B -0.21hy W Among them, P f is the optimized value of the total light intensity of the illuminated surface of the plant canopy, h represents the height from the light source to the illuminated surface of the plant canopy, and y W ,y R and B are independent variables, representing the duty cycle of white wavelength W, red wavelength R and blue wavelength B respectively.

6. The multi-wavelength coordinated LED plant light source real-time dynamic control method according to claim 1 is characterized in that: In step S5, the following operations are specifically performed: The height from the light source to the illuminated surface of the plant canopy during the plant growth process is collected, and the target spectral ratio data, target light intensity and collected height set in the plant growth stage are sent to the multi-wavelength collaborative LED plant light source real-time dynamic control model for inversion to obtain the optimal PWM dimming signal corresponding to each channel.

7. The multi-wavelength coordinated LED plant light source real-time dynamic control method according to claim 5 is characterized in that: In step S6, the following operations are specifically performed: S6.

1. According to the plant growth requirements, input the set target total light intensity of the plant canopy and the spectrum ratio of each band, and calculate the target light intensity of each band of the LED plant light source; S6.

2. Based on the height from the light source to the plant canopy and the target light intensity of each band, the target duty cycle of each wavelength band is calculated using the optimized light source real-time dynamic control model; S6.3, calculating the actual light intensity of each band based on the actual total light intensity of the plant canopy measured by the real-time light sensor, and then calculating the difference between the actual light intensity of each band and the target light intensity; S6.

4. Based on the difference between the actual light intensity of each band and the target light intensity, a multi-wavelength collaborative LED plant light source real-time dynamic control model is used to calculate the adjustment duty cycle of each band; S6.

5. Calculate the actual duty cycle of each wavelength band of the plant light source system according to the target duty cycle and adjustment duty cycle of each wavelength band, and output it to the control system of the plant light source system for adjustment; S6.

6. According to the adjusted light source, the actual total light intensity of the plant canopy measured by the real-time light sensor is compared with the optimized value of the total light intensity of the illuminated surface of the plant canopy. If the accuracy is less than the preset ratio, the adjustment is ended, otherwise return to step S6.

3.

8. The multi-wavelength coordinated LED plant light source real-time dynamic control method according to claim 7 is characterized in that: In the process of real-time dynamic control of the light source, the multi-wavelength collaborative LED plant light source real-time dynamic control model is used to optimize the calculation of the optimal value of the total light intensity of the illuminated surface of the plant canopy according to the height and duty cycle of each channel.

9. A multi-wavelength collaborative LED plant light source real-time dynamic control system, characterized in that: The real-time dynamic control method of the multi-wavelength coordinated LED plant light source as described in any one of claims 1 to 8 comprises: A data acquisition module is used to obtain the basic data required for photosynthetically active radiation per unit area on the illuminated surface of the plant canopy; The light source real-time dynamic control model construction module is used to construct the light source real-time dynamic control model using the Ploy2D method based on the acquired basic data; The model optimization module is used to dynamically adjust the model according to the light source in real time, and perform iterative optimization training using the Levenberg-Marquardt algorithm based on basic data to obtain an optimized light source real-time dynamic adjustment model; A multi-wavelength collaborative LED plant light source real-time dynamic control model modulation module is used to obtain a multi-wavelength collaborative LED plant light source real-time dynamic control model by combined modulation according to the optimized light source real-time dynamic control model; The calculation module is used to calculate the optimal PWM dimming signal of each band channel based on the real-time dynamic control model of multi-wavelength collaborative LED plant light source according to the set target spectrum ratio, target light intensity and the height from the light source to the illuminated surface of the plant canopy during the plant growth process; The control module is used to obtain the control strategy of the plant light environment according to the optimal PWM dimming signal of each band channel, and realize the coordinated intelligent control of multiple wavelengths in the plant growth light environment.

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