Environmental dynamic self-adaptive control method and system based on phenology driving and storage medium
By introducing effective accumulated temperature (GDD) to dynamically identify crop growth stages and adaptively adjust environmental parameters, the problems of growth imbalance and system instability in greenhouse environmental control are solved, achieving efficient and stable crop growth control.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- GUILIN UNIV OF AEROSPACE TECH
- Filing Date
- 2026-03-25
- Publication Date
- 2026-05-12
AI Technical Summary
Existing greenhouse environmental control technologies cannot match crop growth needs in real time, leading to growth imbalances, reduced stress resistance, and unstable system operation, making them unable to cope with external weather disturbances.
Effective accumulated temperature (GDD) is introduced to dynamically identify crop growth stages, and online calculation and hysteresis control are performed through a PLC controller to dynamically adjust environmental parameters. Combined with hysteresis tolerance mechanism and hysteresis control logic, adaptive adjustment of environmental parameters is achieved.
It improves the accuracy and stability of environmental control, enhances crop growth rate and yield, extends equipment lifespan, and reduces energy consumption.
Smart Images
Figure CN122018321A_ABST
Abstract
Description
Technical Field
[0001] This invention specifically relates to a phenologically driven environmental dynamic adaptive control method, system, and storage medium, and relates to the field of intelligent greenhouse environment control technology. Background Technology
[0002] For high-value sprouts, their quality, yield, and growth cycle are comprehensively affected by microenvironmental factors within the greenhouse, such as temperature, humidity, and light. The environmental requirements of the target crop vary significantly at different phenological stages, such as germination, growth, and maturity. For example, suitable temperature and humidity are required during the germination stage to promote growth.
[0003] For rapid seedling emergence, sufficient light and suitable temperature are needed during the growth period to facilitate nutrient accumulation, while precise environmental control is required during the maturity period.
[0004] Currently, greenhouse environmental control mainly employs two mainstream technical solutions: fixed threshold control and multi-stage static control. Fixed threshold control sets a set of fixed upper and lower limits for environmental parameters throughout the entire growth period, activating corresponding actuators when sensor values exceed these limits. This method ignores the dynamic physiological needs of crops, representing a typical open-loop control approach with low precision and a tendency to cause growth imbalances. While multi-stage static control divides the growth period into several stages based on experience and sets static environmental parameter thresholds for each stage, it still considers stage differences but remains an open-loop control strategy. It cannot address deviations from the preset timetable caused by varietal differences, weather disturbances, or fluctuations in seedling vigor.
[0005] The existing technology suffers from the following major drawbacks: First, low matching degree of physiological needs. The control decisions are not directly coupled with the actual phenological processes of the crop, resulting in a time lag between environmental supply and crop physiological needs, which easily leads to problems such as unbalanced growth rates, decreased stress resistance, and inconsistent quality. Second, lack of adaptive adjustment capability. The greenhouse microclimate is strongly affected by external meteorological disturbances, and the fixed threshold control strategy cannot dynamically adjust environmental targets according to the actual growth rate of the crop, making it difficult to cope with random fluctuations in the microclimate. Third, poor system operational stability: The instantaneous environmental fluctuations near the threshold boundary are not considered, which can easily lead to flickering of growth stage determination or frequent start-stop of the actuator, not only increasing energy consumption but also severely shortening the service life of the equipment.
[0006] Therefore, there is an urgent need for an intelligent control method that can couple environmental control with the actual crop growth process in real time and has dynamic adaptive adjustment capabilities to solve the above-mentioned technical problems. Summary of the Invention
[0007] To address the problems mentioned in the background section, the present invention aims to provide a phenologically driven environmental dynamic adaptive control method, system, and storage medium, comprising:
[0008] S1. The system is initialized and status is detected. The control mode is selected based on the detection results.
[0009] S2, according to the sampling period via PLC controller Environmental parameters are collected and the effective accumulated temperature (GDD) is calculated and updated online.
[0010]
[0011] In the above formula, Accumulated effective temperature at time t , Let t be the average air temperature (°C) during the sampling period at time t. The base temperature (°C) for the growth of the target crop. The sampling time interval (d) The maximum value function represents the effective accumulated temperature.
[0012] S3. Based on GDD, the phenological stage of the target crop is dynamically identified and confirmed to determine the growth stage of the target crop;
[0013] S4. Based on the growth stage of the target crop, determine the corresponding staged environmental control target values;
[0014] S5. Based on the deviation between the current GDD and the theoretical GDD, dynamically adjust the environmental control target value and generate a dynamic environmental control reference value.
[0015] S6. Compare the real-time collected environmental parameters with the dynamic environmental control reference value, and drive the actuator to act based on the hysteresis control logic;
[0016] S7. Repeat steps S2 to S6 to achieve adaptive control of the greenhouse environment.
[0017] Preferably, the dynamic identification and confirmation of the phenological stage of the target crop based on GDD includes: when GDD(t) falls into the threshold interval corresponding to the i-th growth stage of the target crop. If the target crop is in the i-th growth stage, then GDD(t) is determined to be in the i-th growth stage; if GDD(t) continues to satisfy and duration When the target crop's growth stage is determined, the next stage is switched; among them, Indicates the first The lag tolerance for GDD during the reproductive stage is taken as 10% of the maximum threshold for that stage. This indicates the threshold for the duration of continuous overrun, set to 1 hour.
[0018] Preferably, the environmental control target values include nominal temperature, nominal relative humidity, and nominal light intensity.
[0019] Preferably, the formula for calculating the deviation between the current GDD and the theoretical GDD is: .
[0020] Preferably, the dynamic adjustment of the environmental control target value includes: establishing a functional relationship between the dynamic environmental control target value and the GDD deviation by adjusting the coefficient k, wherein the adjustment coefficient k ranges from 0.3 to 0.5 during the sensitive growth period of the target crop and from 0.6 to 0.8 during the vigorous growth period.
[0021] Preferably, comparing the real-time collected environmental parameters with the dynamic environmental control reference value and driving the actuator based on hysteresis control logic includes: independently setting the hysteresis bandwidth for each environmental parameter; driving the actuator when each real-time environmental parameter exceeds the corresponding hysteresis bandwidth threshold range; and stopping the actuator when the parameter returns to the range.
[0022] Preferably, for temperature control, a temperature hysteresis bandwidth is set. ,when When, the drive executes to start heating, when When this happens, cooling will be initiated. Stop when the time is right; for relative humidity control, set the relative humidity hysteresis bandwidth. ,when When, humidification will be started. Dehumidification is started at the appropriate time. Stop when the light intensity is reached; for light intensity control, set the light intensity hysteresis bandwidth. ,when When, the supplementary lighting is activated. Then the sunshade will be activated. Stop when the time comes.
[0023] Preferably, it also includes a manual control mode: in this mode, the PLC disables the automatic control logic and directly responds to the instructions of the human-machine interface (HMI) to control the actuators independently.
[0024] The present invention also provides an environmental dynamic adaptive control system based on phenology-driven methods, comprising:
[0025] At least one PLC controller;
[0026] Multiple environmental parameter sensors are communicatively connected to the PLC controller;
[0027] Multiple environmental control actuators are driven by the PLC controller;
[0028] A human-machine interface (HMI) is connected to the PLC controller and is used for parameter setting, status display, and mode switching.
[0029] The PLC controller is configured to execute any of the control methods described above.
[0030] The present invention also provides a computer-readable storage medium storing a computer program, characterized in that, when the computer program is executed by a processor, it implements the steps of the control method as described in any of the preceding claims.
[0031] Compared with the prior art, the beneficial effects of the present invention are as follows:
[0032] I. This invention introduces effective accumulated temperature (GDD) into the crop environmental control process. By calculating the cumulative GDD value online, it achieves accurate identification of the target crop growth stage and explicitly incorporates crop phenological information into the control decision. This solves the problem that traditional fixed threshold control cannot match the dynamic physiological needs of crops and improves the targeting and accuracy of environmental control.
[0033] Second, a dynamic threshold adjustment mechanism based on GDD deviation is set up, which can flexibly adjust the environmental control target value according to the deviation between the actual crop growth process and the theoretical expectation, effectively respond to the impact of external disturbances on the greenhouse microclimate, ensure the time matching degree between environmental supply and the physiological needs of target crops, promote the growth and development of garlic sprouts, and improve yield and quality.
[0034] Third, the introduction of lag tolerance and lag control mechanisms avoids frequent switching of reproductive stages caused by short-term environmental fluctuations near the threshold boundary. On the other hand, it reduces the frequent start-up and shutdown of the actuators, improves the stability of system operation, extends the service life of equipment, and reduces energy consumption and maintenance costs.
[0035] Fourth, it is compatible with both automatic and manual control modes. The automatic mode meets the intelligent needs of daily production, while the manual mode provides flexible operation space for system debugging and anomaly handling, adapting to the usage needs of different production scenarios and making it highly practical.
[0036] Fifth, the algorithm has low computational complexity and can be executed efficiently in a loop on the PLC platform, adapting to the real-time control needs of IoT greenhouse environments. Moreover, the parameter calibration is flexible and can be adjusted according to different garlic varieties and regional climate characteristics, making it widely applicable. Attached Figure Description
[0037] For ease of explanation, the present invention will be described in detail below with reference to specific embodiments and accompanying drawings.
[0038] Figure 1This is a flowchart of the phenologically driven environmental dynamic adaptive control method in an embodiment of the present invention;
[0039] Figure 2 This is a schematic diagram illustrating the dynamic threshold adjustment principle based on GDD deviation in an embodiment of the present invention. Detailed Implementation
[0040] To make the objectives, technical solutions, and advantages of this invention clearer, the invention is described below with reference to specific embodiments shown in the accompanying drawings. However, it should be understood that these descriptions are merely exemplary and not intended to limit the scope of the invention. Furthermore, descriptions of well-known structures and technologies are omitted in the following description to avoid unnecessarily obscuring the concept of the invention.
[0041] It should also be noted that, in order to avoid obscuring the invention with unnecessary details, only the structures and / or processing steps closely related to the solution according to the invention are shown in the accompanying drawings, while other details that are not closely related to the invention are omitted.
[0042] Specific implementation method one: Combining Figures 1 to 2 This embodiment describes a phenologically driven environmental dynamic adaptive control method applied to a greenhouse environmental control system including a programmable logic controller (PLC), comprising:
[0043] S1. The system is initialized and status is detected. The control mode is selected based on the detection results.
[0044] After system startup, the PLC controller sequentially initializes and performs status checks on the temperature and humidity sensors, light sensors, actuators, and communication modules. Status checks can include, but are not limited to, three stages: communication status check, data validity check, and actuator response check. Communication check can use the receipt of valid data frames within three consecutive sampling periods as a criterion. Data validity check compares the collected values with preset physical constraint ranges; specifically, anomalies are determined when air temperature, relative humidity, or light intensity exceeds thresholds. Actuator checks verify the consistency between control commands and feedback signals through short-term jogging. When any detection item fails to meet normal conditions, the system automatically enters an abnormal operating condition handling process: pausing the automatic control algorithm, freezing the current growth stage determination results, and switching the heating, ventilation, and humidification actuators to preset safe states, i.e., the environmental thresholds required for the corresponding stage. Simultaneously, the HMI displays the abnormality type, abnormal parameters, and occurrence time. Operators can then isolate, reset, or replace the abnormal equipment in manual control mode. Only after the abnormality is resolved and the initialization check is passed again can the system resume automatic operation. Under normal system conditions, the PLC loads the target effective accumulated temperature threshold and staged environmental control parameters corresponding to each growth stage of the target crop, and allows operators to calibrate the control parameters in manual control mode. The parameter calibration uses the stage nominal environmental parameters as initial values, and corrects the dynamic adjustment coefficient by manually adjusting the environment and recording the crop growth process and accumulated temperature changes.
[0045] S2, according to the sampling period via PLC controller Environmental parameters are collected and the effective accumulated temperature (GDD) is calculated and updated online. In automatic control mode, the PLC controller collects data from the greenhouse according to a fixed sampling period. The specific sampling period is... The timeout period can be set to 60 minutes and can be configured according to the greenhouse size and environmental stability. Air temperature is simultaneously collected by multiple temperature and humidity sensors deployed at different locations. The PLC calculates the arithmetic mean of the temperatures at each measuring point as the representative temperature for the current moment, reducing the impact of local microclimates on the calculation results. Effective accumulated temperature (GDD) is updated online with temperature as the core variable; its calculation formula is as follows:
[0046]
[0047] In the above formula, Accumulated effective temperature at time t , Let t be the average air temperature (°C) during the sampling period at time t. The base temperature (°C) for the growth of the target crop. The sampling time interval (d); when If the temperature during that period has no effective contribution to the growth of the target crop, its accumulated temperature increment is recorded as 0. LC completes a GDD update after each sampling cycle and transmits the updated results to the growth stage identification and threshold adjustment module in real time.
[0048] S3. Based on GDD, the phenological stage of the target crop is dynamically identified and confirmed to determine the growth stage of the target crop;
[0049] The PLC controller quantitatively compares the real-time accumulated GDD value with the pre-set GDD threshold range for each growth stage to achieve stable identification of the target crop's growth stage. Through the quantitative classification and judgment mechanism, it can effectively avoid frequent switching of growth stages caused by short-term environmental fluctuations, and ensure the stability and engineering applicability of the growth stage identification results.
[0050] S4. Based on the growth stage of the target crop, determine the corresponding staged environmental control target values;
[0051] Based on the identified current reproductive stage, the PLC controller automatically matches the corresponding staged environmental control target values. The environmental control target values include the nominal setpoints and allowable fluctuation ranges of the current stage's temperature, relative humidity, and light intensity, which serve as a benchmark for dynamic threshold adjustment within this reproductive stage.
[0052] S5. Based on the deviation between the current GDD and the theoretical GDD, dynamically adjust the environmental control target value and generate a dynamic environmental control reference value.
[0053] S6. The real-time collected environmental parameters are compared with the dynamic environmental control reference value, and the actuator is driven to act based on the hysteresis control logic. Specifically, the PLC controller compares the real-time collected environmental parameters such as air temperature, relative humidity and light intensity with the corresponding control thresholds after dynamic adjustment, and sets independent hysteresis bandwidth according to different environmental parameters to realize fractional hysteresis control.
[0054] S7. Repeat steps S2 to S6 to achieve adaptive control of the greenhouse environment.
[0055] Specific Implementation Method Two: This implementation method is a further limitation of Specific Implementation Method One. Based on GDD, the dynamic identification and confirmation of the target crop's phenological stage includes: when GDD(t) falls into the threshold interval corresponding to the i-th growth stage of the target crop... If GDD(t) exceeds the upper limit of the current stage for a short period of time, the target crop is determined to be in the i-th growth stage; However, it did not exceed the set hysteresis tolerance. Or the time exceeds the continuous judgment threshold When the system maintains the original stage decision unchanged; when GDD(t) continues to satisfy and duration When the target crop's growth stage is determined, the next stage is switched; among them, Indicates the first The lag tolerance for GDD during the reproductive stage is taken as 10% of the maximum threshold for that stage. The threshold for the continuous over-limit time is set to 1 hour. Any content not mentioned in this embodiment is the same as in Specific Embodiment 1.
[0056] Specific Implementation Method 3: This implementation method is a further limitation of Specific Implementation Method 1 or 2. The environmental control target values include nominal temperature, nominal relative humidity, nominal light intensity and their corresponding fluctuation range. Contents not mentioned in this implementation method are the same as those in Specific Implementation Method 1 or 2.
[0057] Specific Implementation Method Four: This implementation method is a further limitation of Specific Implementation Methods One, Two, or Three. The formula for calculating the deviation between the current GDD and the theoretical GDD is as follows: ;
[0058] Taking temperature regulation as an example, the environmental control target value is dynamically adjusted based on the GDD deviation. The formula for calculating the dynamic temperature reference value is as follows:
[0059]
[0060] In the above formula, This represents the nominal temperature setpoint for the current stage. denoted as GDD deviation value, and k is an adjustment coefficient used to limit the influence of developmental deviation on threshold correction.
[0061] Taking relative humidity control as an example, the formula for calculating the dynamic relative humidity reference value is:
[0062]
[0063] in, Dynamic relative humidity target value This is the current nominal humidity setpoint. Relative humidity adjustment coefficient.
[0064] Similarly, the formula for calculating the dynamic light intensity reference value is:
[0065]
[0066] in, Dynamic relative illumination target value, This is the current nominal illumination setpoint. Relative illumination adjustment coefficient.
[0067] This mechanism can flexibly adjust environmental targets according to crop growth rate, improving the time matching degree between environmental supply and physiological needs. The contents not mentioned in this embodiment are the same as those in specific embodiments one, two or three.
[0068] Specific Implementation Method Five: This implementation method further defines Specific Implementation Methods One, Two, Three, or Four. Dynamic adjustment of the environmental control target value includes: adjusting the coefficient k, where the value of the coefficient k is differentiated based on the crop's physiological sensitivity to environmental changes at different growth stages, in order to balance the regulatory response.
[0069] Speed and system stability. A functional relationship is established between the dynamic environmental control target value and the GDD deviation, where...
[0070] During physiologically sensitive stages such as the seedling and maturity stages, crops have poor tolerance to drastic environmental fluctuations. The value of k ranges from 0.3 to 0.5, allowing environmental regulation to focus on gradual correction and avoiding physiological stress on the crop. During vigorous growth periods such as the growing season, the value of k ranges from 0.6 to 0.8, indicating strong adaptability. Crops respond more actively to environmental changes, enhancing the system's ability to correct deviations in developmental progress and ensuring yield formation. Content not mentioned in this embodiment is the same as in specific embodiments one, two, three, or four.
[0071] Specific Implementation Method Six: This implementation method is a further limitation of Specific Implementation Methods One, Two, Three, Four, or Five. It compares the real-time collected environmental parameters with the dynamic environmental control reference values and drives the actuator based on hysteresis control logic, including: independently setting hysteresis bandwidth for each environmental parameter; driving the actuator when each real-time environmental parameter exceeds the corresponding hysteresis bandwidth threshold range; and stopping the actuator when the parameter returns to the range. Content not mentioned in this implementation method is the same as in Specific Implementation Methods One, Two, Three, Four, or Five.
[0072] Specific Implementation Method Seven: This implementation method is a further limitation of Specific Implementation Methods One, Two, Three, Four, Five, or Six. The PLC controller compares the real-time collected environmental parameters such as air temperature, relative humidity, and light intensity with the corresponding dynamically adjusted control thresholds, and sets independent hysteresis bandwidths according to different environmental parameters to achieve fractional hysteresis control. When the air temperature... Exceeding the dynamic temperature reference value The temperature regulation actuator is triggered when the hysteresis bandwidth is within the specified range, wherein the temperature hysteresis bandwidth is set to 1.0 ℃: when Less than When the PLC starts the heating device; when Greater than When the air temperature returns to normal, the PLC activates the ventilation or cooling device; when the air temperature returns to normal... When within the specified range, the corresponding actuator should be stopped.
[0073] The relative humidity control employs the same hysteresis strategy, when the real-time relative humidity... Exceeding the dynamic humidity reference value The humidity control actuator is triggered when the hysteresis bandwidth is within the specified range, where the humidity hysteresis bandwidth is set to 5%. Less than When, turn on the humidifier; when Greater than When the humidity returns to within the allowable fluctuation range, the actuator will stop operating.
[0074] Light intensity control is also based on the hysteresis criterion, when the real-time light intensity Exceeding dynamic lighting reference value The hysteresis bandwidth range triggers the shading or supplemental lighting device, wherein the illumination hysteresis bandwidth is set to 10 Lux: when Less than When, activate the supplemental lighting device; when Greater than When the light intensity returns to the allowable fluctuation range, the corresponding actuator is stopped. By setting the quantized hysteresis bandwidth for key environmental parameters such as temperature, humidity and light, the actuator can be effectively prevented from frequently starting and stopping near the threshold, thereby improving the system's operational stability and equipment lifespan. Contents not mentioned in this embodiment are the same as those in specific embodiments one, two, three, four, five or six.
[0075] Specific Implementation Method Eight: This implementation method is a further limitation of Specific Implementation Methods One, Two, Three, Four, Five, Six, or Seven, and also includes a manual control mode: In this mode, the PLC shields the automatic control logic and directly responds to the instructions of the human-machine interface (HMI) to control the actuators individually, realizing system debugging, handling of abnormal working conditions, and adjustment of control parameters. The contents not mentioned in this implementation method are the same as those in Specific Implementation Methods One, Two, Three, Four, Five, Six, or Seven.
[0076] Specific Implementation Method Nine: The present invention also provides an environmental dynamic adaptive control system based on phenology-driven methods, including:
[0077] At least one PLC controller;
[0078] Multiple environmental parameter sensors are communicatively connected to the PLC controller;
[0079] Multiple environmental control actuators are driven by the PLC controller;
[0080] A human-machine interface (HMI) is connected to the PLC controller and is used for parameter setting, status display, and mode switching.
[0081] The PLC controller is configured to execute any of the control methods described above.
[0082] Specific Implementation Method 10: A computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the control method described above.
[0083] Specific Implementation Method Eleven: This implementation method selects garlic sprouts as the target crop. Preferably, the PLC control layer applied to the CGDTS framework uses a Siemens S7-1200 series PLC as the controller, paired with temperature and humidity sensors, light sensors, heaters, humidifiers, axial flow fan actuators, and a touch screen as the human-machine interface (HMI). The preferred garlic sprout variety is "Jinxiang Garlic," whose growth stages are divided into three stages: seedling stage, growth stage, and maturity stage. The GDD thresholds for each stage are pre-calibrated through field trials: seedling stage GDD threshold 0-150℃·d, growth stage GDD threshold 150-350℃·d, maturity stage GDD threshold 350-450℃·d.
[0084] The specific steps of the control method in this embodiment are as follows:
[0085] Step 1: After system startup, the PLC controller performs status checks on the TAS-WS-R0X000 temperature and humidity sensor, TAS-GZ-R0X000 light sensor, heater, humidifier, fan, shading net motor, and RS485 communication module. The status of each component is displayed through the HMI. After confirming that there are no faults, the GDD thresholds and staged environmental control parameters for each growth stage of "Jinxiang Garlic" are loaded into the PLC storage module. Specifically, the nominal temperature for the seedling stage is 15-18℃ and the relative humidity is 60%-70%; the nominal temperature for the growth stage is 20-25℃ and the relative humidity is 55%-65%; and the nominal temperature for the maturity stage is 18-22℃ and the relative humidity is 60%-70%. The operator selects the automatic control mode through the touch screen.
[0086] Step 2: In automatic control mode, the PLC controller collects data from each sensor every 10 minutes, taking the average temperature from the three temperature and humidity sensors as the core variable, based on the formula... Calculate the cumulative GDD value, where T is taken as 5℃ as the base temperature for garlic sprout growth. The sampling interval is 10 minutes, or 1 / 6 of an hour.
[0087] Step 3: The PLC compares the real-time cumulative GDD value with the preset threshold. If the cumulative GDD is 80℃·d, it is determined that the seedling stage is in progress. The hysteresis tolerance range is set to 8% of the current stage GDD switching threshold, i.e., 150×8%=12℃·d. The time threshold for continuous exceedance is 1.5 hours. If the cumulative GDD exceeds 162℃·d (150+12) for 1.5 hours, it is determined that the stage has transitioned to the growth stage.
[0088] Step 4: After determining that the seedling stage is reached, the system automatically matches the target values for environmental control during the seedling stage: nominal temperature 16℃, allowable fluctuation range ±0.8℃, relative humidity 65%, allowable fluctuation range ±4%.
[0089] Step 5: The adjustment coefficient k during the seedling stage is set to 0.4. If the current cumulative GDD is 100℃·d and the target GDD for this stage is 150℃·d, then... Dynamic temperature reference value This means lowering the temperature control threshold to 14℃ to ensure the slow growth needs of seedlings.
[0090] Step 6: Set the temperature hysteresis bandwidth to ±0.5℃. If the real-time temperature is 13.4℃, which is lower than the dynamic threshold of 14℃, the PLC will trigger the heater to run. When the temperature rises to 14.5℃, the heater will stop running.
[0091] Step 7: The PLC continuously performs environmental perception, GDD calculation, stage identification, threshold adjustment, and actuator control in 10-minute cycles until the operator switches to manual mode or the system stops running.
[0092] Step 8: When the humidifier needs maintenance, the operator selects the manual control mode via the touchscreen and directly sends a stop command to the humidifier. After maintenance is completed, switch back to the automatic control mode.
[0093] This embodiment achieves dynamic matching between greenhouse environmental parameters and the physiological needs of "Jinxiang Garlic" at different growth stages through the above steps. Experimental verification shows that compared with traditional fixed threshold control, the growth cycle of garlic sprouts is shortened by 10%-15%, the yield is increased by 8%-12%, the number of equipment start-ups and shutdowns is reduced by more than 30%, and the operational stability is significantly improved.
[0094] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.
Claims
1. A phenologically driven environmental dynamic adaptive control method, applied to a greenhouse environmental control system including a programmable logic controller (PLC), characterized in that, include: S1. The system is initialized and status is detected. The control mode is selected based on the detection results. S2. The PLC controller collects environmental parameters according to the sampling period Δt and calculates and updates the effective accumulated temperature (GDD) online. ； In the above formula, Accumulated effective temperature at time t , Let t be the average air temperature (°C) during the sampling period at time t. The base temperature (°C) for the growth of the target crop. The sampling time interval (d) The maximum value function represents the effective accumulated temperature. S3. Based on GDD, the phenological stage of the target crop is dynamically identified and confirmed to determine the growth stage of the target crop; S4. Based on the growth stage of the target crop, determine the corresponding staged environmental control target values; S5. Based on the deviation between the current GDD and the theoretical GDD, dynamically adjust the environmental control target value and generate a dynamic environmental control reference value. S6. Compare the real-time collected environmental parameters with the dynamic environmental control reference value, and drive the actuator to act based on the hysteresis control logic; S7. Repeat steps S2 to S6 to achieve adaptive control of the greenhouse environment.
2. The environmental dynamic adaptive control method based on phenology-driven approach according to claim 1, characterized in that, The dynamic identification and confirmation of the phenological stage of the target crop based on GDD includes: when GDD(t) falls into the threshold interval corresponding to the i-th growth stage of the target crop. If the target crop is in the i-th growth stage, then GDD(t) is determined to be in the i-th growth stage; if GDD(t) continues to satisfy and duration When the target crop's growth stage is determined, the next stage is switched; among them, Indicates the first The lag tolerance for GDD during the reproductive stage is taken as 10% of the maximum threshold for that stage. This indicates the threshold for the duration of continuous overrun, set to 1 hour.
3. The environmental dynamic adaptive control method based on phenology-driven control according to claim 2, characterized in that, The environmental control target values include nominal temperature, nominal relative humidity, and nominal light intensity.
4. The environmental dynamic adaptive control method based on phenology-driven control according to claim 3, characterized in that, The formula for calculating the deviation between the current GDD and the theoretical GDD is as follows: .
5. The environmental dynamic adaptive control method based on phenology-driven control according to claim 4, characterized in that, The dynamic adjustment of the environmental control target value includes: establishing a functional relationship between the dynamic environmental control target value and the GDD deviation through the adjustment coefficient k, wherein the adjustment coefficient k takes a value range of 0.3 to 0.5 during the sensitive growth period of the target crop and a value range of 0.6 to 0.8 during the vigorous growth period.
6. The environmental dynamic adaptive control method based on phenology-driven control according to claim 5, characterized in that, The process of comparing real-time collected environmental parameters with the dynamic environmental control reference value and driving the actuator based on hysteresis control logic includes: independently setting hysteresis bandwidth for each environmental parameter; driving the actuator when each real-time environmental parameter exceeds the corresponding hysteresis bandwidth threshold range; and stopping the actuator when the parameter returns to the range.
7. The environmental dynamic adaptive control method based on phenology-driven control according to claim 6, characterized in that, For temperature control, set the temperature hysteresis bandwidth. ,when When, the drive executes to start heating, when When this happens, cooling will be initiated. Stop when the time is right; for relative humidity control, set the relative humidity hysteresis bandwidth. ,when When, humidification will be started. Dehumidification is started at the appropriate time. Stop when the light intensity is reached; for light intensity control, set the light intensity hysteresis bandwidth. ,when When, the supplementary lighting is activated. Then the sunshade will be activated. Stop when the time comes.
8. The environmental dynamic adaptive control method based on phenology-driven control according to claim 7, characterized in that, It also includes a manual control mode: in this mode, the PLC disables the automatic control logic and directly responds to the instructions of the human-machine interface (HMI) to control the actuators independently.
9. A phenologically driven environmental dynamic adaptive control system, characterized in that, include: At least one PLC controller; Multiple environmental parameter sensors are communicatively connected to the PLC controller; Multiple environmental control actuators are driven by the PLC controller; A human-machine interface (HMI) is connected to the PLC controller and is used for parameter setting, status display, and mode switching. The PLC controller is configured to execute the control method as described in any one of claims 1 to 8.
10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the control method as described in any one of claims 1 to 8.