Agricultural ambient light control method and control system based on multi-sensing mechanism

Abstract

The invention discloses an agricultural environment light control method and control system based on a multi-sensing mechanism. The method comprises the following steps: acquiring environment data in an agricultural environment; according to the environment data, calculating a dynamic illumination target value through an environment influence weighted fusion model; calculating an intermediate illumination target value through a smooth transition model according to the corrected illumination data and the dynamic illumination target value; calculating an illumination deviation value according to the corrected illumination data and the intermediate illumination target value; and according to the illumination deviation value, based on a PID control algorithm, generating an illumination control signal and outputting the illumination control signal to a light supplement execution mechanism so as to realize illumination control in the agricultural environment. Firstly, perception precision is improved through multi-dimensional environment data correction, and secondly, illumination requirements are matched through a dynamic fusion model; and finally, the robustness of the system is enhanced through smooth transition and PID control, and accurate and adaptive agricultural light control is realized.

Description

Technical Field

[0001] This invention relates to an agricultural ambient light control method and control system based on a multi-sensor mechanism, belonging to the field of ambient light control technology. Background Technology

[0002] At the environmental perception level, traditional light control methods generally suffer from a lack of dimensionality. Existing light sensors cannot adequately account for interference from environmental factors such as temperature, humidity, and air pressure during measurement. Specifically, high temperatures exacerbate sensor thermal noise, humidity changes easily alter the refractive index of the optical path, and air pressure fluctuations affect spectral transmission characteristics. These factors combined result in a significant discrepancy between the raw measurements acquired by the sensors and the actual effective light radiation received by the crop canopy, leading to inaccurate basic perception data and impacting the reliability of all subsequent control decisions.

[0003] At the level of generating control targets, existing light control technologies mostly employ fixed light setpoints or can only perform limited stage switching. This static target setting method not only fails to match the differentiated physiological needs of crops at different growth stages, such as the seedling and fruiting stages, but also fails to consider the dynamic impact of environmental stress factors on the actual light tolerance and demand intensity of crops. For example, when the temperature is unsuitable or the humidity is too high, the crop's response to environmental stress will change its actual light tolerance. However, existing control strategies lack intelligent decision-making mechanisms that can integrate real-time environmental conditions with crop growth models, resulting in a disconnect between light supply and the actual needs of crops.

[0004] Furthermore, existing light control strategies suffer from significant shortcomings in robustness and adaptability. Some schemes employing PID control directly address the absolute deviation between a fixed target value and the measured value. When significant adjustments to the light setpoint are required due to crop replacement or changes in growth stage, this direct control method is highly susceptible to system oscillations, impacting control stability. Simultaneously, existing normalization methods are mostly designed based on fixed ranges, failing to adapt to dynamic changes in the target value itself. This results in poor cross-condition adaptability of the system under different operating conditions, making it difficult to maintain stable and reliable control performance in complex and ever-changing agricultural environments. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art and provide an agricultural ambient light control method and control system based on a multi-sensor mechanism. First, the sensing accuracy is improved by correcting multi-dimensional environmental data. Second, the light demand is matched by a dynamic fusion model. Finally, the robustness of the system is enhanced by smooth transition and PID control, thus realizing precise and adaptive agricultural light control.

[0006] To achieve the above objectives, the present invention is implemented using the following technical solution:

[0007] On one hand, this invention discloses an agricultural ambient light control method based on a multi-sensor mechanism, comprising:

[0008] Acquire environmental data in the agricultural environment; the environmental data includes temperature data, humidity data, air pressure data, and corrected light data;

[0009] Based on the environmental data, the dynamic illumination target value is calculated using an environmental impact weighted fusion model.

[0010] Based on the corrected illumination data and dynamic illumination target value, the intermediate illumination target value is calculated using a smooth transition model;

[0011] Calculate the illumination deviation value based on the corrected illumination data and the intermediate illumination target value;

[0012] Based on the light deviation value, a light control signal is generated using a PID control algorithm and output to the supplementary lighting actuator to achieve light control in the agricultural environment.

[0013] Furthermore, the acquisition of the corrected illumination data includes:

[0014] Acquire visible light and infrared data from the agricultural environment to calculate effective light radiation data;

[0015] Based on the temperature data, humidity data, and air pressure data, the effective light radiation data is dynamically compensated to obtain the corrected light radiation data.

[0016] Furthermore, the expression for the effective illumination radiation data is as follows:

[0017] ;

[0018] In the formula, This represents the effective solar radiation data at time t; This represents the visible light data at time t; This represents the infrared light data at time t; Indicates the IR suppression coefficient;

[0019] The expression for the corrected illumination data is as follows:

[0020] ;

[0021] In the formula, This represents the corrected illumination data at time t; This represents the temperature correction factor; This represents the temperature data at time t; Indicates the humidity correction factor; This represents the humidity data at time t; This represents the pressure correction factor; This represents the air pressure data at time t.

[0022] Furthermore, the expression for the dynamic illumination target value is:

[0023] ;

[0024] In the formula, This represents the dynamic illumination target value at time t; This represents the baseline light requirement value when the growth stage is S.

[0025] This represents the temperature weighting coefficient; Indicates the humidity weighting coefficient; This represents the air pressure weighting coefficient;

[0026] This represents the temperature effect function at time t based on temperature data T and growth stage S;

[0027] This represents the humidity effect function at time t based on humidity data H and growth stage S.

[0028] This represents the pressure influence function based on pressure data P and growth stage S at time t.

[0029] Furthermore, the expression for the reference illumination requirement value is as follows:

[0030] ;

[0031] In the formula, This represents the baseline light requirement when the growth stage is S. Indicates the baseline light intensity during the early stages of growth; Indicates the baseline light intensity during the growth and maturity period; This represents the growth stage mapping function.

[0032] Furthermore, the expression for the temperature influence function is as follows:

[0033] ;

[0034] In the formula, This represents the temperature effect function at time t based on temperature data T and growth stage S; This represents the temperature data at time t;

[0035] This represents the safe illumination ratio coefficient under low temperature stress; This represents the safe light intensity ratio under high temperature stress.

[0036] This represents the minimum temperature tolerance threshold when the growth stage is S. This indicates the lower limit of the optimal temperature range for growth stage S; This indicates the upper limit of the optimal temperature range for growth stage S; This represents the highest temperature tolerance threshold when the growth stage is S.

[0037] The expression for the humidity effect function is as follows:

[0038] ;

[0039] In the formula, This represents the humidity effect function at time t based on humidity data H and growth stage S. This represents the humidity data at time t;

[0040] This represents the safe light intensity ratio under low humidity stress. This represents the safe light intensity ratio under high humidity stress.

[0041] This indicates the minimum humidity tolerance threshold at growth stage S. Indicates the growth stage as The lower limit of the optimal humidity range at that time; This indicates the upper limit of the optimal humidity range when the growth stage is S; This represents the highest humidity tolerance threshold when the growth stage is S.

[0042] The expression for the air pressure influence function is as follows:

[0043] ;

[0044] In the formula, This represents the pressure influence function at time t based on pressure data P and growth stage S. This represents the air pressure data at time t;

[0045] The fundamental coefficient representing the effect of air pressure. This represents the minimum air pressure tolerance threshold when the growth stage is S. This represents the highest air pressure tolerance threshold when the growth stage is S.

[0046] Furthermore, the expression for the intermediate illumination target value is as follows:

[0047] ;

[0048] In the formula, This represents the intermediate illumination target value at time t; This represents the corrected illumination data at time t; This represents the dynamic illumination target value at time t; Indicates the smooth transition coefficient. .

[0049] Furthermore, the calculation of the illumination deviation value includes:

[0050] Calculate the normalized illumination value based on the corrected illumination data and the intermediate illumination target value;

[0051] The illumination deviation value is calculated based on the normalized illumination value, and the expression for the illumination deviation value is as follows:

[0052] ;

[0053] ;

[0054] In the formula, This represents the illumination deviation value at time t; This represents the normalized illumination value at time t;

[0055] This represents the intermediate illumination target value at time t; This represents the corrected illumination data at time t.

[0056] Furthermore, the expression for the illumination control signal is as follows:

[0057] ;

[0058] In the formula, This represents the illumination control signal at time t; This represents a proportionality coefficient with respect to illumination; Represents the integral coefficient with respect to illumination; Represents the differential coefficient with respect to illumination; Represents the derivative with respect to time t; This represents the illumination deviation value at time t; This represents the integral of the illumination deviation value at time t; This represents the derivative of the illumination deviation at time t.

[0059] On the other hand, this invention discloses an agricultural ambient light control system based on a multi-sensor mechanism, applicable to the aforementioned agricultural ambient light control method based on a multi-sensor mechanism, comprising:

[0060] The data acquisition module is used to acquire environmental data in the agricultural environment; the environmental data includes temperature data, humidity data, air pressure data, and corrected light data.

[0061] The dynamic lighting module is used to calculate the target value of dynamic lighting based on the environmental data through an environmental impact weighted fusion model;

[0062] The intermediate lighting module is used to calculate the intermediate lighting target value based on the corrected lighting data and the dynamic lighting target value through a smooth transition model;

[0063] The illumination deviation module is used to calculate the illumination deviation value based on the corrected illumination data and the intermediate illumination target value;

[0064] The illumination control module is used to generate an illumination control signal based on the illumination deviation value and a PID control algorithm, and output it to the supplementary lighting actuator to achieve illumination control in the agricultural environment.

[0065] Compared with the prior art, the beneficial effects achieved by the present invention are as follows:

[0066] This invention discloses an agricultural environmental light control method and control system based on a multi-sensor mechanism. Firstly, by acquiring multi-dimensional environmental data including temperature, humidity, air pressure, and corrected light intensity data, it effectively overcomes the shortcomings of traditional methods that rely solely on single light intensity measurements and ignore environmental interference. Since the light intensity data has been corrected, the influence of factors such as temperature, humidity, and air pressure on sensor measurements is eliminated, making the basic data used in control calculations closer to the actual effective light radiation received by the crop canopy. This fundamentally improves the accuracy and reliability of the entire control system.

[0067] Secondly, unlike traditional technologies that use fixed light setting values, this invention calculates dynamic light target values ​​using an environmental impact weighted fusion model. This model can dynamically calculate the most suitable light demand under current environmental conditions based on real-time multi-dimensional environmental information such as temperature, humidity, and air pressure. This allows the light control target to automatically adjust according to environmental changes and the potential physiological needs of crops, achieving a dynamic match between light supply and actual crop needs, effectively avoiding insufficient or excessive light waste.

[0068] Finally, this invention introduces a smooth transition model to calculate intermediate light target values, instead of directly feeding abruptly changed target values ​​into the controller. This mechanism effectively buffers drastic jumps in light target values ​​caused by sudden environmental changes or growth stage transitions, making the control process smoother. Based on this, calculating light deviations and performing PID control significantly reduces system oscillations and improves control stability. Even in scenarios with significant adjustments to light requirements, the system can achieve a smooth transition, thereby enhancing the robustness and adaptability of the entire control system in complex agricultural environments. Attached Figure Description

[0069] Figure 1 This is a flowchart of the agricultural ambient light control method based on a multi-sensor mechanism provided in Embodiment 1 of the present invention. Detailed Implementation

[0070] The present invention will be further described below with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and should not be used to limit the scope of protection of the present invention.

[0071] Example 1

[0072] This embodiment 1 provides a method for controlling agricultural ambient light based on a multi-sensor mechanism, including:

[0073] Acquire environmental data in the agricultural environment; environmental data includes temperature data, humidity data, air pressure data, and corrected light data;

[0074] Based on environmental data, dynamic illumination target values ​​are calculated using an environmental impact weighted fusion model.

[0075] Based on the corrected illumination data and dynamic illumination target value, the intermediate illumination target value is calculated using a smooth transition model.

[0076] Calculate the illumination deviation value based on the corrected illumination data and the intermediate illumination target value;

[0077] Based on the light deviation value, a light control signal is generated using a PID control algorithm and output to the supplementary lighting actuator to achieve light control in the agricultural environment.

[0078] The technical concept of this invention is as follows: First, by acquiring multi-dimensional environmental data including temperature, humidity, air pressure, and corrected light intensity data, the shortcomings of traditional methods that rely solely on single light intensity measurements and ignore environmental interference are effectively overcome. Since the light intensity data has been corrected, the influence of factors such as temperature, humidity, and air pressure on sensor measurements is eliminated, making the basic data used in control calculations closer to the actual effective light radiation received by the crop canopy. This fundamentally improves the accuracy and reliability of the entire control system.

[0079] Secondly, unlike traditional technologies that use fixed light setting values, this invention calculates dynamic light target values ​​using an environmental impact weighted fusion model. This model can dynamically calculate the most suitable light demand under current environmental conditions based on real-time multi-dimensional environmental information such as temperature, humidity, and air pressure. This allows the light control target to automatically adjust according to environmental changes and the potential physiological needs of crops, achieving a dynamic match between light supply and actual crop needs, effectively avoiding insufficient or excessive light waste.

[0080] Finally, this invention introduces a smooth transition model to calculate intermediate light target values, instead of directly feeding abruptly changed target values ​​into the controller. This mechanism effectively buffers drastic jumps in light target values ​​caused by sudden environmental changes or growth stage transitions, making the control process smoother. Based on this, calculating light deviations and performing PID control significantly reduces system oscillations and improves control stability. Even in scenarios with significant adjustments to light requirements, the system can achieve a smooth transition, thereby enhancing the robustness and adaptability of the entire control system in complex agricultural environments.

[0081] like Figure 1 As shown, the specific steps are as follows:

[0082] Step 1: Obtain environmental data in the agricultural environment; environmental data includes temperature data, humidity data, air pressure data, and corrected light data.

[0083] 1.1 Temperature and humidity data.

[0084] In this embodiment, the agricultural environment is pre-configured with a high-precision digital temperature and humidity sensor based on MEMS (Micro-Electro-Mechanical Systems) technology. Specifically, the Sensirion SHT31 temperature and humidity sensor is used to collect temperature and humidity data. This sensor, with its extremely high measurement accuracy, fast response speed, and I2C digital bus characteristics, can monitor environmental temperature and humidity in real time and provide standardized digital signal output.

[0085] The communication control methods for its temperature and humidity sensors include:

[0086] First, the system initiates signal transmission based on the start command sent to the SHT31 temperature and humidity sensor via the I2C bus;

[0087] Subsequently, the SHT31 temperature and humidity sensor transmits 16-bit humidity data and 16-bit temperature data according to the preset timing sequence, along with an 8-bit CRC (Cyclic Redundancy Check) verification code.

[0088] Finally, the control module verifies and parses the data according to a preset algorithm.

[0089] The advantages of this approach are as follows: the SHT31 temperature and humidity sensor provides high-precision monitoring with a temperature accuracy of ±0.3℃ and a relative humidity accuracy of ±2%, meeting the needs of precision agriculture; its digital signal output eliminates analog signal conversion errors, and the I2C interface simplifies system wiring. The real-time monitoring function provides accurate compensation for the measurement errors of the light sensor and facilitates timely system adjustments, thereby significantly improving overall control accuracy and environmental adaptability.

[0090] 1.2. Air pressure data.

[0091] In this embodiment, the agricultural environment is pre-equipped with a high-precision digital barometric pressure sensor based on MEMS technology, specifically using a BMP280 barometric pressure sensor to collect barometric pressure data. This sensor, with its high stability, wide measurement range, and low power consumption, can monitor changes in ambient atmospheric pressure in real time. Its integrated piezoresistive sensing element converts ambient pressure into an electrical signal and outputs standardized pressure data via an I2C digital bus.

[0092] Changes in atmospheric pressure can affect the measurement accuracy of light sensors and the accuracy of environmental sensing. Therefore, the introduction of air pressure monitoring functionality allows for dynamic compensation and correction of light measurement results, thereby improving overall measurement accuracy. Furthermore, the sensor supports an I2C interface, facilitating integration with the main controller and simplifying system design. The purpose of selecting this sensor is to provide reliable atmospheric pressure data with high accuracy and stability, enriching the dimensions of environmental monitoring and thus enhancing the overall performance and reliability of the system.

[0093] 1.3 Corrected lighting data.

[0094] The acquisition of the corrected illumination data includes:

[0095] Acquire visible light and infrared data from the agricultural environment to calculate effective light radiation data;

[0096] Based on temperature, humidity and air pressure data, the effective light radiation data is dynamically compensated to obtain corrected light data.

[0097] Specifically, the agricultural environment in this embodiment is pre-configured with a dual-channel visible light and infrared sensor, such as the TSL2561 or TSL2591 integrated module. This module has dual-channel spectral detection capability, supports flexible gain and integration time configuration, and achieves infrared suppression through dual-channel measurement, effectively distinguishing and accurately measuring the intensity of visible light and infrared light in the environment.

[0098] Its operation process includes: First, powering on and initializing the sensor via the I2C bus, configuring the working mode, gain level, and integration time; then, the sensor acquires raw data from the visible light channel and the infrared light channel respectively, converts them into digital values, and stores them in the data register; finally, the raw data from these two channels is read via the I2C protocol to provide input for subsequent ambient light intensity calculation.

[0099] The beneficial effects of this processing method are as follows: infrared suppression through dual-channel measurement significantly reduces the interference of infrared radiation on visible light measurements, providing more accurate light intensity data that closely approximates the effective radiation from plant photosynthesis. Simultaneously, its wide measurement range and configurable characteristics allow it to flexibly adapt to various agricultural environments ranging from low to high light.

[0100] The expression for effective irradiance data is as follows:

[0101] ;

[0102] In the formula, This represents the effective solar radiation data at time t; This represents the visible light data at time t; This represents the infrared light data at time t; This represents the IR suppression coefficient.

[0103] In this embodiment, the IR suppression coefficient is defined as the response ratio of the visible light channel to the infrared channel, which is used to eliminate measurement interference caused by the inherent high responsivity of silicon-based sensors in the near-infrared band of 700-1100nm.

[0104] The visible light and infrared dual-channel sensor selected in this embodiment is designed with a spectral response range of visible light data Ch0 covering the photosynthetically active radiation band of 400-700 nm. However, because the filter cannot completely block infrared light, and silicon-based photosensitive elements themselves have inherently high responsivity in the near-infrared band, coupled with the fact that major light sources in agricultural environments, such as sunlight and white LEDs, emit abundant near-infrared radiation, significant infrared interference signals are mixed into the raw readings of visible light data Ch0, resulting in severely inflated measurements. Therefore, eliminating infrared interference through algorithms is the core step in achieving accurate sensing. In contrast, ultraviolet light accounts for a very low energy proportion in artificial lighting environments, and the filter at the front end of the sensor's visible light channel has already achieved efficient cutoff of ultraviolet light; therefore, the influence of ultraviolet light is negligible within the engineering accuracy range.

[0105] The corrected expression for the illumination data is as follows:

[0106] ;

[0107] In the formula, This represents the corrected illumination data at time t; This represents the temperature correction factor; This represents the temperature data at time t; Indicates the humidity correction factor; This represents the humidity data at time t; This represents the pressure correction factor; This represents the air pressure data at time t. This step is responsible for compensating and correcting for effective solar radiation using multiple environmental parameters, eliminating errors caused by changes in temperature, humidity, and air pressure in optical measurements.

[0108] This step solves the problem of severe inaccuracy in measurement data caused by environmental factors such as temperature, humidity, air pressure, and infrared radiation in traditional single-spot light sensors, enabling accurate sensing of the true and effective light radiation of the crop canopy. It fundamentally ensures the accuracy and reliability of the system's sensing data, providing a reliable data foundation for subsequent control and significantly improving the system's environmental adaptability.

[0109] Step 2: Calculate the dynamic illumination target value based on environmental data using an environmental impact weighted fusion model.

[0110] 2.1 The environmental impact weighted fusion model in this embodiment determines the basic light requirement of the crop based on its current growth stage. It calculates the baseline value by querying the built-in crop growth database and calling the baseline light requirement function. The expression for the baseline light requirement value is as follows:

[0111] ;

[0112] In the formula, This represents the baseline light requirement when the growth stage is S. Indicates the baseline light intensity during the early stages of growth; Indicates the baseline light intensity during the growth and maturity period; This represents the growth stage mapping function.

[0113] 2.2 The environmental impact weighted fusion model in this embodiment is also responsible for quantifying the degree of impact of environmental stresses such as temperature, humidity, and air pressure on the actual light requirements of crops.

[0114] The expression for the temperature effect function is as follows:

[0115] ;

[0116] In the formula, This represents the temperature effect function at time t based on temperature data T and growth stage S; This represents the temperature data at time t;

[0117] This represents the safe illumination ratio coefficient under low temperature stress; This represents the safe light intensity ratio under high temperature stress.

[0118] This represents the minimum temperature tolerance threshold when the growth stage is S. This indicates the lower limit of the optimal temperature range for growth stage S; This indicates the upper limit of the optimal temperature range for growth stage S; This represents the highest temperature tolerance threshold when the growth stage is S.

[0119] Among them, the safe illumination ratio coefficient under low temperature stress Safe light intensity ratio under high temperature stress These are two independent configurable parameters, each ranging from (0, 1). Their specific values ​​are determined by consulting crop physiology databases or conducting cultivation experiments, depending on the crop type, variety, and growth stage, and are usually not equal.

[0120] The expression for the humidity effect function is as follows:

[0121] ;

[0122] In the formula, This represents the humidity effect function at time t based on humidity data H and growth stage S. This represents the humidity data at time t;

[0123] This represents the safe light intensity ratio under low humidity stress. This represents the safe light intensity ratio under high humidity stress.

[0124] This indicates the minimum humidity tolerance threshold at growth stage S. Indicates the growth stage as The lower limit of the optimal humidity range at that time; This indicates the upper limit of the optimal humidity range when the growth stage is S; This indicates the highest humidity tolerance threshold when the growth stage is S.

[0125] Among them, the safe light intensity ratio under low humidity stress Safety light ratio coefficient under high humidity stress These are two independent configurable parameters, both ranging from (0, 1). The specific values ​​of the two parameters are determined based on the crop species and their physiological responses to water stress, and are usually not equal.

[0126] The expression for the air pressure effect function is as follows:

[0127] ;

[0128] In the formula, This represents the pressure influence function at time t based on pressure data P and growth stage S. This represents the air pressure data at time t;

[0129] The fundamental coefficient representing the effect of air pressure. This represents the minimum air pressure tolerance threshold when the growth stage is S. This represents the highest air pressure tolerance threshold when the growth stage is S.

[0130] Temperature and humidity exhibit well-defined optimal ranges and stress thresholds for crop photosynthesis and growth, displaying a non-linear "plateau-rapid drop" characteristic, thus requiring piecewise functions for characterization. In contrast, within the typical pressure variation range of greenhouse agriculture, pressure primarily affects photosynthesis indirectly through its influence on air density and gas diffusion rate; its effect is continuous and gradual, without exhibiting the sensitive critical points seen in temperature and humidity. Therefore, this scheme employs a linear interpolation function for modeling. This function indicates that, within the permissible pressure range, crop light utilization efficiency increases gradually with increasing pressure. This modeling approach physically aligns with the mechanism of pressure action while avoiding the introduction of redundant non-linear parameters in engineering, achieving an optimal balance between accuracy and complexity.

[0131] 2.3 The environmental impact weighted fusion model in this embodiment is also responsible for weighted fusion of the independent impacts of each environmental factor and dynamic correction of the baseline light demand value corresponding to the crop growth stage, so as to obtain the final light control target.

[0132] The expression for the dynamic illumination target value is:

[0133] ;

[0134] In the formula, This represents the dynamic illumination target value at time t; This represents the baseline light requirement value when the growth stage is S.

[0135] This represents the temperature weighting coefficient; Indicates the humidity weighting coefficient; This represents the air pressure weighting coefficient;

[0136] This represents the temperature effect function at time t based on temperature data T and growth stage S;

[0137] This represents the humidity effect function at time t based on humidity data H and growth stage S.

[0138] This represents the pressure influence function based on pressure data P and growth stage S at time t.

[0139] Where the weight coefficients satisfy Furthermore, each weighting coefficient is a configurable parameter, determined by querying a crop physiology database or through cultivation experiments.

[0140] This step overcomes the core shortcomings of traditional control methods, such as fixed light target values ​​that are disconnected from the dynamic physiological needs and environmental stresses of crops, and achieves intelligent and adaptive control targets. It enables light control targets to meet the physiological needs of crops in real time, realizing a fundamental shift from "fixed settings" to "dynamic demand tracking," and providing the optimal light environment for crop growth.

[0141] Step 3: Calculate the intermediate lighting target value using a smooth transition model based on the corrected lighting data and dynamic lighting target value.

[0142] This step is responsible for ensuring a smooth transition between the dynamic target value and the current actual value, avoiding system oscillations caused by a step change in the target value.

[0143] The expression for the intermediate illumination target value is as follows:

[0144] ;

[0145] In the formula, This represents the intermediate illumination target value at time t; This represents the corrected illumination data at time t; This represents the dynamic illumination target value at time t; Indicates the smooth transition coefficient. The smooth transition coefficient determines the speed and smoothness with which the system tracks the target value.

[0146] This step not only achieves a smooth transition of the setpoint by introducing an intermediate illumination target value, avoiding control oscillation, but also incorporates the current measured value into the consideration of smooth transition, so that the intermediate illumination target value always remains related to the current state of the system. This avoids the problem of control saturation caused by an excessive difference between the setpoint and the actual value when the system response is lagging, and also improves the dynamic response characteristics of the system to a certain extent.

[0147] Step 4: Calculate the illumination deviation value based on the corrected illumination data and the intermediate illumination target value.

[0148] Calculate the illumination deviation value, including:

[0149] Calculate the normalized illumination value based on the corrected illumination data and the intermediate illumination target value;

[0150] The illumination deviation value is calculated based on the normalized illumination value. The expression for the illumination deviation value is as follows:

[0151] ;

[0152] ;

[0153] In the formula, This represents the illumination deviation value at time t; This represents the normalized illumination value at time t;

[0154] This represents the intermediate illumination target value at time t; This represents the corrected illumination data at time t.

[0155] The dimensionless normalized illumination deviation value is obtained by subtracting the normalized illumination value from the ideal value of 1. This ratio normalization method converts the illumination deviation into a dimensionless relative error, making the PID controller less sensitive to large changes in the target value and improving the system's robustness and cross-stage adaptability.

[0156] Step 5: Based on the light deviation value, generate a light control signal using a PID control algorithm and output it to the supplementary lighting actuator to achieve light control in the agricultural environment.

[0157] The expression for the illumination control signal is as follows:

[0158] ;

[0159] In the formula, This represents the illumination control signal at time t; This represents a proportionality coefficient with respect to illumination; Represents the integral coefficient with respect to illumination; Represents the differential coefficient with respect to illumination; Represents the derivative with respect to time t; This represents the illumination deviation value at time t; This represents the integral of the illumination deviation value at time t; This represents the derivative of the illumination deviation at time t.

[0160] In this embodiment, the supplementary lighting actuator receives the illumination control signal and adjusts the luminous intensity of the supplementary lighting fixture, such as an LED lamp group, in real time through driving circuits such as PWM pulse width modulation or DALI digital addressable lighting interface, thereby achieving precise closed-loop control of the agricultural environment's illumination conditions.

[0161] This step solves the problems of traditional PID control, which is prone to system oscillation and poor adaptability due to large jumps in the target value. It improves the control stability and robustness across operating conditions. The control system becomes less sensitive to changes in the magnitude of the target value itself, parameter tuning is simpler, and the system can maintain excellent control performance with small overshoot and smooth response under different growth stages and environmental disturbances.

[0162] Example 2

[0163] This embodiment 2 provides an agricultural ambient light control system based on a multi-sensor mechanism, applicable to the aforementioned agricultural ambient light control method based on a multi-sensor mechanism, including:

[0164] The data acquisition module is used to acquire environmental data in the agricultural environment; the environmental data includes temperature data, humidity data, air pressure data, and corrected light data.

[0165] The dynamic lighting module is used to calculate the target value of dynamic lighting based on environmental data through an environmental impact weighted fusion model.

[0166] The intermediate lighting module is used to calculate the intermediate lighting target value based on the corrected lighting data and the dynamic lighting target value through a smooth transition model;

[0167] The illumination deviation module is used to calculate the illumination deviation value based on the corrected illumination data and the intermediate illumination target value;

[0168] The illumination control module is used to generate illumination control signals based on the illumination deviation value and the PID control algorithm, and output them to the supplementary lighting actuator to realize illumination control in the agricultural environment.

[0169] By adopting the above-mentioned agricultural ambient light control method and system based on multi-sensor mechanisms and comprehensively implementing the aforementioned key improvements, the following significant beneficial effects have been achieved:

[0170] 1. A fundamental improvement in the accuracy of light perception has been achieved: Through multi-sensor fusion and dynamic compensation mechanisms, the interference of environmental factors such as temperature, humidity, air pressure, and infrared radiation on light measurement has been effectively eliminated, enabling the light data acquired by the system to truly reflect the actual light received by the crop canopy, laying a reliable data foundation for precise control.

[0171] 2. Intelligent and precise control targets have been achieved: By introducing a dynamic target feedforward mechanism based on crop growth model and environment coupling, the light control target is no longer a fixed value, but can be adaptively adjusted according to the physiological needs of crops at different growth stages and the real-time environmental stress state, making the supplemental lighting strategy more in line with the crop growth law and effectively promoting the improvement of crop yield and quality.

[0172] 3. Significantly improves the system's control stability and robustness: By introducing a smooth transition algorithm and a ratio normalized PID control mechanism, system oscillations caused by setpoint jumps are effectively avoided, making the control system insensitive to large changes in the target value. It can maintain excellent control performance with fast, stable, and no overshoot under different growth stage transitions and external environmental disturbances.

[0173] 4. Enhanced system versatility and intelligence: This solution forms a complete closed-loop architecture of perception-decision-control, which does not depend on specific crops or fixed environments. It can adapt to a variety of application scenarios through the configuration of models and parameters, realizing a fundamental transformation of agricultural lighting environment from traditional experience control to data-driven intelligent control, while reducing the difficulty of system maintenance and parameter tuning.

[0174] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0175] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0176] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0177] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0178] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for controlling agricultural ambient light based on a multi-sensor mechanism, characterized in that, include: Acquire environmental data in the agricultural environment; the environmental data includes temperature data, humidity data, air pressure data, and corrected light data; Based on the environmental data, the dynamic illumination target value is calculated using an environmental impact weighted fusion model. Based on the corrected illumination data and dynamic illumination target value, the intermediate illumination target value is calculated using a smooth transition model; Calculate the illumination deviation value based on the corrected illumination data and the intermediate illumination target value; Based on the light deviation value, a light control signal is generated using a PID control algorithm and output to the supplementary lighting actuator to achieve light control in the agricultural environment.

2. The agricultural ambient light control method based on a multi-sensor mechanism according to claim 1, characterized in that, The acquisition of the corrected illumination data includes: Acquire visible light and infrared data from the agricultural environment to calculate effective light radiation data; Based on the temperature data, humidity data, and air pressure data, the effective light radiation data is dynamically compensated to obtain corrected light radiation data.

3. The agricultural ambient light control method based on a multi-sensor mechanism according to claim 2, characterized in that, The expression for the effective light radiation data is as follows: ； In the formula, This represents the effective solar radiation data at time t; This represents the visible light data at time t; This represents the infrared light data at time t; Indicates the IR suppression coefficient; The expression for the corrected illumination data is as follows: ； In the formula, This represents the corrected illumination data at time t; This represents the temperature correction factor; This represents the temperature data at time t; Indicates the humidity correction factor; This represents the humidity data at time t; This represents the pressure correction factor; This represents the air pressure data at time t.

4. The agricultural ambient light control method based on a multi-sensor mechanism according to claim 1, characterized in that, The expression for the dynamic illumination target value is: ； In the formula, This represents the dynamic illumination target value at time t; This represents the baseline light requirement value when the growth stage is S. This represents the temperature weighting coefficient; Indicates the humidity weighting coefficient; This represents the air pressure weighting coefficient; This represents the temperature effect function at time t based on temperature data T and growth stage S; This represents the humidity effect function at time t based on humidity data H and growth stage S. This represents the pressure influence function based on pressure data P and growth stage S at time t.

5. The agricultural ambient light control method based on a multi-sensor mechanism according to claim 4, characterized in that, The expression for the reference illumination requirement value is as follows: ； In the formula, This represents the baseline light requirement when the growth stage is S. Indicates the baseline light intensity during the early stages of growth; Indicates the baseline light intensity during the growth and maturity period; This represents the growth stage mapping function.

6. The agricultural ambient light control method based on a multi-sensor mechanism according to claim 4, characterized in that, The expression for the temperature effect function is as follows: ； In the formula, This represents the temperature effect function at time t based on temperature data T and growth stage S; This represents the temperature data at time t; This represents the safe illumination ratio coefficient under low temperature stress; This represents the safe light intensity ratio under high temperature stress. This represents the minimum temperature tolerance threshold when the growth stage is S. This indicates the lower limit of the optimal temperature range for growth stage S; This indicates the upper limit of the optimal temperature range for growth stage S; This represents the highest temperature tolerance threshold when the growth stage is S. The expression for the humidity effect function is as follows: ； In the formula, This represents the humidity effect function at time t based on humidity data H and growth stage S. This represents the humidity data at time t; This represents the safe light intensity ratio under low humidity stress. This represents the safe light intensity ratio under high humidity stress. This indicates the minimum humidity tolerance threshold at growth stage S. Indicates the growth stage as The lower limit of the optimal humidity range at that time; This indicates the upper limit of the optimal humidity range when the growth stage is S; This represents the highest humidity tolerance threshold when the growth stage is S. The expression for the air pressure influence function is as follows: ； In the formula, This represents the pressure influence function at time t based on pressure data P and growth stage S. This represents the air pressure data at time t; The basic coefficient representing the effect of air pressure. This represents the minimum air pressure tolerance threshold when the growth stage is S. This represents the highest air pressure tolerance threshold when the growth stage is S.

7. The agricultural ambient light control method based on a multi-sensor mechanism according to claim 1, characterized in that, The expression for the intermediate illumination target value is as follows: ； In the formula, This represents the intermediate illumination target value at time t; This represents the corrected illumination data at time t; This represents the dynamic illumination target value at time t; Indicates the smooth transition coefficient. .

8. The agricultural ambient light control method based on a multi-sensor mechanism according to claim 1, characterized in that, The calculation of the illumination deviation value includes: Calculate the normalized illumination value based on the corrected illumination data and the intermediate illumination target value; The illumination deviation value is calculated based on the normalized illumination value, and the expression for the illumination deviation value is as follows: ； ； In the formula, This represents the illumination deviation value at time t; This represents the normalized illumination value at time t; This represents the intermediate illumination target value at time t; This represents the corrected illumination data at time t.

9. The agricultural ambient light control method based on a multi-sensor mechanism according to claim 1, characterized in that, The expression for the illumination control signal is as follows: ； In the formula, This represents the illumination control signal at time t; This represents a proportionality coefficient with respect to illumination; Represents the integral coefficient with respect to illumination; Represents the differential coefficient with respect to illumination; Represents the derivative with respect to time t; This represents the illumination deviation value at time t; This represents the integral of the illumination deviation value at time t; This represents the derivative of the illumination deviation at time t.

10. An agricultural ambient light control system based on a multi-sensor mechanism, applicable to the agricultural ambient light control method based on a multi-sensor mechanism as described in any one of claims 1-9, characterized in that, include: The data acquisition module is used to acquire environmental data in the agricultural environment; The environmental data includes temperature data, humidity data, air pressure data, and corrected light data; The dynamic lighting module is used to calculate the target value of dynamic lighting based on the environmental data through an environmental impact weighted fusion model; The intermediate lighting module is used to calculate the intermediate lighting target value based on the corrected lighting data and the dynamic lighting target value through a smooth transition model; The illumination deviation module is used to calculate the illumination deviation value based on the corrected illumination data and the intermediate illumination target value; The illumination control module is used to generate an illumination control signal based on the illumination deviation value and a PID control algorithm, and output it to the supplementary lighting actuator to achieve illumination control in the agricultural environment.

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