A physical regulation method for agroforestry variable operation based on optical impedance dissipation

Abstract

This invention relates to the interdisciplinary field of agricultural machinery automation control and precision spraying / fertilizer equipment. More specifically, it relates to a physical control method for variable-operation agricultural and forestry operations based on optical impedance dissipation. Addressing the problem of mis-spraying due to blurred boundaries in variable-operation agricultural machinery, this invention utilizes onboard multi-channel optical hardware to acquire radiation field data. A fractional-order optical attenuation background tensor and a joint impedance tensor are constructed to define the physical barrier boundaries of micro-operations in agricultural machinery. Under this constraint, the minimum dissipation optical path is calculated and the mesoscopic state field is reconstructed, revealing the physiological stress gradient mapped to the hydraulic response. This gradient is then converted into an onboard prescription map, and a PWM control signal with a duty cycle accuracy ≥0.1% and a delay ≤10ms is output via a CAN bus to drive the electro-hydraulic proportional valve of the agricultural and forestry equipment. This invention achieves a millisecond-level physical closed loop from optical sensing to hydraulic execution, preventing mis-spraying at the hardware and electrical level and completing targeted physical control.

Description

Technical Field

[0001] This invention relates to the intersection of agricultural machinery automation control and precision spraying / fertilizer equipment, and more specifically, to a physical control method for agricultural and forestry variable operations based on optical impedance dissipation. Background Technology

[0002] In modern smart agroforestry production, variable-rate operations based on vegetation physicochemical state analysis (such as precision pesticide application and variable-rate fertilization) are the core means to achieve reduced agricultural inputs and increased efficiency. However, existing agroforestry variable-rate operation systems generally face the engineering bottleneck of "mismatch between sensing resolution and electromechanical execution accuracy." In practical applications, limited by the physical flux of sensors, they can usually only acquire spatially sparse canopy multi-band spectral sequences and continuous planar radiation fields lacking in-depth mechanistic characteristics. How to accurately convert these multi-source optical sensing data into physical control commands that can directly drive the underlying hydraulic actuators of agricultural machinery is a core problem that urgently needs to be solved in the field of agricultural machinery automation control.

[0003] Existing technologies, when dealing with such "sensing-control" links, often rely on purely software-level radiation field reconstruction and prescription map generation, which has three fundamental flaws that lead to the failure of the underlying agricultural machinery physical execution: 1. The "mechanistic blind spot" of pure mathematical statistics leads to physical distortion of control commands: Existing technologies mostly rely on inverse distance ratios in Euclidean space or inferences from geostatistical variograms. These methods attempt to fit nonlinear biophysical evolution processes with purely mathematical models. This blind smoothing, lacking a physical transmission engine, causes the generated prescription maps to drift at physical boundaries, directly leading to ineffective spraying or target deviation by the agricultural machinery actuators in complex canopy environments.

[0004] 2. Shallow apparent geometry cannot overcome anisotropy, leading to accidental spraying of pesticides / fertilizers outside designated areas: In real agroforestry environments, gradual changes in media properties often extend anisotropically along specific micro-textures (such as furrow orientation and leaf gaps). Existing technologies still use isotropic neighborhood search in Euclidean space, resulting in blurred edges in the extrapolation results at complex mesoscopic structures (such as the boundary between healthy and severely diseased areas). This blurred boundary makes it difficult for electro-hydraulic proportional valves in agricultural machinery to obtain sharp start-stop physical signals, easily causing accidental spraying of pesticides / fertilizers outside designated areas and wasting resources in heterogeneous boundary regions.

[0005] 3. The fragmentation of "physical consistency" in cross-scale evolution leads to an engineering gap of "monitoring without control": Existing multi-source spectral coordination mostly remains at the "pixel-level numerical fitting" level of pure numerical values. The endpoint of its system output often only reaches the software extrapolation level of "generating macroscopic data distribution maps." This fragmentation of physical consistency means that high-precision data extrapolation results cannot establish a rigorous physical mapping mechanism with the dynamic response (such as PWM duty cycle, valve delay) of the underlying agricultural machinery hydraulic actuators, making it difficult to meet the industrial-grade requirements of modern agricultural and forestry equipment for millisecond-level closed-loop control.

[0006] In summary, there is currently a lack of a physical control scheme that can deeply integrate the deduction of radiation transfer mechanism with the underlying electro-hydraulic control of agricultural machinery. Existing technologies cannot provide agricultural machinery with microscopic mutation physical boundaries with extremely high barrier potential under high-resolution continuous field boundary constraints, which leads to the inability to support high-precision, low-latency variable operation underlying hardware drive and precise management of agriculture and forestry in actual agricultural and ecological applications. Summary of the Invention

[0007] This invention provides a physical control method for agricultural and forestry variable operations based on optical impedance dissipation, aiming to solve the following three major technical problems in the failure of underlying agricultural machinery physical execution caused by "lack of physical transmission engine" and "limitations of isotropic optics assumption" during multi-source spectral collaborative reconstruction: 1. The "mechanistic blind spot" of pure mathematical statistical inference leads to physical distortion of underlying control commands: Existing technologies are essentially based on pure mathematical statistical inference in Euclidean space. These methods attempt to fit complex radiative transfer processes controlled by nonlinear mesoscopic physicochemical parameters with linear spatial distances. This blind smoothing without a physical engine foundation causes the inferred state to violate inherent physical laws, and the generated prescription map drifts at the physical boundary, directly causing ineffective spraying or target deviation of agricultural machinery actuators in complex canopy environments.

[0008] 2. Apparent geometric constraints cannot overcome anisotropy, leading to accidental spraying by agricultural machinery: Although some existing technologies attempt to use apparent geometric boundaries as constraints, they neglect the continuous optical connectivity within the canopy. In real-world scenarios, gradual changes in medium properties often extend anisotropically along specific texture directions. Existing technologies still employ isotropic neighborhood search in Euclidean space, resulting in blurred extrapolation results at the edges of complex mesoscopic structures. This blurred boundary prevents the electro-hydraulic proportional valves of agricultural machinery from obtaining sharp start-stop physical signals, easily causing accidental spraying of pesticides / fertilizers and resource waste in heterogeneous interface areas.

[0009] 3. The fragmentation of "physical consistency" in cross-scale evolution leads to an engineering gap of "monitoring without control": Significant scale and mechanism differences exist between discrete spectral sequences and continuous radiation fields. Existing technologies often treat data sources from different observation dimensions as pure digital signals for spatial node-level numerical fitting, with the system output only reaching the software extrapolation level of "generating macroscopic data distribution maps." This fragmentation of physical consistency means that high-precision data extrapolation results cannot establish a rigorous physical mapping mechanism with the dynamic response of the underlying agricultural machinery hydraulic actuators, making it difficult to meet the industrial-grade requirements of modern agricultural and forestry equipment for millisecond-level closed-loop control.

[0010] Therefore, this invention provides a physical control method for agricultural and forestry variable operations based on optical impedance dissipation, comprising the following steps: S1. Construct a multi-source optical-agricultural machinery collaborative hardware sensing system, which includes a low-altitude unmanned aerial vehicle platform equipped with a multi-channel radiation sensor array and a centimeter-level RTK positioning module, and a portable hyperspectral acquisition terminal; acquire continuous radiation field data of agricultural and forestry crop canopy in the target area through the low-altitude unmanned aerial vehicle platform, and acquire discrete multi-band canopy spectral sequences in the target area through the portable hyperspectral acquisition terminal; extract the photoelectric response attenuation gradient of the continuous radiation field in multi-scale space through the airborne data processing unit, quantify the physical transmission resistance of agricultural machinery micro-operations, and generate a global continuous optical attenuation background tensor; S2. The airborne data processing unit calls a preset multi-band collaborative analysis operator to convert the continuous radiation field data into a vegetation canopy biochemical-morphological collaborative boundary condition field; using the vegetation canopy biochemical-morphological collaborative boundary condition field as input, it drives the radiation transfer simulation kernel of the coupled absorption-scattering mechanism, and combines atmospheric and micro-topographic environmental parameters to evolve and output a photosynthetically effective radiation reference field. S3. Calibrate the radiative state deviation between the photosynthetically active radiation reference field and the discrete multi-band canopy spectral sequence at the sampling nodes; using the radiative potential energy coupling mechanism, embed the potential energy directional derivative of the photosynthetically active radiation reference field into the optical attenuation background tensor to reshape the radiation-structure joint impedance tensor; using the radiation-structure joint impedance tensor as the constraint space, analyze the minimum dissipation optical path between discrete nodes and unsampled nodes in the entire domain; S4. Based on the minimum dissipation optical path, configure the hardware control weights for driving the electro-hydraulic proportional valve response; drive the radiation state deviation to migrate in a restricted manner along the canopy microstructure to generate a global compensation field; superimpose the global compensation field onto the photosynthetically active radiation reference field, analyze the micro-geometric scattering components and assimilate them, reconstruct and output a high-fidelity vegetation canopy mesostate field, and analyze and generate the physiological stress physical gradient. S5. Combining the microscopic mutation physical boundary defined by the radiation-structure joint impedance tensor, the physiological stress physical gradient is transformed into a prescription map file that can be recognized by the agricultural machinery's onboard navigation; relying on the agricultural machinery variable control unit, combined with the spray nozzle dynamics model and the agricultural machinery's travel parameters, a PWM control signal is generated to drive the electro-hydraulic proportional valve to adjust the hydraulic actuator's action, thereby realizing agricultural and forestry variable operations.

[0011] Preferably, the generation of the optical attenuation background tensor includes the following steps: The anisotropic attenuation rate is calculated using the Grünwald-Letnikov fractional calculus method. The dominant characteristic components of the anisotropic attenuation rate are extracted to define the local optical attenuation factor. The spatial absolute coordinates are coupled with the local optical attenuation factor to generate a fractional optical attenuation background tensor, thereby providing a hard physical impedance boundary for the precise start and stop of the hydraulic valve of agricultural machinery at the underlying algorithm level.

[0012] Preferably, the vegetation canopy biochemical-morphological synergistic boundary condition field includes volume scattering element density or leaf area index characterizing the three-dimensional distribution of the canopy; the multi-band synergistic physicochemical analytical operator is a nonlinear operator used to analyze the physicochemical mapping relationship between continuous radiation field data and vegetation canopy biochemical-morphological synergistic boundary condition field, ensuring that the output boundary condition field can truly reflect the physical entity state that requires agricultural machinery intervention.

[0013] Preferably, the radiative transfer simulation kernel of the coupled absorption-scattering mechanism is a radiative transfer dynamics model constrained by illumination-observation geometry; the radiative transfer dynamics model couples the geometric optical shading effect with the multiple scattering effect inside the canopy, takes the biochemical-morphological synergistic boundary condition field of the vegetation photosphere as input, analyzes the biaxial reflection distribution characteristics at each node in space, and deduce the evolution trend of the radiation state in the unsampled area, so as to eliminate the interference of complex terrain and shading on the visual / optical perception of agricultural machinery.

[0014] Preferably, the minimum dissipation optical path between the analytical discrete node and the globally unsampled node includes the following steps: The fractional-order potential energy evolution gradient matrix of the photosynthetically active radiation reference field is solved to generate a radiation energy gradient field. The radiation energy gradient field is embedded into the fractional-order optical attenuation background tensor to reshape the radiation-structure joint impedance tensor. Using the radiation-structure joint impedance tensor as the constraint space, an anomalous secondary diffusion mechanism is established. The evolution trajectory along the impedance surface between each node is solved using the fractional-order equation to obtain the minimum dissipation optical path, providing a collision-free and zero-boundary underlying physical trajectory reference for agricultural machinery obstacle avoidance and targeted operation.

[0015] Preferably, the restricted migration includes the following steps: An optical dissipation weight based on the Mittag-Leffler function is constructed to characterize the power-law attenuation characteristics of vegetation mesoscopic impedance; the radiation state deviation is driven to perform anomalous subdiffusion dynamics evolution to generate a global compensation field; the state mixing degree in the local neighborhood after superimposing the compensation field is evaluated, and a dynamically adjusted canopy structure scattering gain function is established; the assimilation gain of the microscopic geometric scattering components is enhanced in the structurally homogeneous region, and the assimilation gain is attenuated in the heterogeneous boundary region to suppress nonlinear distortion, thereby suppressing valve malfunction caused by signal smoothing at the hardware electrical level.

[0016] Preferably, converting the physical gradient of physiological stress into a prescription map file recognizable by the agricultural machinery's onboard navigation includes the following steps: Based on the physical gradient of physiological stress, and combined with the microscopic mutation physical boundary indicated by the radiation-structure joint impedance tensor, the target region is divided into different mesoscopic spatial grids; for different mesoscopic spatial grids, and combined with the preset physiological response model, differentiated targeted operation parameters are calculated; the grid data carrying the targeted operation parameters and spatial topological coordinates is converted into prescription map files that can be recognized by agricultural machinery onboard navigation.

[0017] Preferably, the underlying coupling mechanism between the collaborative sensing hardware of the low-altitude unmanned aerial vehicle (UAV) flight platform and the agricultural machinery execution end includes: The airborne data processing unit embeds a hardware driver module based on the Mittag-Leffler heavy-tail attenuation mechanism. During variable operation, the hardware driver module extracts the mesoscopic abrupt change physical boundary calibrated by the optical attenuation background tensor and the radiation-structure joint impedance tensor, and converts it into a PWM duty cycle cutoff command for the electro-hydraulic proportional valve. The CAN bus communication interface on the agricultural machinery side is configured with a millisecond-level response priority interrupt mechanism, which is used to issue the PWM duty cycle cutoff command with a system bus delay of ≤10ms at the moment when the agricultural machinery crosses the mesoscopic abrupt change physical boundary, thereby completely blocking the agricultural machinery from spraying beyond the boundary due to macroscopic data processing delay at the hardware electrical level.

[0018] Preferably, the underlying driving process for generating PWM control signals includes the following steps: The physiological stress physical gradient data carrying the targeted operation parameters are mapped and transformed into the airborne navigation coordinate system of agricultural and forestry operation equipment; combined with the dynamic model of the spray nozzle, the agricultural machinery travel parameters, and the microscopic geometric scattering anomaly distribution of the high-fidelity vegetation canopy mesoscopic state field output, the pipeline opening-speed coupling parameters are calculated; the pipeline opening-speed coupling parameters are converted into electrical signals to generate PWM control signals that drive the electro-hydraulic proportional valve to adjust the hydraulic actuator, thereby realizing variable precision operation at the agricultural and forestry mesoscopic scale.

[0019] Preferably, the PWM control signal driving the electro-hydraulic proportional valve includes the following steps: The duty cycle fine-tuning command of the PWM control signal is converted into the armature displacement of the pilot electromagnet inside the electro-hydraulic proportional valve; a nonlinear hydrodynamic mapping relationship between the armature displacement and the opening area of ​​the main valve core is established; within a response delay window of ≤10ms, the high-frequency chattering characteristic of the PWM control signal is used to overcome the static friction of the main valve core, so that the output flow of the hydraulic actuator matches the microscopic analytical grid resolution of the mesoscopic state field of the vegetation canopy, thereby achieving hysteresis-free targeted physical control.

[0020] The beneficial effects of this invention include: 1. Relying on multi-channel optical sensing hardware, this invention achieves a paradigm shift from blind mathematical fitting to physical radiation dynamics deduction, providing a zero-drift physical benchmark for agricultural machinery operations. This invention abandons the traditional purely data-driven statistical inference of Euclidean space and creatively constructs a physical deduction chain based on a physical multi-channel radiation sensor array and an RTK spatial positioning module. By establishing a radiation transfer simulation kernel with a coupled absorption-scattering mechanism, this invention transforms the sparse spectral deduction problem into a physical transmission evolution process constrained by the physical boundaries of the real atmosphere and micro-topography. The output photosynthetically effective radiation benchmark field strictly follows the laws of multiple scattering of photons and physical radiation attenuation within complex vegetation canopies, fundamentally eliminating the physical consistency fragmentation error in scale expansion inherent in traditional software algorithms. This provides absolutely accurate three-dimensional coordinate constraints for the targeted spatial positioning of underlying agricultural machinery equipment, completely solving the "blind men and the elephant" problem of agricultural machinery operation caused by coordinate distortion in traditional pure algorithm deduction.

[0021] 2. Breaking the isotropic assumption, this invention constructs a physical optical impedance and dissipation mechanism to constrain the boundaries of agricultural machinery operations, enabling precise start-stop of hydraulic valves in complex habitats. Addressing the anisotropy challenge of transport within complex canopy media, this invention innovatively introduces Grünwald-Letnikov fractional calculus to quantify the optical attenuation background tensor characterizing the microscopic physical transport resistance of real agroforestry media. More significantly, in eliminating radiation bias, this invention utilizes the solution of fractional-order equations and Mittag-Leffler heavy-tailed dissipation weights to construct an anomalous secondary diffusion dynamics mechanism. This mechanism not only strictly conforms to the physical extension of the real vegetation canopy's microscopic physical structure but also induces a high-barrier potential barrier at mesoscopic abrupt boundaries. This completely eliminates the structural ambiguity caused by traditional Gaussian smoothing algorithms at the physical level, providing extremely sharp and precise physical intervention boundaries for the electro-hydraulic actuators of subsequent agricultural and forestry equipment. This enables agricultural machinery to trigger millisecond-level valve shut-off when crossing the boundary between healthy and disease / stressed areas, fundamentally preventing the mis-spraying of pesticides / fertilizers and the waste of resources.

[0022] 3. This invention constructs an industrial-grade hardware control closed loop from microscopic physical sensing to macroscopic agricultural machinery execution, breaking through the limitation of traditional assimilation and inversion systems that only output digital maps. The invention uniquely maps the "blocking effect of the least dissipated optical path" in higher-order physical fields directly to the "physical boundary of the duty cycle returning to zero for agricultural machinery hydraulic proportional valves." By relying on the onboard variable control unit and CAN bus, the highly in-depth physical deduction results are seamlessly converted into PWM underlying electrical signals with a duty cycle adjustment accuracy ≥0.1% and an overall response delay ≤10ms, realizing direct linkage control across physical fields from "optical photon transmission impedance" to "agricultural machinery hydraulic fluid impedance." This invention not only outputs a high-fidelity data state field but also directly drives agricultural and forestry operation physical equipment to perform precise pesticide application with extremely low response delay. It establishes a deep cross-application paradigm of agricultural machinery automation equipment and optical physical measurement devices, constructing a very high software-hardware collaborative technology barrier and completely solving the industrial pain point of the disconnect between traditional remote sensing monitoring and actual agricultural production. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 A flowchart illustrating the physical control method for agricultural and forestry variable operations based on optical impedance dissipation provided in an embodiment of the present invention; Figure 2 This is a diagram of the underlying hardware architecture of the electro-hydraulic collaborative physical execution system for variable-rate agricultural and forestry operations provided in this embodiment of the invention.

[0025] Figure 3 This is a schematic diagram illustrating the physical evolution principle of the nuclear-driven photosynthetic effective radiation reference field in the radiative transfer simulation of this invention.

[0026] Figure 4 This is a schematic diagram comparing the optical dissipation of anomalous secondary diffusion based on joint impedance field constraints with that of optical dissipation in traditional Euclidean space isotropic numerical inference.

[0027] Figure 5 This is a calibration curve showing the physical mapping between the duty cycle of the PWM control signal and the flow rate of the agricultural machinery hydraulic actuator in an embodiment of the present invention.

[0028] Figure 6 This is a comparison of high-fidelity multi-band physical response curves of vegetation canopy under different physiological stress states in embodiments of the present invention. Detailed Implementation

[0029] To make the technical problems, solutions, and beneficial effects of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0030] like Figure 1 As shown, this invention provides a physical control method for agricultural and forestry variable operations based on optical impedance dissipation. Its core idea is to abandon the traditional blind fitting model of pure mathematical statistics and establish a fundamental physical chain of "mesoscopic attenuation analysis - boundary condition constraints - radiation mechanism simulation" to generate a photosynthetically effective radiation reference field with a clear radiative transmission mechanism. Furthermore, it innovatively introduces optical anisotropy and the Grünwald-Letnikov fractional calculus mechanism, using the continuous radiation field to construct a fractional optical attenuation background tensor characterizing the medium's transmission impedance. In the joint impedance space, it solves the fractional-order equations to obtain the minimum dissipation optical path and combines the Mittag-Leffler heavy-tailed dissipation mechanism to reconstruct the radiation state deviation through an anomalous secondary diffusion evolution with direction-awareness and long-range memory effects. Finally, based on the reconstructed high-fidelity physical state field, it analyzes the physiological stress gradient and transforms it into an airborne prescription map, outputting a PWM signal with a duty cycle and delay strictly matched to the grid resolution, directly driving the agricultural machinery hydraulic actuator or solenoid valve to complete targeted physical control. This synergistic strategy of underlying physical mechanism deduction, top-level impedance dissipation repair, and terminal physical intervention fundamentally breaks through the limitations of "physical consistency separation" and "isotropic assumption" in traditional multi-source spectral reconstruction, and establishes a new paradigm of software and hardware synergy that directly drives high-end agricultural machinery equipment with high-order mathematical models.

[0031] Furthermore, to clarify the physical properties of this invention that can be manipulated across physical fields, please refer to... Figure 2 The method described in this invention relies on a highly integrated underlying hardware architecture. This architecture uses an onboard data processing unit (ECU) as the computing center and is directly connected to the underlying agricultural machinery execution hardware through a CAN bus with a priority interrupt mechanism. This achieves a microsecond / millisecond-level physical closed loop from front-end multi-channel optical sensing to end-stage electro-hydraulic proportional valve PWM drive, thus providing a solid electromechanical carrier for all subsequent high-order optical impedance calculations and anomalous secondary diffusion evolution.

[0032] To accurately understand the technical solution of this application, the following defines and explains the core high-order mathematical and physical optics terms involved in this invention and their physical mapping mechanism in agricultural machinery control systems: In this application, "high-resolution continuous radiation field data of agricultural and forestry crop canopies" refers to two-dimensional or three-dimensional spatial observation arrays (whose physical carriers may include, but are not limited to, multi-band airborne optical detection matrices, high-resolution UAV canopy radiation flux arrays, etc.) that possess fine spatial structure resolution capabilities and are continuously distributed in space. Its core function is to serve as a continuous fundamental optical data source for resolving canopy mesoscopic structures and inverting vegetation physicochemical parameters, providing a high-precision physical environment base map for variable-rate agricultural machinery operations across the entire domain.

[0033] In this application, "discrete multi-band canopy spectral sequence" refers to a feature vector that is sparsely distributed in space but has extremely high density and rich reflectance information in the spectral dimension (such as a high-fidelity ground-based measured spectrum with hundreds of bands). It is the absolute benchmark for verifying physical inference trends and calibrating the radiation state deviation of the system, and also the absolute anchor point for calibrating the execution accuracy of agricultural machinery and the physical intervention threshold.

[0034] In this application, "mesoscopic scale" refers to a specific agroforestry physical level with a spatial range between 0.1m and 10m. Its physical boundaries simultaneously satisfy the following: (a) significantly larger than purely biological microstructures such as leaf stomata and cell walls (<10⁻³m), so that the optical characteristics are manifested as collective geometric scattering rather than single-leaf transmission; (b) significantly smaller than the macroscopic pixels of traditional satellite remote sensing (>30m), thereby preserving the continuous optical connectivity and structural texture within the canopy; and (c) its spatially heterogeneous nodes can be accurately resolved and matched by an airborne centimeter-level RTK positioning module, ensuring that the physical positioning error of agricultural machinery does not cross this scale grid.

[0035] In this application, the "fractional optical attenuation background tensor" refers to the multi-scale optical heterogeneity within the canopy medium, analytically and quantified based on the Grünwald-Letnikov fractional calculus definition. It is a physical impedance tool capable of simultaneously sensing the orientation of the medium's microstructure and its long-range spatial dependence, resulting in the compression of optical paths aligned with the microstructure direction and the stretching of optical paths crossing physicochemical abrupt boundary boundaries when measuring photon transmission costs. In the control architecture of this invention, this tensor is directly mapped to the "virtual electrical impedance boundary" of an agricultural machinery hydraulic actuator, used to trigger precise valve start-stop in heterogeneous interface regions.

[0036] In this application, the "minimum dissipation optical path" refers to the minimum dissipation path length along the impedance surface between two nodes in space under the aforementioned joint impedance tensor constraint. In the radiation state deviation evolution of this application, this optical path is used to replace the absolute physical straight-line distance (Euclidean distance) to construct a heavy-tailed attenuation weight based on the Mittag-Leffler function. This ensures that the anomalous secondary diffusion of the state deviation not only possesses the ability to strictly block optical sensing across heterogeneous fault boundaries but also preserves the long-range radiation correlation within complex natural media. At the agricultural machinery physical execution level, this path constitutes the underlying physical trajectory benchmark for the agricultural machinery nozzle to perform targeted intervention and avoid non-target areas.

[0037] In this application, "radiative potential energy coupling and anomalous secondary diffusion" is the core physical driving mechanism of the invention. The potential energy coupling mechanism is used to dynamically embed the fractional-order potential energy evolution gradient of the photosynthetically active radiation reference field as a physical driving force field into the fundamental tensor, reshaping it into a radiation-structure joint impedance tensor with an extremely high barrier at the abrupt boundary of the transmission mechanism. Anomalous secondary diffusion refers to the non-Markovian evolution process of radiation state deviation in complex heterogeneous canopies. Compared with traditional Gaussian smoothing, it has extremely strong physical boundary blocking and long-range spatial memory characteristics. At the hardware driving end, this extremely strong physical boundary blocking is transformed into sharp truncation of the PWM control signal, thereby completely eliminating the possibility of agricultural machinery spraying beyond its limits at the electrical level.

[0038] In this application, the "radiative transfer simulation kernel based on coupled absorption-scattering mechanism" refers to a partial differential / integral physics dynamics engine that describes the process of electromagnetic wave radiation flux undergoing multiple scattering, absorption, and geometric attenuation within complex vegetation media. In this application, it uses the biochemical-morphological synergistic boundary condition field of the vegetation canopy as input parameters to forward deduce and generate a photosynthetically effective radiation reference field that conforms to the inherent physical attenuation law, thereby providing agricultural machinery with an absolute physical reference system unaffected by complex terrain and transient shading.

[0039] Example 1 This embodiment takes the monitoring of nitrogen nutrition in winter wheat as an example to verify the application effect of the method described in this invention in high-precision monitoring and precise management of vegetation physiological stress.

[0040] Please refer to Figure 1 The specific implementation steps of this embodiment are as follows: Step S1: Multi-source optics-agricultural machinery collaborative hardware sensing and physical impedance field mapping Continuous radiation field data of agricultural and forestry crop canopies: A multi-rotor low-altitude unmanned aerial vehicle (UAV) equipped with a multi-channel radiation sensor array was used for sensing at a flight altitude of 50m. This platform integrates a detection payload covering a spectral response range of 400-2500nm (such as the Headwall Nano-Hyperspec® hyperspectral imager), a centimeter-level RTK positioning module, and a CAN bus communication interface. Its onboard data processing unit uses an FPGA chip (such as the Xilinx Artix-7 series) with pre-programmed underlying driver firmware to ensure nanosecond-level hardware synchronization between subsequent PWM signal generation and radiation field reconstruction. Through this physical sensing center, high-resolution continuous radiation field data with high-precision three-dimensional spatial geographic coordinates was acquired from the experimental field, with a ground spatial resolution of 2.5cm.

[0041] Discrete multi-band canopy spectral sequence: Discrete canopy spectral sequences (band range 350-2500nm, spectral resolution 1nm) were simultaneously collected from 30 ground sampling points in the experimental field.

[0042] Environmental constraints: Obtain the atmospheric aerosol optical thickness (0.25) and water vapor content (1.5 g / cm²) of the experimental field area on the day; analyze the continuous radiation field observation metadata to extract the solar zenith angle (30°) and observation azimuth angle (0°, vertical observation).

[0043] Space observation benchmark alignment: A multi-source optical benchmark cooperative operator is used to obtain the same control point pairs of the continuous radiation field and the discrete sequence, and the mapping of the physical coordinate domain and the spatial alignment at the mesoscale are performed. The mapping residual is controlled within 0.5 microscopic analytical grid resolutions.

[0044] Optical homogeneity domain definition: For the winter wheat farmland scenario, a multi-scale media boundary constraint model is adopted. Based on the typical physical reflection benchmark of winter wheat at a flight altitude of 50m, the optical attenuation impedance threshold is set to 0.15, the media morphology connectivity factor is set to 0.65, and the spectral homogeneity boundary parameter is set to 0.85. Through the above physical constraint parameters, the continuous radiation field is deconstructed into media units with homogeneous optical properties (such as wheat canopies, furrows, and bare soil at different growth stages).

[0045] Attenuation Tensor Mapping and Drag Extraction: Using an onboard data processing unit, the photoelectric response attenuation gradient of the continuous radiation field across multiple scales is extracted. The optical transmission drag at each microscopic node within the agricultural and forest canopy is quantified, thereby mapping a global continuous optical attenuation background tensor. This tensor field will serve as a physical impedance base, used to subsequently define the dissipation evolution path of radiation state deviations.

[0046] Specifically, in order to accurately capture the long-range physical transport resistance of the complex microstructure of the aforementioned natural medium in the underlying algorithm, the fractional-order optical attenuation background tensor The computational model is implemented using the Grünwald-Letnikov definition of fractional calculus: First, in order to capture the long-range physical attenuation characteristics of the complex microstructure of natural media, the continuous radiation field data of agricultural and forestry crop canopies were quantified in spatial coordinates. Local multiscale fractional-order structure decay tensor : ;in, and The fractional-order spatial anisotropic decay rate is calculated based on the Grünwald-Letnikov definition; The order of a fraction (values ​​in the range 0 < <1); An isotropic physical diffusion substrate; This is a spatial convolution operator. Specifically, for a discrete spatial analytic grid, the... Grünwald-Letnikov fractional decay rate in the direction The calculation formula is: Similarly, Fractional decay rate in direction The calculation formula is: ;in, It is a gamma function; The truncated optical window length is used to characterize the long-range spatial memory effect; This is the spatial step size (offset). yes Spectral reflectance or radiance at coordinate points express In the direction, the historical / neighborhood spectral reflectance or radiance is k pixels away from the current target pixel (x,y); This represents the spectral reflectance or radiance at a distance of k pixels from the current target pixel (x,y) in the y direction; This represents the distance decay weight that varies with distance k. It is an integer (e.g.) This weight is in It will instantly become 0 (the photon information is instantly truncated), when It is a fraction (e.g., 0.5 or 0.8), which is determined by... The calculated weight coefficients do not suddenly become 0 as the distance k increases, but exhibit a power-law decay, i.e., a non-convergent heavy-tailed distribution.

[0047] Deconstructing the decaying tensor The dominant component is used to obtain the eigenvector and eigenvalues ​​characterizing the local impedance attenuation factor. , Based on this, a fractional-order optical attenuation background tensor characterizing the complex heterogeneous transport resistance within the canopy is generated: ;in, , For adaptive adjustment parameters; It is a unit tensor.

[0048] This resistance tensor model causes optical measures to converge along the direction of the medium structure, but diverge when penetrating the boundary of abrupt physical-chemical changes.

[0049] Step S2: Forward simulation of radiation mechanism under physicochemical evolution constraints A nonlinear absorption-reflection operator was constructed using the red-edge band (730 nm) and near-infrared band (850 nm) of continuous radiation field data from agricultural and forestry crop canopies. For example... Figure 3 As shown, a multi-band coordinated physicochemical analytical operator is established based on historical measured benchmark data; this operator is applied to the full-width continuous radiation field to invert and reconstruct the vegetation canopy biochemical-morphological coordinated boundary condition field (i.e., the distribution field characterizing the volume scattering element density) covering the entire experimental field.

[0050] Specifically, when establishing implicit physicochemical mapping relationships, the physical evolution energy functional of the system... Designed as an impedance dissipation constrained form: ;in, For state observation approximation terms, The total number of spatial nodes participating in physical evolution; The input spectral observation features; These are the structural parameters analyzed by the dynamic operator; These are the measured reference parameters; in the formula... Used to analyze the state deviation energy penalty between the operator derivation parameters and the measured baseline parameters, so as to ensure the underlying numerical accuracy of the model inversion results; This is the space impedance stability term. This is the dissipation control coefficient; It is a local spatial adjacency matrix; To analyze the structural parameters of adjacent node j derived by the parsing operator; in the formula The difference penalty used to calculate the predicted parameters between adjacent nodes constrains the inverted structural parameter field to possess optical smoothness characteristics that conform to the texture of natural land features in space. This energy functional ensures that the boundary condition field generated by the inversion possesses continuity in physical space that conforms to the texture of natural land features.

[0051] A multi-current radiative transport simulation kernel with a coupled absorption-scattering mechanism was selected as the inference engine.

[0052] Forward dynamics simulation: The reconstructed “vegetation canopy biochemical-morphological synergistic boundary condition field” is used as the evolutionary boundary of the engine, and the calibrated mean biochemical concentration inside the leaf (e.g., 45 μg / cm²) and environmental constraint parameters are input.

[0053] Global Evolution: The mapping kernel performs forward radiation dynamics analysis on all grid nodes in the global domain, evolving to generate a reference field for photosynthetically effective radiation.

[0054] Specifically, the forward analytic function of the radiative transfer simulation kernel is abstractly expressed as: ;in, The radiation reference value generated for the derivation; For a specific spectral band; This represents the three-dimensional physical space integral domain of the current canopy medium. For the field subject to boundary conditions Constrained nonlinear absorption-scattering cross-section function; To take ambient lighting To observation geometry and internal morphological distribution The phase decay function; This represents the background radiation flux.

[0055] (Note: The reference field obtained at this point already has a spatial trend that conforms to the mechanism, but due to the simplification of the underlying dynamic model, its absolute values ​​may have systematic deviations.) Step S3: Minimum Dissipation Path Solution Based on Potential Energy Coupling Deviation calibration: Extract the theoretical simulation values ​​of the 30 sampling points on the photosynthetically active radiation reference field, compare them with the measured true values ​​of the spectrum, and calibrate the radiation state deviation vector.

[0056] Potential field coupling and joint impedance surface reshaping: The fractional-order potential energy evolution gradient matrix of the photosynthetically active radiation reference field is solved to map the radiation energy gradient field reflecting the abrupt energy level of winter wheat concentration. The potential energy coupling mechanism is activated, and the energy gradient field is embedded into the fractional-order optical attenuation background tensor constructed in step S1, reshaping the radiation-structure joint impedance tensor. .

[0057] First, a joint dynamic drag surface is constructed based on the potential energy coupling mechanism: ;in, The fractional-order optical attenuation background tensor constructed in step S2; is the fractional-order directional derivative vector of the radiative potential energy; For tensor outer product operators; This is an adaptive adjustment coefficient for the coupling strength of the physical field. This impedance tensor not only senses the spatial geometric texture but is also controlled by the internal abrupt changes in the physical radiation mechanism.

[0058] Minimum Dissipation Optical Path Optimization Analysis: Using the joint impedance tensor as the physical constraint space, the minimum dissipation optical path for photon transmission between discrete nodes and globally unsampled nodes is optimized analytically. Specifically, to accurately characterize this complex photon transmission trajectory within the underlying hardware computing power, the system establishes an anomalous secondary diffusion mechanism and uses fractional-order function physical equations to solve for the evolution trajectory along the impedance surface between nodes. Its underlying mathematical mechanism is expressed as follows: ;in, For the fractional gradient operator of the joint resistance surface; For the fractional gradient operator in standard Euclidean space; The minimum dissipation optical path with the sampling point as the source is to be determined; It is the inverse matrix of the impedance tensor; This is the local diffusion rate function.

[0059] Step S4: Constrained Dynamic Evolution and Stress Gradient Analysis Based on the minimum dissipation optical path described above, the system is configured with hardware control weights possessing long-range memory decay characteristics to drive the constrained dynamic evolution of the radiation state deviation along the canopy microstructure. To realize this long-range memory decay characteristic in the control system, the underlying evolution model employs a heavy-tailed decay mechanism based on the Mittag-Leffler function for hardware computational allocation. ;in, These are the absolute coordinates of the spatial node to be repaired; For the first The coordinates of a discrete sampling node; N is the total number of discrete sampling nodes; The state deviation calibrated at the discrete sampling nodes; Nodes to be reconstructed With sampling nodes The minimum dissipation optical path is calculated along the joint impedance surface between them; The heavy-tailed attenuation optical dissipation weighting function is constructed based on the minimum dissipation optical path and the Mittag-Leffler function. Its physical meaning characterizes the directional penetration probability of a photon reaching the target node after undergoing multiple diffusion evolutions in a complex medium. This is the normalized partition function of the global optical transmission probability. This enables the realization of a global compensation field. The evolution and precise reconstruction of optical dissipation.

[0060] Specifically, in order to transform the "long-range memory decay characteristic" described in claim 1 into an executable low-level operator, the hardware control weight function... Based on the Mittag-Leffler function, its mathematical analytical expression is as follows: ;in, A single-parameter Mittag-Leffler function; For the least dissipated optical path; A scale factor used to control the diffusion decay rate; The characteristic order of the diffusion (value range 0 < <1); It is a gamma function; The non-negative integer index of the series expansion term.

[0061] Compared to the Gaussian weights that decay exponentially and rapidly in traditional Euclidean space, the Mittag-Leffler heavy-tailed function mechanism decays extremely slowly (power-law decay) over long distances, accurately preserving the long-range physical correlations of the canopy medium.

[0062] State evolution closed loop: reconstructing the global compensation field The closed loop is then superimposed back onto the photosynthetically active radiation reference field, thereby accurately dissipating the radiation state deviation in the forward extrapolation of the system and obtaining the initial extrapolation field.

[0063] To more intuitively understand the technical principles and effects of this step, please refer to... Figure 4 . Figure 4 This paper presents a comparison between the anomalous secondary diffusion based on the minimum dissipation optical path proposed in this invention (right figure) and the traditional isotropic fitting of Euclidean space (left figure). Figure 4 As shown on the left, existing technologies employ isotropic evolutionary influence domains, which cannot perceive the physicochemical abrupt boundaries of complex media, leading to unnatural state crossings that penetrate these boundaries and resulting in "blurring of mesoscopic structure and spectral state." However, as... Figure 4 As shown on the right, this invention utilizes the radiation-structure joint impedance tensor to dynamically adjust the evolution boundary of anomalous secondary diffusion into a dissipation-constrained surface conforming to the microstructure orientation. This physical-dynamic mechanism ensures that the dissipation evolution of radiation state deviation is a precise reconstruction along the minimum dissipation path with highly consistent physicochemical properties within the canopy medium.

[0064] Geometric scattering component analysis: Multi-directional spatial geometric analytical operators are used to analyze the continuous radiation field and capture the micro-geometric scattering components of the canopy (such as leaf margins and crevices).

[0065] State assimilation: An assimilation weight function based on multidimensional inner product energy similarity is constructed. In regions with highly homogeneous mesoscopic structures, the assimilation gain of the canopy microscopic geometric scattering components is enhanced to improve the resolution of the spatial microstructure; in regions with heterogeneous physical properties, the assimilation gain is attenuated to strictly suppress nonlinear spectral distortion of the multidimensional spectrum during deduction and reconstruction.

[0066] Specifically, the steady-state assimilation calculation model based on spectral energy conservation is as follows: First, calculate the initial inferred field feature vector within the local spatial neighborhood. With continuous radiation spectral vector spectral inner product similarity between (i.e., generalized spectral energy approximation): ;in, This represents the L2 norm of the eigenvector.

[0067] Secondly, an adaptive assimilation gain function is constructed based on this similarity. ; ;in, This is the gain adjustment coefficient; The threshold for mixed heterogeneity.

[0068] The final output is a high-precision mesoscopic state field of the vegetation canopy. The dimensions are expressed as follows: ;in, The initial inference field generated for the aforementioned anomalous secondary diffusion evolution is in the first... Radiation value of dimension; This refers to the microscopic geometric scattering components analytically extracted by a multi-directional spatial geometric analytical operator. This assimilation model mathematically guarantees that the intrinsic conservation ratio of the original spectral energy will not be disrupted during the state derivation process.

[0069] State extrapolation verification and gradient analysis: A high-fidelity continuous radiation field of the vegetation canopy with both 2.5cm spatial resolution and 1nm spectral dimension was generated. Cross-validation showed that the root mean square error (RMSE) of the high-fidelity vegetation canopy mesoscopic state field constructed in this embodiment was 0.012 at unsampled points, representing a 68% improvement in accuracy compared to traditional isotropic static fitting methods. Based on this high-fidelity state field, the nitrogen physiological stress gradient at different spatial nodes within the experimental field was accurately and quantitatively analyzed.

[0070] Step S5: Closed-loop of the physical execution layer of agricultural machinery with electro-hydraulic proportional coordination By combining the blocking effect of the joint impedance tensor on the minimum dissipation optical path, the physical boundary of microscopic mutations in agricultural machinery variable operations is defined, and the physiological stress gradient obtained above is transformed into a variable application prescription map file for winter wheat nitrogen fertilizer that can be recognized by the agricultural machinery's onboard navigation. After the prescription map is input to the agricultural tractor equipped with the variable fertilization system via the CAN bus, the physiological stress gradient data is mapped to the agricultural machinery navigation coordinate system by the variable control unit on the agricultural machinery. Combined with the spray nozzle dynamics model and the current agricultural machinery travel parameters (speed of about 2 m / s), the pipeline opening-speed coupling parameters are calculated in real time.

[0071] To seamlessly translate the high-precision spatial extrapolation results into physical actions, this embodiment embeds a hard-coded protocol based on the Mittag-Leffler heavy-tail decay mechanism into the underlying driver module. When the airborne data processing unit detects a step in the radiation-structure joint impedance tensor of the forward grid (i.e., crossing the boundary between health and stress), the CAN bus communication interface triggers a millisecond-level physical action response priority interrupt, instantly converting the impedance step into a PWM duty cycle fine-tuning or truncation command.

[0072] Specifically, the system outputs a PWM control signal to directly drive the electro-hydraulic proportional valve (such as a Bosch Rexroth high-frequency proportional solenoid valve). To overcome the static friction and hydraulic force of the main valve core within an extremely short time window, the underlying drive mechanism superimposes a high-frequency dither signal with a frequency of 200Hz and an amplitude of 5% of the rated current onto the basic PWM signal. The duty cycle fine-tuning command of this PWM control signal is first converted into the microscopic displacement of the armature of the pilot electromagnet inside the electro-hydraulic proportional valve, and then precisely controls the opening area of ​​the main valve core through a nonlinear hydrodynamic mapping relationship.

[0073] To ensure that the accuracy of physical application does not compromise the accuracy of algorithm deduction, the system sets the duty cycle adjustment accuracy of the PWM signal to ≥0.1%. Meanwhile, since the high-fidelity mesoscopic state field grid resolution reconstructed in this embodiment is as high as 2.5cm, the physical time window for traversing a single grid is only 12.5ms at a typical agricultural machinery operating speed (approximately 2m / s). Therefore, the system rigidly constrains the overall response delay from signal output to valve action to ≤10ms. According to dynamic calculations, a 10ms system delay will result in a maximum physical position control hysteresis of 2cm at a vehicle speed of 2m / s. Since this hysteresis distance (2cm) is strictly smaller than the physical size of the microscopic analytical grid (2.5cm), this stringent "spatiotemporal coupling constraint" ensures, in physical principle, that the error of the targeted application action will not cross the grid boundary and will always accurately fall within the target mesoscopic space.

[0074] Furthermore, such as Figure 5As shown, through high-frame-rate industrial camera capturing valve core displacement and joint calibration verification with a high-frequency flow meter, a strict physical causal mapping exists between the PWM control signal output by this system and the hydraulic actuator action: under the excitation of the flutter signal, the pilot stage electromagnet armature completes micro-displacement within 2.1ms, and the main valve core opening area reaches the target opening within 6.8ms, with an overall physical response delay of only 9.3±0.4ms as measured. At this time, for every 1% increase in the PWM duty cycle, the fertilizer application rate increases linearly by 0.82±0.03L / min. This detailed fluid dynamics and electromechanical calibration data thoroughly confirms the underlying hardware connectivity and high-frequency physical response capability of this invention from optical sensing to mechanical action, effectively eliminating nutrient stress in winter wheat and increasing the overall nitrogen fertilizer utilization rate of the experimental field by 21.5%.

[0075] Example 2

[0076] This embodiment aims to use the method described in this invention to perform high-fidelity radiation field simulation and precise control of forestry media targets (taking Masson pine forest as an example) under complex undulating terrain, so as to isolate the geometric and physical interference of the terrain and monitor the changes in canopy mesoscopic structure caused by early physiological stress.

[0077] Please refer to Figure 1 The specific implementation steps of this embodiment are as follows: Step S1: Multi-source optics-agricultural machinery collaborative hardware sensing and physical impedance field mapping Data collection environment: Hilly forest areas with different health gradients were selected, and data were collected during sunny, cloudless summer days with stable light.

[0078] Acquisition of continuous radiation field data of crop canopy: A high-precision low-altitude unmanned aerial vehicle (UAV) platform equipped with a multi-channel radiation sensor array was used. This platform integrates a detection payload with a spectral response range covering 400-2500 nm, a centimeter-level RTK positioning module, and an onboard data processing unit. With a relative flight altitude of 50 meters, continuous radiation field data of crop canopy with a spatial resolution of approximately 0.05 meters was acquired. The overlap rates in both the flight direction and the lateral direction were set to be no less than 75% to ensure the robustness of subsequent three-dimensional morphological analysis.

[0079] Discrete multi-band canopy spectral sequence acquisition: A portable hyperspectral acquisition terminal (covering the 350-2500nm band) was used simultaneously to acquire discrete multi-band spectra of the canopy of 30 pre-selected sample trees within the sample plot, and the average value was taken. The three-dimensional geospatial coordinates of each sampling point were recorded using a centimeter-level high-precision positioning module.

[0080] Atmospheric-microtopographic boundary parameters: obtaining aerosol optical thickness and near-surface water vapor content; extracting illumination and observation geometric parameters; deriving the microtopographic gradient field (slope, aspect) of the sample plot from the 1:10,000 high-precision digital elevation model (DEM) to constrain the shadow effect of hilly terrain.

[0081] Spatial coordinate mapping: The coordinates of discrete sampling points are used as vector nodes and superimposed with the continuous radiation field data of agricultural and forestry crop canopies to align with a high-precision coordinate reference.

[0082] Definition of homogeneous optical domain: A multi-scale medium boundary constraint model is adopted, and the scale and compactness parameters are optimized for the tree canopy characteristics. The continuous radiation field is decomposed into medium units (single tree canopy), background patches and shadow patches with homogeneous optical properties.

[0083] Attenuation Tensor Mapping and Drag Extraction: The system extracts multi-scale photoelectric response attenuation gradients within the target patch using an onboard data processing unit. Due to the hilly terrain, the tree canopy has distinct "sun-facing" and "shaded" sides. The system accurately quantifies the physical response heterogeneity and optical transmission drag caused by the direction of illumination, mapping a continuous optical attenuation background tensor. This tensor can intelligently establish a physical barrier between the sun-facing and shaded sides during subsequent evolution.

[0084] Step S2: Forward simulation of radiation mechanism under physicochemical evolution constraints Physicochemical operator analysis: Nonlinear difference operators are constructed using the characteristic bands of the continuous radiation field, and physicochemical analytical operators for canopy structure parameters are established by combining ground-measured spectral reference data.

[0085] Global Reconstruction: This operator is applied to the full-width continuous radiation field to invert and reconstruct a global vegetation canopy biochemical-morphological synergistic boundary condition field that has been stripped of topographic geometric interference. This boundary condition field intuitively reflects the physiological structural variations caused by diseases and is the core boundary condition driving the subsequent radiation simulation kernel.

[0086] Model selection: A radiative transfer simulation kernel with coupled geometric optics occlusion mechanism was chosen. This kernel is particularly adept at resolving the photon collision and anisotropic scattering patterns in discontinuous canopy media under complex three-dimensional terrain.

[0087] Physical simulation and deduction: Input: The reconstructed “vegetation canopy biochemical-morphological synergistic boundary condition field”, the “micro-topographic gradient field” exported from the DEM, and the illumination geometric parameters are used as the dynamic boundary condition input simulation kernel.

[0088] Operation: The simulation verifies the forward radiation dynamics of the entire forest area on a grid-by-grid basis, and evolves the absolute intrinsic radiation flux that each spatial node should exhibit under the current terrain and illumination boundaries.

[0089] Output: Generates a photosynthetically active radiation reference field containing full-band mechanism information.

[0090] Step S3: Minimum Dissipation Path Solution Based on Potential Energy Coupling Deviation calibration: The measured sequence of multi-band samples from 30 discrete sampling points is compared with the theoretical simulation value of the photosynthetically active radiation reference field to calibrate the radiation state deviation vector of the system.

[0091] Potential field coupling and joint impedance surface reshaping: The fractional-order potential energy evolution gradient matrix of the photosynthetically active radiation reference field is solved to map the radiation energy gradient field characterizing the boundary of early physiological stress mutations. The potential field coupling mechanism is activated and embedded as an additional dynamic physical perturbation term into the fractional-order optical attenuation background tensor constructed in step S1, reshaping it into a radiation-structure joint impedance tensor with a mesoscopic mutation barrier.

[0092] Minimum Dissipation Optical Path Optimization Analysis: Using the reconstructed joint impedance tensor as the physical constraint space, the minimum dissipation optical path for photon transmission between discrete nodes and globally unsampled nodes is optimized analytically. In the low-level solution of the airborne data processing unit, the system uses fractional-order function physical equations to solve for the evolution trajectory along the impedance surface between each node. This physical constraint space allows the photon transmission algorithm derivation to adaptively avoid the abrupt canopy closure boundaries of high impedance forest areas.

[0093] Step S4: Constrained Dynamic Evolution and Stress Gradient Analysis Constrained Dynamic Evolution and Boundary Blocking: Using the joint impedance tensor as the physical constraint space, the algorithm seeks the analytical minimum dissipation optical path. When driving the radiation state deviation to migrate in a constrained manner, the underlying algorithm configures hardware control weights with long-range memory decay characteristics (relying on the Mittag-Leffler heavy-tail decay mechanism), so that it not only evolves along the pure geometric isoilluminance line, but is also constrained by the high barrier of the physical mechanism field: once the propagation path penetrates the "abrupt boundary" at the junction of health and stress, the joint impedance tensor will induce a violent photoelectric response decay abrupt change, causing the path to diverge, thereby strictly blocking the unnatural outbound migration of the radiation state deviation.

[0094] State evolution closed loop: The global compensation field is reconstructed and its closed loop is superimposed back to the photosynthetically effective radiation reference field, thereby accurately dissipating the radiation state deviation of the system's forward extrapolation and obtaining the initial extrapolation field.

[0095] State Assimilation: Multi-directional spatial geometric analytical operators are used to analyze the microscopic morphological characteristics of the continuous radiation field. Under the constraint of spectral energy conservation, an assimilation weight function based on multidimensional inner product energy similarity is constructed to assimilate the steady-state microscopic geometric scattering components of the canopy to the initial extrapolation field, outputting the final high-precision mesoscopic state field of the vegetation canopy.

[0096] Stress Feature Identification and Gradient Analysis: High-fidelity multi-band physical response curves for different health gradient targets are extracted from the final high-precision mesoscopic state field of the vegetation canopy. Please refer to... Figure 6 The high-fidelity physical response curves clearly show that: the baseline healthy state exhibits a steep dynamic response in the 700-750nm region (red edge); mild canopy microvariation states show a blue shift in physical potential energy and a significant decrease in near-infrared reflectance flux; and severe mesoscopic structural variation states show a gradual response evolution with a sharp drop in reflectance flux. By deconstructing the physical response boundaries of sensitive absorption valleys in multi-band sequences to calibrate mesoscopic heterogeneity states, the physiological stress gradient in forest areas was quantitatively analyzed. The accuracy of early microvariation analysis reached 92.5%, significantly better than the traditional isotropic static fitting algorithm (75%) that does not incorporate optical impedance surfaces and anomalous secondary diffusion evolution mechanisms. This extremely high-precision early microvariation analysis provides an absolutely reliable physical trigger threshold for the "millisecond-level precise cutoff" of the UAV electro-hydraulic proportional valve in the complex forest area in subsequent step S5.

[0097] Step S5: Closed-loop of the physical execution layer of agricultural machinery with electro-hydraulic proportional coordination By combining the blocking effect of the joint impedance tensor on the minimum dissipation optical path with the above-mentioned early physiological stress diagnosis results, the physical boundary of micro-mutation of targeted drug application in forest areas is defined, the micro-occurrence range of diseases in Masson pine forests (such as pine wilt disease) is accurately located, and the physiological stress gradient is converted into a targeted drug application prescription map file for forest diseases that can be identified by agricultural machinery onboard navigation.

[0098] After the prescription map instruction is sent to the forestry aviation plant protection platform, the airborne navigation system, relying on the variable control unit on the platform and combined with RTK positioning, maps the prescription map to a three-dimensional spatial coordinate system, and calculates the flight speed coupling parameters in real time by combining the preset aviation spray nozzle dynamics model and UAV travel parameters.

[0099] In complex and undulating forest terrain, aerial plant protection operations are highly susceptible to pesticide drift due to wind fields and response lag. To address this, this embodiment fully utilizes the "mesoscopic mutation barrier" constructed in step S3. When the aerial plant protection drone crosses the high barrier (i.e., the physical boundary between diseased and healthy tree canopies) calibrated by the joint impedance tensor at a specific speed (e.g., 5 m / s), the onboard underlying hardware driver module extracts the impedance mutation signal and forcibly sends a PWM duty cycle cutoff command via the CAN bus.

[0100] Driven by this command, the electro-hydraulic proportional valve of the aerial spraying system rapidly cuts off the pilot oil circuit within ≤10ms, driving the high-frequency electromagnetic anti-drip valve to close instantly. Simultaneously, the high-pressure liquid in the pipeline is rapidly depressurized through the bypass return valve. This hardware-level electrical cutoff, directly triggered by the optical impedance barrier, allows the nozzle flow rate to drop from full load to zero within 8.5ms the moment the drone leaves the diseased tree canopy, with the physical position control error strictly limited to within 5cm (5m / s × 10ms = 5cm). Finally, the system outputs a PWM control signal with a duty cycle and response delay strictly matched to the microscopic analytical grid resolution, directly driving the aerial plant protection equipment to complete targeted physical control. This physical-level closed loop enables early and precise eradication of diseases in complex undulating terrain, completely preventing accidental spraying of healthy forest areas due to macroscopic data processing delays at the hardware and electrical level, thus avoiding the ecological risk of diseases evolving into macroscopic death and large-scale spread.

[0101] Furthermore, the physical control method and precise management closed loop described in this invention are not limited to the aforementioned nitrogen fertilizer variable addition and aerial targeted pesticide application. Based on the high-fidelity vegetation canopy mesoscopic state field reconstructed by this invention, those skilled in the art can combine it with multi-source agricultural / ecological response models to derive various precise management variants of physical automated equipment. For example: (1) Meteorological stress defense linkage: By analyzing the microscopic characteristics of early low temperature damage and heat dissipation in the mesoscopic state field of the orchard canopy, the optical impedance boundary is directly mapped to the thermodynamic intervention boundary, and the bottom PWM control signal is output. The opening of the combustion valve of the intelligent anti-frost heating device deployed on the slope terrain or the servo motor speed of the turbulence fan is adjusted in millisecond-level delay to achieve a precise electromechanical control closed loop for cold protection and disaster avoidance. (2) Biological stress sound and light intervention: By analyzing the abnormal distribution of micro-geometric scattering caused by specific insect pests (such as pine caterpillars) in the forest canopy, the micro-outbreak center of the pest is defined. Based on the underlying hardware driver module, the hardware control command with adjustable duty cycle is output to the Internet of Things node in the forest area. At the moment of crossing the pest impedance boundary, the control relay of the sound wave insect repellent device or the trapping lamp array in a specific frequency band is hard-triggered to realize the automated physical ecological management of non-chemical reagents.

[0102] The embodiments described above are merely some preferred implementations of the present invention in specific agricultural and forestry scenarios. Those skilled in the art should understand that the "optical impedance physical deduction and agricultural machinery execution layer closed-loop" architecture described in this invention is not limited to the specific crop varieties or operating equipment mentioned above. Its core principle of cross-physical field control, from mesoscopic quantum impedance to macroscopic electromechanical / hydraulic impedance, can also be seamlessly transferred to broader intelligent ecological equipment physical intervention scenarios. For example, the hydraulic variable-drive for wetland vegetation ecological restoration equipment, the motor control of precision physical seeding devices in grassland degradation areas, and even the adaptive cruise and variable-drive of pesticide pump valves for unmanned vessels used for algae control in complex waterways—all fields of intelligent agricultural machinery and physical ecological engineering that require the collaborative operation of "multi-source optical precision sensing and automated physical hardware operation." All equivalent substitutions and extensions made within the physical deduction framework and underlying electromechanical control mechanism of this invention should be included within the scope of protection of this invention.

[0103] The above are merely preferred embodiments of this application and are not intended to limit this application. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A physical control method for variable-rate agricultural and forestry operations based on optical impedance dissipation, characterized in that, Includes the following steps: S1. Construct a multi-source optical-agricultural machinery collaborative hardware sensing system, which includes a low-altitude unmanned aerial vehicle platform equipped with a multi-channel radiation sensor array and a centimeter-level RTK positioning module, and a portable hyperspectral acquisition terminal; acquire continuous radiation field data of agricultural and forestry crop canopy in the target area through the low-altitude unmanned aerial vehicle platform, and acquire discrete multi-band canopy spectral sequences in the target area through the portable hyperspectral acquisition terminal; extract the photoelectric response attenuation gradient of the continuous radiation field in multi-scale space through the airborne data processing unit, quantify the physical transmission resistance of agricultural machinery micro-operations, and generate a global continuous optical attenuation background tensor; S2. The airborne data processing unit calls a preset multi-band collaborative analysis operator to convert the continuous radiation field data into a vegetation canopy biochemical-morphological collaborative boundary condition field; using the vegetation canopy biochemical-morphological collaborative boundary condition field as input, it drives the radiation transfer simulation kernel of the coupled absorption-scattering mechanism, and combines atmospheric and micro-topographic environmental parameters to evolve and output a photosynthetically effective radiation reference field. S3. Calibrate the deviation of the radiative state between the photosynthetically active radiation reference field and the discrete multi-band canopy spectral sequence at the sampling node; By utilizing the radiation potential energy coupling mechanism, the potential energy directional derivative of the photosynthetically active radiation reference field is embedded into the optical attenuation background tensor, thus reshaping and forming the radiation-structure joint impedance tensor. Using the radiation-structure joint impedance tensor as the constraint space, the minimum dissipation optical path between discrete nodes and unsampled nodes in the global domain is analyzed. S4. Based on the minimum dissipation optical path, configure the hardware control weights for driving the response of the electro-hydraulic proportional valve; The radiation state deviation is driven to migrate in a restricted manner along the direction of the canopy microstructure, generating a global compensation field; The global compensation field is superimposed on the photosynthetically active radiation reference field, the microscopic geometric scattering components are analyzed and assimilated, and a high-fidelity vegetation canopy mesoscopic state field is reconstructed and output, and the physiological stress physical gradient is generated. S5. Combining the microscopic mutation physical boundary defined by the radiation-structure joint impedance tensor, the physiological stress physical gradient is transformed into a prescription map file that can be recognized by the agricultural machinery's onboard navigation; relying on the agricultural machinery variable control unit, combined with the spray nozzle dynamics model and the agricultural machinery's travel parameters, a PWM control signal is generated to drive the electro-hydraulic proportional valve to adjust the hydraulic actuator's action, thereby realizing agricultural and forestry variable operations.

2. The method for physical control of agricultural and forestry variable operations based on optical impedance dissipation according to claim 1, characterized in that, The generation of the optical attenuation background tensor includes the following steps: The anisotropic attenuation rate is calculated using the Grünwald-Letnikov fractional calculus method. The dominant characteristic components of the anisotropic attenuation rate are extracted to define the local optical attenuation factor. The spatial absolute coordinates are coupled with the local optical attenuation factor to generate a fractional optical attenuation background tensor.

3. The method for physical control of agricultural and forestry variable operations based on optical impedance dissipation according to claim 1, characterized in that, The vegetation canopy biochemical-morphological synergistic boundary condition field includes the volume scattering element density or leaf area index characterizing the three-dimensional distribution of the canopy; the multi-band synergistic physicochemical analytical operator is a nonlinear operator used to analyze the physicochemical mapping relationship between continuous radiation field data and the vegetation canopy biochemical-morphological synergistic boundary condition field.

4. The method for physical control of agricultural and forestry variable operations based on optical impedance dissipation according to claim 1, characterized in that, The radiative transfer simulation kernel of the coupled absorption-scattering mechanism is a radiative transfer dynamics model constrained by illumination-observation geometry. The radiative transfer dynamics model couples the geometric optical shading effect with the multiple scattering effect inside the canopy, and uses the biochemical-morphological synergistic boundary condition field of the vegetation photosphere as input to analyze the biaxial reflection distribution characteristics at each node in space.

5. The method for physical control of agricultural and forestry variable operations based on optical impedance dissipation according to claim 1, characterized in that, The minimum dissipation optical path between the analytical discrete node and the globally unsampled node includes the following steps: The fractional-order potential energy evolution gradient matrix of the photosynthetically active radiation reference field is solved to generate a radiation energy gradient field. The radiation energy gradient field is embedded into the fractional-order optical attenuation background tensor to reshape the radiation-structure joint impedance tensor. An anomalous secondary diffusion mechanism is established using the radiation-structure joint impedance tensor as the constraint space. The evolution trajectory along the impedance surface between each node is solved using the fractional-order equation to obtain the minimum dissipation optical path.

6. The method for physical control of agricultural and forestry variable operations based on optical impedance dissipation according to claim 1, characterized in that, The restricted migration includes the following steps: An optical dissipation weight based on the Mittag-Leffler function is constructed to characterize the power-law decay characteristics of vegetation mesoscopic impedance; the radiation state deviation is driven to perform anomalous sub-diffusion dynamics evolution to generate a global compensation field; the state mixing degree in the local neighborhood after superimposing the compensation field is evaluated, and a dynamically adjusted canopy structure scattering gain function is established; the assimilation gain of the microscopic geometric scattering component is enhanced in the structurally homogeneous region, and the assimilation gain is attenuated in the heterogeneous boundary region.

7. The method for physical control of agricultural and forestry variable operations based on optical impedance dissipation according to claim 1, characterized in that, Converting the physical gradient of physiological stress into a prescription map file recognizable by agricultural machinery onboard navigation includes the following steps: Based on the physical gradient of physiological stress, and combined with the microscopic mutation physical boundary indicated by the radiation-structure joint impedance tensor, the target region is divided into different mesoscopic spatial grids; for different mesoscopic spatial grids, and combined with the preset physiological response model, differentiated targeted operation parameters are calculated; the grid data carrying the targeted operation parameters and spatial topological coordinates is converted into prescription map files that can be recognized by agricultural machinery onboard navigation.

8. The method for physical control of agricultural and forestry variable operations based on optical impedance dissipation according to claim 1, characterized in that, The underlying coupling mechanism between the collaborative sensing hardware of the low-altitude unmanned aerial vehicle (UAV) flight platform and the agricultural machinery execution end includes: The airborne data processing unit embeds a hardware driver module based on the Mittag-Leffler heavy-tail attenuation mechanism. During variable operation, the hardware driver module extracts the mesoscopic abrupt change physical boundary calibrated by the optical attenuation background tensor and the radiation-structure joint impedance tensor, and converts it into a PWM duty cycle cutoff command for the electro-hydraulic proportional valve. The CAN bus communication interface on the agricultural machinery side is configured with a millisecond-level response priority interrupt mechanism, which is used to issue the PWM duty cycle cutoff command with a system bus delay of ≤10ms at the moment when the agricultural machinery crosses the mesoscopic abrupt change physical boundary.

9. A method for physical control of agricultural and forestry variable operations based on optical impedance dissipation according to claim 8, characterized in that, The underlying driving process for generating PWM control signals includes the following steps: The physiological stress physical gradient data carrying the targeted operation parameters are mapped and transformed into the airborne navigation coordinate system of the agricultural and forestry operation equipment; combined with the dynamic model of the spray nozzle, the agricultural machinery travel parameters, and the microscopic geometric scattering anomaly distribution of the high-fidelity vegetation canopy mesoscopic state field output, the pipeline opening-speed coupling parameters are calculated; the pipeline opening-speed coupling parameters are converted into electrical signals to generate PWM control signals that drive the electro-hydraulic proportional valve to regulate the hydraulic actuator.

10. A method for physical control of variable-rate agricultural and forestry operations based on optical impedance dissipation according to claim 9, characterized in that, The PWM control signal drives the electro-hydraulic proportional valve, including the following steps: The duty cycle fine-tuning command of the PWM control signal is converted into the armature displacement of the pilot electromagnet inside the electro-hydraulic proportional valve; a nonlinear hydrodynamic mapping relationship between the armature displacement and the opening area of ​​the main valve core is established; within a response delay window of ≤10ms, the high-frequency chattering characteristic of the PWM control signal is used to overcome the static friction of the main valve core, so that the output flow of the hydraulic actuator matches the microscopic analytical grid resolution of the mesoscopic state field of the vegetation canopy.

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