Construction of nonlinear response model of soil moisture and implementation system of precise water distribution

Abstract

The present application relates to the technical field of general control system of nonlinear feedback and precision process control, disclose a kind of construction and accurate water distribution execution system of soil moisture nonlinear response model, including characteristic perception module, infiltration damping observation module, pulse width modulation module and actuator module, module calculates the derivative term of porous medium controlled object characteristic parameter, extracts the instantaneous slope of trajectory vector in infiltration dynamic phase plane, and utilizes determination logic to trigger duty cycle constraint when second derivative term is negative and instantaneous slope absolute value exceeds threshold, and the medium flow rate is adjusted by actuator, the present application utilizes trajectory curvature feature to characterize the nonlinear evolution of internal damping of controlled object, realizes the pre-judgment to infiltration stall point, eliminates the physical phase lag of control loop, suppresses the adjustment overshoot, and ensures the operation of system under complex damping working condition.

Description

Construction of Soil Moisture Nonlinear Response Model and Precision Water Distribution Execution System Technical Field

[0001] This invention relates to the construction of a nonlinear soil moisture response model and a precise water distribution execution system, belonging to the technical field of general control systems for nonlinear feedback and precision process control. Background Technology

[0002] Current agricultural water resource management utilizes automated systems for precision irrigation. By monitoring soil moisture content deviations, electromagnetic valve groups are switched on and off according to preset logic to maintain stable soil moisture in the controlled area. The infiltration process of porous soil media is driven by the coupling of matrix potential, gravitational potential, and pore air pressure. Water enters the micropores and is obstructed from escaping into the gas phase. The infiltration rate exhibits a nonlinear decay characteristic as the moisture content increases. The controlled object shows time-varying damping characteristics that fluctuate drastically with changes in moisture content during the irrigation response process.

[0003] Existing technologies employ linear models or fixed-gain adjustment, which address the controlled object model mismatch problem in soil physical response. During the dry season, soil physical damping is low, requiring rapid response adjustment; near saturation, physical damping surges, and existing control parameters cause feedback overshoot. Increasing sensor accuracy or real-time Richards equation solving presents challenges in parameter accuracy and high deployment costs. Besides hardware limitations, algorithmic logic lag and control mismatch restrict system steady-state performance. For example, Chinese invention patent CN118883454B discloses a soil moisture content feedback method based on multi-temporal soil line consistency correction. The proposed method and system integrates multiple optical images to construct a theoretical feature space and uses soil slope to correct the drought index to improve the accuracy of water content inversion. However, this inversion scheme is based on static observation and focuses on macroscopic estimation of the state of the controlled object. It lacks microscopic capture of the instantaneous dynamic characteristics of the water infiltration process. The water distribution execution link cannot identify the nonlinear evolution of damping inside the soil medium and cannot establish physical coupling between the sensing data and the pulse characteristics of the actuator. There is a physical phase lag when facing the infiltration stall point. The logic framework that emphasizes inversion over control causes the system to produce regulation overshoot and deep leakage under complex damping conditions, which cannot meet the requirements of precise flow regulation.

[0004] Therefore, the technical problem to be solved by this invention is how to construct a general closed-loop control model that can capture the nonlinear time-varying characteristics of the physical evolution of the controlled object in real time and has the functions of adaptive parameter tuning and physical state alignment, solve the problem of physical phase lag of the control loop and steady-state stall of the system under complex damping conditions, and realize adaptive flow regulation in precision process control. Summary of the Invention

[0005] To address the problems mentioned in the background art, the technical solution of this invention is as follows: A system for constructing a nonlinear soil moisture response model and implementing precise water distribution, comprising a soil moisture data acquisition module, an infiltration damping observation module, a pulse width modulation module, and an actuator module:

[0006] The infiltration damping observation module is connected to the soil moisture data acquisition module, and the infiltration damping observation module is equipped with a phase plane mapping unit.

[0007] The pulse width modulation module is connected to the infiltration damping observation module. The pulse width modulation module contains decision logic and constraint logic.

[0008] The input terminal of the actuator module is connected to the output terminal of the pulse width modulation module;

[0009] The soil moisture data acquisition module is used to obtain real-time water content sequences that characterize the state of the controlled object;

[0010] The infiltration damping observation module is used to calculate the first and second derivative terms of the real-time water content sequence. It also uses the phase plane mapping unit to construct an infiltration dynamic phase plane with the first derivative term as the abscissa and the second derivative term as the ordinate. The module calculates the instantaneous slope of the trajectory vector of the real-time water content sequence in the infiltration dynamic phase plane. The instantaneous slope is defined as the ratio of the second derivative term to the first derivative term.

[0011] The pulse width modulation module is used to generate a stall trigger signal when the second derivative term is negative and the absolute value of the instantaneous slope exceeds a preset damping change threshold using judgment logic. Then, it uses constraint logic to respond to the stall trigger signal and reduces the duty cycle of a preset reference control pulse sequence according to a ratio that is monotonically increasing with the absolute value of the instantaneous slope, thereby generating an adjustment drive command.

[0012] The actuator module is used to receive adjustment drive commands and adjust the medium flow rate in the delivery pipeline.

[0013] Preferably, the infiltration damping observation module is equipped with a causal arbitration logic. The causal arbitration logic is used to establish the temporal correlation between the regulation driving command and the real-time water content sequence when the regulation driving command is in the pulse opening period, and to activate the feature extraction of the second derivative term. When the change characteristics of the real-time water content sequence do not match the triggering timing of the regulation driving command, the pulse width modulation module locks the current duty cycle regulation state constant to suppress random interference signals induced by non-regulation, and ensures that the input data of the judgment logic comes from the real infiltration feedback.

[0014] Preferably, the pulse width modulation module executes adaptive sleep logic; outside the pulse opening period of the adjustment drive command, the infiltration damping observation module monitors the downward slope of the real-time water content sequence; when the downward slope is greater than the preset slope threshold, the pulse width modulation module switches to the off state and proportionally extends the sampling interval of the soil moisture data acquisition module until the downward slope is lower than the preset slope threshold, so as to utilize the residual energy of the soil to complete the medium infiltration.

[0015] Preferably, the system also includes an initial boundary calibration module; before the formal adjustment cycle starts, the pulse width modulation module outputs a standardized detection medium flow of a preset duration from the command execution module; the initial boundary calibration module identifies the initial infiltration resistance of the controlled object based on the water content rise slope of the standardized detection medium flow fed back by the infiltration damping observation module, and performs feedforward bias compensation on the gain of the adjustment drive command based on the initial infiltration resistance.

[0016] Preferably, the infiltration damping observation module includes a bypass leakage determination unit; the bypass leakage determination unit is used to calculate the instantaneous fluctuation residual of the real-time water content sequence relative to the predicted value of the dynamic compensation model; when the variance of the instantaneous fluctuation residual exceeds the preset structural mutation threshold, the pulse width modulation module activates the gain clamping logic to limit the upper limit of the duty cycle of the adjustment drive command, so as to prevent the risk of deep leakage caused by the infiltration of non-uniform media.

[0017] Preferably, the system further includes a zero-point drift correction module; the zero-point drift correction module is used to obtain the measured saturation characteristic value of the controlled area within the steady-state range where the first derivative of the real-time water content sequence tends to zero; the zero-point drift correction module generates a zero-point compensation bias based on the deviation between the measured saturation characteristic value and the preset calibration benchmark, and feeds the zero-point compensation bias back to the infiltration damping observation module to perform online zero-point correction on the real-time water content sequence.

[0018] Preferably, the infiltration damping observation module executes an asynchronous interference filtering program; this program monitors slope abrupt changes in the real-time water content sequence and calculates the timing offset of these abrupt changes relative to the pulse edge in the adjustment drive command; when the timing offset exceeds a preset physical response time delay interval, the infiltration damping observation module determines that the current slope abrupt change is caused by pipeline pressure fluctuations and locks the current gain correction factor, wherein the physical response time delay interval is set to... to .

[0019] Preferably, the pulse width modulation module determines the corrected duty cycle for generating the adjustment drive command according to the following rules. : ,in, To adjust the output duty cycle of the drive command, The original duty cycle of the control pulse sequence is used as a reference. The instantaneous slope The preset reduction weighting coefficient is used; when the second derivative term is negative and the absolute value of the instantaneous slope exceeds the preset damping change threshold, the pulse width modulation module activates the calculation logic for correcting the duty cycle.

[0020] Preferably, the system also includes a fluctuation feedback module, which is used to collect the instantaneous head pressure of the delivery pipeline; when the pulse width modulation module generates the adjustment drive command, it superimposes a gain correction term that is inversely proportional to the instantaneous head pressure to compensate for the interference of external pipeline pressure fluctuations on the adjustment accuracy.

[0021] Preferably, the soil moisture data acquisition module includes a distributed frequency domain reflectance sensor array, used for... to The real-time water content sequence is extracted within the sampling period; the infiltration damping observation module extracts the water content sequence within the continuous sampling period. The data from each sampling period are weighted and averaged to smooth the waveform characteristics of the first and second derivative terms and suppress quantization noise generated by sampling.

[0022] Compared with the prior art, the beneficial effects of the present invention are:

[0023] 1. In the nonlinear response model of soil moisture, the first and second derivative terms of water content are used to construct the infiltration dynamic phase plane. The motion trajectory vector of the real-time water content sequence on the phase plane is extracted, enabling the system to have the ability to predict the limit of physical energy acceptance inside the controlled object and the ability to compensate for nonlinearity. Through the control algorithm of the phase plane trajectory curvature, the parameter self-optimization and real-time clamping of control gain are realized in the nonlinear feedback process, which improves the stability of the system for time-varying nonlinear links. While ensuring the robustness of the control system, it avoids water from exceeding the crop root layer and causing deep leakage.

[0024] 2. Establish a causal arbitration logic between the water distribution drive command and the real-time moisture content sequence. Use the actuator action pulse as the reference system for information extraction. Combined with an asynchronous interference filtering program, the physical meaning of the sensing signal is purified. The system activates the second derivative term feature extraction within the preset physical response time delay interval after the water distribution pulse is activated. The signal fluctuations that do not have a time-series coupling relationship with the water distribution action are judged as background noise caused by external pipeline pressure fluctuations. The multi-mechanism collaborative signal processing method enables the control loop to have noise resistance. It can shield non-irrigation induced random interference without relying on digital filtering algorithms. It ensures that each adjustment of the nonlinear compensation factor comes from the actual soil infiltration feedback, and improves the system's operational robustness under complex pipeline network multi-valve concurrent conditions.

[0025] 3. A multi-dimensional closed-loop maintenance system integrating initial boundary calibration, bypass leakage detection, and zero-point drift correction is implemented. By deeply mining the physical fingerprints generated at different stages of the control process, the state of the controlled object is refined. The initial boundary calibration module uses the echo slope of the standardized probe water flow before formal water distribution to set the feedforward bias for the acceleration compensation logic, eliminating systematic deviations in the initial stage of control. The bypass leakage detection unit uses the instantaneous fluctuation residual of the measured data stream relative to the predicted value of the dynamic model to identify non-uniform infiltration mutations caused by soil cracking or biological porosity, and prevents leakage risks through gain clamping constraints. The zero-point drift correction module uses the steady-state residual signal of the gravity redistribution equilibrium stage after irrigation stops to achieve online dynamic compensation for sensor aging. The information reuse mechanism throughout the entire operation cycle enables the system to have adaptive alignment capability for environmental changes, extending the maintenance-free cycle of field battery-powered nodes while ensuring control accuracy. Attached Figure Description

[0026] Figure 1 is a control logic block diagram of the nonlinear response to soil moisture and the precision water distribution system of the present invention;

[0027] Figure 2 is a comparison of the steady-state performance of the control strategy under the multi-gradient initial moisture content of the present invention;

[0028] Figure 3 is a timing diagram of the interaction between bypass leakage risk identification and gain clamping protection in this invention. Detailed Implementation

[0029] The present invention will be further described below with reference to the accompanying drawings and embodiments. The following description is only for explaining the present invention and does not constitute a limitation on the scope of protection of the present invention.

[0030] This invention provides a soil moisture nonlinear response model construction and a precise water allocation execution system, comprising a soil moisture data acquisition module, an infiltration damping observation module, a pulse width modulation module, and an execution mechanism module. The soil moisture data acquisition module is connected to the infiltration damping observation module to acquire the real-time soil moisture content sequence of the controlled area. The infiltration damping observation module includes a phase plane mapping unit for calculating the first and second derivative terms of the real-time moisture content sequence and constructing the dynamic phase plane of infiltration. The pulse width modulation module is connected to the infiltration damping observation module and includes decision and constraint logic to generate adjustment drive commands based on the characteristic parameters output by the infiltration damping observation module. The input end of the execution mechanism module is connected to the output end of the pulse width modulation module to receive the adjustment drive commands and adjust the medium flow rate in the delivery pipeline. To address the interference of time-varying damping generated by the porous soil medium at different moisture contents on the sensing accuracy, the soil moisture data acquisition module employs a distributed frequency domain reflectance sensor array. ms to The real-time water content sequence is extracted within a sampling period of milliseconds (ms), and the infiltration damping observation module continuously... The data from each sampling period are weighted and averaged to smooth the waveform characteristics of the first and second derivative terms and suppress quantization noise generated by sampling.

[0031] During the construction of the infiltration dynamic phase plane, the infiltration damping observation module uses the first derivative term as the abscissa and the second derivative term as the ordinate to calculate the instantaneous slope of the trajectory vector of the real-time water content sequence within the infiltration dynamic phase plane. Instantaneous slope Follow the following relationships: In the formula, The instantaneous slope; It is the second derivative term; The second derivative term is the first derivative term; the pulse width modulation module uses decision logic to monitor characteristic parameters, and when the second derivative term is negative and the instantaneous slope is... When the absolute value exceeds the preset damping mutation threshold, a stall trigger signal is generated. The constraint logic responds to the stall trigger signal by reducing the duty cycle of the preset reference control pulse sequence according to the following formula, and generating an adjustment drive command: ,in, To adjust the output duty cycle of the drive command; The original duty cycle of the control pulse sequence is used as a reference. The preset reduction weight coefficient; The instantaneous slope is used; by nonlinearly reducing the duty cycle, the system avoids feedback overshoot caused by a surge in the physical damping of the controlled object, achieving dynamic alignment between the control gain and the object characteristics, and enabling the water distribution flow rate to self-calibrate as the soil's carrying capacity decreases; to offset the nonlinear interference caused by external water supply network pressure fluctuations on the water distribution flow rate, a real-time pressure gain compensation procedure is executed through a fluctuation feedback module, which collects the instantaneous head pressure of the delivery pipeline in real time. The system's internal memory stores a set of reference head pressures corresponding to the rated flow conditions. Processing logic calculation gain correction term Gain correction term Follow the formula below: ,in, For gain correction term, As the reference head pressure, For instantaneous head pressure, the pulse width modulation module, during the generation of adjustment drive commands, will use the original output duty cycle calculated based on the phase plane trajectory characteristics. With gain correction term The multiplication operation is performed to obtain the final drive command after superimposed pressure compensation, so that the flow rate of the medium in the delivery pipeline remains constant through active reverse adjustment of the duty cycle when the pressure at the pipeline end changes abruptly.

[0032] To shield against pressure fluctuations caused by concurrent operation of multiple valves in complex pipe networks, the infiltration damping observation module incorporates a causal arbitration logic and an asynchronous interference filtering program. When the adjustment drive command is in the pulse-on period, it establishes a temporal correlation between the adjustment drive command and the real-time water content sequence, and activates feature extraction of the second derivative term. The asynchronous interference filtering program monitors slope abrupt changes in the real-time water content sequence and obtains the temporal offset of the slope abrupt change relative to the pulse edge in the adjustment drive command. When the temporal offset exceeds the preset physical response time delay interval, it determines that the current slope abrupt change is caused by pipe network pressure fluctuations. The pulse width modulation module locks the current duty cycle adjustment state constant to suppress random interference signals induced by non-adjustment. The physical response time delay interval is set to 100ms to 500ms. When the asynchronous interference filtering program is executed, the processor extracts the first derivative of the water content sequence in real time. Calculate its variance with steady-state background noise. The deviation, if It was determined to be a point of abrupt change in slope and the time was marked. The logic unit synchronously retrieves the rising edge of the most recent adjustment drive instruction. Calculate the difference ,determination In ms to When outside the ms interval, the pulse width modulation module blocks the duty cycle register. The update command will maintain the current adjustment state until... The regression response interval achieves hard alignment of the sensing signal and the physical execution action in the time domain. This time delay interval is based on experimental determination of the wet peak transport rate gradient of different soil media and is used to remove pressure pseudo fluctuations caused by multiple valves in the pipeline network.

[0033] To address the reference drift caused by long-term sensor operation, the system includes a zero-point drift correction module. This module acquires the measured saturation characteristic values ​​of the controlled area within the steady-state region where the first derivative of the real-time moisture content sequence approaches zero. Based on the deviation between the measured saturation characteristic values ​​and a preset calibration benchmark, it generates a zero-point compensation bias. This bias is fed back to the infiltration damping observation module for online zero-point correction of the real-time moisture content sequence. The pulse width modulation module executes adaptive sleep logic. Outside of the pulse activation period of the adjustment drive command, the infiltration damping observation module monitors the decreasing slope of the real-time moisture content sequence. When the decreasing slope exceeds a preset slope threshold, the pulse width modulation module switches to a closed state and proportionally extends the sampling interval of the soil moisture data acquisition module until the decreasing slope falls below a preset slope. Threshold; The system eliminates the uncertainty of initial infiltration resistance through the initial boundary calibration module. Before the formal adjustment cycle starts, the pulse width modulation module outputs a standardized detection medium flow of preset duration from the command execution module. The initial boundary calibration module identifies the initial infiltration resistance of the controlled object based on the water content rise slope corresponding to the standardized detection medium flow, and performs feedforward bias compensation on the gain of the adjustment drive command based on the initial infiltration resistance. For the leakage risk caused by non-uniform media, the infiltration damping observation module includes a bypass leakage judgment unit, which is used to calculate the instantaneous fluctuation residual of the real-time water content sequence relative to the predicted value of the dynamic compensation model. When the variance of the instantaneous fluctuation residual exceeds the preset structural mutation threshold, the pulse width modulation module activates the gain clamping logic to limit the upper limit of the duty cycle of the adjustment drive command.

[0034] Example 1: In an application scenario involving heavy loam irrigation areas with high clay content, high summer temperatures cause soil cracking. When a nonlinear soil moisture response model is constructed and a precise water allocation system is deployed under these conditions, the soil moisture data acquisition module utilizes a distributed frequency domain reflectance sensor array to... The sampling period of ms extracts the real-time water content sequence. To suppress non-uniform infiltration interference caused by cracks and determine the initial infiltration boundary, the pulse width modulation module outputs a duration of ms before the adjustment cycle starts. The standardized detection medium flow of s, the initial boundary calibration module identifies the initial infiltration resistance of the controlled object based on the collected water content rise slope, and sets the feedforward bias weight for the acceleration compensation logic in the infiltration damping observation module. The infiltration damping observation module performs continuous processing on the extracted sequence. The weighted average calculation over several periods yields the first derivative term, excluding quantization noise. With the second derivative term The system establishes a temporal correlation between the adjustment drive command and the real-time moisture content sequence through causal arbitration logic. When the moisture content fluctuation point is at a time offset relative to the pulse edge in the adjustment drive command, the system will determine the timing of the adjustment. ms to When the signal is within the preset physical response time delay range of ms, it is determined to be a real infiltration feedback and the extraction of second derivative features is activated. This process uses the deterministic action of the actuator as a physical reference system to provide real physical response data for the parameter tuning of the nonlinear model.

[0035] To address the technical conflict between the risk of deep seepage caused by rapid water infiltration during irrigation and the crop's water supply requirements, the infiltration damping observation module and the pulse width modulation module operate within the same control loop. The infiltration damping observation module calculates the instantaneous slope of the trajectory vector on the infiltration dynamic phase plane. Its definition is as follows: In the formula, The instantaneous slope; It is the second derivative term; For the first derivative term, when the second derivative term... Negative value and instantaneous slope When the absolute value exceeds the preset damping abrupt change threshold, the pulse width modulation module calculates the output duty cycle according to the following formula. ,in, To adjust the output duty cycle of the drive command; The original duty cycle of the control pulse sequence is used as a reference. Set the original duty cycle for the preset reduction weighting coefficient. for Reduce weighting coefficients for s, when the instantaneous slope is monitored in real time for At that time, the generated adjustment drive command output duty cycle Calculated as The actuator module receives the instruction and adjusts the medium flow rate in the delivery pipeline, causing the energy input to automatically decrease as the soil moisture potential energy gradient nonlinearly decays. The contradiction between the need for high response speed and preventing water from exceeding the crop root layer within a single execution architecture is resolved by changing the boundary properties of the problem. The complex Richards partial differential equation numerical solution is transformed into kinematic characteristic observation based on the phase plane trajectory curvature. When the bypass leakage detection unit detects that the instantaneous fluctuation residual variance of the real-time water content sequence relative to the predicted value of the kinetic compensation model exceeds the structural mutation threshold, the system determines that non-uniform medium infiltration has occurred and activates gain clamping logic, limiting the upper limit of the duty cycle of the adjustment drive instruction. During the intermittent period of the water distribution cycle, the pulse width modulation module performs adaptive sleep according to the slope of the water content decrease. When the slope of the decrease is greater than a preset threshold, the system locks into a closed state and proportionally extends the sampling interval until the gravity redistribution of water is completed. When the first derivative term... When the soil moisture content approaches zero, the zero-point drift correction module generates a zero-point compensation bias by using the deviation between the measured saturation characteristic value and the preset calibration benchmark. This bias is then used to perform online zero-point correction on the real-time moisture content sequence. The soil moisture content in the controlled area eventually stabilizes within the preset target range, and the systematic deviation caused by sensor aging is compensated.

[0036] Example 2: This experiment was used to verify the construction of the nonlinear response model of soil moisture and the control performance of the precise water distribution system in heavy loam soil with dry cracks. The experimental platform used a physical simulation irrigation soil box, whose internal filling depth was [missing information]. cm and clay content is % of heavy soil, sensor pre-buried depth is The soil moisture data acquisition module's functional specifications require a measurement accuracy better than cm. % and the sampling frequency range covers Hz to Hz, to simulate the complex electromagnetic environment of farmland, the signal-to-noise ratio superimposed in the experimental signal path is . Gaussian white noise of dB and frequency of Hz power frequency interference harmonics, core parameter sampling period The setting depends on the trade-off between the signal spectrum bandwidth and the processor's computational load. When the main energy distribution of the moisture content signal is in... Below Hz, to satisfy the Nyquist sampling theorem and allow sufficient filtering margin, the sampling period... Set as ms, for the initial state definition procedure, the initial moisture content of the heavy loam soil before the test was calibrated by the oven-drying method. %, infiltration resistance coefficient Initial curvature calibration of the response curve extracted by standardized probe sequences.

[0037] During the signal purification phase, the infiltration damping observation module performs a weighted average calculation, which will continuously... The raw data from each sampling period is smoothed, and the pulse edge of the adjustment drive command is used as a reference frame using causal arbitration logic. ms to Activation feature extraction within the physical response time delay interval of milliseconds was performed, and the experimental observation showed that the pseudo-fluctuation amplitude of the original water content sequence under pipeline pressure fluctuations reached [value missing]. After processing by the asynchronous interference filtering program, the residual noise amplitude of the output sequence is reduced to %. The intermediate process data confirms the shielding effectiveness of causal arbitration logic against non-regulatory induced disturbances, paving the way for subsequent extraction of the first derivative term reflecting the evolution of damping within the soil. With the second derivative term Provides a data source that conforms to physical continuity; to demonstrate the synergistic effect of the present invention's solution in resolving the contradiction between response speed and leakage prevention, the experiment includes the present invention's sample group, a control group A with the nonlinear compensation logic removed, and a reduction in weighting coefficients. For control group B, which exceeded the limit, the initial water content was set as the core problem gradient, and the steady-state characteristics of each group at the end of the infiltration period were recorded. The experimental data are shown in Table 1.

[0038] Table 1: Performance Comparison Data of Different Control Schemes under Different Initial Moisture Content Gradients

[0039]

[0040] Analysis of the data in Table 1 shows that as the initial moisture content increases from... % increased to %, Instantaneous slope of the sample group of this invention It exhibits a non-linear upward trend, and its output duty cycle According to the formula Perform monotonically decreasing adjustment, where To adjust the output duty cycle of the drive command, The original duty cycle of the control pulse sequence is used as a reference. The preset reduction weight coefficient, The instantaneous slope is given by control group A at an initial moisture content of [missing information]. Under operating conditions of %, due to the lack of compensation for time-varying damping, the steady-state moisture content overshoots, leading to a leakage rate reaching [percentage missing]. mL, while the sample group of the present invention, under the same operating conditions, had its duty cycle reduced to mL. The leakage is limited to mL, control group B due to Set as This leads to excessive clamping, which prolongs the time required for the water content to rise to the target range, thus failing to meet the water distribution timeliness requirements.

[0041] Example 3: This example, in conjunction with Figures 1 to 3, describes the construction of the nonlinear response model for soil moisture and the precise water distribution execution system. As shown in Figure 1, the soil moisture data acquisition module acquires the real-time water content sequence characterizing the state of the controlled object and transmits it to the infiltration damping observation module. The phase plane mapping unit inside this module processes the input data to calculate the derivative term and extract the instantaneous slope of the trajectory vector. The generated first-order derivative term, second-order derivative term, and instantaneous slope are transmitted to the pulse width modulation module. The pulse width modulation module uses the built-in decision logic and constraint logic to analyze the characteristic parameters and generates instructions by reducing the duty cycle according to a specific algorithm when responding to the stall trigger signal. Finally, it outputs the adjustment drive instruction containing the corrected duty cycle to the actuator module, which receives the instruction and adjusts the medium flow rate in the delivery pipeline.

[0042] As shown in Figure 2, the horizontal axis represents the gradient setting of the initial moisture content, covering multiple test points from 5.3% to 49.8%, and the vertical axis represents the percentage value of the steady-state moisture content. The legend distinguishes the three different control strategy objects of this invention: sample group, control group A, and control group B, and intuitively presents the distribution of steady-state moisture content values ​​achieved by different control groups and the height of the comparative bars under specific initial moisture content conditions such as 15.1% and 35.4%. As shown in Figure 3, the execution logic of the bypass leakage judgment unit is that the soil moisture data acquisition module inputs the real-time moisture content sequence, and the bypass leakage judgment unit sends the data to the dynamic compensation... The model requests a predicted value. After calculating the predicted water content at the current moment and returning the predicted value, the judgment unit calculates the residual between the measured value and the predicted value and calculates the residual variance. Then, it enters the logic branch for judgment: when the residual variance exceeds the structural mutation threshold, the system determines that non-uniform medium infiltration has occurred and sends a leakage risk alarm. It triggers the pulse width modulation module to start the gain clamping logic, limits the upper limit of the duty cycle, and sends a restricted drive command to the actuator module to achieve the goal of preventing deep leakage risk. When the residual variance is normal, the system maintains the normal state and sends a normal drive command to the actuator module.

[0043] Example 4: In the construction of the nonlinear response model of soil moisture and the digital deployment of the precision water distribution execution system, to address the accuracy requirements of the computing nodes for processing discrete sampled data, the system incorporates a numerical difference operator into the infiltration damping observation module, with the sampling period set to [missing information]. In the At each sampling time, the soil moisture data acquisition module outputs a moisture content of [value missing]. The infiltration damping observation module executes the following operating procedure, using the backward difference operator to calculate the first derivative term. That is, it follows the formula below: ,in, For the first The first derivative term at each sampling time; This represents the measured moisture content at the current moment. This represents the measured moisture content at the previous moment. For the sampling period, based on the obtained first derivative sequence, a difference operation is performed again to obtain the second derivative term. That is, it follows the formula below: ,in, For the first The second derivative term at each sampling time, The first derivative term at the current moment, This is the first derivative term from the previous time step.

[0044] The input data is a real-time water content sequence after weighted average smoothing. The processing logic follows the physical meaning of the second-order central difference approximation. The output is a set of feature vectors mapped to the infiltration dynamic phase plane in real time, with the sampling period set as... For example, if the time is ms The moisture content is %,time for %,time for %, then the calculation yields for % / s, for % / s, derived for % / s Through this differential procedure, the system achieves digital extraction of the kinematic characteristics of the controlled object. To logically capture the risk of deep leakage caused by the infiltration of non-uniform media, the bypass leakage judgment unit within the infiltration damping observation module operates a dynamic compensation model, employing a second-order autoregressive operator structure. Its predicted values... Follows the following discretization recurrence relation: ,in, This is the predicted moisture content at the current moment; and The measured moisture content at a historical moment; The duty cycle of the drive command output is adjusted in the previous moment; , and As model coefficients, before the system starts the adjustment cycle, it uses a standardized response sequence excited by the probe medium flow to identify model coefficients through a least squares algorithm, and the processing logic calculates the measured values ​​in real time. Compared with the predicted value Instantaneous fluctuation residuals between ,Right now The determination procedure maintains a duration of [length]. Using a sliding time window, the variance of the residual sequence is statistically analyzed. This model architecture transforms pore fluid dynamics processes into observation-based statistical predictions, providing a reference benchmark for identifying abrupt changes in soil structure.

[0045] For damping abrupt change threshold in control logic With structural mutation threshold The system is configured to use a calibration procedure based on probe flow fingerprinting. During the initial boundary calibration phase, the initial boundary calibration module records the response characteristics and damping abrupt change threshold for the standardized probe medium flow. The calculation method is set to the maximum absolute value of the instantaneous slope during the detection phase. The multiple, i.e., follows the formula: ,in, This is the damping abrupt change threshold; The instantaneous slope sequence extracted during the detection phase, and the structural abrupt change threshold. Set as the mean of the residual variance during the detection phase Following the statistical criterion of three standard deviations, if the instantaneous slope peak measured during the detection phase is... The mean of the residual variance is Then the calibrated for , for This procedure bases the judgment logic on the physical fingerprint of the controlled object of the current land parcel, when the instantaneous slope The absolute value exceeds Furthermore, when the second derivative term is negative, the pulse width modulation module generates a stall trigger signal, and when the residual variance... Exceed At that time, the gain clamping logic is activated. The closed-loop system formed by the above numerical calculation path and model parameter calibration procedure solves the phase lag and model mismatch problems caused by the physical nonlinearity of the controlled object. The system maintains the synchronization between the adjustment command and the physical response in the discrete time step, so that the precise water distribution execution system completes the flow clamping before the soil acceptance capacity reaches the critical point. The discretization coefficients of the dynamic compensation model are... , and Online identification is performed by adjusting the standardized detection medium flow response sequence before cycle start-up, and the parameter matrix is ​​corrected in real time using the recursive least squares method. The bypass leakage detection unit performs sampling at the sampling time. Calculate the measured value Compared with model predictions Instantaneous fluctuation residual and maintain a length of Sliding window statistical residual variance ,like Exceeding the structural mutation threshold The logic layer cuts off the linear growth path of the duty cycle and activates gain clamping logic to limit the upper limit of the output duty cycle to the reference value. The following are methods to prevent deep seepage caused by soil dry cracks or biological pores, among which... The value is set to the mean of the residual variance during the detection phase. By adhering to the statistical three-standard-deviation criterion to isolate normal infiltration fluctuations, and by converting functional steps into mathematical operators and statistical judgment rules, the system achieves adaptive alignment under different soil conditions, preventing deep leakage and improving the stability of water distribution operations.

[0046] Example 5: In an application scenario where the system is deployed in a sandy loam irrigation area, the reduction of weighting coefficients is performed. and damping mutation threshold The on-site pre-calibration procedure ensures that the soil moisture data acquisition module remains in a silent observation state. min to establish the baseline moisture content of the sensor array in the current media environment. Compared to the background noise variance parameter, the duty cycle of the pulse width modulation module driving the actuator module output remains constant. And the duration is The calibration pulse sequence of s, and maintain the instantaneous head pressure of its delivery pipeline at s MPa, the infiltration damping observation module records the instantaneous slope of the calibration pulse excitation. And extract the maximum absolute value of its sequence. Damping mutation threshold According to the relation Calculations show that This is the damping mutation threshold, and its unit is... , The weighting coefficients are reduced to the maximum absolute value of the instantaneous slope sequence extracted during the detection phase. Based on the first derivative of moisture content The residual mean square error minimization criterion in the steady-state interval is determined by performing a gradient search operator on specific sample points of the sandy loam soil. s.

[0047] When the system faces the risk of rapid saturation due to the high permeability of sandy loam soil, the initial infiltration resistance identified by the initial boundary calibration module... As a feedforward bias term, the injection acceleration compensation logic, during the formal water distribution cycle, as the soil moisture content approaches the pore acceptance limit, the instantaneous slope within the infiltration dynamic phase plane... In the second derivative term The damping mutation threshold is reached under negative conditions. The pulse width modulation module executes the corrected duty cycle formula. To regulate the flow rate of the medium in the delivery pipeline, To adjust the output duty cycle of the drive command, The original duty cycle of the control pulse sequence is used as a reference. To reduce the weighting coefficients, the unit is seconds (s). The instantaneous slope is expressed in units of 1 / 2 t. When the instantaneous slope From the linear interval Increased to the damping abrupt change region At that time, the output duty cycle From the benchmark value Automatic decay to This causes the water distribution per unit time to decrease synchronously with the decrease of the soil moisture potential energy gradient, ultimately resulting in the first derivative term of the water content. The evolution trajectory remains within the preset physical response range and the leakage in the lower part of the root layer is limited to Less than mL.

[0048] Example 6: In a scenario where a system is deployed on a plot of land containing a heterogeneous gravel layer, a field calibration procedure is performed to ensure the consistency of the coupling between the sensor and the medium interface. After the distributed frequency domain reflectance sensor group in the soil moisture data acquisition module is installed, the pressure output by the actuator module is... MPa and duration is The exhaust wetting flow of s is calculated using the first derivative term of the real-time moisture content sequence. The time point at which stability is reached is used to establish the sensing benchmark for that specific physical layer. The processor counts the continuous flow under static emptying conditions. The root mean square value of the voltage deviation at each sampling point is used as the basis for calculating the correction term for the boundary value of the physical response time delay interval in the asynchronous interference filtering program.

[0049] When the system faces a nonlinear jump in infiltration rate caused by a sudden change in the geological composition, the system determines the corrected duty cycle through controlled gradient experiments. With instantaneous slope Interpolation operator between The infiltration damping observation module is located at water content gradients of... %, %, %as well as Calculate the maximum instantaneous slope at the test point of %, and combine it with the original duty cycle of the reference control pulse sequence. Based on the minimum corrected duty cycle that satisfies the non-stall condition calculated using discrete nodes, a nonlinear reduced relation term generated by a second-order spline interpolation algorithm is used to calculate the adjustment drive command in the formal water distribution cycle, so that the medium flow velocity in the delivery pipeline is within the second derivative term. When a negative inflection point occurs, flow clamping is performed according to the soil pore characteristic curve. The risk of deep leakage in the controlled area is limited to the preset volume percentage limit in multiple sets of simulations with different permeability.

[0050] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0051] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A soil moisture nonlinear response model construction and a precise water distribution execution system, characterized in that, The system includes a soil moisture data acquisition module, an infiltration damping observation module, a pulse width modulation module, and an actuator module. The infiltration damping observation module is connected to the soil moisture data acquisition module and contains a phase plane mapping unit. The pulse width modulation module is connected to the infiltration damping observation module and contains decision logic and constraint logic. The input end of the actuator module is connected to the output end of the pulse width modulation module. The soil moisture data acquisition module is used to acquire the real-time water content sequence characterizing the state of the controlled object. The infiltration damping observation module is used to calculate the first and second derivative terms of the real-time water content sequence and construct an infiltration dynamic phase plane with the first derivative term as the abscissa and the second derivative term as the ordinate using the phase plane mapping unit. It calculates the instantaneous slope of the trajectory vector of the real-time water content sequence in the infiltration dynamic phase plane, and the instantaneous slope is defined as the ratio of the second derivative term to the first derivative term. The pulse width modulation module is used to generate a stall trigger signal when the second derivative term is negative and the absolute value of the instantaneous slope exceeds a preset damping abrupt change threshold using judgment logic. In response to the stall trigger signal, the constraint logic reduces the duty cycle of the preset reference control pulse sequence according to a ratio that is monotonically increasing with the absolute value of the instantaneous slope, thereby generating an adjustment drive command. The actuator module is used to receive the adjustment drive command and adjust the medium flow rate of the delivery pipeline.

2. The soil moisture nonlinear response model construction and precise water distribution execution system according to claim 1, characterized in that, The infiltration damping observation module is equipped with a causal arbitration logic. The causal arbitration logic is used to establish the temporal correlation between the regulation driving command and the real-time water content sequence when the regulation driving command is in the pulse opening period, and to activate the feature extraction of the second derivative term. When the change characteristics of the real-time moisture content sequence do not match the trigger timing of the adjustment drive command, the pulse width modulation module locks the current duty cycle adjustment state to a constant value.

3. The soil moisture nonlinear response model construction and precise water distribution execution system according to claim 1, characterized in that, The pulse width modulation module executes adaptive sleep logic; outside the pulse on period of the adjustment drive command, the infiltration damping observation module monitors the downward slope of the real-time water content sequence; when the downward slope is greater than the preset slope threshold, the pulse width modulation module switches to the off state and proportionally extends the sampling interval of the soil moisture data acquisition module until the downward slope is lower than the preset slope threshold.

4. The soil moisture nonlinear response model construction and precise water distribution execution system according to claim 1, characterized in that, The system also includes an initial boundary calibration module; before the formal adjustment cycle starts, the pulse width modulation module outputs a standardized detection medium flow of a preset duration from the command execution module; the initial boundary calibration module identifies the initial infiltration resistance of the controlled object based on the slope of water content rise of the standardized detection medium flow fed back by the infiltration damping observation module, and performs feedforward bias compensation on the gain of the adjustment drive command based on the initial infiltration resistance.

5. The soil moisture nonlinear response model construction and precise water distribution execution system according to claim 1, characterized in that, The infiltration damping observation module includes a bypass leakage determination unit. The bypass leakage determination unit is used to calculate the instantaneous fluctuation residual of the real-time water content sequence relative to the predicted value of the dynamic compensation model. When the variance of the instantaneous fluctuation residual exceeds the preset structural mutation threshold, the pulse width modulation module activates the gain clamping logic to limit the upper limit of the duty cycle of the adjustment drive command in order to prevent the risk of deep leakage caused by the infiltration of non-uniform media.

6. The soil moisture nonlinear response model construction and precise water distribution execution system according to claim 1, characterized in that, The system also includes a zero-point drift correction module; the zero-point drift correction module is used to obtain the measured saturation characteristic value of the controlled region in the steady-state region where the first derivative of the real-time water content sequence tends to zero. The zero-point drift correction module generates a zero-point compensation bias based on the deviation between the measured saturation characteristic value and the preset calibration benchmark, and feeds the zero-point compensation bias back to the infiltration damping observation module to perform online zero-point correction on the real-time water content sequence.

7. The soil moisture nonlinear response model construction and precise water distribution execution system according to claim 1, characterized in that, The infiltration damping observation module executes an asynchronous interference filtering program. This program monitors slope abrupt changes in the real-time water content sequence and calculates the timing offset of these abrupt changes relative to the pulse edge in the adjustment drive command. When the timing offset exceeds the preset physical response time delay interval, the infiltration damping observation module determines that the current slope abrupt change is caused by pipeline pressure fluctuations and locks the current gain correction factor. The physical response time delay interval is set to... to 。 8. The soil moisture nonlinear response model construction and precise water distribution execution system according to claim 1, characterized in that, The pulse width modulation module determines the corrected duty cycle for generating the adjustment drive command according to the following rules. ： ,in, To adjust the output duty cycle of the drive command, The original duty cycle of the control pulse sequence is used as a reference. The instantaneous slope The preset reduction weighting coefficient is used; when the second derivative term is negative and the absolute value of the instantaneous slope exceeds the preset damping change threshold, the pulse width modulation module activates the calculation logic for correcting the duty cycle.

9. The soil moisture nonlinear response model construction and precise water distribution execution system according to claim 1, characterized in that, The system also includes a fluctuation feedback module, which is used to collect the instantaneous head pressure of the delivery pipeline; when the pulse width modulation module generates the adjustment drive command, it superimposes a gain correction term that is inversely proportional to the instantaneous head pressure.

10. The soil moisture nonlinear response model construction and precise water distribution execution system according to claim 1, characterized in that, The soil moisture data acquisition module includes a distributed frequency domain reflectance sensor group, which is used to extract the real-time water content sequence within a sampling period of 20ms to 100ms; the infiltration damping observation module performs a weighted average calculation on the data of 5 consecutive sampling periods to smooth the waveform characteristics of the first and second derivative terms.

Images