Layered-type environment control system and method for laying hen house based on multi-dimensional environmental parameter fusion

Abstract

The present application relates to the technical field of poultry breeding environment control, and particularly relates to a stacked layer henhouse environment control system and method based on multi-dimensional environment parameter fusion, which divides the environment control space unit through modeling and collection, generates a space coupling weight and a device parameter space influence matrix, obtains a candidate collaborative regulation instruction through demand fusion, conflict analysis and collaborative evaluation, and generates a layered and partitioned collaborative regulation instruction or modifies the device parameter space influence matrix through micro-step execution, the present application divides the environment control space unit, collects an environment parameter group and an execution device state group, quantifies space coupling and device influence, fuses state deviation and regulation demand, analyzes device margin and regional conflict, and generates a layered and partitioned collaborative regulation instruction or modifies the device parameter space influence matrix through device space effective action rate screening, micro-step trial and response verification.

Description

Technical Field

[0001] This invention relates to the field of poultry farming environmental control technology, and more specifically, to a layered layer hen house environmental control system and method based on the fusion of multi-dimensional environmental parameters. Background Technology

[0002] Stratified layer hen houses are a common form of rearing in large-scale layer hen farming. They increase the number of hens per unit area through multi-layered cage arrangements and are equipped with environmental control equipment such as ventilation, cooling, humidification, heating, dust removal, and lighting to maintain the necessary environment for hen growth, egg production, and health. However, due to significant differences in cage height, high flock density, and the influence of cage and flock distribution on airflow within stratified layer hen houses, variations in environmental parameters such as temperature, humidity, carbon dioxide concentration, ammonia concentration, dust concentration, and light intensity can easily occur between different layers, cage rows, and air intake and exhaust sides. Especially under conditions of high summer temperatures, winter insulation and ventilation, changes in flock age, or accumulated manure, the environmental deviations in local areas may not match the average parameters within the house. If adjustments are made uniformly based on only a few sampling points or the overall house average, it is difficult to accurately reflect the true environmental control needs of each local area.

[0003] Existing environmental control technologies for layer hen houses typically collect parameters such as temperature, humidity, gas concentration, and light intensity, and adjust the operation of fans, evaporative cooling pads, air inlets, heating equipment, or lighting equipment according to preset thresholds, playing a positive role in maintaining the basic breeding environment. However, with the increasing scale and stocking density of tiered layer hen houses, single-parameter threshold control or uniform house-wide adjustment still has room for improvement when facing scenarios involving multiple areas, multiple devices, and multiple coupled parameters. For example, increasing ventilation can help reduce ammonia and carbon dioxide concentrations, but it may also alter the temperature and airflow velocity in some layers; enhancing local cooling capacity may improve the conditions in high-temperature areas, but it can affect the humidity and wind conditions in adjacent areas; adjusting light parameters to meet production rhythms also requires consideration of differences in light exposure across different layers and flock stress management.

[0004] Furthermore, the functions of various control devices within a stacked layer hen house are not limited to a single location. The impact range, response time, and attenuation of the effects of fans, air intake regulators, evaporative cooling pads, airflow diversion devices, and lighting equipment vary across different environmental control units. Different areas may simultaneously request control measures in the same or opposite directions. For example, one floor may require enhanced ventilation to improve air quality, while adjacent floors may not be suitable for excessive ventilation due to temperatures near the lower limit; one area may require rapid cooling, while another affected area requires stable temperature and humidity. In such cases, directly adjusting equipment based solely on the deviation of a single area may fail to adequately consider remaining equipment control margins, the cumulative effects of spatial propagation, differences in the urgency of needs, and environmental disturbances in non-target areas.

[0005] Therefore, this application proposes a layered environmental control system and method for laying hen houses based on the fusion of multi-dimensional environmental parameters. Summary of the Invention

[0006] To address the shortcomings of existing technologies, the present invention aims to provide a layered environmental control system and method for layered chicken houses based on the fusion of multi-dimensional environmental parameters.

[0007] To achieve the above objectives, the present invention provides the following technical solution: A layered environmental control system for layer hen houses based on multi-dimensional environmental parameter fusion includes: The data acquisition and modeling module is used to divide the stacked egg-laying hen house into environmental control space units. It collects environmental parameter groups and execution equipment status groups for each environmental control space unit according to a preset sampling period, and generates spatial coupling weights and equipment parameter spatial influence matrices. The fusion demand module is used to generate a fusion state vector based on the environmental parameter set of each environmental control space unit, generate a state deviation vector based on the fusion state vector and the preset target state vector, and generate a control demand vector based on the state deviation vector, the equipment parameter space influence matrix and the changing trend of the environmental parameter set. The conflict resolution module is used to generate conflict resolution results based on the control demand vectors of multiple environmental control space units. The conflict resolution results include the remaining adjustment margin of each execution device, the set of available execution devices, the device function demand vector, and the conflict degree of regional control demand. The collaborative evaluation module is used to determine the target environmental control spatial unit set, the non-target environmental control spatial unit set, multiple candidate collaborative control commands and the corresponding effective spatial utilization rate of equipment based on the fused state vector, state deviation vector, control demand vector, equipment action demand vector, callable execution equipment set, spatial coupling weight and equipment parameter spatial influence matrix; The microstep execution module is used to generate microstep trial instructions and response verification quantities based on candidate collaborative control instructions and the effective action rate of the device space, and to generate hierarchical and partitioned collaborative control instructions or correct the device parameter space influence matrix based on the response verification quantities.

[0008] In one embodiment, the environmental parameter group includes at least two types of parameters selected from indoor climate parameters, air quality parameters, and light parameters; the execution device status group includes the operating status and adjustment status of the execution device, and the adjustment status includes the current adjustment amount and the adjustable range; the execution device includes at least two types of devices selected from ventilation equipment, temperature and humidity control equipment, air intake control equipment, and airflow guiding equipment.

[0009] In one embodiment, the device parameter space influence matrix includes at least the expected direction of influence, expected magnitude of influence, expected range of influence, expected response time, effect attenuation coefficient, and effect confidence level of the device on the environmental parameter group within the environmental control space unit.

[0010] In one embodiment, the regulation demand vector includes at least two demand components, each demand component including demand direction, demand intensity, demand urgency and delayable regulation margin; the at least two demand components include at least two of climate regulation demand components, air quality regulation demand components and light regulation demand components.

[0011] In one embodiment, the regional regulation demand conflict degree is obtained by weighted fusion of the demand anisotropic coupling amount, equipment call competition amount, spatial propagation superposition amount, response timing mismatch amount and urgency bias amount between different environmental control spatial units; the demand anisotropic coupling amount is determined by the degree of opposite demand direction under the same demand component, the difference in demand intensity and the angle between the regulation demand vectors.

[0012] In one embodiment, the device call contention quantity is determined by the degree of inversion, superposition, and remaining adjustment margin occupation of the device action demand vector for the same executing device; the spatial propagation superposition quantity is determined by the degree of overlap of the expected influence range corresponding to the device parameter spatial influence matrix and spatial coupling weight; the response timing mismatch quantity is determined by the degree of matching between the demand urgency and the expected response time; and the urgency bias quantity is determined by the difference between the demand urgency and the delayable adjustment margin.

[0013] In one embodiment, the effective action rate of the device space is obtained by fusing the effective action term and the constraint cost term through a normalized ratio; the effective action term includes the target deviation convergence gain determined by the convergence degree of the state deviation vector of the target environmental control space unit set, the spatial selectivity gain determined by the difference in the expected influence range between the target environmental control space unit set and the non-target environmental control space unit set, and the action confidence correction amount determined by the action confidence degree.

[0014] In one embodiment, the constraint cost term includes the non-target deviation diffusion cost determined by the degree of increase in the state deviation vector of the non-target environmental control space unit set, the conflict residual penalty determined by the degree of conflict of regional control demand, and the equipment load penalty determined by the degree of occupancy of the remaining control margin.

[0015] In one embodiment, the microstep execution module is specifically used to determine the candidate collaborative control instructions that meet the preset selection criteria for the effective utilization rate of the equipment space as the benchmark collaborative control instructions, generate and execute microstep trial instructions according to the preset microstep coefficients, obtain the changes in the fusion state vector and the changes in the regional control demand conflict degree within the response observation window based on the expected response duration, and generate the response verification quantity; generate hierarchical and partitioned collaborative control instructions or correct the equipment parameter space influence matrix based on the response verification quantity.

[0016] In one embodiment, the layered environmental control method for layer hen houses based on multi-dimensional environmental parameter fusion includes: Step 1: Divide the stacked layer hen house into environmental control space units, and collect environmental parameter groups and execution equipment status groups; Step 2: Generate spatial coupling weights and spatial influence matrices of device parameters based on the environmental parameter group and the execution device status group; Step 3: Generate a fused state vector based on the environmental parameter set, and generate a state deviation vector based on the preset target state vector; Step 4: Generate the control demand vector based on the state deviation vector, the influence matrix of the equipment parameter space, and the changing trends of the environmental parameter set; Step 5: Based on the control demand vectors of multiple environmental control spatial units, generate conflict resolution results including remaining control margin, set of callable execution equipment, equipment function demand vector, and regional control demand conflict degree; Step 6: Based on the conflict resolution results, spatial coupling weights, and equipment parameter spatial influence matrix, determine the target environmental control spatial unit set, the non-target environmental control spatial unit set, multiple candidate coordinated control commands, and the corresponding equipment spatial effective action rate; Step 7: Generate micro-step trial commands and response verification quantities based on candidate coordinated control commands and equipment space effective action rates, and generate hierarchical and partitioned coordinated control commands or correct equipment parameter space influence matrices based on response verification quantities.

[0017] Compared with the prior art, the present invention has the following beneficial effects: This invention divides a stacked layer hen house into environmental control spatial units and collects environmental parameter groups and equipment status groups for each unit according to a preset sampling period. It further generates spatial coupling weights and equipment parameter spatial influence matrices, quantifying environmental differences, equipment operating ranges, and spatial transmission relationships between different levels, cage arrangements, and air inlet and outlet sides. Compared to methods that adjust based on only a few sampling points or average parameters within the house, this invention can more accurately identify local environmental deviations and their degree of influence from equipment adjustments, improving the completeness and zoning precision of the environmental status modeling for stacked layer hen houses. By generating a fused state vector based on the environmental parameter set of each environmental control space unit, and combining it with the preset target state vector to generate a state deviation vector, and further generating a control demand vector based on the state deviation vector, the equipment parameter space influence matrix, and the changing trend of the environmental parameter set, the control direction, control intensity, and changing trend of each environmental control space unit can be analyzed in a unified manner. At the same time, by obtaining the remaining adjustment margin of each execution device, the set of available execution devices, the equipment action demand vector, and the regional control demand conflict degree through conflict analysis, it can take into account the equipment adjustability, the urgency of regional demand, and the equipment call competition relationship when there are differences or conflicts in control demand in multiple regions, thereby improving the coordination of control decisions. By collaboratively evaluating and determining the target environmental control spatial unit set, the non-target environmental control spatial unit set, multiple candidate collaborative control commands, and the corresponding equipment spatial effective utilization rate, the system can comprehensively measure the environmental improvement benefits of the target area, the environmental disturbance risks of the non-target area, and the equipment regulation load before generating control commands. Furthermore, by using micro-step trial commands to obtain the changes in the fused state vector and the changes in the regional control demand conflict degree within the response observation window, the system generates response verification quantities. When the actual response meets expectations, the system forms hierarchical and regional collaborative control commands. When there are deviations between the actual response and expectations, the system corrects the equipment parameter spatial influence matrix, thereby improving the stability, adaptability, and continuous optimization capability of the environmental control process. Attached Figure Description

[0018] Figure 1 This is a block diagram of the overall system structure of the layered environmental control system for laying hen houses based on the fusion of multi-dimensional environmental parameters of the present invention; Figure 2 This is a schematic diagram of the environmental control space unit division and data acquisition modeling process in this invention; Figure 3 This is a schematic diagram of the process of the layered environmental control method for layered chicken houses based on the fusion of multi-dimensional environmental parameters according to the present invention. Detailed Implementation

[0019] Example 1: Refer to Figures 1 to 2 A layered environmental control system for layer hen houses based on the fusion of multi-dimensional environmental parameters includes: In this embodiment, each collected data point uses a preset sampling period as the time base, and the environmental parameter groups and execution device status groups within the same environmental control space unit are time-aligned. Let the number of environmental control space units be... The number of devices to be executed is The number of environmental parameters is ; Number the environmental control space unit. To execute the device number, Number the environmental parameters. This is the preset sampling period number. The environmental parameter group includes the sampled values ​​of each environmental parameter, and the device status group includes the operating status, current adjustment value, and upper and lower limits of the adjustable range.

[0020] The normalized trend of environmental parameter groups is denoted as

[0021] in, For the first In the first environmental control space unit Normalized variation trend of each environmental parameter For the first The first environmental control space unit in the first The first sample collected in the preset sampling period One environmental parameter, For the first The lower limit of the allowable environmental parameter, For the first The maximum allowable limit for each environmental parameter. The time interval between two adjacent preset sampling periods. To prevent extremely small positive numbers with a denominator of zero, the valid sampling state is determined based on the valid state of the original sampled value or the supplemented state, and participates in the confidence correction. All fusion coefficients are non-negative, and the sum of the coefficients under the same fusion term is one. The preset selection conditions, preset response conditions, allowable disturbance range, and equipment load limit thresholds are calibrated based on the preset target state vector, the adjustable range of the executing equipment, the allowable disturbance range of the non-target environmental control space unit set, and historical operation records, and remain unchanged within the same control cycle.

[0022] The data acquisition and modeling module is used to divide the stacked layer hen house into environmental control space units. It collects environmental parameter sets and equipment status sets for each environmental control space unit according to a preset sampling period, and generates spatial coupling weights and equipment parameter spatial influence matrices. Based on the number of cage layers, the location of longitudinal passages, and the positions of the air inlet and exhaust sides, the stacked layer hen house is divided into multiple environmental control space units. For example, the area near the air inlet side of the upper cage layer, the middle area of ​​the middle cage layer, and the area near the exhaust side of the lower cage layer are each considered as an independent environmental control space unit. According to the preset sampling cycle, the environmental parameter group and the execution equipment status group of each environmental control space unit are collected. The environmental parameter group includes at least two types of parameters from the indoor climate parameters, air quality parameters and light parameters. The indoor climate parameters include temperature and humidity, the air quality parameters include carbon dioxide concentration, ammonia concentration and dust concentration, and the light parameters include light intensity and light duration. The illumination duration is the cumulative duration of effective illumination within the current photocycle. At the beginning of the current photocycle, the illumination duration is set to zero; it is recalculated at the start of the next photocycle. Let the th photocycle be... The first environmental control space unit in the first The illumination intensity for each preset sampling period is The effective illumination threshold is The effective light indicator is Under effective lighting conditions Take one example, under ineffective lighting conditions. Take zero. The illumination duration of each environmental control space unit is denoted as

[0023] in, For the first The first environmental control space unit in the first The illumination duration corresponding to each preset sampling period This is the duration of illumination corresponding to the previous preset sampling period. This is the time interval between two adjacent preset sampling periods. When verifying the response involving illumination duration, It participates in the calculation of the fusion state vector change as the current cumulative state of the optical cycle.

[0024] The execution equipment status group includes the operating status and adjustment status of the execution equipment. The adjustment status includes the current adjustment amount and the adjustable range. The execution equipment includes at least two types of equipment among ventilation equipment, temperature and humidity control equipment, air intake control equipment and airflow guiding equipment. For example, it records the current speed of the fan, the opening ratio of the wet curtain, the opening degree of the air intake window and the angle of the guide plate. Based on the relationship between the environmental parameter groups of adjacent environmental control space units within a continuous preset sampling period, and combined with the changes in the status group of the execution equipment, a spatial coupling weight and a spatial influence matrix of equipment parameters are generated. The spatial coupling weight is determined according to the interlayer distance, airflow connectivity, and degree of synchronous change of environmental parameter groups between environmental control space units. For example, when there is a stable correlation between the temperature rise of the upper environmental control space unit on the exhaust side and the ammonia concentration change of the middle environmental control space unit, the spatial coupling weight between the two is increased. The spatial coupling weight is determined based on the spatial distance between the two environmental control spatial units, the airflow connectivity, and the degree of synchronous change of environmental parameter sets. Let the first... The first environmental control space unit and the first The spatial coupling weight between each environmental control space unit is: The calculation formula is

[0025] in, The value range is from zero to one. For spatial distance related terms, This is an airflow connectivity term. This refers to the degree of synchronous change of the environmental parameter group. and This represents the spatial coupling weight fusion coefficient. The spatial distance correlation term is obtained by normalizing the distance between two environmental control spatial units. The airflow connectivity term is obtained by normalizing the inlet side position, exhaust side position, longitudinal channel position, cage layer position, and the current adjustment status of the airflow guiding equipment. The environmental parameter group synchronization change degree term is obtained by the consistency of the normalized change trend of environmental parameters within a continuous preset sampling period.

[0026] The equipment parameter space influence matrix should include at least the expected direction, expected magnitude, expected range, expected response time, effect attenuation coefficient, and effect confidence level of the equipment on the environmental parameter group within the environmental control space unit. The equipment parameter spatial influence matrix is ​​indexed according to the executing equipment, environmental control spatial unit, and environmental parameters. Let the... The device parameter space influence matrix for a preset sampling period is as follows: Its matrix elements are

[0027] in, The expected direction of impact, The expected impact range, To indicate the expected scope of impact, For the expected response time, The attenuation coefficient is the effect factor. The confidence level is the level of the effect. Pick or , respectively corresponding to the first when the adjustment amount of the execution device increases The environmental parameters decreased, remained unchanged, or increased.

[0028] In the The execution device for the first In the first environmental control space unit Each environmental parameter is set to one when it is within the detectable influence range and to zero when it is outside the detectable influence range; when using a gradual influence range... Take the normalized value between zero and one.

[0029] The expected impact magnitude is determined based on the correspondence between changes in the adjustment amount of the executing equipment and the normalized state changes of environmental parameters within the preset response observation window, denoted as .

[0030] in, For the first In the first environmental control space unit The normalized actual change of each environmental parameter within a preset response observation window. For the first The change in the adjustment amount of each actuator To prevent extremely small positive numbers with a denominator of zero. and The results are obtained based on the detectable influence range, stable response time, spatial influence amplitude attenuation relationship, consistency of actual influence direction, dispersion of actual influence amplitude, and normalization of effective sampling state.

[0031] For example, when the ventilation equipment increases its speed, the expected impact on the temperature and ammonia concentration in the environmental control space unit near the exhaust side is to decrease, while the expected impact on the environmental control space unit far from the exhaust side is to decrease according to the effect attenuation coefficient, and the effect confidence level is determined based on the consistency of multiple sampling results.

[0032] The fusion demand module is used to generate a fusion state vector based on the environmental parameter set of each environmental control space unit, generate a state deviation vector based on the fusion state vector and the preset target state vector, and generate a control demand vector based on the state deviation vector, the equipment parameter space influence matrix, and the changing trend of the environmental parameter set. For each environmental control space unit, the indoor climate parameters, air quality parameters, and light parameters in the environmental parameter set are normalized according to parameter type, allowable fluctuation range, and environmental requirements corresponding to the age of laying hens, forming a fusion state vector under the same dimensions. Let the first The target value for each environmental parameter is The lower limit is allowed to be The maximum allowed is . No. In the first environmental control space unit The normalized state value of each environmental parameter is

[0033] in, For normalized state values, For the first The first environmental control space unit in the first The first sample collected in the preset sampling period One environmental parameter, To prevent extremely small positive numbers with a denominator of zero.

[0034] No. The fusion state vector of each environmental control space unit is

[0035] in, For the fused state vector, For the first In the first environmental control space unit The environmental parameter at the first The fusion weights are determined based on a preset sampling period. The fusion weights are obtained by normalizing the environmental requirements corresponding to parameter type, layer height, cage position, day / night time, and laying hen age.

[0036] Let the first The preset target state vector of each environmental control space unit is: The state deviation vector is

[0037] in, This is the state deviation vector. For the first Each environmental control space unit corresponds to a preset target state vector. When the normalized state values ​​are established with the target value as the center, Take the zero vector; when the normalized state values ​​are established in a non-centered manner, Take the corresponding normalized target state vector.

[0038] Each vector element in the fusion state vector corresponds to the parameter state of temperature, humidity, carbon dioxide concentration, ammonia concentration, dust concentration, light intensity or light duration, and different fusion weights are set according to the layer height, cage position and day and night time. When environmental parameters are within the target range, the corresponding vector elements participate in the state deviation calculation according to their fusion weights; when environmental parameters exceed the target range, the corresponding vector elements participate in the state deviation calculation according to the deviation direction and deviation magnitude. When illumination parameters are within the target range, the corresponding regulation demand component is processed with a lower demand intensity and a larger delayable regulation margin; when they exceed the target range or the cumulative illumination duration of the current photoperiod deviates from the target photoperiod, the demand component is generated according to the deviation direction.

[0039] A control demand vector is generated by combining the state deviation vector, the equipment parameter space influence matrix, and the changing trends of the environmental parameter set. The equipment parameter space influence matrix provides the expected direction, magnitude, range, response time, attenuation coefficient, and confidence level of the effect of the executing device on the environmental parameter set. The changing trends of the environmental parameter set are determined based on the rise and fall amplitude and rate of change of the same parameter within a continuous preset sampling period. The control demand vector includes at least two demand components, each of which includes demand direction, demand intensity, demand urgency, and delayable control margin. No. In the first environmental control space unit The environmental parameters correspond to the demand parameters, including the demand direction. Demand intensity Urgency of demand and delayable adjustment margin Demand direction Take the following values ​​respectively: downward direction, no need for regulation, and upward direction. and ;when When the positive time is taken, the downward direction is taken, when When it is negative, take the upward direction. There is no need for regulation when the time is zero.

[0040] Demand intensity is denoted as

[0041] in, and This represents the demand intensity fusion coefficient.

[0042] When the normalization trend points towards the allowable boundary The distance from the current parameter normalized state value to the corresponding allowable boundary normalized state value is determined by the ratio of the absolute value of the normalized change trend; when it does not point to the allowable boundary, The urgency level is recorded according to the preset upper limit time, and the corresponding demand components are not treated as urgent out-of-bounds states.

[0043] in, For the first In the first environmental control space unit The estimated time when an environmental parameter reaches its permissible limit based on its current trend of change.

[0044] The delayable adjustment margin is denoted as

[0045] in, For the execution devices in the set of callable execution devices whose expected direction of influence matches the direction of demand, the first... In the first environmental control space unit The shorter expected response time of each environmental parameter. When there is no execution device in a responsive state that matches the expected direction of influence with the demand direction, the corresponding demand component is recorded as an unresponsive component. The response time is recorded according to a preset upper limit and is not used as a matching item for the executing device when candidate coordinated control commands are generated. The regulation demand vector of each environmental control space unit is formed by arranging the demand parameters corresponding to each environmental parameter according to the environmental parameter number.

[0046] When temperature and ammonia concentration rise simultaneously, the demand direction of the climate regulation component is towards cooling, while the demand direction of the air quality regulation component is towards reducing ammonia concentration. The intensity of these two demands increases according to the degree and trend of deviation from the state deviation vector. When the light intensity does not deviate from the preset target state vector, the light regulation demand component maintains a low demand intensity or a large deferred control margin. Through this processing, the regulation demand vector can simultaneously reflect the differences between the climate regulation demand component, the air quality regulation demand component, and the light regulation demand component.

[0047] The conflict resolution module generates conflict resolution results based on the control demand vectors of multiple environmental control space units. These results include the remaining adjustment margin of each execution device, the set of available execution devices, the device function demand vector, and the degree of conflict in regional control demand. It reads the control demand vectors of multiple environmental control space units and, combined with the operating status, current adjustment amount, and adjustable range of each execution device, calculates the remaining adjustment margin of each device. When a certain execution device is in a responsive state and the remaining adjustment margin meets the adjustment requirements of the corresponding demand component, the execution device is included in the set of callable execution devices, and the device action demand vector is formed according to the correspondence between the control demand vector and the device parameter space influence matrix. No. The positive residual adjustment margin of each actuator is the difference between the upper limit of the adjustable range and the current adjustment amount, while the negative residual adjustment margin is the difference between the current adjustment amount and the lower limit of the adjustable range. When When it is positive, it corresponds to the first The remaining adjustment margin in the direction of increasing adjustment amount of each actuator; when When it is negative, it corresponds to the first The remaining adjustment margin in the direction of the reduction of the adjustment amount of each execution device. When the execution device is in a responsive state and the remaining adjustment margin matches the corresponding demand direction, the execution device is included in the set of callable execution devices. .

[0048] No. The execution device faces the first The functional requirements of each environmental control space unit are denoted as:

[0049] in, For the first The execution device faces the first The functional requirements of a single environmental control space unit. In terms of demand direction, The expected direction of impact, For demand intensity, The expected impact range, To indicate the expected scope of impact, The attenuation coefficient is the effect factor. The confidence level is the level of the effect. When it is positive, it corresponds to the first The function of increasing the adjustment amount of the actuator in the direction of the demand; When it is negative, it corresponds to the first The function of reducing the adjustment amount of each actuator requires... Arranged according to the environmental control space unit number, forming the [number]th A vector of device function requirements for each execution device.

[0050] For example, the upper-level environmental control space unit near the exhaust side has a control demand vector for cooling and reducing ammonia concentration, while the middle-level environmental control space unit near the air intake side has a control demand vector for maintaining temperature and improving air intake stability. At this time, the remaining adjustment margin of the ventilation equipment, the adjustable range of the air intake adjustment equipment, and the current angle of the airflow guiding equipment are all included in the calculation to obtain the effect requirements of different execution equipment when facing different environmental control space units. The degree of regional regulation demand conflict is calculated based on the equipment action demand vector, spatial coupling weight, and equipment parameter spatial influence matrix. Among them, the anisotropic coupling amount of demand is determined by the degree of opposite demand direction, the difference in demand intensity, and the angle between regulation demand vectors under the same demand component; the equipment call competition amount is determined by the degree of oppositeity and superposition of the equipment action demand vector to the same executing equipment, and the degree of occupation of remaining regulation margin; the spatial propagation superposition amount is determined by the degree of overlap of expected influence range; the response timing mismatch amount is determined by the degree of matching between demand urgency and expected response time; and the urgency bias amount is determined by the difference between demand urgency and delayable regulation margin. No. The first environmental control space unit and the first The degree of conflict between regional regulation needs of each environmental control spatial unit is denoted as:

[0051] in, To address the conflict between regional regulatory demands, For the required anisotropic coupling quantity, For device access contention, For spatial propagation superposition, In response to timing mismatch, This is the urgency bias. and This represents the conflict degree fusion coefficient. The above items were normalized according to differences in demand direction, competition among execution equipment, spatial coupling weight, differences in expected response time, and differences in demand urgency.

[0052] For example, increasing the rotation speed of ventilation equipment will reduce the ammonia concentration on the exhaust side, but may increase the temperature fluctuation on the intake side. In this case, the demand anisotropic coupling quantity and the spatial propagation superposition quantity are given higher weights. When the demand urgency of the air quality regulation demand component on the exhaust side is significantly higher than that of the climate regulation demand component on the intake side, the urgency bias quantity corrects the regional regulation demand conflict degree, thereby obtaining the conflict analysis results including the remaining regulation margin, the set of available execution equipment, the equipment function demand vector, and the regional regulation demand conflict degree.

[0053] The collaborative evaluation module is used to determine the target environmental control spatial unit set, the non-target environmental control spatial unit set, multiple candidate collaborative control commands, and the corresponding effective action rate of equipment space based on the fused state vector, state deviation vector, control demand vector, equipment action demand vector, callable execution equipment set, spatial coupling weight, and equipment parameter spatial influence matrix.

[0054] Based on the fused state vector, state deviation vector, and regulation demand vector of each environmental control space unit, the regulation priority of different environmental control space units is ranked. Combined with the equipment action demand vector, the set of callable execution equipment, spatial coupling weight, and equipment parameter spatial influence matrix, the target environmental control space unit set and the non-target environmental control space unit set are determined. Among them, environmental control space units with larger state deviation vector amplitudes, higher urgency of regulation demand vectors, and smaller delay margins for regulation are assigned to the target environmental control space unit set, while environmental control space units that are within the expected influence range of the execution equipment but do not have corresponding urgent regulation demands are assigned to the non-target environmental control space unit set. For example, if the upper-level environmental control space unit near the exhaust side has a superimposed deviation of temperature rise and ammonia concentration rise, and the ventilation equipment and airflow guiding equipment have a high confidence of their effect on this area, then this area is identified as the target environmental control space unit set; if the temperature of the middle-level environmental control space unit near the air intake side is close to the preset target state vector, but is within the expected influence range of the ventilation equipment and air intake regulating equipment, then this area is identified as the non-target environmental control space unit set. Within the set of callable execution devices, the adjustment direction and adjustment range of ventilation equipment, temperature and humidity control equipment, air intake control equipment and airflow guiding equipment are combined to form multiple candidate coordinated control commands, and the corresponding effective utilization rate of the equipment space is calculated for each candidate coordinated control command. Candidate coordinated control instructions are arranged by number Record, the first in the candidate coordinated regulation instruction The change in adjustment corresponding to each actuator is denoted as The corresponding execution device that did not participate in the execution of this candidate coordinated control command. The value is zero; the corresponding execution device participating in the candidate coordinated control command is... It does not exceed the remaining adjustment margin of the actuator in the same adjustment direction.

[0055] The target environmental control space unit set consists of environmental control space units whose state deviation vector, regulation demand vector, and regional regulation demand conflict degree meet the preset regulation triggering conditions; the non-target environmental control space unit set consists of environmental control space units within the expected influence range of candidate coordinated regulation instructions that are not included in the target environmental control space unit set.

[0056] No. The candidate coordinated regulation instruction for the first In the first environmental control space unit The expected response of each environmental parameter is denoted as

[0057] in, For the expected response volume, For a set of callable execution devices, The expected direction of impact, The expected impact range, To indicate the expected scope of impact, The attenuation coefficient is the effect factor. The confidence level is the level of the effect.

[0058] The effective utilization rate of the equipment space is obtained by fusing the effective utilization term and the constraint cost term through normalized ratio. The effective utilization term includes the target deviation convergence benefit, spatial selectivity gain, and utilization confidence correction. The target deviation convergence benefit is determined based on the convergence degree of the state deviation vector of the target environmental control spatial unit set. The spatial selectivity gain is determined based on the difference in the expected influence range between the target environmental control spatial unit set and the non-target environmental control spatial unit set. The utilization confidence correction is determined based on the utilization confidence level. The constraint cost term includes the non-target deviation diffusion cost, conflict residual penalty, and equipment load penalty. The non-target deviation diffusion cost is determined based on the increase in the state deviation vector of the non-target environmental control spatial unit set. The conflict residual penalty is determined based on the conflict degree of regional regulation demand. The equipment load penalty is determined based on the degree of utilization of the remaining regulation margin. No. The effective utilization rate of the equipment space corresponding to each candidate coordinated control command is denoted as:

[0059] in, For the effective utilization rate of equipment space, For effective action terms, To constrain the cost term, To prevent extremely small positive numbers with a denominator of zero, the effective action term is formed by weighting the target deviation convergence gain, spatial selectivity gain, and action confidence correction; the constraint cost term is formed by weighting the non-target deviation diffusion cost, conflict residual penalty, and equipment load penalty. The benchmark coordinated control command is determined according to the candidate coordinated control commands with the higher equipment spatial effective action rate that meet the preset selection criteria.

[0060] For example, if the candidate coordinated control command is to increase the speed of the exhaust side ventilation equipment, moderately increase the opening of the intake air regulating equipment, and adjust the angle of the airflow guiding equipment, and if the expected deviations of the temperature and ammonia concentration in the target environmental control space unit set converge significantly, the temperature fluctuations in the non-target environmental control space unit set are small, and the remaining regulation margin occupancy is at a low level, then the candidate coordinated control command will achieve a high effective utilization rate of the equipment space.

[0061] The microstep execution module generates microstep trial instructions and response verification quantities based on candidate coordinated control instructions and equipment space effective action rates. It then generates hierarchical and partitioned coordinated control instructions or corrects the equipment parameter space influence matrix based on the response verification quantities. Multiple candidate coordinated control instructions and their corresponding equipment space effective action rates are sorted and filtered. Candidate coordinated control instructions whose equipment space effective action rates meet preset selection criteria are determined as benchmark coordinated control instructions. These criteria include equipment space effective action rates falling within a preset sorting range, effective action items exceeding constraint cost items, and equipment load penalties not exceeding a preset occupancy threshold. The adjustment amplitude in the benchmark coordinated control instructions is proportionally reduced according to a preset microstep coefficient to generate microstep trial instructions, while maintaining the adjustment direction, target environmental control space unit set, and callable execution device set unchanged. Let the benchmark coordinated control command be The micro-step probing command is The preset microstep coefficient is ,but

[0062] in, Based on the coordinated control instructions, This is a micro-step probing command. Preset microstepping coefficients. The determination is based on the minimum adjustment resolution of the executing equipment, the allowable fluctuation range of the corresponding environmental parameters, and the allowable disturbance range of the non-target environmental control space unit set, and satisfies the following conditions. .

[0063] The response observation window is set according to the expected response duration in the equipment parameter spatial influence matrix. Within the response observation window, the fusion state vector change and regional regulation demand conflict degree change of each environmental control spatial unit are continuously acquired. The convergence magnitude of the state deviation vector of the target environmental control spatial unit set, the increase magnitude of the state deviation vector of the non-target environmental control spatial unit set, the decrease magnitude of the regional regulation demand conflict degree, and the difference between the response arrival time and the expected response duration are used to generate the response verification quantity. The response observation window, starting from the execution time of the microstepping probe command, covers the relatively long expected response time of the executing equipment participating in the microstepping probe command to the corresponding environmental parameters within the target environmental control spatial unit set. The response observation window records changes in environmental parameters of the target and non-target environmental control spatial unit sets, changes in the degree of conflict between regional control demands, and the actual response arrival time.

[0064] The response verification quantity is denoted as

[0065] in, In response to the verification quantity, Let $\mathbf{ ... The increase in the state deviation vector of the non-target environmental control space unit set. To determine the extent to which regional regulation and demand conflict has decreased. It is a normalized measure of the difference between the response arrival time and the expected response duration. and To verify the fusion coefficients, when the response verification quantity reaches the response threshold, the disturbance of the non-target environmental control space unit set does not exceed the allowable disturbance range, and the regional control demand conflict degree does not increase, a hierarchical and regional coordinated control command is generated based on the benchmark coordinated control command; if any of the conditions are not met, the equipment parameter space influence matrix is ​​corrected.

[0066] When the response verification quantity shows that the temperature, ammonia concentration, or illumination status within the target environmental control space unit set converges in the expected direction, the deviation of the non-target environmental control space unit set is within the allowable range, and the regional control demand conflict degree does not show an abnormal increase, a hierarchical and regional coordinated control instruction is generated based on the benchmark coordinated control instruction; when the response verification quantity shows that the actual influence direction is inconsistent with the expected influence direction, the actual influence amplitude is significantly lower than the expected influence amplitude, the response arrival time exceeds the expected response duration, or the deviation of the non-target environmental control space unit set spreads, the expected influence amplitude, expected response duration, effect attenuation coefficient, and effect confidence degree in the spatial influence matrix of the equipment parameters are corrected according to the response verification quantity.

[0067] The correction to the spatial influence matrix of equipment parameters is based on the deviation between the actual response and the expected response. The parameter to be corrected is denoted as... The parameters to be corrected include the expected impact magnitude. Expected response time and the effect attenuation coefficient The corresponding actual response parameters are denoted as ,but

[0068] in, The corrected parameters are those to be corrected. Here are the correction coefficients for the parameters to be corrected, and The actual effect attenuation coefficient is determined based on the attenuation relationship between the actual influence amplitude of different environmental control space units after the execution of the microstep probing command and the actual influence amplitude within the target environmental control space unit set.

[0069] The confidence level correction for the effect is denoted as

[0070] in, The confidence level of the effect before correction. The adjusted confidence level. For confidence level adjustment, This is a truncation function. It applies when the actual influence direction matches the expected influence direction and the actual influence magnitude meets the deviation requirement from the expected magnitude. Take the positive adjustment amount; when the actual impact direction is inconsistent with the expected impact direction, or when deviations occur in the non-target environmental control space unit set, Take the negative adjustment amount.

[0071] Example 2: Refer to Figure 3 A layered environmental control method for layer hen houses based on multi-dimensional environmental parameter fusion includes: In this second embodiment, the calculation methods for spatial coupling weight, equipment parameter spatial influence matrix, fusion state vector, state deviation vector, regulation demand vector, equipment action demand vector, regional regulation demand conflict degree, candidate collaborative regulation command, equipment spatial effective action rate, micro-step trial command, response verification quantity, and equipment parameter spatial influence matrix correction are consistent with the calculation methods of the corresponding modules in the first embodiment.

[0072] Step 1: Divide the stacked layer hen house into environmental control spatial units and collect environmental parameter groups and equipment status groups. Incorporate environmental differences across different levels and areas within the stacked layer hen house into a unified processing scope, avoiding reliance solely on the overall average environment as the basis for control. By collecting environmental parameter groups and equipment status groups for each environmental control spatial unit, the correspondence between the environmental state and the status of the equipment within the stacked layer hen house can be obtained, providing fundamental data for stratified and zoned control.

[0073] Step 2: Generate spatial coupling weights and a spatial influence matrix for equipment parameters based on the environmental parameter group and the device status group. Establish the environmental correlation between different environmental control spatial units and clarify the spatial influence law of the device on the environmental parameter group. The spatial coupling weights reflect the environmental propagation relationship between environmental control spatial units, and the spatial influence matrix for equipment parameters reflects the direction, magnitude, range, and response characteristics of the device's adjustment actions on the environmental parameter group.

[0074] Step 3: Generate a fused state vector based on the environmental parameter set, and generate a state deviation vector based on the preset target state vector. This converts multiple types of parameters in the environmental parameter set into a unified fused state expression, reducing the bias caused by judging a single environmental parameter. By comparing the fused state vector with the preset target state vector, the state deviation vector is obtained, clearly indicating the degree and direction of deviation of the current environmental state of each environmental control space unit from the target state.

[0075] Step 4: Generate a control demand vector based on the state deviation vector, the equipment parameter space influence matrix, and the changing trends of the environmental parameter set. This combines the current deviation state, the influence capability of the executing equipment, and the environmental change trend to form a demand expression oriented towards control actions. The control demand vector not only reflects the deviation of the environmental parameter set from the preset target state vector but also, in conjunction with the changing trends of the environmental parameter set, distinguishes between different states: continuous deterioration, trending towards stability, or gradual improvement.

[0076] Step 5: Based on the control demand vectors of multiple environmental control spatial units, generate conflict analysis results including remaining control margin, set of available execution equipment, equipment function demand vector, and regional control demand conflict degree. This process addresses potential differences in control direction, competition among execution equipment, and overlapping spatial impacts among multiple environmental control spatial units. The conflict analysis results clarify the remaining control space of each execution equipment, the range of execution equipment currently available for control, the function demand of each execution equipment, and the degree of conflict between regional control demands.

[0077] Step Six: Based on the conflict analysis results, spatial coupling weights, and the spatial influence matrix of equipment parameters, determine the target environmental control spatial unit set, the non-target environmental control spatial unit set, multiple candidate coordinated control commands, and their corresponding equipment spatial effective utilization rates. In cases involving multiple regional demands and the influence of multiple executing devices, conduct a coordinated evaluation of the candidate coordinated control commands. The target environmental control spatial unit set represents the key control targets, the non-target environmental control spatial unit set represents the areas where adverse effects need to be limited, and the equipment spatial effective utilization rate reflects the comprehensive effect level of the candidate coordinated control commands between target benefits and constraint costs.

[0078] Step 7: Generate micro-step trial commands and response verification quantities based on candidate coordinated control commands and equipment space effective utilization rates. Then, generate hierarchical and regional coordinated control commands or correct the equipment parameter space influence matrix based on the response verification quantities. Before formally forming large-scale coordinated control actions, verify the actual response effect of candidate coordinated control commands through micro-step trial commands. The response verification quantity reflects the changes in the fused state vector and the conflict degree of regional control demand before and after the execution of the micro-step trial command. When the response verification quantity meets the preset response conditions, a hierarchical and regional coordinated control command is generated; when the response verification quantity does not meet the preset response conditions, the equipment parameter space influence matrix is ​​corrected.

[0079] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A layered environmental control system for layer hen houses based on multi-dimensional environmental parameter fusion, characterized in that, include: The data acquisition and modeling module is used to divide the stacked egg-laying hen house into environmental control space units. It collects environmental parameter groups and execution equipment status groups for each environmental control space unit according to a preset sampling period, and generates spatial coupling weights and equipment parameter spatial influence matrices. The fusion demand module is used to generate a fusion state vector based on the environmental parameter set of each environmental control space unit, generate a state deviation vector based on the fusion state vector and the preset target state vector, and generate a control demand vector based on the state deviation vector, the equipment parameter space influence matrix and the changing trend of the environmental parameter set. The conflict resolution module is used to generate conflict resolution results based on the control demand vectors of multiple environmental control space units. The conflict resolution results include the remaining adjustment margin of each execution device, the set of available execution devices, the device function demand vector, and the conflict degree of regional control demand. The collaborative evaluation module is used to determine the target environmental control spatial unit set, the non-target environmental control spatial unit set, multiple candidate collaborative control commands and the corresponding effective spatial utilization rate of equipment based on the fused state vector, state deviation vector, control demand vector, equipment action demand vector, callable execution equipment set, spatial coupling weight and equipment parameter spatial influence matrix; The microstep execution module is used to generate microstep trial instructions and response verification quantities based on candidate collaborative control instructions and the effective action rate of the device space, and to generate hierarchical and partitioned collaborative control instructions or correct the device parameter space influence matrix based on the response verification quantities.

2. The layered environmental control system for layer hen houses based on multi-dimensional environmental parameter fusion as described in claim 1, characterized in that, The environmental parameter group includes at least two types of parameters from the following: indoor climate parameters, air quality parameters, and light parameters; the execution equipment status group includes the operating status and adjustment status of the execution equipment, and the adjustment status includes the current adjustment amount and adjustable range; the execution equipment includes at least two types of equipment from the following: ventilation equipment, temperature and humidity control equipment, air intake control equipment, and airflow guiding equipment.

3. The layered environmental control system for layer hen houses based on multi-dimensional environmental parameter fusion as described in claim 2, characterized in that, The equipment parameter space influence matrix includes at least the expected direction, expected magnitude, expected range, expected response time, effect attenuation coefficient, and effect confidence level of the executing equipment on the environmental parameter group within the environmental control space unit.

4. The layered environmental control system for layer hen houses based on multi-dimensional environmental parameter fusion as described in claim 3, characterized in that, The regulation demand vector includes at least two demand components, each of which includes demand direction, demand intensity, demand urgency, and deferable regulation margin; the at least two demand components include at least two of the following: climate regulation demand component, air quality regulation demand component, and light regulation demand component.

5. The layered environmental control system for layer hen houses based on multi-dimensional environmental parameter fusion according to claim 4, characterized in that, The degree of conflict between regional regulation and control demands is obtained by weighted fusion of the anisotropic coupling of demands between different environmental control spatial units, the competition for equipment calls, the superposition of spatial propagation, the mismatch of response timing, and the urgency bias; the anisotropic coupling of demands is determined by the degree of opposite demand directions under the same demand components, the difference in demand intensity, and the angle between the regulation and control demand vectors.

6. The layered environmental control system for layer hen houses based on multi-dimensional environmental parameter fusion according to claim 5, characterized in that, The equipment call contention quantity is determined by the degree of opposition, superposition, and remaining adjustment margin occupation of the equipment action demand vector for the same execution equipment; the spatial propagation superposition quantity is determined by the degree of overlap of the expected influence range corresponding to the equipment parameter spatial influence matrix and spatial coupling weight; the response timing mismatch quantity is determined by the degree of matching between the demand urgency and the expected response time; the urgency bias quantity is determined by the difference between the demand urgency and the delayable adjustment margin.

7. The layered environmental control system for layer hen houses based on multi-dimensional environmental parameter fusion according to claim 1, characterized in that, The effective action rate of the equipment space is obtained by fusing the effective action term and the constraint cost term through normalized ratios; the effective action term includes the target deviation convergence gain determined by the convergence degree of the state deviation vector of the target environmental control space unit set, the spatial selectivity gain determined by the difference in the expected influence range between the target environmental control space unit set and the non-target environmental control space unit set, and the action confidence correction determined by the action confidence degree.

8. The layered environmental control system for layer hen houses based on multi-dimensional environmental parameter fusion according to claim 7, characterized in that, The constraint cost includes the non-target deviation diffusion cost determined by the increase in the state deviation vector of the non-target environmental control space unit set, the conflict residual penalty determined by the degree of conflict of regional regulation demand, and the equipment load penalty determined by the degree of utilization of the remaining regulation margin.

9. The layered environmental control system for layer hen houses based on multi-dimensional environmental parameter fusion according to claim 8, characterized in that, The microstep execution module is specifically used to determine the candidate coordinated control commands that meet the preset selection criteria for the effective utilization rate of the equipment space as the benchmark coordinated control commands, generate and execute microstep trial commands according to the preset microstep coefficients, obtain the changes in the fusion state vector and the changes in the conflict degree of regional control demand within the response observation window based on the expected response duration, and generate response verification quantities; generate hierarchical and regional coordinated control commands or correct the spatial influence matrix of equipment parameters based on the response verification quantities.

10. A layered layer hen house environmental control method based on multi-dimensional environmental parameter fusion, applied to the layered layer hen house environmental control system based on multi-dimensional environmental parameter fusion as described in any one of claims 1-9, characterized in that, include: Step 1: Divide the stacked layer hen house into environmental control space units, and collect environmental parameter groups and execution equipment status groups; Step 2: Generate spatial coupling weights and spatial influence matrices of device parameters based on the environmental parameter group and the execution device status group; Step 3: Generate a fused state vector based on the environmental parameter set, and generate a state deviation vector based on the preset target state vector; Step 4: Generate the control demand vector based on the state deviation vector, the influence matrix of the equipment parameter space, and the changing trends of the environmental parameter set; Step 5: Based on the control demand vectors of multiple environmental control spatial units, generate conflict resolution results including remaining control margin, set of callable execution equipment, equipment function demand vector, and regional control demand conflict degree; Step 6: Based on the conflict resolution results, spatial coupling weights, and equipment parameter spatial influence matrix, determine the target environmental control spatial unit set, the non-target environmental control spatial unit set, multiple candidate coordinated control commands, and the corresponding equipment spatial effective action rate; Step 7: Generate micro-step trial commands and response verification quantities based on candidate coordinated control commands and equipment space effective action rates, and generate hierarchical and partitioned coordinated control commands or correct equipment parameter space influence matrices based on response verification quantities.

Images