A remote control system and method for three-dimensional shrimp and crab breeding facilities

Abstract

The present invention relates to the field of automatic control, and in particular to a remote control system and method for three-dimensional shrimp and crab breeding facilities. It includes: collecting environmental parameter data, using an environmental parameter estimation algorithm based on time series data prediction to process and analyze the environmental parameter data to obtain future environmental parameter prediction values, and using an environmental state prediction and evaluation algorithm to predict and evaluate to obtain future environmental state index prediction values; based on the future environmental parameter prediction values ​​and future environmental state index prediction values, using an adaptive feedback control algorithm to calculate and obtain preliminary control instructions, and saturating the preliminary control instructions to obtain final control instructions; sending the final control instructions to the device, and executing the final control instructions. It solves the technical problem that the traditional control system can only rely on real-time collected data for feedback, lacks the ability to accurately predict future environmental states, and is prone to damage to the equipment due to overload or operational errors.

Description

Technical Field

[0001] The present invention relates to the field of automatic control, and in particular to a remote control system and method for three-dimensional shrimp and crab breeding facilities. Background Art

[0002] With the rapid development of the global aquaculture industry, the continuous innovation of aquaculture technology and the improvement of intelligence, more and more farms have begun to explore environmentally friendly and sustainable aquaculture methods. Shrimp and crab are two important economic species in aquaculture. The problems of environmental control and aquaculture management faced in the aquaculture process are gradually emerging. Especially under the conditions of modern facilities, how to improve aquaculture efficiency and reduce environmental pressure has become an issue that needs to be urgently addressed in the aquaculture industry.

[0003] In recent years, with the continuous advancement of the Internet of Things (IoT), artificial intelligence (AI), big data and automation technology, the management methods of shrimp and crab farming have gradually developed towards intelligence, automation and remoteness. In order to improve farming efficiency and reduce environmental impact, control systems and control methods for shrimp and crab three-dimensional farming facilities have emerged. The use of remote control systems can achieve all-weather, real-time monitoring and precise control of shrimp and crab three-dimensional farming facilities, thereby reducing labor costs, reducing losses caused by improper human operations, and improving the sustainability of aquaculture.

[0004] However, the existing control methods for shrimp and crab three-dimensional farming facilities have the following technical problems: in a dynamic environment, control decisions need to be made in real time based on the current state and predicted values ​​of future environmental parameters. If the changes cannot be responded to in time, control lag will occur, thereby affecting the efficiency and accuracy of equipment operation; traditional control systems can only rely on real-time collected data for feedback and lack the ability to accurately predict future environmental conditions; existing control methods fail to consider the mutual influence of multiple parameters in the environment; traditional control systems do not consider the physical limitations of the equipment, which can easily lead to damage to the equipment due to overload or operational errors. Summary of the invention

[0005] The present invention provides a remote control system and method for a three-dimensional shrimp and crab breeding facility to solve the problem that in a dynamic environment, it is necessary to make control decisions in real time according to the current state and predicted values ​​of future environmental parameters. If the changes cannot be responded to in time, control lag will occur, thereby affecting the efficiency and accuracy of equipment operation; traditional control systems can only rely on real-time collected data for feedback, and lack the ability to accurately predict future environmental states; existing control methods fail to consider the mutual influence between multiple parameters in the environment; traditional control systems do not consider the physical limitations of the equipment, which easily leads to technical problems such as damage to the equipment due to overload or operating errors.

[0006] A remote control system and method for a three-dimensional shrimp and crab breeding facility of the present invention specifically includes the following technical solutions:

[0007] A method for remotely controlling a three-dimensional shrimp and crab breeding facility comprises the following steps:

[0008] S1: Collect environmental parameter data, process and analyze the environmental parameter data using an environmental parameter estimation algorithm based on time series data prediction, and obtain future environmental parameter prediction values;

[0009] S2: Based on the predicted values ​​of future environmental parameters, the predicted values ​​of future environmental status indicators are obtained by using the environmental status prediction and evaluation algorithm;

[0010] S3: Based on the predicted values ​​of future environmental parameters and future environmental status indicators, an adaptive feedback control algorithm is used to calculate a preliminary control instruction, and the preliminary control instruction is saturated to obtain a final control instruction; the final control instruction is sent to the device and executed.

[0011] Preferably, the S1 specifically includes:

[0012] In the process of implementing the environmental parameter estimation algorithm based on time series data prediction, the change rate of each environmental parameter is calculated, the calculated change rate of the environmental parameter is multiplied by the prediction time interval, and the preliminary adjustment of the future environmental state based on the current environmental parameter change trend is calculated.

[0013] Preferably, the S1 specifically includes:

[0014] In the process of implementing the environmental parameter estimation algorithm based on time series data prediction, the environmental parameter data within the prediction time interval is used to adjust the prediction, and the historical data of the environmental parameters are weighted to obtain the predicted values ​​of the future environmental parameters. The prediction generation formula of the environmental parameter data is:

[0015] ,

[0016] in, is The first time prediction Environmental parameter data, indicating the predicted value of future environmental parameters; Indicated in The first Environmental parameter data; is the prediction time interval, which is the time difference between the prediction moment and the current moment; Indicates Environmental parameter data in history The rate of change at a moment; Indicated in The first Environmental parameter data; Indicates The weighting coefficient of the historical data of environmental parameters; Represents the weighted sum of historical data of environmental parameters; For The first Environmental parameters, indicating the historical data of environmental parameters; represents an exponential decay function; Represents the attenuation coefficient.

[0017] Preferably, the S2 specifically includes:

[0018] In the process of implementing the environmental state prediction and evaluation algorithm, the predicted values ​​of future environmental parameters are weighted to obtain the predicted values ​​of future environmental state indicators. The calculation formula for the prediction and evaluation of environmental state indicators is:

[0019] ,

[0020] in, For The environmental state index value predicted at any moment represents the predicted value of the future environmental state index; Indicates the number of environmental parameters; Indicates The weight coefficient of the predicted value of future environmental parameters; Indicates The predicted values ​​of future environmental parameters and The interaction weight coefficient between the predicted values ​​of future environmental parameters; Indicated in The moment Predicted values ​​of future environmental parameters.

[0021] Preferably, the S3 specifically includes:

[0022] The adaptive feedback control algorithm includes two parts: feedforward control and feedback correction.

[0023] Preferably, the S3 specifically includes:

[0024] The feedforward control adjusts the influence of the future environmental state index prediction value and the future environmental parameter prediction value on the preliminary control instruction of the equipment through the first weighting coefficient and the second weighting coefficient in the generation of the preliminary control instruction of the equipment; the feedback correction is achieved by calculating the error between the control instruction and the actual response of the equipment. When the error is extremely large, the correction value is also extremely large; when the error is extremely small, the correction value is also extremely small.

[0025] Preferably, the S3 specifically includes:

[0026] The calculation formula for the preliminary control command is:

[0027] ,

[0028] in, Indicates the device exist Preliminary control instructions that need to be executed at all times; Indicates the device a first weighting coefficient in generating preliminary control instructions; Indicates the device a second weighting coefficient in generating preliminary control instructions; Indicates Environmental parameter data for equipment The influence coefficient of the preliminary control instruction; Represents the error term, and the calculation formula is: , is the equipment exist Actual response at the moment and equipment exist Preliminary control instructions that need to be executed at all times The error between .

[0029] Preferably, the S3 specifically includes:

[0030] The saturation function is introduced to perform saturation processing on the preliminary control instruction to obtain the final control instruction. The specific formula is:

[0031] ,

[0032] in, Indicates the device exist The final control instructions that need to be executed at all times; represents the saturation function; Indicates the device Maximum control instructions; Indicates the device The minimum control instruction.

[0033] A remote control system for shrimp and crab three-dimensional breeding facilities, comprising the following parts:

[0034] Environmental parameter acquisition module, future environmental parameter prediction module, environmental status prediction and evaluation module, equipment control instruction generation module, equipment control execution module;

[0035] Environmental parameter collection module: collects environmental parameter data in real time and outputs the collected environmental parameter data to the future environmental parameter prediction module;

[0036] Future environmental parameter prediction module: Based on the environmental parameter data of the environmental parameter acquisition module, the environmental parameter estimation algorithm based on time series data prediction is used to predict the future environmental parameter prediction value, and the future environmental parameter prediction value is output to the environmental state prediction and evaluation module and the equipment control instruction generation module;

[0037] Environmental state prediction and evaluation module: Based on the future environmental parameter prediction value of the future environmental parameter prediction module, the environmental state prediction and evaluation algorithm is used to predict and evaluate to obtain the future environmental state index prediction value, and the future environmental state index prediction value is output to the equipment control instruction generation module;

[0038] Equipment control instruction generation module: Based on the future environmental parameter prediction value of the future environmental parameter prediction module and the future environmental state index prediction value of the environmental state prediction and evaluation module, the module uses an adaptive feedback control algorithm to calculate and obtain a preliminary control instruction, uses a saturation function to perform saturation processing on the preliminary control instruction, obtains a final control instruction, and outputs the final control instruction to the equipment control execution module;

[0039] Equipment control execution module: remotely controls the three-dimensional shrimp and crab breeding facilities according to the final control instructions generated by the equipment control instruction generation module.

[0040] The beneficial effects of the technical solution of the present invention are:

[0041] 1. By arranging a sensor network, collecting environmental parameter data in real time and using an environmental parameter estimation algorithm based on time series data prediction, the environmental parameter data at a certain moment in the future is predicted, thereby achieving accurate prediction of future environmental parameter data. By introducing a time decay mechanism and weighting environmental parameter historical data, the trend of environmental parameter changes can be captured, and the accurate prediction of future environmental parameter changes can be improved. By adopting a mechanism that combines the rate of change of environmental parameters with the time interval, the remote control system of the shrimp and crab three-dimensional breeding facility can flexibly respond to changes in environmental conditions, accurately predict future environmental parameter data, and reduce the impact of environmental fluctuations on shrimp and crab three-dimensional breeding facilities.

[0042] 2. Based on the predicted values ​​of future environmental parameters, the predicted values ​​of future environmental status indicators are calculated through the environmental status prediction and evaluation algorithm. The mutual influence and weighting factors between the predicted values ​​of different environmental parameters are taken into consideration, and a double weighting mechanism is used for refined modeling to improve the accuracy of environmental status evaluation. The interaction between the predicted values ​​of different environmental parameters obtained through weighted prediction can reflect the multiple influencing factors in a complex environment. The environmental status evaluation takes into account the weights and interactions of the predicted values ​​of different environmental parameters, so that the remote control system of shrimp and crab three-dimensional breeding facilities can adjust its operation according to the refined environmental status, thereby enhancing the adaptability of the remote control system of shrimp and crab three-dimensional breeding facilities to complex environments.

[0043] 3. Based on the predicted values ​​of future environmental parameters and future environmental status indicators, an adaptive feedback control algorithm is used to generate preliminary control instructions, and they are limited by a saturation function to ensure that the preliminary control instructions are within the operating limit of the equipment. By using feedforward control and feedback correction, it is possible to respond quickly to the behavior of the equipment and make dynamic adjustments based on real-time errors to keep the equipment in the best working state at all times. By saturating the preliminary control instructions, it is ensured that the equipment operates within a safe operating range, preventing equipment failures due to control instruction overload or excessive errors, thereby improving the safety and stability of the remote control system of the shrimp and crab three-dimensional breeding facility.

[0044] 4. The remote control system of shrimp and crab three-dimensional breeding facilities can monitor, predict and adjust equipment behavior in real time during remote control, greatly improving the accuracy and reliability of remote operation and reducing the need for equipment maintenance and human intervention. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 This is a structural diagram of a remote control system for a three-dimensional shrimp and crab breeding facility according to the present invention;

[0046] Figure 2 The present invention provides a flow chart of a remote control method for a three-dimensional shrimp and crab breeding facility. DETAILED DESCRIPTION

[0047] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the technical scheme in the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiment of the present invention. Obviously, the described embodiment is only a part of the embodiment of the present invention, not all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0048] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0049] The specific scheme of a remote control system and method for a three-dimensional shrimp and crab breeding facility provided by the present invention is described in detail below with reference to the accompanying drawings.

[0050] Refer to the attached Figure 1 , which shows a structural diagram of a remote control system for a three-dimensional shrimp and crab breeding facility provided by an embodiment of the present invention, the system includes the following parts:

[0051] Environmental parameter acquisition module, future environmental parameter prediction module, environmental status prediction and evaluation module, equipment control instruction generation module, equipment control execution module;

[0052] Environmental parameter acquisition module: Arrange sensor networks to collect environmental parameter data in real time through the sensor networks, and output the collected environmental parameter data to the future environmental parameter prediction module;

[0053] Future environmental parameter prediction module: Based on the environmental parameter data of the environmental parameter acquisition module, the environmental parameter estimation algorithm based on time series data prediction is used to predict the future environmental parameter prediction value, and the future environmental parameter prediction value is output to the environmental state prediction and evaluation module and the equipment control instruction generation module;

[0054] Environmental state prediction and evaluation module: Based on the future environmental parameter prediction value of the future environmental parameter prediction module, the environmental state prediction and evaluation algorithm is used to predict and evaluate to obtain the future environmental state index prediction value, and the future environmental state index prediction value is output to the equipment control instruction generation module;

[0055] Equipment control instruction generation module: Based on the future environmental parameter prediction value of the future environmental parameter prediction module and the future environmental state index prediction value of the environmental state prediction and evaluation module, the module uses an adaptive feedback control algorithm to calculate the preliminary control instruction, uses a saturation function to perform saturation processing on the preliminary control instruction, obtains the final control instruction, and outputs the final control instruction to the equipment control execution module;

[0056] Equipment control execution module: According to the final control instructions generated by the equipment control instruction generation module, remote control of the three-dimensional shrimp and crab breeding facilities is realized.

[0057] Refer to the attached Figure 2 , which shows a flow chart of a method for remotely controlling a three-dimensional shrimp and crab breeding facility provided by an embodiment of the present invention, the method comprising the following steps:

[0058] S1. Collect environmental parameter data, process and analyze the environmental parameter data using an environmental parameter estimation algorithm based on time series data prediction, and obtain future environmental parameter prediction values;

[0059] Arrange a sensor network, the sensor network includes but is not limited to water quality sensors, air quality sensors, soil sensors; the water quality sensor is used to detect data such as water acidity (pH value), water dissolved oxygen concentration, water temperature, etc.; the air quality sensor is used to monitor data such as air temperature, air humidity, air gas concentration (such as CO2, NH3), etc.; the soil sensor is used to detect data such as soil humidity, soil acidity (pH value), soil temperature, etc.; collect environmental parameter data in real time through the sensor network to obtain an environmental parameter data set , Indicated in The first Environmental parameter data, such as water pH, water dissolved oxygen concentration, water temperature, , Indicates the number of environmental parameters;

[0060] According to the environmental parameter data collected in real time, the environmental parameter estimation algorithm based on time series data prediction is used to process and analyze the environmental parameter data collected in real time, and the environmental parameter data at a certain moment in the future is predicted by combining the time decay mechanism with the weighted influence of the environmental parameter historical data, that is, the future environmental parameter prediction value;

[0061] The environmental parameter estimation algorithm based on time series data prediction reflects the change trend of the current environmental parameter data relative to the historical environmental parameter data by calculating the change rate of each environmental parameter, and helps predict the future change direction and rate of the environmental parameter data; based on the difference between the environmental parameter data at the current moment and the environmental parameter data at a certain moment in history, the change rate of the environmental parameter is obtained after normalization processing of the historical time interval; after the change rate of the environmental parameter is calculated, it is multiplied by the predicted time interval to calculate the preliminary adjustment of the future environmental state based on the current environmental parameter change trend, and the change range of the environmental parameter at the future moment is inferred by using the current environmental parameter data and the change rate of each environmental parameter;

[0062] In addition to considering the changes in current environmental parameters, the environmental parameter data within the prediction time interval will be used to further adjust the prediction. Since the state of the environment or equipment is easily affected by the historical state, it is necessary to weight the historical data of environmental parameters to capture long-term change trends. The environmental parameters in each historical time interval will be assigned different weights according to the distance from the current moment. The weight of the historical data of environmental parameters is controlled by an exponential decay function, that is, the farther the historical data of environmental parameters is from the current moment, the faster the weight will decay.

[0063] The prediction formula for environmental parameter data is:

[0064] ,

[0065] in, Indicated in The first time prediction Environmental parameter data, i.e., predicted values ​​of future environmental parameters; Indicated in The first time collection Environmental parameter data; Indicates the prediction time interval, that is, the time difference between the prediction moment and the current moment, which can be set according to the specific implementation scenario and is not limited here; Indicates Environmental parameter data in history The rate of change at each moment reflects the dynamics of environmental parameter changes; Indicated in The first time collection Environmental parameter data; Indicates The weighting coefficient of the historical data of the environmental parameters is used to control the influence of the historical data of the environmental parameters on the predicted values ​​of the future environmental parameters. It can be set according to the specific implementation scenario and is not limited here. Represents the weighted sum of historical data of environmental parameters, that is, historical The weighted contribution of environmental parameter data at each moment to the predicted value of future environmental parameters; Indicated in The first time collection environmental parameters, i.e. historical data of environmental parameters; represents an exponential decay function, as time As the climate changes, the contribution of historical environmental parameter data to future environmental parameter predictions gradually decreases. Represents the attenuation coefficient, which is used to control the attenuation speed. It can be set according to the specific implementation scenario and is not limited here.

[0066] S2. Based on the predicted values ​​of future environmental parameters, the predicted values ​​of future environmental status indicators are obtained by using the environmental status prediction and evaluation algorithm;

[0067] Based on the predicted value of the environmental parameter at a certain moment in the future, the environmental state index value at a certain moment in the future is predicted and evaluated using the environmental state prediction and evaluation algorithm, that is, the future environmental state index prediction value;

[0068] The environmental state prediction and evaluation algorithm will weight the predicted values ​​of different environmental parameters, and set weight coefficients according to the importance of different future environmental parameter predicted values, so as to adjust the contribution of different future environmental parameter predicted values ​​in the final environmental state prediction; there are mutual influences or correlations between different future environmental parameter predicted values ​​predicted in the same environment, and it is necessary to model the mutual influences between sensors to further optimize the future environmental parameter predicted values, and through a double weighting mechanism, not only the individual contribution of each predicted future environmental parameter predicted value is considered, but also the synergy and interaction between different predicted future environmental parameter predicted values ​​are considered, and the interaction between different predicted future environmental parameter predicted values ​​is represented by an interaction weight coefficient;

[0069] The calculation formula for the prediction and evaluation of environmental status indicators is:

[0070] ,

[0071] in, Indicated in The environmental state index value predicted at any moment is the future environmental state index prediction value; Express The environmental parameters are summed up; Indicates The weight coefficient of the predicted value of the future environmental parameter is used to adjust the contribution of the predicted values ​​of different future environmental parameters in the prediction of the final environmental state. It can be set according to the specific implementation scenario and is not limited here. Indicated in The first time prediction Environmental parameter data, i.e., predicted values ​​of future environmental parameters; It represents the weighted sum of the interaction terms of different predicted values ​​of future environmental parameters, taking into account the interaction between different predicted values ​​of future environmental parameters, and can further refine the environmental state prediction, especially when there is obvious mutual dependence or correlation between the predicted values ​​of future environmental parameters; Indicates The predicted values ​​of future environmental parameters and The interaction weight coefficient between the predicted values ​​of the future environmental parameters is used to describe the correlation or mutual influence between the predicted values ​​of the future environmental parameters. It can be set according to the specific implementation scenario and is not limited here; Indicated in The moment Predicted values ​​of future environmental parameters.

[0072] S3. Based on the predicted values ​​of future environmental parameters and the predicted values ​​of future environmental status indicators, a preliminary control instruction is calculated using an adaptive feedback control algorithm, and the preliminary control instruction is saturated to obtain a final control instruction; the final control instruction is sent to the device, and the final control instruction is executed;

[0073] Based on the predicted values ​​of future environmental parameters and future environmental state indicators, the adaptive feedback control algorithm is used to calculate the preliminary control instructions;

[0074] The adaptive feedback control algorithm includes two parts: feedforward control and feedback correction;

[0075] The purpose of the feedforward control is to respond quickly to the behavior of the device in advance. The first weighting coefficient and the second weighting coefficient in the generation of the preliminary control instruction are used to adjust the future environmental state indicator prediction value and the future environmental parameter prediction value to the device respectively. the extent of the impact of the initial control order;

[0076] The feedback correction process is realized by calculating the error between the preliminary control instruction and the actual response of the device. When the error is extremely large, the feedback correction value is also extremely large; when the error is extremely small, the feedback correction value is also extremely small. In order to avoid instability of the remote control system of the shrimp and crab three-dimensional breeding facility caused by over-adjustment, square and logarithmic adjustment are also combined to ensure that excessive reaction to the error can be suppressed, so that the remote control system of the shrimp and crab three-dimensional breeding facility can smoothly transition and avoid the occurrence of mutations or shocks.

[0077] The calculation formula for the preliminary control command is:

[0078] ,

[0079] in, Indicates the device exist Preliminary control instructions that need to be executed at all times; Indicates the device The first weighted coefficient in the generation of preliminary control instructions reflects the impact of the predicted value of the future environmental state index on the equipment. The degree of influence of the preliminary control instruction can be set according to the specific implementation scenario and is not limited here; Indicated in The environmental state index value predicted at any moment is the future environmental state index prediction value; Indicates the device The second weighting coefficient in the generation of preliminary control instructions is used to control the future environmental parameter prediction value on the equipment The degree of influence of the preliminary control instruction can be set according to the specific implementation scenario and is not limited here; Indicated in The first time prediction Environmental parameter data, i.e., predicted values ​​of future environmental parameters; Indicates Environmental parameter data for equipment The influence coefficient of the preliminary control instruction can be set according to the specific implementation scenario and is not limited here; Represents the error term, and the calculation formula is: , is the equipment exist Actual response at the moment and equipment exist Preliminary control instructions that need to be executed at all times The error between them directly affects the feedback correction value and is the key factor in correcting the initial control command. It represents the logarithmic adjustment factor, which reduces the correction amplitude in the case of large errors by logarithmically transforming the square of the error term, thus avoiding overreaction of the remote control system of shrimp and crab three-dimensional breeding facilities in the case of large errors, smoothing the feedback correction, and enhancing the stability of the remote control system of shrimp and crab three-dimensional breeding facilities;

[0080] In order to avoid equipment damage or instability of the remote control system of shrimp and crab three-dimensional breeding facilities due to overcorrection, the saturation function is used to saturate the preliminary control instructions to ensure that the final control instructions will not exceed the operating limit of the equipment and prevent the equipment from overloading or overreacting;

[0081] The calculation formula of the final control instruction is:

[0082] ,

[0083] in, Indicates the device exist The final control instructions that need to be executed at all times; It represents the saturation function, which is used to ensure that the device control command is always between the maximum and minimum control range of the device. When the calculated preliminary control command exceeds the maximum and minimum control range, the saturation function will automatically correct to the maximum or minimum value. The specific formula is as follows:

[0084] ,

[0085] in, Indicates the device exist Preliminary control instructions that need to be executed at all times; Indicates the device The maximum control instruction is specified by the design parameters of the equipment; Indicates the device The minimum control instructions are specified by the design parameters of the equipment;

[0086] Through saturation processing, the remote control system of shrimp and crab three-dimensional breeding facilities can effectively limit the scope of control instructions and ensure that the equipment operates within a safe range;

[0087] The final control command is sent to the device through a remote communication network (such as the Internet of Things). After receiving the final control command, the device performs corresponding operations to realize remote control of the three-dimensional shrimp and crab breeding facilities.

[0088] In summary, a remote control system and method for a three-dimensional shrimp and crab breeding facility has been completed.

[0089] The order of the embodiments of the invention is for description only and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0090] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0091] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that the technical solutions described in the above embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention.

Claims

1. A remote control method for a three-dimensional shrimp and crab breeding facility, characterized in that: The following steps are involved: S1: Collect environmental parameter data, process and analyze the environmental parameter data using an environmental parameter estimation algorithm based on time series data prediction, and obtain future environmental parameter prediction values; S2: Based on the predicted values ​​of future environmental parameters, the predicted values ​​of future environmental status indicators are obtained by using the environmental status prediction and evaluation algorithm; S3: Based on the predicted values ​​of future environmental parameters and future environmental state indicators, the adaptive feedback control algorithm is used to calculate the preliminary control instructions. The calculation formula of the preliminary control instructions is: ， in, Indicates the device exist Preliminary control instructions that need to be executed at all times; For The environmental state index value predicted at any moment represents the predicted value of the future environmental state index; Indicates the device a first weighting coefficient in generating preliminary control instructions; Indicates the device a second weighting coefficient in generating preliminary control instructions; Indicates the number of environmental parameters; Indicates Environmental parameter data for equipment The influence coefficient of the preliminary control instruction; is The first time prediction Environmental parameter data, indicating the predicted value of future environmental parameters; Represents the error term, and the calculation formula is: , is the equipment exist Actual response at the moment and equipment exist Preliminary control instructions that need to be executed at all times The error between The preliminary control instruction is saturated to obtain a final control instruction; the final control instruction is sent to the device and executed.

2. A method for remotely controlling a three-dimensional shrimp and crab breeding facility according to claim 1, characterized in that: The S1 specifically includes: In the process of implementing the environmental parameter estimation algorithm based on time series data prediction, the change rate of each environmental parameter is calculated, the calculated change rate of the environmental parameter is multiplied by the prediction time interval, and the preliminary adjustment of the future environmental state based on the current environmental parameter change trend is calculated.

3. A method for remotely controlling a three-dimensional shrimp and crab breeding facility according to claim 2, characterized in that: The S1 specifically includes: In the process of implementing the environmental parameter estimation algorithm based on time series data prediction, the environmental parameter data within the prediction time interval is used to adjust the prediction, and the historical data of the environmental parameters are weighted to obtain the predicted values ​​of the future environmental parameters. The prediction generation formula of the environmental parameter data is: ， in, is The first time prediction Environmental parameter data, indicating the predicted value of future environmental parameters; Indicated in The first Environmental parameter data; is the prediction time interval, which is the time difference between the prediction moment and the current moment; Indicates Environmental parameter data in history The rate of change at a moment; Indicated in The first Environmental parameter data; Indicates The weighting coefficient of the historical data of environmental parameters; Represents the weighted sum of historical data of environmental parameters; For The first Environmental parameters, indicating the historical data of environmental parameters; represents an exponential decay function; Represents the attenuation coefficient.

4. A method for remotely controlling a three-dimensional shrimp and crab breeding facility according to claim 1, characterized in that: The S2 specifically includes: In the process of implementing the environmental state prediction and evaluation algorithm, the predicted values ​​of future environmental parameters are weighted to obtain the predicted values ​​of future environmental state indicators. The calculation formula for the prediction and evaluation of environmental state indicators is: ， in, For The environmental state index value predicted at any moment represents the predicted value of the future environmental state index; Indicates the number of environmental parameters; Indicates The weight coefficient of the predicted value of future environmental parameters; Indicates The predicted values ​​of future environmental parameters and The interaction weight coefficient between the predicted values ​​of future environmental parameters; Indicated in The moment Predicted values ​​of future environmental parameters.

5. A method for remotely controlling a three-dimensional shrimp and crab breeding facility according to claim 1, characterized in that: The S3 specifically includes: The adaptive feedback control algorithm includes two parts: feedforward control and feedback correction.

6. A method for remotely controlling a three-dimensional shrimp and crab breeding facility according to claim 5, characterized in that: The S3 specifically includes: The feedforward control adjusts the influence of the future environmental state index prediction value and the future environmental parameter prediction value on the preliminary control instruction of the equipment through the first weighting coefficient and the second weighting coefficient in the generation of the preliminary control instruction of the equipment; the feedback correction is achieved by calculating the error between the control instruction and the actual response of the equipment. When the error is extremely large, the correction value is also extremely large; when the error is extremely small, the correction value is also extremely small.

7. A method for remotely controlling a three-dimensional shrimp and crab breeding facility according to claim 1, characterized in that: The S3 specifically includes: The saturation function is introduced to perform saturation processing on the preliminary control instruction to obtain the final control instruction. The specific formula is: ， in, Indicates the device exist The final control instructions that need to be executed at all times; represents the saturation function; Indicates the device exist Preliminary control instructions that need to be executed at all times; Indicates the device Maximum control instructions; Indicates the device The minimum control instruction.

8. A remote control system for a three-dimensional shrimp and crab breeding facility, applied to a remote control method for a three-dimensional shrimp and crab breeding facility as claimed in claim 1, characterized in that: Includes the following sections: Environmental parameter acquisition module, future environmental parameter prediction module, environmental status prediction and evaluation module, equipment control instruction generation module, equipment control execution module; Environmental parameter collection module: collects environmental parameter data in real time and outputs the collected environmental parameter data to the future environmental parameter prediction module; Future environmental parameter prediction module: Based on the environmental parameter data of the environmental parameter acquisition module, the environmental parameter estimation algorithm based on time series data prediction is used to predict the future environmental parameter prediction value, and the future environmental parameter prediction value is output to the environmental state prediction and evaluation module and the equipment control instruction generation module; Environmental state prediction and evaluation module: Based on the future environmental parameter prediction value of the future environmental parameter prediction module, the environmental state prediction and evaluation algorithm is used to predict and evaluate to obtain the future environmental state index prediction value, and the future environmental state index prediction value is output to the equipment control instruction generation module; Equipment control instruction generation module: Based on the future environmental parameter prediction value of the future environmental parameter prediction module and the future environmental state index prediction value of the environmental state prediction and evaluation module, the module uses an adaptive feedback control algorithm to calculate and obtain a preliminary control instruction, uses a saturation function to perform saturation processing on the preliminary control instruction, obtains a final control instruction, and outputs the final control instruction to the equipment control execution module; Equipment control execution module: remotely controls the three-dimensional shrimp and crab breeding facilities according to the final control instructions generated by the equipment control instruction generation module.

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