A method and system for controlling moisture stability at the outlet of a feeder

Abstract

The application discloses a kind of feeding machine outlet moisture stability control method and system, it is related to feeding machine moisture control technical field, comprising: according to the required total water quantity of incoming material flow, incoming material moisture and outlet moisture set value, according to incoming material flow, feeding ratio and material liquid moisture determines material liquid moisture, according to the difference of required total water quantity and material liquid moisture, determines the theoretical water quantity of current period;According to the historical average correction of current processing material brand, after the correction of theoretical water quantity, the modified theoretical water quantity is obtained;According to the difference of outlet moisture set value before d period and outlet moisture actual value of current period, determine lag deviation value, to obtain the water quantity correction of current period, according to the water quantity correction of current period and modified theoretical water quantity, the actual water quantity is obtained.It offsets incoming material fluctuation and material liquid moisture influence, significantly overcomes control hysteresis, realizes the accurate, stable control of outlet moisture.

Description

Technical Field

[0001] This invention relates to the field of moisture control technology for feeders, and in particular to a method and system for controlling the stability of moisture at the outlet of a feeder. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] In the tobacco processing industry, controlling the moisture content at the outlet of the feeder is a crucial step in ensuring the quality of tobacco leaf processing. It affects the effectiveness of subsequent processes such as tobacco shredding and ultimately determines the consistency of the final tobacco product's quality. Currently, the commonly used method for moisture control in feeders is to detect the actual moisture content of the material at the outlet using an outlet moisture meter, and then use PID control to regulate the amount of water added, thereby achieving closed-loop control of the outlet moisture content.

[0004] However, existing control methods have many shortcomings in practical applications, making it difficult to meet the high-precision production requirements for outlet moisture stability. Specific problems include: First, the moisture content and flow rate of incoming materials are prone to fluctuations, which existing control methods cannot effectively address. These fluctuations are directly transmitted to the feeder outlet, causing the outlet moisture content to deviate from the set value. Second, the feeder liquid is not converted for moisture content, leading to differences in the amount of water introduced by different feeding ratios. This affects the precise control of the actual water addition, causing deviations in the PID control benchmark. Third, PID control itself has significant lag; the time required from the feeder head entering dynamic adjustment to reaching a stable moisture state is long, during which moisture overshoot and large fluctuations are likely to occur. Fourth, different grades of tobacco leaves vary, and the hot air temperature during production also changes. Both of these factors affect the moisture adsorption and evaporation processes, and existing control methods do not consider these variables, further reducing the stability and accuracy of outlet moisture control.

[0005] The aforementioned problems lead to significant fluctuations in moisture content at the outlet of the feeder during tobacco processing, making it difficult to achieve standardized and high-precision control and hindering the consistent improvement of tobacco product quality. Summary of the Invention

[0006] To address the aforementioned issues, this invention proposes a method and system for controlling the stability of moisture content at the outlet of a feeder. By employing feedforward, feedback supplementation, and empirical value correction, the method effectively offsets the effects of incoming material fluctuations and material moisture content, improves the accuracy of the control benchmark, significantly overcomes control lag, shortens steady-state time, and ultimately promotes the upgrade of production control from automation to intelligence, achieving precise and stable control of outlet moisture content.

[0007] To achieve the above objectives, the present invention adopts the following technical solution: In a first aspect, the present invention provides a method for controlling the stability of moisture content at the outlet of a feeder, comprising: The required total water volume is determined based on the set values ​​of incoming material flow rate, incoming material moisture content, and outlet moisture content. The water content carried in by the material liquid is determined based on the incoming material flow rate, feeding ratio, and material liquid moisture content. The theoretical water volume to be added in the current cycle is determined based on the difference between the required total water volume and the water content carried in the material liquid. Based on the historical average correction amount of the current processed material brand, the theoretical water addition amount is corrected to obtain the corrected theoretical water addition amount; Based on the export moisture setting value from d cycles ago and the current cycle The difference between the actual value of the outlet moisture content and the actual value of the water content is used to determine the lag deviation value, thereby obtaining the water volume correction amount for the current period. The actual water volume is obtained based on the water volume correction amount for the current period and the correction theoretical water volume.

[0008] As an alternative implementation method, the total required water volume for: ; ; in, Incoming material flow rate; Moisture content of the incoming material; Set a value for export moisture content; To generate traffic for the target.

[0009] As an alternative implementation method, the water carried in by the feed liquid is the product of the incoming flow rate, the feeding ratio, and the water content of the feed liquid.

[0010] As an alternative implementation method, the actual water addition volume for the current cycle is: ; in, To correct the theoretical water addition, the corrected theoretical water addition is the sum of the historical average correction and the theoretical water addition. The actual value of outlet moisture at time t The filtering function; For PID control calculations, The setpoint for export moisture content d cycles ago. Total delay.

[0011] As an alternative implementation method, d is the total delay. The corresponding number of cycles; total delay The total time to respond to adjustment actions is the sum of transmission delay and filtering delay.

[0012] As an alternative implementation, the historical average correction amount for the processed material brand is updated as follows: ; in, This is the updated average correction amount; This is the average correction amount before the update; This is the average correction amount calculated from the data of this production batch; This is the smoothing coefficient.

[0013] Secondly, the present invention provides a control system for the stability of moisture content at the outlet of a feeder, comprising: The feedforward module is configured to determine the required total water volume based on the feed flow rate, feed moisture content and outlet moisture content setpoints, determine the water content carried in by the feed liquid based on the feed flow rate, feeding ratio and feed liquid moisture content, and determine the theoretical water volume to be added in the current cycle based on the difference between the required total water volume and the water content carried in by the feed liquid. The experience correction module is configured to correct the theoretical water addition amount based on the historical average correction amount of the current processed material brand, and then obtain the corrected theoretical water addition amount. The feedback module is configured to compare the outlet moisture setpoint from d cycles ago with the current cycle. The difference between the actual value of the outlet moisture content and the actual value of the water content is used to determine the lag deviation value, thereby obtaining the water volume correction amount for the current period. The actual water volume is obtained based on the water volume correction amount for the current period and the correction theoretical water volume.

[0014] Thirdly, the present invention provides an electronic device including a memory and a processor, and computer instructions stored in the memory and running on the processor, wherein the computer instructions, when executed by the processor, perform the method described in the first aspect.

[0015] Fourthly, the present invention provides a computer-readable storage medium for storing computer instructions, which, when executed by a processor, perform the method described in the first aspect.

[0016] Fifthly, the present invention provides a computer program product, including a computer program that, when executed by a processor, implements the method described in the first aspect.

[0017] Compared with the prior art, the beneficial effects of the present invention are as follows: Effectively offsets the impact of incoming material fluctuations and liquid moisture content, and improves the accuracy of control benchmarks: The method of this invention accurately calculates the total required water volume and the moisture content brought in by the liquid, and clarifies the theoretical water addition volume for the current cycle. It incorporates key influencing factors such as incoming material flow rate, incoming material moisture content, feeding ratio, and liquid moisture content into the calculation scope, solving the problems of existing technologies that do not consider liquid moisture conversion and cannot cope with incoming material fluctuations. This makes the calculation benchmark for water addition more accurate and reduces outlet moisture fluctuations from the source.

[0018] Significantly overcomes control lag and shortens steady-state time: This invention addresses the core issues of lag in outlet moisture meter detection and lag in PID control. The correction process is designed as a function related to the time series. By calling the difference between the outlet moisture setpoint from d cycles ago and the current actual value, the lag deviation is determined, effectively compensating for the lag effect. At the same time, a historical average correction amount based on brand classification and a learning mechanism are introduced to significantly improve the initial control accuracy, reduce reliance on lag feedback, and significantly shorten the time for the feeder to reach moisture steady state from dynamic adjustment. This solves the pain points of large moisture fluctuations and long steady-state time caused by the lag in existing PID control.

[0019] Adapting to the influence of multiple variables and improving the versatility and stability of control: The method of this invention learns from the experience value of brand classification, fully considers the differences in tobacco leaf grades of different brands, and can indirectly adapt to the influence of environmental variables such as hot air temperature on moisture control, making the control logic more universal and able to meet the needs of different production conditions, further improving the stability of outlet moisture control, and ensuring the consistency of tobacco material moisture under different brands and different operating conditions.

[0020] Promoting the upgrade of production control from automation to intelligence: The method of this invention breaks through the traditional automation control mode that relies solely on real-time PID adjustment. By introducing historical data learning, time series correction, and multi-variable collaborative calculation, it achieves intelligent and precise control of water addition, reduces the need for manual intervention, improves the level of intelligence in production control, provides technical support for the standardization and high-precision management of tobacco processing, and helps to improve overall production efficiency and product quality consistency.

[0021] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0023] Figure 1 This is a flowchart of the method for controlling the moisture stability at the outlet of a feeder provided in Embodiment 1 of the present invention; Figure 2 This is a timing diagram for delay control provided in Embodiment 1 of the present invention; Figure 3 The flowchart of the feedback experience value correction process provided in Embodiment 1 of the present invention is shown. Detailed Implementation

[0024] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0025] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, 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 pertains.

[0026] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, unless the context clearly indicates otherwise, the singular form is intended to include the plural form as well. Furthermore, it should be understood that the terms “comprising” and “including”, and any variations thereof, are intended to cover non-exclusive inclusion, for example, a process, method, system, product, or apparatus that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0027] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0028] Example 1 This embodiment provides a method for controlling the stability of moisture content at the outlet of a feeder, such as... Figure 1 As shown, it includes: The required total water volume is determined based on the set values ​​of incoming material flow rate, incoming material moisture content, and outlet moisture content. The water content carried in by the material liquid is determined based on the incoming material flow rate, feeding ratio, and material liquid moisture content. The theoretical water volume to be added in the current cycle is determined based on the difference between the required total water volume and the water content carried in the material liquid. Based on the historical average correction amount of the current processed material brand, the theoretical water addition amount is corrected to obtain the corrected theoretical water addition amount; Based on the export moisture setting value from d cycles ago and the current cycle The difference between the actual value of the outlet moisture content and the actual value of the water content is used to determine the lag deviation value, thereby obtaining the water volume correction amount for the current period. The actual water volume is obtained based on the water volume correction amount for the current period and the correction theoretical water volume.

[0029] In the above scheme, based on the water addition principle of the tobacco processing feeder, the required water addition amount can be determined by knowing the incoming material moisture content, incoming material flow rate, outlet moisture setpoint, and feeding ratio. The water addition amount is corrected by the measurement value of the outlet moisture meter. To overcome the lag problem of the outlet moisture meter, the correction process is transformed from real-time calculation to a time-series related function, and a Smith predictor is used to solve the control lag problem. Finally, by introducing experience values ​​and learning mechanisms based on brand classification, the initial accuracy of control is greatly improved, the dependence on lag feedback is reduced, the time to reach a steady state is shortened, and the production process control is upgraded from automation to intelligence.

[0030] The entire scheme is divided into three parts: feedforward control, feedback supplementation, and feedback experience value correction. The method of this embodiment will be described in detail below based on these three parts.

[0031] I. Theoretical water addition and feedback correction based on the outlet moisture meter.

[0032] 1. The calculation process for the theoretical water addition includes: (1) Assuming that only the moisture and liquid content increase or decrease during the production process, and the total dry matter remains constant, the dry matter flow rate is first calculated based on the incoming material flow rate and the incoming material moisture content. : .

[0033] Then, the target output flow rate is calculated based on the dry matter flow rate and the outlet moisture setpoint. : Target output flow .

[0034] in, Incoming material flow rate (kg / h); Moisture content of the incoming material; Set a value for export moisture content.

[0035] (2) Calculate the total water required based on the target output flow rate, the outlet moisture setting, the incoming flow rate, and the incoming moisture. This is the moisture quality balance that the entire system needs to achieve.

[0036] .

[0037] (3) Calculate the feeding flow rate based on the incoming material flow rate and the feeding ratio, and then calculate the water carried in by the material liquid based on the feeding flow rate and the water content of the liquid. ; ; ; in, This refers to the proportion of ingredients added. This refers to the moisture content of the liquid (i.e., the water content of the liquid itself). This refers to the feed flow rate.

[0038] (4) Based on the required total water volume Water carried in by the liquid The difference determines the theoretical water addition. .

[0039] Therefore, the theoretical water addition for: .

[0040] Simplified to: .

[0041] 2. The feedback correction process based on the outlet moisture meter includes: In actual production, due to factors such as fluctuations in incoming material moisture content, measurement errors, and equipment accuracy, the actual outlet moisture value measured by the outlet moisture meter may vary. With set value There are discrepancies. Therefore, real-time monitoring and correction are necessary.

[0042] In this embodiment, the PID control principle is used for correction: Actual value of export moisture With set value deviation value .

[0043] The control system (usually a PLC or DCS) calculates the water volume correction amount using a PID algorithm based on the deviation e. .

[0044] if , indicating that it is slightly dry, then If the value is positive, increase the amount of water added; if This indicates that it is slightly damp. If the value is negative, reduce the amount of water added.

[0045] Final actual water flow rate .

[0046] Therefore, by combining feedforward control (theoretical calculation, fast response) and feedback control (PID correction based on moisture meter, high accuracy), accurate and stable control of outlet moisture can be achieved.

[0047] Second, address the lag issue in moisture control correction.

[0048] (1) Current period The historical adjustment actions corresponding to the read moisture values.

[0049] In the current cycle Filtered value of outlet moisture read (i.e., the current period) The moisture content at the outlet of the moisture meter is the filtered measurement value, not the actual water volume added in the current cycle. The impact is not due to the actual water volume added d cycles prior. The impact.

[0050] Assuming the setpoint remains stable during this period, then the setpoint for outlet moisture content is based on the setpoint from d cycles ago. Compared with the current cycle Filtered value of outlet moisture The difference determines the lag deviation value. .

[0051] If the set value remains unchanged, If the settings change, the historical settings must be used.

[0052] In this embodiment, d is the total delay. The corresponding number of control cycles. For example, if = 30 seconds, control cycle = 5 seconds, then d = 6.

[0053] Total delay The total time for responding to a regulatory action is approximately: .

[0054] Among them, transmission delay The time required from the occurrence of the adjustment action (changing the water volume) to the arrival of the affected material in the moisture meter. Estimated using the distance L between the devices and the belt speed v. .

[0055] Sampling and filtering period T / filtering delay Moisture analyzers do not output signals continuously; instead, they sample at fixed intervals (e.g., once per second). To prevent fluctuations (noise) in individual samples from causing drastic system fluctuations, the control system filters multiple consecutive samples (e.g., moving average filtering, low-pass filtering). Filtering introduces a certain computational delay. For example, a 10-second moving average window introduces approximately a 5-second delay. The time constant of a low-pass filter also represents a delay.

[0056] (2) In this embodiment, we take the control cycle k as an example and assume that a calculation and output are performed once in each control cycle.

[0057] The PID controller is based on the hysteresis deviation value Calculate the water volume correction for the current period. : ; in, From the start time to , , , These are PID control parameters.

[0058] (3) Finally, the actual amount of water added in the current cycle This is the theoretical water addition for the current cycle. Water volume correction for the current cycle The sum, that is: .

[0059] The key point of the above process is: The correction is applied to the state after d cycles. The controller calculates the correction amount at the current time k to influence the moisture reading at the future time (k+d). The greater the lag (the larger d), the more the PID control parameters (…). , , The more conservative the setting (i.e., the proportional gain) Reduce integration time (Increase), otherwise the system will oscillate violently, the process is as follows Figure 2 As shown.

[0060] Combining the above processes, the formula for calculating the actual amount of water added is: ; Where t represents time; This represents the filtering function applied to the raw measurements from the moisture meter. This represents the calculation of the deviation value within the parentheses by the PID controller.

[0061] In practical PLC / DCS programming, this is usually achieved by accurately measuring or estimating the material's travel time from the water addition point to the moisture meter. Establish a FIFO (First-In, First-Out) queue in the control program to store historical water addition settings. Compare the current moisture meter reading with... The setpoint is compared to the time-previous value to obtain an effective deviation signal. This deviation signal is then used for PID calculations and output. This method of handling time delays is considered a simplified application of the Smith predictor and is a standard method for controlling processes with large time delays.

[0062] III. Feedback-based experience value correction: a key step from automation to intelligence. By introducing experience values ​​and learning mechanisms based on brand classification, the initial accuracy of control is greatly improved, the reliance on delayed feedback is reduced, and the time to reach a stable state is shortened.

[0063] like Figure 3 As shown, the specific steps include the following.

[0064] 1. Application of empirical values ​​as feedforward preset correction values.

[0065] (1) Identify the brand of the current processed material Retrieve the historical average correction value corresponding to the brand from the experience value database. It is used as the initial value of the PID controller output, or directly as the feedforward compensation value.

[0066] Therefore, the revised theoretical water addition is: ; in, The initial water addition setting value is based on a combination of theoretical water addition and the brand's historical experience. Retrieved from an experience database, targeting the current brand The average correction amount can be positive (meaning that the brand usually needs to add more water than theoretically calculated) or negative (meaning that usually less water needs to be added).

[0067] (2) Subsequently, the outlet moisture meter continues to perform feedback correction to obtain the actual water addition for the current cycle. : ; in, The initial value is no longer set to zero, but rather to a more optimal starting point. Start fine-tuning for faster response and less overshoot.

[0068] (3) In summary, .

[0069] 2. Experience points are learned and updated in the background.

[0070] The learning process occurs after a batch of production is completed, using data from the stable production phase of that batch to update the brand's experience values.

[0071] Taking the exponential moving average method as an example: ; in, The updated brand experience points will be stored in the database for future use. The previous experience value (i.e., the value called at the start of this production run); This is a representative correction amount calculated from the data of this production batch; The smoothing coefficient is a constant between 0 and 1, representing the degree of trust in the new data. The closer it is to 1, the faster the learning speed, but it is more susceptible to noise from a single batch. The closer it is to 0, the slower the learning speed and the more stable the experience points. For example, =0.2 is a common choice, meaning that new batches of data contribute 20% of the weight, while historical experience contributes 80% of the weight.

[0072] in, This represents the statistical value of PID correction during the stable production period of this batch. There are multiple calculation methods: (1) Average value method (most commonly used): The average value is taken over time t within the stable interval.

[0073] (2) Median method (better resistance to interference): The median is taken over the stable interval for time t.

[0074] (3) Steady-state value method: At the end of the batch The final value (assuming the system is fully stable).

[0075] Combining the above three parts, feedforward control is as follows: .

[0076] The feedback was supplemented as follows: .

[0077] The learning update is as follows: .

[0078] Therefore, in response to the problems of large fluctuations in outlet moisture content, control lag, and insufficient precision in existing technologies, this paper proposes to achieve precise and stable control of outlet moisture content through scientific control logic and intelligent design, while adapting to the characteristics of different brands, and ultimately achieving a higher level of uniformity and stability control.

[0079] Example 2 This embodiment provides a control system for the stability of moisture content at the outlet of a feeder, including: The feedforward module is configured to determine the required total water volume based on the feed flow rate, feed moisture content and outlet moisture content setpoints, determine the water content carried in by the feed liquid based on the feed flow rate, feeding ratio and feed liquid moisture content, and determine the theoretical water volume to be added in the current cycle based on the difference between the required total water volume and the water content carried in by the feed liquid. The experience correction module is configured to correct the theoretical water addition amount based on the historical average correction amount of the current processed material brand, and then obtain the corrected theoretical water addition amount. The feedback module is configured to compare the outlet moisture setpoint from d cycles ago with the current cycle. The difference between the actual value of the outlet moisture content and the actual value of the water content is used to determine the lag deviation value, thereby obtaining the water volume correction amount for the current period. The actual water volume is obtained based on the water volume correction amount for the current period and the correction theoretical water volume.

[0080] It should be noted that the above modules correspond to the steps described in Embodiment 1, and the examples and application scenarios implemented by the above modules and the corresponding steps are the same, but are not limited to the content disclosed in Embodiment 1. It should also be noted that the above modules, as part of the system, can be executed in a computer system such as a set of computer-executable instructions.

[0081] In further embodiments, the following is also provided: An electronic device includes a memory and a processor, as well as computer instructions stored in the memory and running on the processor, wherein the computer instructions, when executed by the processor, perform the method described in Embodiment 1. For brevity, further details are omitted here.

[0082] It should be understood that in this embodiment, the processor can be a central processing unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor, etc.

[0083] Memory may include read-only memory and random access memory, and provides instructions and data to the processor. A portion of memory may also include non-volatile random access memory. For example, memory may also store information about the device type.

[0084] A computer-readable storage medium for storing computer instructions, which, when executed by a processor, perform the method described in Embodiment 1.

[0085] The method in Example 1 can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor. The software modules can reside in readily available storage media in the field, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory, and the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method. To avoid repetition, a detailed description is not provided here.

[0086] A computer program product includes a computer program that, when executed by a processor, implements the method described in Embodiment 1.

[0087] The present invention also provides at least one computer program product tangibly stored on a non-transitory computer-readable storage medium. The computer program product includes computer-executable instructions, such as instructions included in program modules, which execute in a device on a target real or virtual processor to perform the processes / methods described above. Typically, program modules include routines, programs, libraries, objects, classes, components, data structures, etc., that perform specific tasks or implement specific abstract data types. In various embodiments, the functionality of program modules can be combined or divided among program modules as needed. The machine-executable instructions for the program modules can execute within a local or distributed device. In a distributed device, the program modules can reside in both local and remote storage media.

[0088] The computer program code used to implement the methods of the present invention may be written in one or more programming languages. This computer program code may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the computer or other programmable data processing device, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a computer, partially on a computer, as a stand-alone software package, partially on a computer and partially on a remote computer, or entirely on a remote computer or server.

[0089] In the context of this invention, computer program code or related data may be carried by any suitable carrier to enable a device, apparatus, or processor to perform the various processes and operations described above. Examples of carriers include signals, computer-readable media, and the like. Examples of signals may include electrical, optical, radio, sound, or other forms of propagation signals, such as carrier waves, infrared signals, etc.

[0090] Those skilled in the art will recognize that the units and algorithm steps described in connection with the various examples of this embodiment can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this invention.

[0091] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A method for controlling the stability of moisture content at the outlet of a feeder, characterized in that, include: The required total water volume is determined based on the set values ​​of incoming material flow rate, incoming material moisture content, and outlet moisture content. The water content carried in by the material liquid is determined based on the incoming material flow rate, feeding ratio, and material liquid moisture content. The theoretical water volume to be added in the current cycle is determined based on the difference between the required total water volume and the water content carried in the material liquid. Based on the historical average correction amount of the current processed material brand, the theoretical water addition amount is corrected to obtain the corrected theoretical water addition amount; Based on the export moisture setting value from d cycles ago and the current cycle The difference between the actual value of the outlet moisture content and the actual value of the water content is used to determine the lag deviation value, thereby obtaining the water volume correction amount for the current period. The actual water volume is obtained based on the water volume correction amount for the current period and the correction theoretical water volume.

2. The method for controlling the stability of moisture content at the outlet of a feeder as described in claim 1, characterized in that, Total water required for: ； ； in, Incoming material flow rate; Moisture content of the incoming material; Set a value for export moisture content; To generate traffic for the target.

3. The method for controlling the stability of moisture content at the outlet of a feeder as described in claim 1, characterized in that, The water content introduced by the feed liquid is the product of the incoming flow rate, the feeding ratio, and the water content of the feed liquid.

4. The method for controlling the stability of moisture content at the outlet of a feeder as described in claim 1, characterized in that, The actual water volume added in the current cycle is: ； in, To correct the theoretical water addition, the corrected theoretical water addition is the sum of the historical average correction and the theoretical water addition. The actual value of outlet moisture at time t The filtering function; For PID control calculations, The setpoint for export moisture content d cycles ago. Total delay.

5. The method for controlling the stability of moisture content at the outlet of a feeder as described in claim 4, characterized in that, d is the total delay The corresponding number of cycles; Total delay The total time to respond to adjustment actions is the sum of transmission delay and filtering delay.

6. The method for controlling the stability of moisture content at the outlet of a feeder as described in claim 1, characterized in that, The historical average correction for processed material brands has been updated as follows: ； in, This is the updated average correction amount; This is the average correction amount before the update; This is the average correction amount calculated from the data of this production batch; This is the smoothing coefficient.

7. A control system for the stability of moisture content at the outlet of a feeder, characterized in that, include: The feedforward module is configured to determine the required total water volume based on the feed flow rate, feed moisture content and outlet moisture content setpoints, determine the water content carried in by the feed liquid based on the feed flow rate, feeding ratio and feed liquid moisture content, and determine the theoretical water volume to be added in the current cycle based on the difference between the required total water volume and the water content carried in by the feed liquid. The experience correction module is configured to correct the theoretical water addition amount based on the historical average correction amount of the current processed material brand, and then obtain the corrected theoretical water addition amount. The feedback module is configured to compare the outlet moisture setpoint from d cycles ago with the current cycle. The difference between the actual value of the outlet moisture content and the actual value of the water content is used to determine the lag deviation value, thereby obtaining the water volume correction amount for the current period. The actual water volume is obtained based on the water volume correction amount for the current period and the correction theoretical water volume.

8. An electronic device, characterized in that, It includes a memory and a processor, as well as computer instructions stored in the memory and running on the processor, which, when executed by the processor, perform the method according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, Used to store computer instructions, which, when executed by a processor, perform the method described in any one of claims 1-6.

10. A computer program product, characterized in that, Includes a computer program, which, when executed by a processor, implements the method described in any one of claims 1-6.

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