Method, device, equipment and medium for controlling outlet parameters of a tobacco primary processing machine

Abstract

The application discloses a kind of control method, device, equipment and medium to the control of tobacco making feeder outlet parameter.The method comprises: obtaining the production process data corresponding to tobacco making feeder;Based on the prediction control model determined in advance, the production process data is processed, and the control data of adjustable parameter is obtained;Based on control data, the parameter adjustment equipment corresponding to the adjustable parameter is controlled, so that in the process of controlling parameter adjustment equipment, the actual controlled information of controlled outlet parameter reaches preset control target.Solve the problem that the parameter control precision is low and the control effect is poor in the prior art based on personal experience to configure the feeding outlet parameter, improve the control precision of the tobacco making feeder outlet parameter, so that the control effect can reach the preset control target, to meet the demand of tobacco making, to ensure the effect of tobacco quality.

Description

TECHNICAL FIELD

[0001] The present application relates to the tobacco processing technical field, and particularly relates to a control method, device, equipment and medium for an outlet parameter of a cut tobacco adding machine. BACKGROUND

[0002] The outlet moisture and the outlet temperature of the cut tobacco adding machine are very important process index parameters on a cut tobacco line, and the quality of the cut tobacco is directly affected by the two parameters. Therefore, in the cut tobacco production process, the two outlet parameters need to be regulated and controlled to meet the cut tobacco demand.

[0003] In the prior art, the regulation and control of the outlet moisture and the outlet temperature is usually performed by adjusting parameters such as the opening degree of the moisture exhaust door and the hot air speed. The setting of these parameters is mainly determined by the operator according to personal experience. This method is easily affected by subjective factors and changes in environmental temperature and humidity, resulting in a large deviation between the control result of the outlet moisture and the outlet temperature and the actual cut tobacco demand, thereby affecting the quality of the cut tobacco. SUMMARY

[0004] The present application provides a control method, device, equipment and medium for an outlet parameter of a cut tobacco adding machine to improve the control precision of the outlet parameter of the cut tobacco adding machine, so that the control effect can reach a preset control target, thereby meeting the cut tobacco demand and ensuring the quality of the cut tobacco.

[0005] According to an aspect of the present application, a control method for an outlet parameter of a cut tobacco adding machine is provided, which comprises the following steps:

[0006] obtaining production process data corresponding to the cut tobacco adding machine; wherein the production process data comprises data of a plurality of control parameters, the control parameters further comprise unadjustable control parameters, adjustable control parameters and controlled outlet parameters; the controlled outlet parameters comprise the outlet moisture and the outlet temperature of the cut tobacco adding machine;

[0007] processing the production process data based on a predetermined prediction control model to obtain control data of the adjustable control parameters; wherein the prediction control model is constructed based on a model prediction control algorithm;

[0008] controlling a parameter adjustment device corresponding to the adjustable control parameters based on the control data, so that the actual controlled information of the controlled outlet parameters reaches a preset control target in the process of controlling the parameter adjustment device.

[0009] According to another aspect of the present application, a control device for an outlet parameter of a cut tobacco adding machine is provided, which comprises:

[0010] The data acquisition module is configured to acquire production process data corresponding to the cut tobacco feeding machine, wherein the production process data comprises data of a plurality of control parameters, the control parameters further comprise unadjustable parameters, adjustable parameters and controlled outlet parameters, and the controlled outlet parameters comprise feeding outlet moisture and outlet temperature.

[0011] The model processing module is configured to process the production process data based on a predetermined predictive control model to obtain control data of the adjustable parameters, wherein the predictive control model is constructed based on a model predictive control algorithm.

[0012] The control module is configured to control a parameter adjustment device corresponding to the adjustable parameters based on the control data, so that actual controlled information of the controlled outlet parameters reaches a preset control target in the process of controlling the parameter adjustment device.

[0013] According to another aspect of the present application, an electronic device is provided, which comprises:

[0014] at least one processor; and

[0015] a memory connected to the at least one processor in communication; wherein,

[0016] the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the control method of the outlet parameters of the cut tobacco feeding machine according to any one of the embodiments of the present application.

[0017] According to another aspect of the present application, a computer readable storage medium is provided, which stores computer instructions for enabling a processor to execute the control method of the outlet parameters of the cut tobacco feeding machine according to any one of the embodiments of the present application when the processor executes the computer instructions.

[0018] The technical scheme of the embodiment of the present application comprises the following steps: obtaining production process data corresponding to the tobacco cutting and feeding machine; wherein the production process data comprises data of a plurality of control parameters, the control parameters further comprise unadjustable parameters, adjustable parameters and controlled outlet parameters; the controlled outlet parameters comprise feeding outlet moisture and outlet temperature; processing the production process data based on a pre-determined prediction control model to obtain control data of the adjustable parameters; and controlling the parameter adjustment equipment corresponding to the adjustable parameters based on the control data, so that the actual controlled information of the controlled outlet parameters reaches the preset control target in the process of controlling the parameter adjustment equipment. The problems of low parameter control precision and poor control effect caused by the configuration of the feeding outlet parameters based on personal experience in the prior art are solved. The prediction control model constructed based on the model prediction control algorithm is used to analyze the correlation between the control parameters to obtain the control data of the adjustable parameters, so that the parameter adjustment equipment corresponding to the adjustable parameters is controlled through the control data, the actual controlled information of the controlled outlet parameters reaches the preset control target in the process of controlling the parameter adjustment equipment, the control precision of the tobacco cutting and feeding outlet parameters is improved, and the control effect reaches the preset control target, thereby meeting the tobacco cutting demand and ensuring the quality of the tobacco.

[0019] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present application, nor is it used to limit the scope of the present application. Other features of the present application will become apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0021] Figure 1 is a flow chart of a control method for the outlet parameters of the tobacco cutting and feeding machine according to the first embodiment of the present application;

[0022] Figure 2 is a structural schematic diagram of a control device for the outlet parameters of the tobacco cutting and feeding machine according to the second embodiment of the present application;

[0023] Figure 3 is a structural schematic diagram of an electronic device for implementing the control method for the outlet parameters of the tobacco cutting and feeding machine according to the present application. DETAILED DESCRIPTION

[0024] In the following, the technical solutions in the embodiments of the present application will be described clearly and completely with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all the other embodiments obtained by a person of ordinary skill in the art without creative work should belong to the protection scope of the present application.

[0025] It should be noted that the terms "first", "second", and the like in the specification and claims of the present application and the above-described drawings are used to distinguish similar objects, and do not necessarily indicate a specific order or a chronological sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device that includes a series of steps or units does not necessarily have to include only those steps or units clearly listed, but can include other steps or units that are not clearly listed or inherent to the process, method, product or device.

[0026] Embodiment one

[0027] Figure 1 is a flow chart of a control method for an outlet parameter of a tobacco additive machine according to the first embodiment of the present application. The present embodiment can be applied to the case of controlling the moisture and temperature of the outlet of the additive machine in the tobacco production process. The method can be executed by a control device for the outlet parameter of the tobacco additive machine. The control device for the outlet parameter of the tobacco additive machine can be realized in the form of hardware and / or software, and can be configured in a computing device. As shown in Figure 1 the method comprises:

[0028] S110, obtaining production process data corresponding to the tobacco additive machine; the production process data includes data of a plurality of control parameters, the control parameters including unadjustable control parameters, adjustable control parameters and controlled outlet parameters.

[0029] In actual production process, the moisture and temperature of the feeding outlet are important parameters affecting the quality of the production process. The parameters cannot be directly controlled and are affected by other parameters. The moisture and temperature of the feeding outlet are controlled parameters. For example, the outlet temperature is affected by the hot air temperature of the feeding cylinder, the moisture removal opening, the fresh air opening, the feeding inlet temperature, the compensation steam and other parameters. The outlet moisture is affected by the feeding ratio, the moisture removal opening, the feeding inlet moisture, the compensation steam and other parameters. Considering that the moisture removal opening, the fresh air opening and the feeding ratio are fixed index values, they cannot be adjusted when participating in the control of the controlled outlet parameters. The feeding inlet moisture and temperature are controlled by the previous process (moisture conditioning) and are uncontrollable parameters. Therefore, the moisture removal opening, the fresh air opening, the feeding ratio, the feeding inlet moisture and temperature can be regarded as uncontrolled parameters. Of course, the uncontrolled parameters are not limited to these. The compensation steam is a controllable parameter, which can be adjusted to passively control the controlled parameter information.

[0030] In the embodiment, the data of each control parameter at the current time can be obtained as production process data. Alternatively, the control input of the control parameter at the current time and the historical data of the control parameter in the production process before the current time can be obtained as production process data, so as to predict the control data of the controllable parameter in the control parameter at the next time or the next period through the production process data in a period. For example, the data acquisition period can be set to obtain the production process data. For example, the data acquisition period is set to 10 seconds, and the production process data within 10 seconds including the current time and before the current time is obtained each time.

[0031] S120, processing the production process data based on a predetermined prediction control model to obtain control data of the controllable parameter.

[0032] The prediction control model can be constructed based on the model prediction control (MPC) algorithm. In the process of controlling the feeding outlet parameters, the model parameters in the prediction control model can be updated based on the actual controlled information of the controlled outlet parameters to dynamically optimize the parameter control strategy and make the control effect optimal. The controllable parameter refers to the compensation steam, including but not limited to process compensation steam flow and hot air compensation steam flow.

[0033] In the embodiment, the production process data can be taken as the input of the prediction control model, and the control data of the controllable parameters can be determined by solving a finite time optimal control problem. Optionally, the control data can include the control period, control step, control speed, etc. of the controllable parameters, for example, the compensation steam flow is increased by 0.1 kg per second, and the steam flow rate is controlled in the range of 5-50 m / s.

[0034] It should be noted that the control parameters in the production process data affect each other, and the input and output of the prediction control model also affect each other. The control data of the controllable parameters in the production process can be obtained by analyzing the correlation between the control parameters. In the embodiment, the production process data is processed based on the predetermined prediction control model to obtain the control data of the controllable parameters, including: performing correlation analysis on the data of multiple control parameters based on the prediction control model to determine the control data of the process compensation steam flow and the hot air compensation steam flow.

[0035] Specifically, after the production process data is input into the prediction control model, the prediction control model can perform correlation analysis on the data of the control parameters, and adjust the control information of the control parameters in combination with the control target of the control parameters to obtain the control data of the process compensation steam flow and the control data of the hot air compensation steam flow. For example, if the outlet moisture exceeds the preset range or the fluctuation error is large, the control value of the process compensation steam flow is adjusted.

[0036] On the basis of the above technical solutions, the prediction control model can also be constructed in advance. The construction method of the prediction control model can be: obtaining historical production process information corresponding to the tobacco primary feeding machine; processing the historical production process information to obtain to-be-used production process information; performing step analysis on the to-be-used production process information to obtain the prediction control model.

[0037] The historical production process information includes parameter information of multiple control parameters.

[0038] In the embodiment, the production process data of the cut tobacco feeding machine in the historical production stage can be acquired as the historical production process information. Considering that the historical production process information can have some dirty data, which is not conducive to data processing, the historical production process information can be cleaned to obtain the to-be-used production process information. For example, the useless information in the historical production process information is filtered out, and the error values and null values are replaced to improve the data quality. Considering that the to-be-used production process information includes data with time sequence attributes, the parameter data of one stage can affect the parameter data of the next stage. Therefore, the step test can be used to analyze the step relationship between the control parameters in the to-be-used production process information, and the prediction control model is constructed through the step relationship. For example, the transfer function can be used to analyze the law of change of the control parameters over time. For example, the parameter data of the unadjustable parameters, the adjustable parameters and the controlled outlet parameters in one stage are taken as the input of the prediction control model, and the parameter data of the next stage is taken as the output response of the prediction control model. The two sequences are connected through the transfer factor to establish the transfer function model, that is, the prediction control model. Alternatively, the to-be-used production process information is modeled by using the generation model to generate the prediction control model. For example, the distribution of the control parameters in the to-be-used production process information is analyzed from the statistical point of view, the control parameters are sampled according to the probability density function, the conditional probability distribution between the control parameters is established (the conditional probability distribution can be formed by the generation model according to the Bayes theorem), and the mathematical model constructed can be used as the prediction control model.

[0039] For example, the historical data in the past production process is collected for preliminary analysis, the historical data is cleaned to filter out useless data, the historical data after cleaning is analyzed by step test, the generation model or the transfer function model is used to analyze the correlation between the control parameters, and the prediction control model is generated. The prediction control model is a multivariate dynamic model, which can be used to determine the actual response of the production process. Each variable is a control parameter, and the actual response can be represented by a response curve. The response curve can reflect the time lag, dynamic time, mutual influence between multiple inputs / outputs, complex response process (such as inverse response, integral response) and the like, so that the prediction control model has the function of predicting the future production process dynamic behavior, gives the future control strategy, and enables the output change under different control strategies to be observed.

[0040] In order to improve the accuracy of model prediction and the precision of parameter control, after the prediction control model is constructed, the prediction control model can be tested offline to optimize the model parameters in the prediction control model and improve the control effect of the feeding outlet parameters.

[0041] In the embodiment, the method further includes: performing offline simulation test based on the predictive control model to obtain a simulation response result of the controlled outlet parameter in the control parameters; and correcting model parameters in the predictive control model based on a standard control target of the controlled outlet parameter and the simulation response result, to update the predictive control model.

[0042] In actual application, the predictive control model can be imported into simulation software to perform offline simulation test, and the controlled outlet parameter can be taken as a control target. After inputting control data of each control parameter, a simulation response result of the controlled outlet parameter can be obtained, which can represent a control effect on the control target. Further, the control effect can be analyzed according to the simulation response result of the control target, and the model parameters in the predictive control model can be corrected to make the output of the predictive control model reach the target control effect.

[0043] S130, controlling a parameter adjustment device corresponding to the controllable parameter based on the control data, so that the actual controlled information of the controlled outlet parameter reaches the preset control target in the process of controlling the parameter adjustment device.

[0044] The preset control target can be a condition for evaluating whether the actual controlled information of the controlled outlet parameter reaches a preset control effect, such as that the fluctuation frequency of the controlled outlet parameter is within a preset range, or the fluctuation tends to be stable, and the like.

[0045] Specifically, the parameter adjustment device corresponding to the controllable parameter can be controlled to work through the control data of the controllable parameter, the parameter information of the controllable parameter can be adjusted, and the actual controlled information of the controlled outlet parameter can be adjusted to reach the preset control target in the process of adjusting the controllable parameter.

[0046] Further, whether the model parameters in the predictive control model need to be updated can be determined through the actual controlled information of the controlled outlet parameter and the preset control target. When the preset control target is not reached, the model parameters in the predictive control model are dynamically updated, the control data of the control parameters is determined, and dynamic control is realized to make the target control effect be reached.

[0047] Optionally, if the actual controlled information of the controlled outlet parameter does not reach the preset control target, the control attribute of the control parameter can be determined according to the predictive control model based on the actual controlled information and the preset control target, the control data of the controllable parameter can be determined based on the control attribute, and the parameter adjustment device corresponding to the controllable parameter can be controlled based on the control data, so that the actual controlled information of the controlled outlet parameter reaches the preset control target.

[0048] The control attribute includes, but is not limited to, control weight, control priority, control period, control step length, control upper and lower limits, and the like.

[0049] In the embodiment, whether the actual controlled information of the controlled outlet parameter reaches the preset control target can be determined. If not, the control attribute of the control parameter can be adjusted according to the error between the actual controlled information and the preset control target, for example, the priority of the control target (the controlled outlet parameter) is adjusted according to the control effect; the control weight, the control priority, the control period, the control step and the control upper and lower limits of the controllable parameter are adjusted, and so on. Thus, the new control data of the controllable parameter is determined according to the control attribute through the predictive control model, the parameter adjusting device corresponding to the controllable parameter is controlled based on the control data, so that the actual controlled information of the controlled outlet parameter can reach the preset control target, the dynamic control of the parameter is realized, and the control effect is improved.

[0050] In the embodiment, the implementation manner that the actual controlled information of the controlled outlet parameter does not reach the preset control target can be that the fluctuation attribute of the actual controlled information of the controlled outlet parameter in the preset time length is determined; if the fluctuation attribute does not satisfy the preset fluctuation condition, it is determined that the actual controlled information does not reach the preset control target.

[0051] The fluctuation attribute includes, but is not limited to, the fluctuation range, the fluctuation amplitude, the range and the standard deviation.

[0052] For example, the production process data of the tobacco adding machine is collected in real time, and the abnormal data is removed, the normal data is automatically recorded into the predictive control model to control the outlet moisture and the outlet temperature in real time, the actual controlled information can be displayed through the dynamic curve, the curve is tracked and analyzed in real time, the fluctuation attribute of the actual controlled information in the preset time length is analyzed, if the fluctuation attribute does not satisfy the preset fluctuation condition, for example, the fluctuation range exceeds the preset range, the fluctuation amplitude exceeds the preset threshold, and so on, it is determined that the actual controlled information does not reach the preset control target. At this time, the control priority, the control weight, the control period, the control step and the control upper and lower limits of the controllable parameter can be adjusted according to the control effect, so as to obtain the appropriate control step, the constraint upper and lower limits, the appropriate prediction time and so on, and thus the control data of the controllable parameter is obtained.

[0053] In the embodiment, the target display panel can be set in advance, and the control data of the controllable parameter, the change curve of the actual controlled information of the controlled outlet parameter in the preset time length and the fluctuation attribute corresponding to the change curve are displayed correspondingly based on the target display panel.

[0054] Exemplarily, an AI control panel can be added on the device interface, control data of the adjustable parameter can be displayed, and a change curve of actual controlled information of the controlled outlet parameter within a preset time length and fluctuation attributes corresponding to the change curve can be correspondingly displayed, so that the control situation and control effect of the parameter are simply and directly displayed.

[0055] The technical scheme of the embodiment, by acquiring production process data corresponding to the tobacco cutting and feeding machine, wherein the production process data includes data of a plurality of control parameters, the control parameters further include unadjustable parameters, adjustable parameters and controlled outlet parameters, the controlled outlet parameters include feeding outlet moisture and outlet temperature, processing the production process data based on a pre-determined prediction control model to obtain control data of the adjustable parameters, and controlling the parameter adjustment device corresponding to the adjustable parameters based on the control data, so that the actual controlled information of the controlled outlet parameters reaches the preset control target in the process of controlling the parameter adjustment device, solves the problem of low parameter control precision and poor control effect caused by the configuration of the feeding outlet parameters based on personal experience in the prior art, realizes the analysis of the correlation between the control parameters by the prediction control model constructed based on the model prediction control algorithm, obtains the control data of the adjustable parameters, and controls the parameter adjustment device corresponding to the adjustable parameters through the control data, so that the actual controlled information of the controlled outlet parameters reaches the preset control target in the process of controlling the parameter adjustment device, not only improves the control precision of the tobacco cutting and feeding outlet parameters, but also makes the control effect reach the preset control target, thereby meeting the tobacco cutting demand and achieving the effect of ensuring the quality of tobacco.

[0056] Embodiment Two

[0057] Figure 2 is a structural schematic diagram of a device for controlling the outlet parameters of a tobacco cutting and feeding machine according to the embodiment two of the present application. As shown in Figure 2 the device includes a data acquisition module 210, a model processing module 220 and a control module 230.

[0058] The data acquisition module 210 is configured to acquire production process data corresponding to the cut tobacco feeding machine; the production process data includes data of a plurality of control parameters, the control parameters include unadjustable control parameters, adjustable control parameters, and controlled outlet parameters; the controlled outlet parameters include feeding outlet moisture and outlet temperature; the model processing module 220 is configured to process the production process data based on a predetermined predictive control model to obtain control data of the adjustable control parameters; the predictive control model is constructed based on a model predictive control algorithm; and the control module 230 is configured to control a parameter adjustment device corresponding to the adjustable control parameters based on the control data, so that actual controlled information of the controlled outlet parameters reaches a preset control target in the process of controlling the parameter adjustment device.

[0059] The technical scheme of the embodiment is configured to acquire production process data corresponding to the cut tobacco feeding machine; the production process data includes data of a plurality of control parameters, the control parameters include unadjustable control parameters, adjustable control parameters, and controlled outlet parameters; the controlled outlet parameters include feeding outlet moisture and outlet temperature; the production process data is processed based on a predetermined predictive control model to obtain control data of the adjustable control parameters; and a parameter adjustment device corresponding to the adjustable control parameters is controlled based on the control data, so that actual controlled information of the controlled outlet parameters reaches a preset control target in the process of controlling the parameter adjustment device. The technical scheme solves the problem that the feeding outlet parameters are configured based on personal experience in the prior art, which leads to low parameter control precision and poor control effect. The technical scheme realizes analysis of the correlation between the control parameters by using a predictive control model constructed based on a model predictive control algorithm, obtains control data of the adjustable control parameters, controls a parameter adjustment device corresponding to the adjustable control parameters by using the control data, and makes actual controlled information of the controlled outlet parameters reach a preset control target in the process of controlling the parameter adjustment device. The technical scheme not only improves the control precision of the cut tobacco feeding outlet parameters, but also enables the control effect to reach the preset control target, thereby meeting the cut tobacco demand and achieving the effect of ensuring the quality of cut tobacco.

[0060] Based on the above device, optionally, the adjustable control parameters include process compensation steam flow and hot air compensation steam flow; the model processing module 220 is configured to perform correlation analysis on the data of the plurality of control parameters based on the predictive control model to determine control data of the process compensation steam flow and the hot air compensation steam flow.

[0061] On the basis of the above device, optionally, the device further comprises a feedback module, the feedback module is used for if the actual controlled information of the controlled outlet parameter does not reach the preset control target, based on the actual controlled information and the preset control target, according to the prediction control model, the control attribute of the control parameter is determined, and the control data of the controllable parameter is determined based on the control attribute, so as to control the parameter adjusting equipment corresponding to the controllable parameter based on the control data, so that the actual controlled information of the controlled outlet parameter reaches the preset control target.

[0062] Among them, the control attribute includes at least one of the control weight, control priority, control period, control step and control upper and lower limit of the control parameter.

[0063] On the basis of the above device, optionally, the device further comprises a judgment module, and the judgment module comprises a fluctuation attribute determination unit and a judgment unit.

[0064] The fluctuation attribute determination unit is used for determining the fluctuation attribute of the actual controlled information of the controlled outlet parameter within a preset time length; wherein the fluctuation attribute includes fluctuation range, fluctuation amplitude, range and standard deviation;

[0065] The judgment unit is used for determining that the actual controlled information does not reach the preset control target if the fluctuation attribute does not satisfy the preset fluctuation condition.

[0066] On the basis of the above device, optionally, the device further comprises a model construction module, and the model construction module comprises a historical information determination unit, a data processing unit and an analysis unit.

[0067] The historical information determination unit is used for acquiring historical production process information corresponding to the cut tobacco feeder; wherein the historical production process information contains parameter information of the plurality of control parameters;

[0068] The data processing unit is used for processing the historical production process information to obtain to-be-used production process information;

[0069] The analysis unit is used for performing step analysis on the to-be-used production process information to obtain the prediction control model.

[0070] On the basis of the above device, optionally, the device further comprises an offline simulation module, and the offline simulation module comprises a simulation test unit and a model updating unit.

[0071] The simulation test unit is used for performing offline simulation test based on the prediction control model to obtain a simulation response result of the controlled outlet parameter in the control parameter;

[0072] A model updating unit is configured to correct model parameters in the predictive control model based on the standard control target of the controlled outlet parameter and the simulation response result, so as to update the predictive control model.

[0073] Based on the above device, optionally, the device further comprises a panel display module, the panel display module is configured to display the change curve of the actual controlled information of the controlled outlet parameter within a preset time length and the fluctuation attribute corresponding to the change curve based on the control data of the adjustable parameter of the target display panel.

[0074] The device for controlling the outlet parameter of the tobacco manufacturing and material adding machine provided in the embodiments of the present application can execute the method for controlling the outlet parameter of the tobacco manufacturing and material adding machine provided in any of the embodiments of the present application, and has the function modules and beneficial effects corresponding to the execution method.

[0075] Embodiment three

[0076] Figure 3 is a structural schematic diagram of an electronic device for implementing the method for controlling the outlet parameter of the tobacco manufacturing and material adding machine. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular telephones, smart phones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not intended to limit the implementations of the present application described and / or claimed in this document.

[0077] As shown in Figure 3 The electronic device 10 includes at least one processor 11, and a memory, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., which is in communication connection with the at least one processor 11, wherein the memory stores a computer program that can be executed by the at least one processor. The processor 11 can execute various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0078] A plurality of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network, such as the Internet, and / or various telecommunication networks.

[0079] The processor 11 can be various general and / or special purpose processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 performs various methods and processes described above, such as the control method for the tobacco-adding machine outlet parameters.

[0080] In some embodiments, the control method for the tobacco-adding machine outlet parameters can be implemented as a computer program tangibly embodied in a computer readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded onto the RAM 13 and executed by the processor 11, one or more steps of the control method for the tobacco-adding machine outlet parameters described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to perform the control method for the tobacco-adding machine outlet parameters by any other appropriate means, such as by means of firmware.

[0081] Various implementations of the systems and techniques described above can be realized in digital electronic circuitry, integrated circuitry, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a system on a chip (SOC), a programmable logic device (PLD), a computer hardware, firmware, software, and / or combinations thereof. These various implementations can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0082] Computer programs for implementing the methods of the present application can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer program, when executed, can cause instructions defined in the flow charts and / or block diagrams to be implemented. The computer program can be executed entirely on a machine, partially on a machine, partially on a machine as a stand-alone software package and partially on a remote machine or entirely on a remote machine or server.

[0083] In the context of the present application, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. A computer-readable storage medium can include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of a machine-readable storage medium will include one or more lines of a program of instructions in a transitory signal, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0084] To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the electronic device. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0085] The systems and techniques described herein can be implemented in a computing system that includes a back end component, e.g., as a data server, or that includes a middleware component, e.g., an application server, or that includes a front end component, e.g., a user computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described herein, or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication, e.g., a communication network. Examples of communication networks include a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0086] The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. A server can be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system, to solve the defects of large management difficulty and weak business scalability in traditional physical host and VPS service.

[0087] It should be understood that the various forms of flow shown above can be re-ordered, added to, or deleted from without departing from the scope of the present disclosure. For example, the steps recited in the present disclosure can be executed in parallel, executed in series, or executed in different orders, as long as the desired results of the technical solutions of the present disclosure can be achieved, and the present disclosure is not limited herein.

[0088] The above detailed description does not constitute a limitation on the protection scope of the present application. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent replacements, and improvements made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method for controlling the outlet parameters of the yarn feeding system, characterized in that, include: Acquire production process data corresponding to the filament feeding machine; wherein, the production process data includes data of multiple control parameters, the control parameters also include non-adjustable parameters, adjustable parameters, and controlled outlet parameters; the controlled outlet parameters include feed outlet moisture and outlet temperature; the adjustable parameters include process compensation steam flow rate and hot air compensation steam flow rate; The production process data is processed based on a predetermined predictive control model to obtain control data for the adjustable parameters; wherein the predictive control model is constructed based on a model predictive control algorithm. Based on the control data, control the parameter adjustment device corresponding to the adjustable parameter, so that in the process of controlling the parameter adjustment device, the actual controlled information of the controlled output parameter reaches the preset control target. The method further includes: if the actual controlled information of the controlled output parameter does not reach the preset control target, then based on the actual controlled information and the preset control target, determining the regulation attribute of the control parameter according to the predictive control model, and determining the control data of the adjustable parameter based on the regulation attribute, so as to control the parameter adjustment device corresponding to the adjustable parameter based on the control data, so as to make the actual controlled information of the controlled output parameter reach the preset control target; wherein, the regulation attribute includes at least one of the control weight, control priority, control period, control step size, and control upper and lower limits of the control parameter; The method for determining that the actual controlled information of the controlled output parameter has not reached the preset control target is as follows: determine the fluctuation attribute of the actual controlled information of the controlled output parameter within a preset time period; if the fluctuation attribute does not meet the preset fluctuation condition, then determine that the actual controlled information has not reached the preset control target; wherein, the fluctuation attribute includes fluctuation range, fluctuation amplitude, range and standard deviation.

2. The method according to claim 1, characterized in that, The process of processing the production process data based on a pre-determined predictive control model to obtain control data for the adjustable parameters includes: Based on the predictive control model, correlation analysis is performed on the data of the multiple control parameters to determine the control data for the process compensation steam flow rate and the hot air compensation steam flow rate.

3. The method according to claim 1, characterized in that, Also includes: Obtain historical production process information corresponding to the filament feeding machine; wherein, the historical production process information includes parameter information of the plurality of control parameters; The historical production process information is processed to obtain the production process information to be used; A step analysis is performed on the production process information to be used to obtain the predictive control model.

4. The method according to claim 3, characterized in that, Also includes: Offline simulation tests were performed based on the predictive control model to obtain the simulation response results to the controlled output parameter in the control parameters. Based on the standard control objective and simulation response results of the controlled outlet parameters, the model parameters in the predictive control model are corrected to update the predictive control model.

5. The method according to any one of claims 1-4, characterized in that, Also includes: The target display panel displays the control data of the adjustable parameters, the actual controlled information of the controlled output parameters, the change curve of the controllable parameters within a preset time period, and the fluctuation attributes corresponding to the change curves.

6. A control device for the outlet parameters of a filament feeding machine, characterized in that, include: The data acquisition module is used to acquire production process data corresponding to the filament feeding machine; wherein, the production process data includes data of multiple control parameters, and the control parameters include non-adjustable parameters, adjustable parameters, and controlled outlet parameters; the controlled outlet parameters include feed outlet moisture and outlet temperature; The model processing module is used to process the production process data based on a pre-determined predictive control model to obtain control data for the adjustable parameters; wherein the predictive control model is constructed based on a model predictive control algorithm. The control module is used to control the parameter adjustment device corresponding to the adjustable parameter based on the control data, so that the actual controlled information of the controlled output parameter reaches the preset control target during the process of controlling the parameter adjustment device. The feedback module is used to determine, based on the actual controlled information and the preset control target, the regulation attribute of the control parameter according to the predictive control model if the actual controlled information of the controlled output parameter does not reach the preset control target, and to determine the control data of the adjustable parameter based on the regulation attribute, so as to control the parameter adjustment device corresponding to the adjustable parameter based on the control data, so as to make the actual controlled information of the controlled output parameter reach the preset control target; wherein, the regulation attribute includes at least one of the following: control weight, control priority, control period, control step size, and control upper and lower limits of the control parameter; The judgment module includes: a fluctuation attribute determination unit, used to determine the fluctuation attribute of the actual controlled information of the controlled output parameter within a preset time period; and a judgment unit, used to determine that the actual controlled information has not reached the preset control target if the fluctuation attribute does not meet the preset fluctuation conditions; wherein the fluctuation attribute includes fluctuation range, fluctuation amplitude, range, and standard deviation.

7. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the control method for the outlet parameters of the filament feeding machine according to any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed by a processor, implement the method for controlling the outlet parameters of the filament feeding machine as described in any one of claims 1-5.

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