CN102871214B - Model prediction based cut tobacco dryer outlet moisture control method - Google Patents
Model prediction based cut tobacco dryer outlet moisture control method Download PDFInfo
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Abstract
The invention discloses a model prediction based cut tobacco dryer outlet moisture control method. Aiming at characteristics of complicated state changes of a cut tobacco dryer during working and diversity of production process modes, an intelligent integrated optimizing control system for the cut tobacco dryer based on an intelligent prediction model and an artificial intelligent operating mode is constructed so as to achieve comprehensive optimization and automation during cut tobacco drying. Aiming at different stages and different production process modes in production, a model capable of describing dynamic process characteristics depending on feed quantity and feed moisture is constructed. On the basis of the model, an on-line optimizing control algorithm which is capable of simultaneously or selectively adjusting multiple process variables, adapting to changes of the feed quantity and the feed moisture and overcoming mutual interference among the variables and influences of various uncertainties during cut tobacco drying and has self-adaptive and self-adjustment functions is designed, and strict requirements on outlet cut tobacco moisture in different working conditions can be met.
Description
Technical Field
The invention relates to an automatic control technology of outlet moisture of a cut tobacco dryer and an implementation method thereof.
Background
Tobacco leaves of a tobacco processing line of a cigarette factory enter a cut tobacco drying process after a leaf pretreatment process, one of the main purposes of the cut tobacco drying process is to control the moisture of cut tobacco at the outlet of a cut tobacco drying cylinder, the cut tobacco drying cylinder adopts saturated steam and hot air to heat the cut tobacco, the moisture in the cut tobacco is evaporated, and the moisture evaporated by the cut tobacco is carried away by the hot air, so that the purpose of controlling the moisture of the cut tobacco is achieved.
The existing cut tobacco drying moisture control adopts a simple PID algorithm and is controlled by some sequential logics, and control loops are relatively independent and poor in coordination, so that real closed-loop automatic control is difficult to achieve. As a plurality of interference factors influencing the moisture at the tobacco shred outlet are included in the tobacco shred drying process, such as: the method is characterized in that the method comprises the following steps of feeding tobacco shred moisture, feeding tobacco shred flow, steam pressure, moisture discharge, hot air temperature, air speed and the like, and the control process has strong nonlinearity, uncertainty, coupling property and hysteresis, so that the main problems of relatively large moisture control fluctuation at the head and tail sections of the tobacco shreds and relevant control quality to experience, quality and responsibility of operators are solved; the influence of external interference is large in the middle stage, the adjusting time is long, the control fluctuation is large, manual intervention is needed, the moisture control system is difficult to guarantee high control precision requirement and control stability, and meanwhile, the improvement and maintenance of the system are difficult. The fluctuation of the outlet moisture influences the internal quality of the cut tobacco and reduces the quality of the whole cut tobacco
Disclosure of Invention
The invention aims to provide a method for controlling moisture at an outlet of a cut-tobacco drier based on model prediction, so as to solve the defects in the background technology.
The invention comprises an intelligent integrated optimization control technology suitable for the process control of a cut tobacco dryer, can realize the comprehensive optimization and automation of the cut tobacco drying process, constructs various models capable of describing the process dynamic characteristics depending on the feeding quantity and the feeding moisture and optimization methods thereof aiming at the production processes of different stages and different production process modes, and develops an optimization control algorithm which can adapt to the change of the feeding quantity and the feeding moisture and overcome the mutual interference among variables and the influence of various uncertain factors in the cut tobacco drying process and has self-adaption and self-adjustment functions on the basis of the models. So as to meet the strict requirements for the moisture of the export cut tobacco in different production stages.
A method for controlling moisture at an outlet of a cut-tobacco drier based on model prediction divides a moisture control system at the outlet of the cut-tobacco drier into three processes: in the process of drying the head, the intermediate process and the tail drying process, the moisture at the outlet enters a stable state with a set value of +/-0.5 percent as soon as possible, the rising speed of the moisture is accelerated, and the amount of dry tobacco shreds at the head part is reduced; in the intermediate stage, keeping the outlet moisture stable around a set value; in the early stage of the dry tail stage, the cut tobacco is stabilized on a set value as much as possible, the moisture at the outlet of the cut tobacco is not reduced too early, and the amount of dry cut tobacco at the dry tail part is reduced, and the method comprises the following steps:
(1) aiming at the characteristic that no outlet moisture detection signal exists in the head production process, on the basis of a tobacco material drying mechanism, a non-parameter model modeling idea is adopted, a plurality of points are obtained by sampling a plurality of input curves, so that the influence of one section of curve is converted into the influence of a plurality of sampling points, and a set model based on a RBF-ARX model and dependent on process variables such as cylinder temperature, wind temperature, moisture exhaust air door, inlet flow and the like of feeding quantity and feeding moisture is constructed;
(2) and calculating the optimal setting curve of each input quantity according to the limit values of the starting point and the end point of each set input quantity (a moisture exhaust air door, a cylinder temperature, an air temperature and an inlet flow) and the expected output curve of the outlet moisture, so that the operation variable in the dry head process is changed according to the optimal setting curve. According to the incoming material condition, self-correcting the process variable to set the model parameter of the model and improve the self-adaptive capacity of the model to the head cut tobacco drying process, and designing a self-adjusting fuzzy tracking control algorithm to enable the water content at the outlet of the head cut tobacco drying process to quickly reach a set value so as to reduce dry cut tobacco, achieve a satisfactory tracking control effect and achieve the self-adaptive capacity to different incoming material flow rates and water contents;
(3) for the intermediate continuous production process, the RBF-ARX model structure is adopted, a cut tobacco drying process dynamic characteristic model depending on the flow and the moisture of the incoming cut tobacco is established, the established cut tobacco drying process RBF-ARX model is taken as a prediction model, and the online intelligent prediction optimization control algorithm of the moisture of the outgoing cut tobacco is designed in consideration of the requirements of different process modes and different operation modes;
(4) the RBF-ARX prediction controller compares the moisture value detected by the discharge end moisture meter with a set moisture value to calculate the optimal values of the hot air volume and the moisture discharge volume on line; the hot air quantity air door automatically controls the servo cylinder to adjust the opening degree of the hot air quantity air door by taking the optimal value of the hot air quantity output by the RBF-ARX predictive control as a set value; the moisture-removing air quantity air door automatically controls the servo cylinder to adjust the opening degree of the moisture-removing air quantity air door by taking the optimal moisture-removing air quantity value output by the RBF-ARX predictive control as a set value; the barrel temperature steam valve automatically tracks and adjusts the opening degree of the pneumatic film regulating valve according to the comparison between the barrel set temperature value and the barrel temperature value detected by the temperature sensor, controls the steam flow and finally stabilizes the steam flow near the barrel set temperature value; a servo cylinder on the heating system automatically tracks and adjusts according to the comparison between the hot air set temperature value and the hot air temperature value measured by the temperature sensor, and finally stabilizes the temperature value to be close to the hot air set temperature value;
(5) aiming at the characteristics that no inlet incoming material instant signal exists in the tail production process but historical incoming material quantity and moisture signals exist, a set model of process variables such as cylinder temperature, air temperature, moisture exhaust air door and cylinder rotating speed which depend on the feeding quantity and the feeding moisture is constructed on the basis of a tobacco material drying mechanism;
(6) according to the set limit values of the starting point and the end point of each input quantity (a moisture exhaust air door, a cylinder temperature, an air temperature and the cylinder motor frequency) and the expected output curve of the outlet moisture, an optimal set curve of each input quantity is calculated, so that the operation variable in the tail drying process changes according to the optimal set curve, the model parameter of the process variable set model is self-corrected according to the incoming material condition, the self-adaptive capacity of the model parameter to the tail tobacco shred drying process is improved, and the outlet moisture in the tail tobacco shred drying process is maintained at the set value as far as possible by adopting a self-adjusting fuzzy tracking control algorithm, so that the dry tail tobacco shreds are reduced, and the satisfactory tracking control effect and the self-adaptive capacity to different incoming material flow rates and water contents are achieved;
(7) and the dynamic characteristic modeling of the dry head process, the intermediate process and the dry tail process adopts an RBF-ARX model structure. Optimizing the structure and parameters of each model in an off-line mode by utilizing historical data;
(8) based on the constructed dynamic characteristic models of the dry head and the dry tail process, optimizing set value models of process variables such as cylinder temperature, a moisture exhaust air door and the like in the dry head and the dry tail process on line so as to adapt to the change of incoming material conditions;
(9) and intelligent integrated optimization control operation in the cut tobacco drying process is realized by using a modularized embedded controller system of an embedded PC technology, so that the moisture control of the cut tobacco dryer outlet based on model prediction is realized.
Has the advantages that:
the invention has the following advantages:
1. the automation of the control of the cut tobacco drying process can be realized, and the manual intervention in the production process is avoided;
2. the control precision is high, the capacity of overcoming various on-site interferences is strong, the outlet moisture of the head section and the tail section can be controlled within +/-0.5% of a set value, the outlet moisture of the middle section can be controlled within +/-0.2% of the set value, the standard deviation is less than or equal to 0.10%, and the outlet moisture fluctuation caused by various interferences can be quickly inhibited; the quantity of dry cut tobacco at the head and tail sections can be reduced to the maximum extent, the quantity of the dry cut tobacco at the head is smaller than 0.7 per mill of the flow of the supplied materials (the dry cut tobacco is cut tobacco with the moisture of less than or equal to 7 percent), the quantity of the dry cut tobacco at the tail section is smaller than 1.4 per mill of the flow of the supplied materials (the dry cut tobacco is cut tobacco with the moisture of less than or equal to 7 percent), the waste and the breakage of the cut tobacco can be greatly reduced, the method can be suitable for cut tobacco with different brands, can be realized in an industrial PLC-level embedded PC control system, and can meet the requirements of actual industrial.
Drawings
FIG. 1 is an illustration of a process variable timing relationship for a cut-tobacco dryer.
Detailed Description
In order to make the technical means, creation features, working procedures and using methods of the present invention easily understood and appreciated, the present invention will be further described with reference to the following embodiments.
1. The process variable timing relationship of the cut-tobacco drier is shown in figure 1. Before the tobacco shred arrives from the previous procedure, detecting the instantaneous flow value of the tobacco shred at the moment at a position far away from a roller of a tobacco dryer, namely the position of u 4; after the NK time has elapsed, the position coming to u5 detects the entry moisture value at this time; after the time of nk1, the tobacco shreds enter the roller, and during the operation in the roller, the moisture exhaust air door, the hot air temperature, the roller motor frequency and the like at the moment are detected at each sampling moment; and finally, after the time of nk2, the cut tobacco is discharged from the tube, and the moisture at the outlet is detected. The tobacco shreds have a longer time from the flow detection value (u4) to the detection of the outlet moisture (y), and the whole system has input variables detectable but no output (outlet moisture) detectable in such a long period of time as the early stage of dry head. After the cut tobacco of the dry tail section is cut off, the system has no two input variables of inlet flow and inlet moisture, but has an output variable. Therefore, the system has a large time lag, and the cut tobacco drying process can be divided into three processes: a head drying process, an intermediate process and a tail drying process.
i) A head drying process: from the moment the inlet flow is detected to the moment the outlet moisture is substantially stabilized at the set value.
ii) an intermediate process: when the moisture at the outlet is stable, the intermediate process is carried out.
iii) Dry Tail Process: when the inlet flow rate is changed from the normal value to 0, the beginning of the tail drying process is marked, and when the moisture content of the outlet is reduced to 3 percent, the end of the whole cut tobacco drying process is marked.
2. The dryer outlet moisture is affected (but with a significant delay) by the inlet moisture and inlet flow rate at which this is detected, as well as by the drum temperature, air temperature, and damper exhaust over time in the drum. Therefore, a RBF-ARX modeling method is adopted to construct a cut tobacco drying process dynamic model of a dry head stage, a middle stage and a dry tail stage. The RBF-ARX model is a nonlinear time-varying model with a linear ARX model structure. The independent variables are a group of semaphores representing the nonlinear state of the system, and the model parameters are adjusted on line in real time by adopting an RBF neural network structure. Similar to the linear ARX model, the RBF-ARX model has excellent approximate effect in a local linear interval, and in addition, the parameters of the RBF-ARX model can be updated and adjusted automatically. Therefore, it also has the property of global adaptation. In the present invention, a RBF network of Gaussian kernels is used to approximate the function coefficients in the state-dependent ARX model.
3. The structure of a Gaussian kernel RBF-ARX model for constructing a dynamic characteristic model of a dry head process is as follows:
wherein,
determining the length of data with inlet moisture and without outlet moisture according to the data sample of the dry head;determining the data length with inlet flow and without inlet moisture according to the data sample of the dry head; based on the actual condition of the dry head portion of the dryer system, the RBF input, i.e.IndexSelected as inlet flow rate and inlet moisture.
The model parameters are optimized offline by a Structured Nonlinear Parameter Optimization Method (SNPOM) combining Levenberg-Marquardt Method (LMM) and linear Least Square Method (LSM). The model order determination is determined by the modeled AIC values.
4. Modeling of the middle process and the dry tail process is also realized by adopting a Gaussian core RBF-ARX model structure similar to modeling of the dry head process.
5. And establishing a set value model of each process variable in the process of the dry head and the dry tail of the cut tobacco dryer based on the established RBF-ARX model of the dynamic process of the dry head and the dry tail. For the dry head process, an optimal input curve of a moisture exhaust air door, air temperature, cylinder temperature and inlet flow can be established; for the dry tail process, an optimal input curve of a moisture exhaust air door, air temperature, barrel temperature and barrel motor frequency can be established. An S-shaped function is adopted to describe an input curve of the moisture exhaust air door, the air temperature, the barrel temperature and the barrel motor frequency, and a trapezoidal curve is adopted to describe an input curve of the inlet flow.
The formula of the S-shaped curve is as follows:
t: time of input in units ofs；
: controlling the starting point value and the end point value of the S-shaped curve;
: controlling the position of a symmetry axis of the S-shaped curve;
: controlling the speed of the S-shaped curve to rise or fall;
the trapezoidal curve formula is as follows:
t: time of input in units ofs；
: 5 parameters of the trapezoidal curve;
the input quantities are substituted into the constructed RBF-ARX model,
namely obtaining the output at a given curveThe predicted outlet moisture value of the model in the case of input. Finding optimal by Levbacket Quercide method (LMM)And the parameters minimize the error between the outlet moisture value output by the model calculation and the outlet moisture set value. Namely:
: an outlet moisture set value;
: in the parameterNext, calculating an outlet water content value by using the RBF-ARX model;
the optimization problem of the optimal curve of the process variable in the process of drying the head or the tail is as follows:
finally, the optimal parameter value can be obtained through parameter optimization, so that the optimal input curve of the cut tobacco dryer in the process of drying the head or the tail of the cut tobacco dryer is designed.
3. In order to adopt an outlet water prediction control method based on an intermediate process RBF-ARX model, the RBF-ARX model is converted into a polynomial structure model shown as follows:
state variables defining the system:
obtaining a set of state space models:
defining the relevant variables:
wherein,is to predict the length of the time domain,is the control time domain length. Suppose thatFrom (8) to (13), there can be obtained:
thus, a multi-step output prediction is obtained:
defining:
predictive control can be achieved by optimizing the following objective function on-line:
wherein,Is a weighting coefficient matrix.
The foregoing shows and describes the general principles and broad features of the present invention and advantages thereof. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof 。
Claims (1)
1. A method for controlling moisture at an outlet of a cut-tobacco drier based on model prediction divides a moisture control system at the outlet of the cut-tobacco drier into three processes: in the process of drying the head, the intermediate process and the tail drying process, the moisture at the outlet enters a stable state with a set value of +/-0.5 percent as soon as possible, the rising speed of the moisture is accelerated, and the amount of dry tobacco shreds at the head part is reduced; in the intermediate stage, keeping the outlet moisture stable around a set value; in the early stage of the dry tail stage, the cut tobacco is stabilized on a set value as much as possible, the moisture at the outlet of the cut tobacco is not reduced too early, and the dry tail part dry cut tobacco quantity is reduced, which is characterized by comprising the following steps:
(1) aiming at the characteristic that no outlet moisture detection signal exists in the head production process, on the basis of a tobacco material drying mechanism, a non-parameter model modeling idea is adopted, a plurality of points are obtained by sampling a plurality of input curves, so that the influence of one section of curve is converted into the influence of a plurality of sampling points, and a setting model based on a RBF-ARX model and dependent on the cylinder temperature, the wind temperature, the moisture exhaust air door and the inlet flow of the feeding amount and the feeding moisture is constructed;
(2) calculating an optimal setting curve of each input quantity according to the set limit values of the starting point and the end point of each input quantity and an expected output curve of the outlet moisture, enabling the operating variables in the head drying process to change according to the optimal setting curve, self-correcting the model parameters of the process variable setting model according to the incoming material conditions, improving the self-adaptive capacity of the model parameters to the head cut tobacco drying process, and designing a self-adjusting fuzzy tracking control algorithm to enable the outlet moisture in the head cut tobacco drying process to quickly reach a set value so as to reduce the dry cut tobacco leaves, achieve a satisfactory tracking control effect and achieve the self-adaptive capacity to different incoming material flows and water contents;
(3) for the intermediate continuous production process, the RBF-ARX model structure is adopted, a cut tobacco drying process dynamic characteristic model depending on the flow and the moisture of the incoming cut tobacco is established, the established cut tobacco drying process RBF-ARX model is taken as a prediction model, and the online intelligent prediction optimization control algorithm of the moisture of the outgoing cut tobacco is designed in consideration of the requirements of different process modes and different operation modes;
(4) the RBF-ARX prediction controller compares the moisture value detected by the discharge end moisture meter with a set moisture value to calculate the optimal values of the hot air volume and the moisture discharge volume on line; the hot air quantity air door automatically controls the servo cylinder to adjust the opening degree of the hot air quantity air door by taking the optimal value of the hot air quantity output by the RBF-ARX predictive control as a set value; the moisture-removing air quantity air door automatically controls the servo cylinder to adjust the opening degree of the moisture-removing air quantity air door by taking the optimal moisture-removing air quantity value output by the RBF-ARX predictive control as a set value; the barrel temperature steam valve automatically tracks and adjusts the opening degree of the pneumatic film regulating valve according to the comparison between the barrel set temperature value and the barrel temperature value detected by the temperature sensor, controls the steam flow and finally stabilizes the steam flow near the barrel set temperature value; a servo cylinder on the heating system automatically tracks and adjusts according to the comparison between the hot air set temperature value and the hot air temperature value measured by the temperature sensor, and finally stabilizes the temperature value to be close to the hot air set temperature value;
(5) aiming at the characteristics that no inlet incoming material instant signal exists in the tail production process but historical incoming material quantity and moisture signals exist, a setting model dependent on the feeding quantity and the feeding moisture is constructed on the basis of a tobacco material drying mechanism;
(6) according to the set limiting values of the starting point and the end point of each input quantity and the expected output curve of the outlet moisture, wherein each input quantity is a moisture exhaust air door, a drum temperature, an air temperature and a drum motor frequency, the optimal setting curve of each input quantity is calculated, the operation variable in the tail drying process is changed according to the optimal setting curve, the model parameter of the model is set according to the incoming material condition self-correction process variable, the self-adaptive capacity of the model to the tail tobacco shred drying process is improved, the outlet moisture in the tail tobacco shred drying process is maintained at the set value as far as possible by adopting a self-adjusting fuzzy tracking control algorithm, so that the dry tail tobacco shreds are reduced, the satisfactory tracking control effect is achieved, and the self-adaptive capacity to different incoming material flow and water contents is improved;
(7) RBF-ARX model structures are adopted for dynamic characteristic modeling of the dry head process, the intermediate process and the dry tail process, and the model structures and parameters are optimized by utilizing historical data and in an off-line mode by using each model;
(8) based on the constructed dynamic characteristic models of the dry head and the dry tail process, optimizing a barrel temperature and set value model of a moisture exhaust air door in the dry head and the dry tail process on line so as to adapt to the change of incoming material conditions;
(9) and intelligent integrated optimization control operation in the cut tobacco drying process is realized by using a modularized embedded controller system of an embedded PC technology, so that the moisture control of the cut tobacco dryer outlet based on model prediction is realized.
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| CN101488024A (en) * | 2009-01-23 | 2009-07-22 | 秦皇岛烟草机械有限责任公司 | On-line quality evaluation and real-time intelligent control method for tobacco process parameter |
| CN101611921A (en) * | 2009-07-24 | 2009-12-30 | 秦皇岛烟草机械有限责任公司 | Sectional type low temperature roller cut tobacco drying equipment |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE2103671C2 (en) * | 1971-01-27 | 1982-12-23 | Hauni-Werke Körber & Co KG, 2050 Hamburg | Process and system for conditioning tobacco |
| US4315515A (en) * | 1980-04-11 | 1982-02-16 | Brown & Williamson Tobacco Corporation | Tobacco drying apparatus |
| CN101488024A (en) * | 2009-01-23 | 2009-07-22 | 秦皇岛烟草机械有限责任公司 | On-line quality evaluation and real-time intelligent control method for tobacco process parameter |
| CN101611921A (en) * | 2009-07-24 | 2009-12-30 | 秦皇岛烟草机械有限责任公司 | Sectional type low temperature roller cut tobacco drying equipment |
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