Перегляд за Автор "Hrama, Mykhailo"

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Automated methods of controlling the flow of syrup in the evaporation station with subsystems of decision support and forecasting
(2022) Hrama, Mykhailo; Sidletskyi, Victor
Introduction. The purpose of the presented study is to substantiate the methods of regulating the consumption of syrup in the evaporation station with a forecasting subsystem, which will allow to predict the behavior of the system and the decision-making subsystem, which will reduce the influence of the human factor on the course of the evaporation process. Materials and methods. The work of the evaporation station with the subsystem of forecasting and decision support when regulating the consumption of syrup was researched. In the automation scheme for regulating the flow rate of syrup, induction flow meters are used as a sensor. Pneumatic saddle valves with a built-in throttle and an electro-pneumatic converter were used as actuators. Results and discussion. The use of neural sensors occurs only in certain specific cases of intelligent control of the evaporation process, there is no data comparing the use of intelligent regulators with classical ones, the possibility of combining the work of several types of intelligent regulators, as well as clear means of predicting their work and supporting decision-making. Therefore, in this paper, a decision-making subsystem has been justified, which made it possible to assess the priorities of user requests when using a human- machine interface. The highest priority was given to the request to display information on possible changes to the adjustment parameters of other control circuits. The forecasting method was also used to compare the methods of regulating the flow rate of syrup in the apparatus, which made it possible to predict the behavior of the system during the formation of the control action and display the finished forecast on the operator's screen and, thus, increase the efficiency of the evaporation station. Statistical data on the behavior of the contours of the automation system in different modes of operation using intelligent and classical regulators were collected, a model for predicting the operation of an evaporation station by the method of local tendency was built and a forecasting algorithm was developed. The accuracy of the obtained forecasting model is also evaluated. The accuracy of the forecasting model was 98% for the PID controller, 95% for the neural fuzzy regulator and 96% for the neural network. Conclusions. The model for predicting the operation of the evaporation station is characterized by high accuracy in general, but during the occurrence of oscillations in the transition process, there is an insignificant delay in predicting these fluctuations. The most important in the output of information by the decision-making subsystem is the function of displaying information about the possible changes to the parameters of regulation of other control circuits.
Comparison between PID and fuzzy regulator for control evaporator plants
(2019) Hrama, Mykhailo; Sidletskyi, Victor; Elperin, Igor
In this paper, a comparison is made between FID and fuzzy controller. The purpose of the study is to determine when the use of which type of regulation will achieve the best indicators of quality control for the regulation of the evaporator. The regulation of such responsible parameters as levels of concentrated juice in the evaporator's buildings, which directly affect the quality and cost of manufactured products, is carried out. First, a mathematical model was developed in the space of states in the Matlab environment and results were obtained with respect to the variation of the problem relative to the initial conditions and with respect to perturbation. Secondly, a mathematical model with a PIDregulator was developed and transient processes for control circuits in all control channels were obtained. Thirdly, a mathematical model with a fuzzy controller was developed and transient processes for control circuits in all control channels were obtained. When comparing the mathematical model with PID and the fuzzy controller, it was concluded that the use of neuro-fuzzy regulation is more appropriate as it leads to an increase in the qualitative parameters of the process compared with the system with PID regulators.
Intelligent automatic control of sugar factory evaporator operation using behavior prediction subsystem
(2022) Hrama, Mykhailo; Sidletskyi, Victor; Elperin, Igor
Introduction. The aim of the presented research was to substantiate the intelligent automatic control of the sugar juice evaporation with the subsystem for behavior prediction, which allows to determine the behavior of the automatic system. Materials and methods. The operation of the evaporator unit with system behavior prediction to regulate the sugar juice level was investigated. Capacitive level gauges were used as a sensor in the automation scheme of sugar juice level control. Pneumatic seat valves with a built-in throttle and an electro¬pneumatic converter were used as actuators. Results and discussion. The use of neuro-fuzzy regulators occurs only in some specific cases of intelligent control of the evaporation process. There is no data comparing the use of intelligent regulators with classical ones and the possibility of combining several types of intelligent regulators, as well as clear means of predicting their work. Therefore, in the present study, a prediction method was used to compare methods to regulate the level of sugar juice in the evaporator. This made it possible to predict the behavior of the system during the formation of the control action and display the finished forecast on the operator's screen, which made it possible to increase the efficiency of the evaporative station. Statistical data on the behavior of the automation system contours in various operating modes were collected using intelligent and classical controllers, and a model was built to determine the operation of the evaporator using the local trend method and the modified algorithm of prediction. The advantage of this method is its easy and fast implementation, which does not require large economic and energy costs. The accuracy of the prediction model was 98% for the PID-controller, 95% for the fuzzy-controller and 96% for the neural network. The obtained model of the system prediction is stable because the absolute error does not change when dividing the time series into intervals. Conclusions. The proposed system of intelligent automated control of the evaporation of sugar juice with a modified prediction method based on local trends has an insignificant delay, while prediction is performed with high accuracy and stability.
Justification of the neuro-fuzzy regulation in evaporator plant control system
(2019) Hrama, Mykhailo; Sidletskyi, Victor; Elperin, Igor
Introduction. The purpose of the study is the determining the use of which type of regulation will achieve the best indicators of quality control for the regulation of the evaporator plant. Materials and methods. The system of management of a five-body evaporator plant of a sugar refinery was researched. The method of synthesis of modal control was used for evaluating the results of the research. Results and discussion. A comparison between FID and fuzzy regulator was made. Regulation of such responsible parameters as levels of concentrated juice in evaporator plant bodies, which directly affect the quality and value of manufactured products, was implemented. First, in the space of states in Matlab environment, a mathematical model was developed and the results obtained regarding the variation of the problem with respect to the initial conditions and perturbations were obtained. Due to them one can conclude that the time of the transition process is within the range from 0.8 to 1.2 seconds. However, the deviation levels in the evaporator plant bodies are too high. Secondly, a mathematical model with a PID-regulator was developed and transition processes for control schemes across all control channels were obtained. In this case, the time of transition processes is within the range of 60 seconds along the channel X1 to 145 seconds along the channel X2, but this led to a significant decrease in the deviation of levels in the bodies. Thirdly, a mathematical model with a fuzzy regulator is developed and transition processes for control schemes in all control channels were obtained. In this case, the time of transition processes is within the range from 50 seconds along the channel X1 to 110 seconds along the channel X2, which is the better result if compared to the PID regulator. Compared with the previous study, the levels in the bodies also significantly decreased. Therefore, the use of neuro- fuzzy regulation leads to an increase in qualitative parameters of the process compared with the system with PID-regulators. Conclusions. The scientific substantiation of the feasibility of using neuro-fuzzy regulation during the implementation of optimal control systems is the novelty of the research results.
Studying the adequacy of the neural network level controller in the automated control system of an evaporator
(2023) Hrama, Mykhailo; Sidletskyi, Victor
The aim of the study is to substantiate the use of neural network control of beet juice level in an evaporator by evaluating the accuracy and adequacy of the model. This allows us to assess how well the model properties describe the course of the real process. The use of mathematical statistics methods is the most common way to test models for adequacy. In the automation scheme of level control, capacitive level gauges are used as a sensor. The actuators are pneumatic seat valves with a built-in throttle and an electropneumatic converter. The use of neural network controllers is found only in some specific cases of intelligent control of the evaporation process, and there are no data comparing the use of intelligent controllers with classical ones. In this paper, the Durbin-Watson d-criterion is used to assess the adequacy of the model. Statistical data on the behavior of the level control system circuits in different operating modes using intelligent and classical controllers were collected and a model of the evaporator unit operation was built. The advantage of the Durbin-Watson criterion is its simple and fast implementation, which does not require large economic and energy costs. The accuracy of the model was also evaluated. The static error of the control quality for the levels in the five enclosures of 25% - 65% (in 10% increments) is within the range of no more than 0.2%. The proposed model of the evaporator station operation is generally characterized by high accuracy.
The use of neural network controllers in the process of sugar evaporation
(2023) Hrama, Mykhailo
The purpose of the presented study is to substantiate the methods of regulating the consumption of syrup in the evaporation station with a forecasting subsystem, which will allow to predict the behavior of the system and the decision-making subsystem, which will reduce the influence of the human factor on the course of the evaporation process. Materials and methods. The work of the evaporation station with the subsystem of forecasting and decision support when regulating the consumption of syrup was researched. In the automation scheme for regulating the flow rate of syrup, induction flow meters are used as a sensor. Pneumatic saddle valves with a built-in throttle and an electro-pneumatic converter were used as actuators.
Use of methods of tensor analysis in the evaporator plant operating system
(2019) Korobiichuk, Igor; Sidletskyi, Victor; Ladanyuk, Anatoly; Elperin, Igor; Hrama, Mykhailo
The issues of the relevance of conduction of research in the areas of analysis and synthesis of evaporator plant operating systems were disclosed; the need of taking into account the peculiarity and interconnection of mass and energy flows of the entire sugar refinery was put forward. This explains the need for new methods of integrating the operating system so that, on the one hand, the evaporator plant operating system is an integral part of the whole system of the sugar refinery management. But at the same time, it shall be flexible and shall not require significant changes in the correction of processes or updating of automation equipment. The article presents a method for using the mathematical apparatus of tensor analysis for determining the nature of the change of the signal of the discrepancy and the formation of the control signal.