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Introduction. The process of sugar crystallization is complex and non-linear, necessitating automatic control and management. However, the lack of instruments for directly measuring solution supersaturation and crystal growth highlights the need for improvements in the control system. Materials and methods. The automation system for the process of sugar crystallization in a vacuum apparatus consists of sensors, converters of actuators, regulatory bodies, a microprocessor controller and an operator station with a SCADA program. The automation system algorithms are implemented in software in the controller and operator station. Results and Discussion. The amount of initial syrup in the vacuum apparatus significantly affects the dry substance content in the massecuite. A high dry substance content ensures highquality massecuite and promotes efficient crystallization. The optimal initial syrup concentration for achieving the standard dry matter content in massecuite 92% is 33%, but it can vary between 25% and 35%. An increase in the initial syrup concentration raises the average temperature of the massecuite during crystallization, which can negatively impact the final product quality. Therefore, temperature control by adjusting the initial syrup amount is crucial for optimal crystallization and producing a high-quality product. The deformation gradient, constructed based on dry substance content and temperature parameters, reflects changes in the crystallization process. These parameters directly influence system properties, which is vital for optimizing the vacuum apparatus process. The obtained surfaces with first-rank strain tensors at 25% and 35% initial syrup values indicate changes in the strain gradient during crystallization. Key aspects such as volume change, strain tensor divergence, velocity, and acceleration are essential for calculating and analyzing the gain, time constant, and delay time in the vacuum sugar crystallization process. Conclusions. Attributes of the crystallization process such as the amplification factor, time constant, and delay time are crucial for configuring and enhancing automated system operations, as precise calculations allow for improving control in automation systems. [ABSTRACT FROM AUTHOR]

Introduction. The aim of the present study was to improve of the automated control system of the sugar plant diffusion station, which does not respond adequately to violations of the technological regime when changing the quality indicators of raw beet materials and the rhythm of work. Materials and methods. The paper considers the data of the diffusion station and the lab for testing of raw materials of the Zhdanivkyi Sugar Plan, Vinnytsia region, Ukraine. To improve the automation system, it is proposed to include a subsystem for resolving conflict modes, and the method of bimatrix non-antagonistic game is used. Results and discussion. Uncontrolled parameters worsen the quality of raw beet materials and chips, disrupt the movement of chips in the scalding unit and column, and affect machine loading. Contradictions arise: an increase in productivity reduces storage losses, but leads to an increase in sugar losses with the cake because higher throughput reduces the time for optimal extraction. Changes in the condition of the raw beet materials decreases the processing quality and plant productivity. For the studied sugar plant, changing chip thickness from 6 to 9.5 m/100 grams of beet caused the voltage on the column motors to vary from 135 to 375 V, leading to changes in plant productivity from 2033 to 2358 t/day and sugar losses from 0.39 to 0.65% by weight of processed beets. An approach to the automation of a diffusion station was proposed. This approach involves supplementing existing systems with a subsystem for resolving conflict modes of operation. The subsystem uses information from the automatic control system, operator inspections, and laboratory data. By applying game theory, it controls the performance of the diffusion station. This algorithm minimizes the total loss of sugar during the storage and processing of beet. It also forms control actions to adjust technological parameters. The methodology involves presenting the problem as a non-antagonistic bimatrix game. In this game, one party aims to increase plant productivity during processing. The other party focuses on reducing losses during processing. The set of strategies involves changing the thickness of the chips. The payoff functions for the parties are productivity and sugar losses during processing. Conclusion. The use of game theory to optimize the productivity of a sugar plant takes into account sugar losses during beet storage, processing sequence, temperature, beet quality, and changes in sugar losses at different plant productivity. [ABSTRACT FROM AUTHOR]

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 electropneumatic 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. [ABSTRACT FROM AUTHOR]

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 humanmachine 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. [ABSTRACT FROM AUTHOR]

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 neurofuzzy 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. [ABSTRACT FROM AUTHOR]