Igor Elperin’s research while affiliated with National University of Food Technologies and other places

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Publications (4)


Development of Logical Control System for the Purification Department at Molasses Production
  • Chapter

January 2020

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31 Reads

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1 Citation

Advances in Intelligent Systems and Computing

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Victor Tregub

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Oleh Klymenko

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[...]

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Marina Chornovan

For the construction of algorithms for logical control of periodic action apparatuses (PAA) a universal language of UML modeling has been selected. UML diagrams have been constructed for implementation of the PAA model for the purification department of the molasses production, namely the diagrams: classes, sequence, condition and activity. With the help of these diagrams the algorithm of logical control for the purification department is developed.


Identification of Technological Objects on the Basis of Intellectual Data Analysis

January 2020

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259 Reads

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3 Citations

Advances in Intelligent Systems and Computing

Considered questions of an authentications of such difficult object as installation of bragger rectification. The considered approach allows automating the process of obtaining a neuro-fuzzy model, and revealing the main dependencies between input and output variables. The approaches considered in the article can be used for development of simulation models of heat-mass exchange processes. Resulting models can be used in control systems, which are formed on the basis of optimal, robust and scenario methods.


Figure 1. Automation of evaporator plant control loops: a -temperature and pressure, b -level
Figure 2. Mathematical model of evaporator plant: Θi -the temperature of the boiling juice in the i-th body ВС [ °С]; i = 0-5 -corresponds to the number of body ВС; Θпі -steam temperature in the i-body of the evaporator plant [ °С]; hi-the level of juice, respectively, in the i-th body ВС [m,% to the length of the tubes of the surface of the heating]; S0,S1,S2,S3,S4,S5-inflow of juice into the I body, an outflow of juice from the I body and an inflow into the II body, an outflow from the II body and an inflow into the III body, an outflow from the III body and an inflow into the IV body, an outflow from the IV body and an inflow into the V body, an outflow from V body accordingly [kg/f]; Wi -the flow of steam generated in the i-th body of the evaporator plant [kg/f]; Gni -consumption of heating steam in the i-th case ВС [kg/f]; bі -concentration of dry matter in the i-body of the evaporator plant [%]; Ski--the flow of condensate in the i-th body of the evaporator plant [kg/f]; Θki -condensate temperature in the i-th body ВС [ °С]; Ci -the content of sucrose in juice in the i-th body ВС [%].
Figure 5. The schematic scheme of an object in the Simulink environment
Figure 9. Mathematic model with fuzzy regulator
Figure 10. Graphical representation of the operation of the fuzzy conclusion algorithm: delX2 -proportional term; IntX2 -integral term; Y2 -result.

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Justification of the neuro-fuzzy regulation in evaporator plant control system
  • Article
  • Full-text available

December 2019

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158 Reads

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5 Citations

Ukrainian Food Journal

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Citations (3)


... Such adjustments can be explained both by a change in the technological and quality indicators of the components at the inlet of the evaporation station, and by the need to change them at the exit of the section. When making changes to the operation of the automation system, the operator must take into account how adjacent sections affect the operation of the evaporation station, as well as the impact of the evaporation station on the operation of adjacent sections of the plant (Hrama et al., 2019). ...

Reference:

Automated methods of controlling the flow of syrup in an evaporator with subsystems of decision support and forecasting
Justification of the neuro-fuzzy regulation in evaporator plant control system

Ukrainian Food Journal

... For example, a UAV flight control system must satisfy a number of conflicting requirements: reliability, simplicity of design, low cost, light weight and power consumption of actuators on the one hand, on the other hand: the accuracy of flight control in the conditions of external UAV perturbations. A compromise between different options can be achieved by use in the production of onboard UAV control system of modern intelligent control methods [19,20]: artificial neural [21]; fuzzy logic [22]; genetic algorithms. As follows, the relevance of the above studies is to develop an onboard UAV control system based on modern intellectual technologies, which will improve the quality and accuracy of stabilization of its motion parameters in the conditions of external disturbances. ...

Development of Logical Control System for the Purification Department at Molasses Production
  • Citing Chapter
  • January 2020

Advances in Intelligent Systems and Computing

... Ключові слова: випарювання, тиск пари, автоматизоване керування, прогнозування. ких речовин неможливе [1]. Отже, для запобігання перетримки та перегрівання цукрового сиропу слід забезпечити найкращі параметри контролю якості. ...

Comparison Between PID and Fuzzy Regulator for Control Evaporator Plants
  • Citing Conference Paper
  • April 2019