Особливості розробки інформаційно-управляючих систем для біотехнологічних об’єктів
Abstract
УДК 681.631
THE FEATURES OF INFORMATION CONTROL SYSTEMS FOR BIOTECHNOLOGICAL OBJECTS
Dudnyk A., PhD,
Lysenko V., Doctor of Science
e-mail: dudnikalla@mail.ua
The agricultural production in the world and Ukraine is filled with modern high-tech enterprises, the hallmark of which is the presence of a biological component. These companies are, first of all, poultry, greenhouses, mushroom production. The part of energy in production costs for these companies reach sometimes 70 % (greenhouses). Under the conditions of the high cost of energy and its actual deficits measures that reduce energy consumption are topical. Our analysis of international experience in the field of automation of control processes in agriculture showed that all of the existing control systems do not take into account possible future changes in the disturbances, in particular air temperature, on the technological object during the entire period of bioobject housing (growing), as well as the dynamics of bioobject states and perform exclusively stabilization mode for technological parameters, given the instantaneous values of the disturbances that is not always effective
With rampant increasing of energy prices is important to use control algorithms of electrotechnical complexes which accompany appropriate technology, taking into account the biological filling state and maximize production profit primarily by reducing energy costs. The intelligent control systems of electrotechnical objects are able to form such algorithms, which are used the theories of stochastic processes, neural networks, game theory and statistical decisions, etc.
Plants states are influenced by solar radiation. Thus, there is a need for analysis and forecasting of outside air temperature and solar radiation intensity for using the forecast results in the formation of electrotechnical complex control strategies with the aim to reduce energy costs in the production of agricultural products.
The solution of this problem is possible in two variants: the identification based on the theory of random processes images (areas) of natural disturbances that characterize the implementation of temperature; neural networks.
Unlike the prediction methods of the theory of random processes, neural network forecasting does not require statistical data on temperature changes in the past, their images developing a system that is running under uncertainty. However, it takes a long time to study and forecast reliability is sensitive to the quality of representation of input information, and cannot enter a priori (expert) information to accelerate learning network.
The research results of intelligent control systems of electrical complexes for biotechnological objects are given in this paper. The study of developed control system shown improving the system performance by 20 % over and reducing of natural gas consumption for heating by 13 % compared with control system that is based on the stabilization algorithm of technological parameters.
References
Lysenko, V. Greenhouse Environment Control System With Neural Network Predictions of External Disturbances / V. Lysenko, V. Reshetyuk, V. Shtepa, A. Dudnyk // Contemporary aspects of production engineering : XXII International students scientific conference, 22–25 May 2013 : abstract. – Warsaw, 2013. – P. 40–52.
Лисенко В. П. Методи і засоби створення структури бази даних для підсистеми моніторингу автоматизованих систем керування технологічними процесами [Електронний ресурс] / В. П. Лисенко, Б. Л. Голуб, А. О. Дудник. Режим доступу: http://archive.nbuv.gov.ua/e-journals/eia/2012_3/12lvp.pdf.
Нейромережеве прогнозування часових рядів температури навко-лишнього природного середовища / В. П. Лисенко, Н. А. Заєць, В. М. Штепа, А. О. Дудник // Біоресурси і природокористування. – К.:НААН України, 2011. – №3–4. – С.102–108.
Downloads
Published
Issue
Section
License
Relationship between right holders and users shall be governed by the terms of the license Creative Commons Attribution – non-commercial – Distribution On Same Conditions 4.0 international (CC BY-NC-SA 4.0):https://creativecommons.org/licenses/by-nc-sa/4.0/deed.uk
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).