Intellectual agents of targets in analytical constructing of optimum systems of management of drum mills
DOI:
https://doi.org/10.33271/crpnmu/64.264Keywords:
quasi-optimal system, optimum management, analytical constructing, intellectual agents, mining complexes, drum millsAbstract
Purpose. Justification of the rational use of intellectual agents in forming of the quasi-optimal systems of management furnaces of complexes of type drum mills as observers of complete order. A method of research consists of decision of the best laws management by the mining complexes by the use of methods of the analytical constructing of optimum regulators withthe input in their structures of such essences as intellectual agents as observers of complete order. Results of research. Management by the mining and processing complexes it is perspective to carry out on the basis of the quasi-optimal systems of management. Taking into account properties and sensitiveness of intellectual agents, expediently to include them at the analytical constructing of regulators in the structure of observers of complete order. This increases in accordance with securing functional of quality criterion of exactness of optimum stabilization of rational technology of process of growing shallow in the drum mills. Scientific novelty. A new structure is set of the quasi-optimal system of management by the technological dynamics of drum mills with the asymptotic observer of complete order. Of efficiency of recognition and operative management it is suggested to carry the rise out on the basis of functional possibilities of intellectual agents of targets, as which an observer comes forward of complete order in aggregate with the considered technological processes in the mining and processing complexes. Practical value. Results of researches allow to recommend a rational chart of quasi-optimal management by the drum mills in accordance with the set criterion. In the spectrum of the active power consumable by the drive electric motor technological constituents are selected, which are conditioned by the difficult vibrations of ore mass of filling of drum. Their maximal values are selected ekstremum by detector and are watched by the observer of complete order with the optimum stabilization. This allows to secure intensification of return of the prepared class.References
1. Мещеряков, Л. І., Галушко, О. М., Сироткіна, О. І., & Демідов, О. Т. (2019). Розпізнавання технологічних станів барабанних млинів на основі нейронних мереж адаптивного резонансу. Збірник наукових праць Національного гірничого університету , (57), 129-137.
2. Meshcheriakov, L., Tokar, L., & Ziborov, К. (2015). Identification of stabilizing modes for the basic parameters of drilling tools. Power Engineering, Control and Information Technologies in Geotechnical Systems , 135-142. https://doi.org/10.1201/b18475-19
3. Мещеряков, Л. І., Випанасенко, С. І., Дрешпак, Н. С., & Ширін, А. Л. (2018). Формування структури підсистеми діагностування гірничих електромеханічних комплексів. Збірник наукових праць Національного гірничого університету , (53), 213-221.
4. Мещеряков, Л. І., Ясир, Ю. Х. А. Х., & Зубарев, А. И. (2010). Программное обеспечение идентификации состояний барабанных мельниц. Збірник наукових праць Національного гірничого університету , (34 (1)), 267-274.
5.Мещеряков, Л. И., Дудля, Н. А., Бородай, В. А., Хархардина, Д. В., & Ясир, Ю.Х.А.Х. (2011). Исследование воздействия технологических нагрузок на локально устойчивые состояния барабанных мельниц. Збірник наукових праць Національного гірничого університету , (36 (2)), 28-36.
Downloads
Published
Issue
Section
License
All articles are published under the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Authors retain copyright and grant the journal right of first publication.
Authors are permitted and encouraged to deposit the final published version of their article, or the Author's Accepted Manuscript (AAM), in institutional or subject-specific open-access repositories (including the university's own institutional repository, CORE, Zenodo, or Figshare), ensuring maximum visibility, accessibility, and impact of the publication.