Сибирский федеральный университет

Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций

Конференция: 6 September 2020 through 12 September 2020; 163576; 163576

Год издания: 2020

Идентификатор DOI: 10.1109/RusAutoCon49822.2020.9208187

Ключевые слова: autocorrelation function, control theory, dynamic system, integral indicator, planning horizon, production system, strategy

Аннотация: The production system (multidimensional object) is considered as a dynamic system with discrete time. Formalized: space (state of the object, control actions, goals, observed values, analytical estimates). Analytical estimates of the state of a dynamic system are formed through the autocorrelation function. The autocorrelation function is calculated with the regulator setting the length of the analyzed time series (analysis depth). A digital copy of the production system is created, characterized by 1.2 million parameters. Modeling the activities of the production system is performed in the author's complex of programs. In total, twenty-eight controller states are calculated to analyze the effect of repeating parameters affecting the activity of the production system. The simulation shows the cyclical dynamics of changes in the autocorrelation function. Formalization of the production system is carried out, which allows you to move on to other methods of analysis of the production system: Kalman filter, neural network forecast, recurrence equation, balances. © 2020 IEEE.

Журнал: Proceedings - 2020 International Russian Automation Conference, RusAutoCon 2020

Номера страниц: 989-993

Издатель: 2020 International Russian Automation Conference, RusAutoCon 2020

• Masaev S. (Siberian Federal University, Institute of Oil and Gas, Krasnoyarsk, Russian Federation)

• Scopus
• РИНЦ (eLIBRARY.RU)