Development of algorithms for prediction of the technological process

This article discusses the development of algorithms for predicting and automatically controlling the process of microalgae cultivation. For the operational management of production, it is necessary to be able to evaluate the values of the criterion during the process for short periods of time and p...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:E3S web of conferences 2023-01, Vol.449, p.4010
Hauptverfasser: Rakhmanov, Sh.R., Turaev, K.
Format: Artikel
Sprache:eng
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:This article discusses the development of algorithms for predicting and automatically controlling the process of microalgae cultivation. For the operational management of production, it is necessary to be able to evaluate the values of the criterion during the process for short periods of time and predict the influence of control actions on the optimality criterion. Since the cultivation process can be carried out in periodic or continuous modes, it is necessary to consider the possibilities and conditions for choosing the optimality criterion. For continuous mode, when at each moment of time the state of the process is determined only by the parameters of the state and does not depend on the state of the process at previous moments of time, an estimation instant can be used. In this case, the criterion will have the meaning of the instantaneous value of the process productivity, referred to profit. In this case, it is a criterion that is directly related to the profit of the considered class of objects. Therefore, it is expedient to choose an optimality criterion in the form of a target product maximization problem. It follows from this expression that for N cultivators connected in series, the total residence time T = 1/λ N must be distributed equally among all cultivators, if individually they have the same volume.
ISSN:2267-1242
2267-1242
DOI:10.1051/e3sconf/202344904010