Digital twin with augmented state extended Kalman filters for forecasting electric power consumption of industrial production systems

BALDASSARRE, A.; Dion, Jean‐Luc; Peyret, Nicolas; Renaud, Franck

doi:10.1016/j.heliyon.2024.e27343

Public

Digital twin with augmented state extended Kalman filters for forecasting electric power consumption of industrial production systems

Published in Heliyon • Mar 1, 2024

Authors:

A. BALDASSARRE

Jean‐Luc Dion

Nicolas Peyret

Abstract

The work aims to develop an effective tool based on Digital Twins (DTs) for forecasting electric power consumption of industrial production systems. DTs integrate dynamic models combined with Augmented State Extended Kalman Filters (ASEKFs) in a learning process. The connection with the real counter...

Subject

Kalman filter

Context (archaeology)

Computer science

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