Publication

Energy consumption dynamical models for smart factories based on subspace identification methods

Conference Article

Conference

IEEE Colombian Conference on Automatic Control (CCAC)

Edition

4th

Pages

6

Doc link

https://doi.org/10.1109/CCAC.2019.8921089

File

Download the digital copy of the doc pdf document

Abstract

Given the need of implementing methodologies in industry for the reduction of the energy consumption costs, it is required to create modelling methodologies that, together with the use of new technologies, will allow identifying energy consumption models based on input-output data. These models will later be used to design a suitable model-based control strategy. In this paper, a subspace identification algorithm based on the RQ decomposition approach has been reported, which is both implemented and validated on a test-bench that emulates the energy consumption of an industrial machine within a manufacturing process. Subsequently, the resultant model fitting when using the proposed modelling methodology has been compared with different identification routines included into the MATLAB System Identification Toolbox™, showing, in general, better results for the proposed methodology in this paper, with up to almost 80% of fitting in some cases.

Categories

control theory.

Author keywords

Industry 4.0, Industrial production systems, modeling, Energy consumption models, subspace identification, RQ decomposition

Scientific reference

M.A. Bermeo and C. Ocampo-Martínez. Energy consumption dynamical models for smart factories based on subspace identification methods, 4th IEEE Colombian Conference on Automatic Control, 2019, Medellin, Colombia, pp. 6.