Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Energy consumption dynamical models for smart factories based on subspace identification methods
Trabajo presentado en el 4th Colombian Conference on Automatic Control (CCAC), celebrado en Medellín (Colombia), del 15 al 18 de octubre de 2019 ; 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. ; This work has been funded by the project IKERCON (ref. C10683).
Energy consumption dynamical models for smart factories based on subspace identification methods
Trabajo presentado en el 4th Colombian Conference on Automatic Control (CCAC), celebrado en Medellín (Colombia), del 15 al 18 de octubre de 2019 ; 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. ; This work has been funded by the project IKERCON (ref. C10683).
Energy consumption dynamical models for smart factories based on subspace identification methods
Bermeo, Miguel (Autor:in) / Ocampo-Martinez, Carlos (Autor:in)
15.10.2019
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
DDC:
690
Enhancing Sustainability and Energy Efficiency in Smart Factories: A Review
DOAJ | 2018
|Subspace identification of low-order reservoir models
British Library Conference Proceedings | 2002
|Hyperspectral Subspace Identification
Online Contents | 2008
|Prediction Models of Energy Consumption in Smart Urban Buildings
Springer Verlag | 2020
|