Energy consumption dynamical models for smart factories based on subspace identification methods
Document typeConference report
Rights accessOpen Access
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.
© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works
CitationBermeo, M.; Ocampo-Martinez, C.A. Energy consumption dynamical models for smart factories based on subspace identification methods. A: Colombian Conference on Automatic Control. "4th IEEE Colombian Conference on Automatic Control". 2019, p. 1-16.