Neuro-fuzzy Modelling of a Linear Fresnel-type Solar Collector System as a Digital Twin

Abstract

One of the main components of a Digital Twin is the modeling of the virtual entity, being this a high-fidelity digital model of the physical entity that represents the modeling of geometry, modeling of physical properties, modeling of behavior, and modeling of rules in the virtual world.This paper presents a model, based on an Adaptive Neuro-Fuzzy Inference System, of a Fresnel linear solar collector system as a Digital Twin, located on the roof of the School of Engineering of the University of Seville, which is a part of an absorption cooling plant.A distributed parameter model of the system has been used to generate artificial data. Real operating data were used to validate the model.

Implementing Industry 4.0: An In-Depth Case Study Integrating Digitalisation and Modelling for Decision Support System Applications

“…Once ANFIS completes its learning process, it generates a fuzzy inference system (FIS) that can be considered a grey-box model as the rules defining the system's behaviour can be extracted from it [28]. Furthermore, this modeling technique offers advantages such as fast update ability and quick execution, as mentioned in [29,30].…”

“…The proposed modelling approach integrates principal component analysis (PCA) with ANFIS, following the methodology presented in [29,33]. PCA is applied to normalised data sets to reduce their input space, resulting in the loading matrix s C, which contains the coefficients of the principal components of each variable.…”