Title Estimador Neuro-borroso, con reducción de complejidad, de las temperaturas de un campo solar cilindro-parabólico
Authors Escaño J.M. , Sánchez A.J. , CEBALLOS GONZÁLEZ, MANUEL, Gallego A.J. , Camacho E.F.
External publication No
Scope Article
Nature Científica
JCR Quartile 4
SJR Quartile 2
JCR Impact 1.25
SJR Impact 0.446
Web https://www.scopus.com/inward/record.uri?eid=2-s2.0-85105305874&doi=10.4995%2fRIAI.2020.13261&partnerID=40&md5=eda98fe601c8d13f5b481a238f65cebf
Publication date 01/01/2021
ISI 000679476000007
Scopus Id 2-s2.0-85105305874
DOI 10.4995/RIAI.2020.13261
Abstract The estimation of unobservable states of a process is important when state space control techniques are applied. These controllers assume that states values are known. When all the states are measurable, there is no need to apply any observer. The case of the solar trough plants using a distributed parameters model presents many state variables which cannot be measured with sensors. In this work an observer based on a fuzzy inference system to estimate the temperature profiles of the loops that make up the solar field is presented. A complexity reduction technique based on Functional Principal Analysis is applied to make the estimator realizable in practice without occupying much memory or spend so much time in its programming in industrial devices. © 2021 Universitat Politecnica de Valencia. All rights reserved.
Keywords Distributed parameter control systems; Functional programming; Fuzzy neural networks; Complexity reduction; Distributed parameters models; Fuzzy inference systems; Industrial devices; Parabolic trough; State-space control; Temperature profiles; Unobservable state; Fuzzy inference
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