Título Fuzzy Model Predictive Control: Complexity Reduction for Implementation in Industrial Systems
Autores Escaño J.M. , Bordons C. , Witheephanich K. , GÓMEZ-ESTERN AGUILAR, FABIO
Publicación externa No
Medio International Journal of Fuzzy Systems
Alcance Article
Naturaleza Científica
Cuartil JCR 1
Cuartil SJR 2
Impacto JCR 4.406
Impacto SJR 0.758
Web https://www.scopus.com/inward/record.uri?eid=2-s2.0-85069722057&doi=10.1007%2fs40815-019-00693-z&partnerID=40&md5=1d6e5fb8cb41c5c7e77f2a9f97e04539
Fecha de publicacion 01/01/2019
ISI 000493567300002
Scopus Id 2-s2.0-85069722057
DOI 10.1007/s40815-019-00693-z
Abstract In this paper, a new fuzzy logic-based control-design technique is presented. The method aims at reducing the complexity of Takagi-Sugeno Fuzzy systems via the reduction of fuzzy rules. This reduction is obtained by finding a function basis via the Functional Principal Component Analysis, and then the model is used for Model Predictive Control (MPC). This procedure is systematic, and eventually leads to feasible low-cost microcontroller-based implementations, which has become a generic need in the era of IoT. In order to validate the results, two experimental setups have been controlled using these principles. The first of these, a mechanical pendulum, presents nonlinear dynamics that suggests the use of linear discrete models at specific operating points. In the second, a pilot plant implementing an industrial process with a chemical reactor and a heat exchanger, presents nonlinear multivariate dynamics that are successfully handled with the Fuzzy MPC Controller. © 2019, Taiwan Fuzzy Systems Association.
Palabras clave Controllers; Feedback control; Fuzzy inference; Fuzzy logic; Pilot plants; Predictive control systems; Principal component analysis; Complexity reduction; Functional principal component analysis; Fuzzy logic based control; Fuzzy model predictive control; Industrial processs; Industrial systems; Specific operating point; Takagi Sugeno fuzzy systems; Model predictive control
Miembros de la Universidad Loyola

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