Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/54744
Type: Artigo de periódico
Title: Application of hierarchical neural fuzzy models to modeling and control of a bioprocess
Author: Meleiro, LAC
Campello, RJGB
Maciel, R
Amaral, WC
Abstract: Hierarchical structures have been introduced in the literature to deal with the dimensionality problem, which is the main drawback to the application of neural networks and fuzzy models to modeling and control of large-scale systems. In the present work, hierarchical neural fuzzy (HNF) models are reviewed, focusing on the model-based control of a biotechnological process. The model considered here consists of a set of neural fuzzy systems connected in cascade and is used in the modeling of an industrial plant for ethyl alcohol ( ethanol) production. Based on the HNF model of the process, a nonlinear model predictive controller (HNF-MPC) is designed and applied to control the process. The performance of the HNF-MPC is illustrated within servo and regulatory scenarios.
Country: EUA
Editor: Taylor & Francis Inc
Rights: fechado
Identifier DOI: 10.1080/08839510600941379
Date Issue: 2006
Appears in Collections:Unicamp - Artigos e Outros Documentos

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