Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/68317
Type: Artigo de periódico
Title: Hierarchical fuzzy models within the framework of orthonormal basis functions and their application to bioprocess control
Author: Campello, RJGB
Von Zuben, FJ
Amaral, WC
Meleiro, LAC
Maciel, R
Abstract: Fuzzy models within the framework of orthonormal basis functions (OBF fuzzy models) have been introduced in previous works and shown to be a very promising approach to the areas of nonlinear system identification and control, since they exhibit several advantages over those dynamic model topologies usually adopted in the literature. As fuzzy models, however, they exhibit the dimensionality problem which is the main drawback to the application of neural networks and fuzzy systems to the modeling and control of large-scale systems. This problem has successfully been dealt with in the literature by means of hierarchical structures composed of submodels connected in cascade. In the present paper a hierarchical fuzzy model within the OBF framework is presented. A data-driven hybrid identification method based on genetic and gradient-based algorithms is described in details. A model-based predictive control scheme is also presented and applied to control of a complex industrial process for ethyl alcohol (ethanol) production. (C) 2003 Elsevier Ltd. All rights reserved.
Subject: hierarchical fuzzy models
orthonormal basis functions
predictive control
biotechnology
Country: Inglaterra
Editor: Pergamon-elsevier Science Ltd
Rights: fechado
Identifier DOI: 10.1016/S0009-2509(03)00309-9
Date Issue: 2003
Appears in Collections:Unicamp - Artigos e Outros Documentos

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