Hierarchical fuzzy models within the framework of orthonormal basis functions and their application to bioprocess control

Campello, R.J.G.B., Von Zuben, F.J., Amaral, W.C., Meleiro, L.A.C., and Maciel Filho, R. (2003) Hierarchical fuzzy models within the framework of orthonormal basis functions and their application to bioprocess control. Chemical Engineering Science, 58 (18). pp. 4259-4270.

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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.

Item ID: 47624
Item Type: Article (Research - C1)
ISSN: 1873-4405
Keywords: hierarchical fuzzy models, orthonormal basis functions, predictive control, biotechnology
Date Deposited: 08 Mar 2017 07:40
FoR Codes: 01 MATHEMATICAL SCIENCES > 0102 Applied Mathematics > 010299 Applied Mathematics not elsewhere classified @ 100%
SEO Codes: 97 EXPANDING KNOWLEDGE > 970101 Expanding Knowledge in the Mathematical Sciences @ 100%
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