Application of hierarchical neural fuzzy models to modeling and control of a bioprocess

Meleiro, L.A.C., Campello, R.J.G.B., Filho, R. Maciel, and Amaral, W.C. (2006) Application of hierarchical neural fuzzy models to modeling and control of a bioprocess. Applied Artificial Intelligence, 20 (9). pp. 797-816.

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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.

Item ID: 47620
Item Type: Article (Research - C1)
ISSN: 1087-6545
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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