APPLICATION OF HIERARCHICAL NEURAL FUZZY MODELS TO MODELING AND CONTROL OF A BIOPROCESS

Autor:	L.A.C. Meleiro, R. Maciel Filho, Ricardo J. G. B. Campello, Wagner Caradori do Amaral
Rok vydání:	2006
Předmět:	Adaptive neuro fuzzy inference system Artificial neural network Neuro-fuzzy Computer science Process (engineering) business.industry Control engineering Machine learning computer.software_genre Fuzzy logic Set (abstract data type) Artificial Intelligence ComputingMethodologies_GENERAL Artificial intelligence business computer Servo Curse of dimensionality
Zdroj:	Applied Artificial Intelligence. 20:797-816
ISSN:	1087-6545 0883-9514
DOI:	10.1080/08839510600941379
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::c7b413aaae20a355e3c4c6bca8fff2ff https://doi.org/10.1080/08839510600941379 Zobrazit plný text záznamu Plný text ve formátu PDF Plný text ve formátu HTML
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