Adaptive Neuro-Fuzzy-Based Control of Drying of Baker's Yeast in Batch Fluidized Bed

Autor:	Uğur Yüzgeç, Mustafa Türker, Hasan Dincer, Mehmet Köni
Rok vydání:	2010
Předmět:	Engineering Adaptive neuro fuzzy inference system Neuro-fuzzy business.industry General Chemical Engineering Control (management) Control engineering Fuzzy logic Control theory Fluidized bed Control system Physical and Theoretical Chemistry business Hybrid learning algorithm
Zdroj:	Drying Technology. 28:205-213
ISSN:	1532-2300 0737-3937
DOI:	10.1080/07373930903524066
Popis:	A control system was designed using adaptive neuro-fuzzy inference system (ANFIS) for industrial-scale batch drying of baker's yeast. The temperature and flow rate of inlet air were considered as the manipulated variables to control the temperature and dry matter of the product, respectively, resulting in two adaptive fuzzy controllers. The membership functions for all inputs were adjusted by a hybrid learning algorithm. The database used in this work comprises large quantities of industrial-scale data (about 570 batches) obtained under different working conditions over one year. This database was used for learning and testing phases of the ANFIS controller. The performance of the proposed controller demonstrates the effectiveness and potential of the proposed ANFIS-based controller.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::6eb9716a9c6830ece3323d8889c3e742 https://doi.org/10.1080/07373930903524066 Zobrazit plný text záznamu Plný text ve formátu PDF Plný text ve formátu HTML
Nepřihlášeným uživatelům se plný text nezobrazuje	K zobrazení výsledku je třeba se přihlásit.