Simple Search:

Intelligent modeling and control of a conveyor belt grain dryer using a simplified type 2 neuro-fuzzy controller


Citation

Lutfy, Omar F. and Selamat, Hazlina and Mohd Noor, Samsul Bahari (2015) Intelligent modeling and control of a conveyor belt grain dryer using a simplified type 2 neuro-fuzzy controller. Drying Technology, 33 (10). pp. 1210-1222. ISSN 0737-3937; ESSN: 1532-2300

Abstract / Synopsis

In this article, a nonlinear autoregressive with exogenous input (NARX) network was utilized to model a conveyor belt grain dryer using a set of input–output data collected during an experiment to dry paddy grains. The resulting NARX model has achieved a remarkable modeling accuracy compared to other previously reported modeling techniques. To control the considered dryer, a simplified type 2 adaptive neuro-fuzzy inference system (ANFIS) controller was proposed. The effectiveness of this controller was demonstrated by several performance tests conducted by computer simulations. Moreover, a comparative study with other related controllers further confirmed the superiority of the proposed dryer controller.


Download File

[img]
Preview
PDF (Abstract)
Intelligent modeling and control of a conveyor belt grain dryer using a simplified type 2 neuro-fuzzy controller.pdf

Download (48kB) | Preview

Additional Metadata

Item Type: Article
Divisions: Faculty of Engineering
DOI Number: 10.1080/07373937.2015.1021007
Publisher: Taylor & Francis
Keywords: Conveyor belt grain dryer; Genetic algorithm; System identification; Type 2 neuro-fuzzy controller
Depositing User: Nabilah Mustapa
Date Deposited: 26 Nov 2008 23:50
Last Modified: 30 Mar 2018 16:23
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1080/07373937.2015.1021007
URI: http://psasir.upm.edu.my/id/eprint/782
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item