UPM Institutional Repository

A genetically trained adaptive neuro-fuzzy inference system network utilized as a proportional-integral-derivative-like feedback controller for non-linear systems.


Citation

Lutfy, Omar Farouq and Mohd Noor, Samsul Bahari and Marhaban, Mohammad Hamiruce and Ali Abbas, Kassim (2009) A genetically trained adaptive neuro-fuzzy inference system network utilized as a proportional-integral-derivative-like feedback controller for non-linear systems. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 223 (3). pp. 309-321. ISSN 0959-6518

Abstract

This paper presents a genetically trained PID (proportional-integral-derivative)-like ANFIS (adaptive neuro-fuzzy inference system) acting as a feedback controller to control non-linear systems. Three important issues are addressed in this paper, which are, first, the evaluation of the ANFIS as a PID-like controller; second, the utilization of the GA (genetic algorithm) alone to train the ANFIS controller, instead of the hybrid learning methods that are widely used in the literature; and, third, the determination of the input and output scaling factors for this controller by the GA. The GA, with real-coding operators, is used to adjust all of the ANFIS parameters, which include the input and output scaling factors, the centres and widths of the input membership functions (MFs), and the consequent parameters. To show the effectiveness of this controller and its learning method, several non-linear plants, including the CSTR (continuous stirred tank reactor), have been selected to be controlled by this controller through simulation. Moreover, this controller's robustness to output disturbances has also been tested and the results clearly indicated the remarkable performance of this controller and its learning algorithm. In addition, the result of comparing the performance of this controller with a genetically tuned classical PID controller has shown the superiority of the PID-like ANFIS controller.


Download File

[img]
Preview
PDF (Abstract)
A genetically trained adaptive neuro.pdf

Download (84kB) | Preview

Additional Metadata

Item Type: Article
Divisions: Faculty of Engineering
DOI Number: https://doi.org/10.1243/09596518JSCE683
Publisher: SAGE Publications
Keywords: ANFIS; Classical PID controller; Genetic algorithms; Neuro-fuzzy systems.
Depositing User: Fatimah Zahrah @ Aishah Amran
Date Deposited: 23 Jul 2014 05:29
Last Modified: 05 Oct 2015 06:06
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1243/09596518JSCE683
URI: http://psasir.upm.edu.my/id/eprint/12702
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item