Paper:
Language: English:

SIRMs Connected Fuzzy Inference Model Applied to Process Control -- Automatic Tuning Using a Genetic Algorithm Carla Cavalcante

Koike^* and Kaoru Hirota^**

*Departamento de Engenharia Mecanica e Engenharia, Universidadl de Brasilia
**Department of Computational Intelligence and Systems Science Interdisciplinary Graduate School of Science and Engineering Tokyo Institute of Technology

Received: November 20, 1998

Accepted: March 4, 1999

Keywords: Fuzzy inference, Genetic algorithm, Automatic tuning

Journal ref: Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.3, No.4 pp. 299-302, 1999

Abstract

A tuning process proposed for the single input rule modules (SIRMs) connected inference model is applied to process control. Using a genetic algorithm (GA), the importance degree is adjusted to improve process response. Simulation using first-order processes with dead time verified the validity of this approach.

[Notice]
* "Preview" is the first 2 pages of the article. You don't need the registration.
* To read the PDF file you will then need to download and install the Adobe Reader.
Adobe Reader is free and available for download here: