Strathprints Home | Open Access | Browse | Search | User area | Copyright | Help | Library Home | SUPrimo

Empirical comparison of methods of fuzzy relational identification

Postlethwaite, Bruce (1991) Empirical comparison of methods of fuzzy relational identification. IEE Proceedings Control Theory and Applications, 138 (3). pp. 199-206. ISSN 0143 7054

Full text not available in this repository. (Request a copy from the Strathclyde author)

Abstract

A number of methods have been proposed for the identification and self learning of relational fuzzy models. The paper compares some of the methods and looks at their tolerance to noise and to the choice of initial fuzzy ranges. Data from runs of a simulated fed-batch fermenter are used as a test case. The results show that identified relational models can give as good results as rule-based models and can be made to be very tolerant of noise in the identification data.

Item type: Article
ID code: 25681
Keywords: modelling, noise, interference, Chemical engineering, Instrumentation, Control and Systems Engineering, Electrical and Electronic Engineering
Subjects: Technology > Chemical engineering
Department: Faculty of Engineering > Chemical and Process Engineering
Related URLs:
Depositing user: Dr. Bruce Postlethwaite
Date Deposited: 29 Jun 2010 09:47
Last modified: 05 Sep 2014 04:25
URI: http://strathprints.strath.ac.uk/id/eprint/25681

Actions (login required)

View Item