Selection Of Optimized Fuzzy Rules For Process Control Systems: Using Genetic Algorithms

QSpace/Manakin Repository

Selection Of Optimized Fuzzy Rules For Process Control Systems: Using Genetic Algorithms

Show full item record


Title: Selection Of Optimized Fuzzy Rules For Process Control Systems: Using Genetic Algorithms
Author: Katebi, S. D.
Abstract: In this paper modeling, selection and optimization of fuzzy rules for multivariable feedback process control and decision making systems are developed and discussed. A general model for multivariable fuzzy rules is derived and sets of fuzzy parameters are assigned to the consequents of each rule. A genetic algorithm is used to optimize these parameters. A genetic algorithm search technique is also developed for the selection of the sub-set of appropriate rules from a larger theoretically possible set. The procedure is implemented on a multivariable dynamic model and results of extensive simulation studies are presented to demonstrate a satisfactory performance of the proposed approach
URI: http://hdl.handle.net/10576/7978
Date: 1996

Files in this item

Files Size Format View
abstract.pdf 1.958Kb PDF View/Open
abstract.doc 20Kb Microsoft Word View/Open
06-96-9-0010-fulltext.pdf 731.3Kb PDF View/Open

This item appears in the following Collection(s)

Show full item record

Search QSpace


Advanced Search

Browse

My Account