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

Show simple item record

Author Katebi, S. D. en_US
Available date 2009-11-25T13:06:24Z en_US
Publication Date 1996 en_US
Citation Engineering Journal of Qatar University, 1996, Vol. 9, Pages 147-169. en_US
URI http://hdl.handle.net/10576/7978 en_US
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 en_US
Language en en_US
Publisher Qatar University en_US
Subject Engineering: Research & Technology en_US
Title Selection Of Optimized Fuzzy Rules For Process Control Systems: Using Genetic Algorithms en_US
Type Article en_US
Pagination 147-169 en_US
Volume Number 9 en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record