DocumentCode
2273740
Title
Multi-objective genetic optimisation for self-organising fuzzy logic control
Author
Abbod, M.F. ; Mahfouf, M. ; Linkens, D.A.
Author_Institution
Sheffield Univ., UK
fYear
1998
fDate
1-4 Sep 1998
Firstpage
1575
Abstract
A multi-objective genetic algorithm is developed for the purpose of optimizing the rule-base of a self-organising fuzzy logic control algorithm (SOFLC). The tuning of the SOFLC optimization is based on selection of the best shaped performance index for modifying the rulebase online. A comparative study is conducted between various methods of multi-objective genetic optimisation using the SOFLC algorithm on a muscle relaxant anaesthesia system, which includes a severe nonlinearity, varying dynamics and time-delay
Keywords
genetic algorithms; best shaped performance index; multi-objective genetic optimisation; muscle relaxant anaesthesia system; self-organising fuzzy logic control; severe nonlinearity; time-delay; varying dynamics;
fLanguage
English
Publisher
iet
Conference_Titel
Control '98. UKACC International Conference on (Conf. Publ. No. 455)
Conference_Location
Swansea
ISSN
0537-9989
Print_ISBN
0-85296-708-X
Type
conf
DOI
10.1049/cp:19980464
Filename
726154
Link To Document