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
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;
Conference_Titel :
Control '98. UKACC International Conference on (Conf. Publ. No. 455)
Conference_Location :
Swansea
Print_ISBN :
0-85296-708-X
DOI :
10.1049/cp:19980464
