Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/4835
Title: Multi-objective genetic optimisation for self-organising fuzzy logic control
Authors: Abbod, MF
Mahfouf, M
Linkens, DA
Keywords: Fuzzy logic;Self-organising;Multi-objective optimisation
Issue Date: 1998
Publisher: IEEE
Citation: IEE Conference Publication, 2(455): 1575-1580, Sep 1998
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 rule-base on-line. A comparative study is conducted between various methods of multi-objective genetic optimisation using the SOFLC algorithm on the muscle relaxant anaesthesia system, which includes a severe non-linearity, varying dynamics and time-delay.
Description: This is the post-print version of the article. The official published version can be accessed from the link below.
URI: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=726154
http://bura.brunel.ac.uk/handle/2438/4835
DOI: http://dx.doi.org/10.1049/cp:19980464
ISBN: 0-85296-708-X
ISSN: 0537-9989
Appears in Collections:Electronic and Computer Engineering
Dept of Electronic and Computer Engineering Research Papers

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