Multi-objective Genetic Optimisation for Self-organising Fuzzy Logic Control
نویسندگان
چکیده
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 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 nonlinearity, varying dynamics and time-delay.
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تاریخ انتشار 2011