Liu, Yan XinYan XinLiuShieh, Jiann ShingJiann ShingShiehSHOU-ZEN FANDoctor, FaiyazFaiyazDoctorJen, Kuo KuangKuo KuangJen2023-12-122023-12-122016-02-129781467396066https://scholars.lib.ntu.edu.tw/handle/123456789/637717In this paper, a novel genetic type-2 self-organising fuzzy logic controller (SOFLC) is proposed for anaesthesia control. The genetic type-2 SOFLC has a hierarchical structure consisting of three layers: a basic type-2 fuzzy logic controller, a self-organising mechanism for online adaption, and a genetic algorithm for offline optimisation. The genetic type-2 SOFLC is tested under different levels of environmental noise and compared with basic type-2 SOFLC that does not optimised. The results show that the proposed genetic type-2 SOFLC can perform better than the type-2 SOFLC in the presence of noise in terms of steady state error.anaesthesia | genetic algorithm | self-organizing fuzzy logic controller | type-2 fuzzy sets[SDGs]SDG15conference paper10.1109/TAAI.2015.74070832-s2.0-84964265451https://api.elsevier.com/content/abstract/scopus_id/84964265451