Title :
Fuzzy control based on new type of Takagi-Sugeno fuzzy inference system
Author :
Anikin, Igor V. ; Zinoviev, Igor P.
Author_Institution :
Inf. Security Syst. Dept., Kazan Nat. Res. Tech. Univ. named after A.N.Tupolev-KAI, Kazan, Russia
Abstract :
We suggested new type of fuzzy inference systems (FIS) based on Takagi-Sugeno. We called it enhanced fuzzy regression (EFR). New FIS uses fuzzy coefficients in right parts of the fuzzy rules. Fuzzy approximation theorem has been proved and learning procedure has been suggested for the EFR. We compared EFR with Mamdani FIS and concluded that EFR can be more effective for fuzzy control.
Keywords :
approximation theory; fuzzy control; fuzzy reasoning; learning (artificial intelligence); regression analysis; EFR; FIS; Takagi-Sugeno fuzzy inference system; enhanced fuzzy regression; fuzzy approximation theorem; fuzzy coefficients; fuzzy control; fuzzy rules; learning procedure; Approximation methods; Fuzzy control; Knowledge based systems; Mathematical model; Pragmatics; Takagi-Sugeno model; Takagi-Sugeno fuzzy inference system; fuzzy control; fuzzy logic;
Conference_Titel :
Control and Communications (SIBCON), 2015 International Siberian Conference on
Conference_Location :
Omsk
Print_ISBN :
978-1-4799-7102-2
DOI :
10.1109/SIBCON.2015.7146977
