Title :
Fuzzy modeling based on L2 gain criterion
Author :
Hori, Tsuyoshi ; Taniguti, Tadanari
Author_Institution :
Dept. of Mech. Eng. & Intelligent Syst., Univ. of Electro-Commun., Chofu, Japan
Abstract :
This paper presents a robust fuzzy modeling based on L2 gain criterion. The most important thing is that fuzzy modeling executes using LMI conditions. We derive an LMI condition to identify the parameters of a Takagi-Sugeno fuzzy model (T-S fuzzy model). The LMI guarantees to minimize the summation of the upper bound of the identification error (SUE) between outputs of a real plant and those of a T-S fuzzy model. More importantly, we derive L2 gain based fuzzy modeling conditions. It achieves robust parameter identification for the data contaminated by noise. An example shows the utility of the proposed iterative LMI approach to L2 gain based fuzzy modeling
Keywords :
automatic gain control; fuzzy control; fuzzy set theory; intelligent control; minimisation; nonlinear systems; parameter estimation; uncertainty handling; L2 gain based fuzzy modeling; L2 gain criterion; LMI conditions; SUE; T-S fuzzy model; Takagi-Sugeno fuzzy model; data contamination; fuzzy modeling conditions; identification error; iterative LMI approach; robust fuzzy modeling; robust parameter identification; Bismuth; Control system synthesis; Fuzzy control; Fuzzy systems; Nonlinear control systems; Nonlinear dynamical systems; Nonlinear equations; Nonlinear systems; Parameter estimation; Robustness;
Conference_Titel :
IFSA World Congress and 20th NAFIPS International Conference, 2001. Joint 9th
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-7078-3
DOI :
10.1109/NAFIPS.2001.944676
