Title :
Fuzzy Modeling for Nonlinear System with Structured Data Uncertainty
Author :
Ding, Haishan ; Mao, Jianqin
Author_Institution :
Beijing Univ. of Aeronaut. & Astronaut., Beijing
Abstract :
In this paper, a new fuzzy modeling method with structured data uncertainty is proposed for nonlinear systems. The new robust modeling criterion, which aims to minimize the worst-case residual error, is formulated. The algorithm to obtain the approximate solutions of modeling problems under the new criterion is given in consideration of data uncertainty with a known structure. The new method is superior to the existing nonlinear modeling approaches. The advantages of the new method are illustrated by simulation results.
Keywords :
data structures; fuzzy set theory; fuzzy systems; nonlinear systems; uncertainty handling; fuzzy modeling; nonlinear system; structured data uncertainty; worst-case residual error; Binary trees; Fuzzy sets; Fuzzy systems; Inference algorithms; Modeling; Nonlinear systems; Parameter estimation; Robustness; Uncertainty;
Conference_Titel :
Fuzzy Systems, 2006 IEEE International Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-9488-7
DOI :
10.1109/FUZZY.2006.1681951