DocumentCode
2220625
Title
Fuzzy identification of nonlinear systems
Author
Ayday, Cem T. ; Eksin, Ibrahim
Author_Institution
Istanbul Tech. Univ., Turkey
fYear
1993
fDate
15-19 Nov 1993
Firstpage
289
Abstract
This paper presents a mathematical way of building a fuzzy model of any nonlinear system. The fuzzy implications of the system model and the least square identification method have been used to describe the nonlinear systems under study. The phase plane on which the nonlinear system is to be represented has been partitioned into fuzzy subregions and a linear fuzzy system model has been identified for each region. Then it has been observed that the overall system behavior has been characterized quite satisfactorily by using this partitioned fuzzy modelling
Keywords
fuzzy set theory; identification; modelling; nonlinear systems; fuzzy identification; least square identification method; linear fuzzy system model; nonlinear systems; overall system behavior; partitioned fuzzy modelling; Buildings; Equations; Fuzzy reasoning; Fuzzy sets; Fuzzy systems; Jacobian matrices; Least squares methods; Mathematical model; Nonlinear systems; Organizing;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Electronics, Control, and Instrumentation, 1993. Proceedings of the IECON '93., International Conference on
Conference_Location
Maui, HI
Print_ISBN
0-7803-0891-3
Type
conf
DOI
10.1109/IECON.1993.339065
Filename
339065
Link To Document