DocumentCode :
345807
Title :
A new criteria for input variable identification of dynamical systems
Author :
Azeem, M. Fazle ; Hanmandlu, M. ; Ahmad, Nesar
Author_Institution :
Dept. of Electr. Eng., Indian Inst. of Technol., New Delhi, India
Volume :
1
fYear :
1998
fDate :
1998
Firstpage :
230
Abstract :
The concept of the approximate fuzzy data model (AFDM) is introduced. An attempt is made for input variable identification for fuzzy modeling of dynamical systems using the fuzzy curve, which is the output of AFDM. An output ratio is defined based on AFDM and system output that gives rise to the proposed criteria whose effectiveness is demonstrated by experimentation on mathematical models as well as by simulation on a few examples of dynamical systems. The proposed criteria thus serve as a significance test for the identification of inputs that actually affect the output
Keywords :
approximation theory; fuzzy systems; identification; process control; approximate fuzzy data model; chemical plant; dynamical systems; fuzzy curve; gas furnace; human operation; input variable identification; input-output data; mathematical models; output ratio; process control; significance test; simulation; system output; Data models; Educational institutions; Fuzzy systems; Input variables; Mathematical model; Performance analysis; System testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
TENCON '98. 1998 IEEE Region 10 International Conference on Global Connectivity in Energy, Computer, Communication and Control
Conference_Location :
New Delhi
Print_ISBN :
0-7803-4886-9
Type :
conf
DOI :
10.1109/TENCON.1998.797128
Filename :
797128
Link To Document :
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