Title :
Modeling technology for (T,p)-ρ table in mass flow-meter
Author :
Jian-guo, Han ; Wu You-Hua ; Jiu-Xi, Liu
Author_Institution :
Beijing Univ. of Chem. Technol., China
Abstract :
A method based on the training technology of a fuzzy inference adaptive artificial neural network and nonlinear least-square (linear in structure) system identification technology for modeling the (T,P)-ρ table for a mass flow-meter is introduced. The model has several advantages such as saving calculation workload and storage space, having essential filterability. Thus the method is an effective help for the current development of high-degree integration technology of measuring and instrumentation
Keywords :
digital simulation; flowmeters; fuzzy logic; fuzzy neural nets; identification; least squares approximations; (T,p)-ρ table; fuzzy inference adaptive artificial neural network; high-degree integration technology; mass flow-meter; modeling technology; nonlinear least-square system identification technology; training technology; Adaptive systems; Artificial neural networks; Current measurement; Fuzzy neural networks; Fuzzy systems; Instruments; Space technology; System identification;
Conference_Titel :
SICE 2000. Proceedings of the 39th SICE Annual Conference. International Session Papers
Conference_Location :
Iizuka
Print_ISBN :
0-7803-9805-X
DOI :
10.1109/SICE.2000.889659
