Delay Time Identification and Dynamic Characteristics Study on ANN Soft Sensor

Author

Du, Dianlin ; Wu, Chongguang ; Luo, Xionglin ; Zuo, Xin

Author_Institution

Inf. Sci. & Technol. Coll., Beijing Univ. of Chem. Technol.

Volume

1

fYear

2006

fDate

16-18 Oct. 2006

Firstpage

42

Lastpage

45

Abstract

Soft sensor software based on ANN (artificial neural network) using BP or RBF was developed to estimate unmeasured variables such as product quality online. Some important topics including how to determine the delay time, how to simulate the dynamic system were discussed and solved. We applied a 3 layers BP network to identify the delay time of nonlinear system, feedback output variables to input layer, and weight of all the input variables to describe dynamic characteristics of the system. This makes the ANN soft sensor reflect truly both the static and dynamic characteristics of the system and provide more adaptability

Keywords

backpropagation; delays; feedback; nonlinear systems; radial basis function networks; supervisory programs; ANN soft sensor software; adaptability; artificial neural network; backpropagation network; delay time identification; dynamic system characteristics; dynamic system simulation; feedback output variable; nonlinear system; radial basis function; unmeasured variable estimation; Artificial neural networks; Chemical sensors; Delay effects; Delay estimation; Mathematical model; Neural networks; Nonlinear dynamical systems; Sensor phenomena and characterization; Sensor systems; Time measurement; artificial neural network; delay; dynamic system; soft sensor; time;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Systems Design and Applications, 2006. ISDA '06. Sixth International Conference on

Conference_Location

Jinan

Print_ISBN

0-7695-2528-8

Type

conf

DOI

10.1109/ISDA.2006.131

Filename

4021406