Adaptive recursive least squares algorithm for joint FIR filtering and pre-delay tracking and its application in the chemical industry process modeling

Author

Yu, Xingxing ; Zhang, Dali ; Yan, Pingfan

Author_Institution

Dept. of Autom., Tsinghua Univ., Beijing, China

fYear

1996

fDate

2-6 Dec 1996

Firstpage

13

Lastpage

17

Abstract

In this paper, the joint FIR filtering and pre-delay tracking system identification problem is considered. The input signal to the unknown system is first delayed then filtered. An adaptive recursive least squares algorithm based on fast transversal filters is developed and applied to the field data from the chemical industry process of some synthetic ammonia plant. In the simulation of 25 hours field running, it gives a relative prediction error no more than 3.6% and the modeling results are reasonable

Keywords

FIR filters; chemical technology; filtering theory; least squares approximations; recursive estimation; recursive filters; tracking; adaptive recursive least squares algorithm; chemical industry process modeling; fast transversal filters; joint FIR filtering; pre-delay tracking; relative prediction error; synthetic ammonia plant; system identification problem; Adaptive filters; Chemical industry; Delay estimation; Filtering algorithms; Finite impulse response filter; Least squares approximation; Least squares methods; Nonlinear filters; Predictive models; Transversal filters;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Technology, 1996. (ICIT '96), Proceedings of The IEEE International Conference on

Conference_Location

Shanghai

Print_ISBN

0-7803-3104-4

Type

conf

DOI

10.1109/ICIT.1996.601531

Filename

601531