A kind of new self-tuning filter and its application

Author

Zhen, Zhu ; Bingkun, Gao ; Tienan, Liu ; Changjiang, Zhang ; Di, Yu

Author_Institution

Dept. of Autom. & Control Eng., Daqing Pet. Inst., Heilongjian, China

Volume

3

fYear

2000

fDate

2000

Firstpage

2215

Abstract

The CARMA model of the systems are developed by system identification methods and its parameters are estimated. Moreover, the state space models of the systems are given according to the lemma of time sequence models and state space models. A new self-tuning filter is described. It comprises the recursive extended least square estimator, Kalman filter and noise statistical estimator. Applied to oil field systems, excellent results were obtained. Validity of the new scheme is indicated

Keywords

Kalman filters; autoregressive moving average processes; estimation theory; filtering theory; least squares approximations; parameter estimation; state-space methods; CARMA model; Kalman filter; identification; least square estimator; noise statistical estimator; parameter estimation; self-tuning filter; state space models; time sequence models; Automatic control; Automation; Filters; Least squares approximation; Lubricating oils; Parameter estimation; Petroleum; Recursive estimation; State-space methods; System identification;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on

Conference_Location

Hefei

Print_ISBN

0-7803-5995-X

Type

conf

DOI

10.1109/WCICA.2000.862996

Filename

862996