DocumentCode :
354100
Title :
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
Link To Document :
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