DocumentCode :
3551284
Title :
Least squares identification of non-stationary MA systems
Author :
Ding, Feng ; Shi, Yang ; Chen, Tongwen
Author_Institution :
Dept. of Test & Control Eng., Nanchang Inst. of Aeronaut. Technol., China
fYear :
2005
fDate :
8-10 June 2005
Firstpage :
4778
Abstract :
The correlation analysis based methods are not suitable for identifying parameters of non-stationary MA systems, for which two algorithms are developed, an iterative and a recursive multi-innovation least squares ones. The basic idea is to replace immeasurable noise terms in the information vector by the estimation residuals, which are computed also according to the parameter estimates. This is a hierarchical computation process. Furthermore, the conditions of convergence of the parameter estimation by the recursive algorithm are derived. The simulation results validate the algorithms proposed.
Keywords :
control system synthesis; convergence; least squares approximations; moving average processes; parameter estimation; predictive control; recursive estimation; AR models; ARMA models; auxiliary model identification; convergence properties; estimation residuals; hierarchical identification; iterative-recursive multiinnovation least squares; least squares identification; martingale convergence theorem; multi-innovation identification; noise terms; nonstationary MA systems; parameter estimation; recursive algorithm; Algorithm design and analysis; Computational modeling; Convergence; Iterative algorithms; Iterative methods; Least squares methods; Parameter estimation; Performance analysis; Signal processing algorithms; Time series analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference, 2005. Proceedings of the 2005
ISSN :
0743-1619
Print_ISBN :
0-7803-9098-9
Electronic_ISBN :
0743-1619
Type :
conf
DOI :
10.1109/ACC.2005.1470751
Filename :
1470751
Link To Document :
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