自动化学报2012，Vol.38Issue(3)：491-496,6.DOI:10.3724/SP.J.1004.2012.00491
基于偏差消除最小二乘估计和Durbin方法的两阶段ARMAX参数辨识
Two-stage ARMAX Parameter Identification Based on Bias-eliminated Least Squares Estimation and Durbin's Method
摘要
Abstract
This paper proposes a two-stage identification approach for the parameter identification of autoregressive moving average with exogenous variable (ARMAX) model. First, a bias-eliminated least squares method is employed to identify the autoregressive part with exogenous variable (ARX). Then, the Durbin's method is employed to transform the parameter identification of the moving average (MA) part into that of a long autoregressive (AR) model. The MA parameters are derived directly from the parameter relationship between the MA part and its equivalent long AR model. Finally, the noise variance can be computed by using the identified MA parameters. The performance comparison against the extended least-squares method in numerical simulations validates the effectiveness of the two-stage identification approach.关键词
自回归移动平均模型/参数辨识/Durbin方法/偏差消除最小二乘法Key words
Autoregressive moving average with exogenous variable (ARMAX) model/parameter identification/Durbin's method/bias-eliminated least squares method引用本文复制引用
辛斌,白永强,陈杰..基于偏差消除最小二乘估计和Durbin方法的两阶段ARMAX参数辨识[J].自动化学报,2012,38(3):491-496,6.基金项目
国家杰出青年科学基金(60925011)资助 （60925011）
