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2014 Data Filtering Based Recursive Least Squares Algorithm for Two-Input Single-Output Systems with Moving Average Noises
Xianling Lu, Wei Zhou, Wenlin Shi
J. Appl. Math. 2014: 1-8 (2014). DOI: 10.1155/2014/694053

Abstract

This paper studies identification problems of two-input single-output controlled autoregressive moving average systems by using an estimated noise transfer function to filter the input-output data. Through data filtering, we obtain two simple identification models, one containing the parameters of the system model and the other containing the parameters of the noise model. Furthermore, we deduce a data filtering based recursive least squares method for estimating the parameters of these two identification models, respectively, by replacing the unmeasurable variables in the information vectors with their estimates. The proposed algorithm has high computational efficiency because the dimensions of its covariance matrices become small. The simulation results indicate that the proposed algorithm is effective.

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Xianling Lu. Wei Zhou. Wenlin Shi. "Data Filtering Based Recursive Least Squares Algorithm for Two-Input Single-Output Systems with Moving Average Noises." J. Appl. Math. 2014 1 - 8, 2014. https://doi.org/10.1155/2014/694053

Information

Published: 2014
First available in Project Euclid: 2 March 2015

zbMATH: 07010714
MathSciNet: MR3191134
Digital Object Identifier: 10.1155/2014/694053

Rights: Copyright © 2014 Hindawi

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