A filtering based recursive least squares estimation algorithm for pseudo-linear auto-regressive systems

Sheng Ding

doi:10.1016/j.jfranklin.2013.10.018

A filtering based recursive least squares estimation algorithm for pseudo-linear auto-regressive systems

2014-03-01

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DOI：10.1016/j.jfranklin.2013.10.018

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Abstract

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This paper uses the filtering technique, transforms a pseudo-linear auto-regressive system into an identification model and presents a new recursive least squares parameter estimation algorithm pseudolinear auto-regressive systems. The proposed algorithm has a high computational efficiency because the dimensions of its covariance matrices become small compared with the recursive generalized least squares algorithm. (C) 2013 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

Keywords:

PARAMETER-ESTIMATION ALGORITHMS

SELF-TUNING CONTROL

IDENTIFICATION METHODS

PERFORMANCE ANALYSIS

ITERATIVE ESTIMATION

STOCHASTIC-SYSTEMS

OUTPUT ESTIMATION

STATE

A filtering based recursive least squares estimation algorithm for pseudo-linear auto-regressive systems

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