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A filtering based recursive extended least squares identification algorithm

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Based on the standard recursive generalized extended least squares (RGELS) algorithm and the filtering based recursive least squares (F-RLS) algorithm, a new type of filtering based algorithm is presented for ARARMAX model in this paper. The core idea is to transform the ARARMAX model into an ARMAX model by introducing a filter for the input and output data. With such a treatment, the system can be decomposed into two subsystems. Then, a recursive identification algorithm is constructed by replacing immeasurable terms in information vectors with their estimates respectively. A numerical simulation example is employed to show the effectiveness of the proposed algorithm.

Original languageEnglish
Title of host publicationProceedings of the 38th Chinese Control Conference, CCC 2019
EditorsMinyue Fu, Jian Sun
PublisherIEEE Computer Society
Pages1678-1681
Number of pages4
ISBN (Electronic)9789881563972
DOIs
StatePublished - Jul 2019
Externally publishedYes
Event38th Chinese Control Conference, CCC 2019 - Guangzhou, China
Duration: 27 Jul 201930 Jul 2019

Publication series

NameChinese Control Conference, CCC
Volume2019-July
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference38th Chinese Control Conference, CCC 2019
Country/TerritoryChina
CityGuangzhou
Period27/07/1930/07/19

Keywords

  • ARARMAX
  • Filtering
  • Least squares
  • Parameter estimation

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