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Algorithms 2015, 8(2), 280-291; doi:10.3390/a8020280

Model Equivalence-Based Identification Algorithm for Equation-Error Systems with Colored Noise

Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi 214122, China
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Author to whom correspondence should be addressed.
Academic Editor: Tom Burr
Received: 1 May 2015 / Accepted: 19 May 2015 / Published: 2 June 2015
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Abstract

For equation-error autoregressive (EEAR) systems, this paper proposes an identification algorithm by means of the model equivalence transformation. The basic idea is to eliminate the autoregressive term in the model using the model transformation, to estimate the parameters of the converted system and further to compute the parameter estimates of the original system using the comparative coefficient way and the model equivalence principle. For comparison, the recursive generalized least squares algorithm is given simply. The simulation results verify that the proposed algorithm is effective and can produce more accurate parameter estimates. View Full-Text
Keywords: least squares; comparative coefficient; model equivalence; equation-error system least squares; comparative coefficient; model equivalence; equation-error system
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Meng, D.; Ding, F. Model Equivalence-Based Identification Algorithm for Equation-Error Systems with Colored Noise. Algorithms 2015, 8, 280-291.

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