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Errors-in-variables methods in system identification
DOI:10.1016/j.automatica.2006.11.025.png)
Abstract
En 中文
The paper gives a survey of errors-in-variables methods in system identification. Background and motivation are given, and examples illustrate why the identification problem can be difficult. Under general weak assumptions, the systems are not identifiable, but can be parameterized using one degree-of-freedom. Examples where identifiability is achieved under additional assumptions are also provided. A number of approaches for parameter estimation of errors-in-variables models are presented. The underlying assumptions and principles for each approach are highlighted. (C) 2007 Elsevier Ltd. All rights reserved.
Keywords:
system identification
errors-in-variables
parameter estimation
identifiability
consistency
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Journal
IF:
5.9
Papers:
1.2W
Citations:
5.2W
Organization
No organization information available
Cited Papers
Frequency-domain system identification using non-parametric noise models estimated from a small number of data sets
AUTOMATICA
IF5.9

