DocumentCode :
3244283
Title :
Identifiability and well-posedness in nonlinear system I/O modeling
Author :
Pearson, A.E.
Author_Institution :
Div. of Eng., Brown Univ., Providence, RI, USA
fYear :
1989
fDate :
13-15 Dec 1989
Firstpage :
624
Abstract :
If a specified set of parameterized nonlinear state differential equations possesses an equivalent input-output differential operator model, then the latter model has the potential for deciding the issue of the identifiability property of the former model in a straightforward manner. This property is discussed in relation to the property of well-posedness for the least-squares parameter identification of a class of input-output models that are separable in the parameters
Keywords :
differential equations; least squares approximations; nonlinear systems; parameter estimation; I/O modeling; identifiability; input-output differential operator model; least-squares parameter identification; nonlinear system; parameter estimation; parameterized nonlinear state differential equations; well-posedness; Differential equations; Least squares approximation; Least squares methods; Nonlinear systems; Parameter estimation; Phasor measurement units; Signal processing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control, 1989., Proceedings of the 28th IEEE Conference on
Conference_Location :
Tampa, FL
Type :
conf
DOI :
10.1109/CDC.1989.70192
Filename :
70192
Link To Document :
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