Title :
Identification of errors-in-variables systems with nonlinear output measurements
Author_Institution :
Dept. of Math., Renmin Univ. of China, Beijing, China
Abstract :
This paper concerns the identification problem of the errors-in-variables (EIV) systems with nonlinear output measurements using iid inputs. Under reasonable conditions, recursive estimates are given for the parameters of the EIV systems. The strong consistency of the recursive algorithms is proved. Two simulation examples are provided, which justify the theoretical results.
Keywords :
recursive estimation; errors-in-variables system identification; nonlinear output measurement; recursive estimation; Abstracts; Approximation algorithms; Approximation methods; Educational institutions; Electronic mail; Measurement uncertainty; ARMA; Errors-in-variables (EIV); Nonlinear Measurement; Recursive Estimate; Stochastic Approximation (SA); Strong consistency; System Identification;
Conference_Titel :
Control Conference (CCC), 2012 31st Chinese
Conference_Location :
Hefei
Print_ISBN :
978-1-4673-2581-3
