Identification of errors-in-variables systems with nonlinear output observations

Authors:
Qijiang Song
Affiliations:
-
Venue:
Automatica (Journal of IFAC)
Year:
2013

Citing 6
Cited 0

Computer-controlled systems: theory and design (2nd ed.)

Computer-controlled systems: theory and design (2nd ed.)
Digital Control and Implementation

Digital Control and Implementation
Survey paper: Errors-in-variables methods in system identification

Automatica (Journal of IFAC)
Identifiability of errors in variables dynamic systems

Automatica (Journal of IFAC)
Brief Identification of dynamic errors-in-variables models: Approaches based on two-dimensional ARMA modeling of the data

Automatica (Journal of IFAC)
Strongly consistent coefficient estimate for errors-in-variables models

Automatica (Journal of IFAC)

Quantified Score

Hi-index	22.14

Visualization

Abstract

This paper concerns the identification problem of errors-in-variables (EIV) systems with nonlinear output observations. Under independent and identically distributed (iid) Gaussian inputs with unknown variance, recursive algorithms for estimating the parameters of the EIV systems are presented. For a large class of nonlinear observations, conditions on the system are imposed to guarantee the almost sure convergence of the estimates. Some simulation examples are included to justify the theoretical results.