Errors-in-variables identification in dynamic networks-consistency results for an instrumental variable approach

DOI10.1016/j.automatica.2015.09.021zbMath1329.93048OpenAlexW2174744382MaRDI QIDQ901094

Xavier Bombois, Arne G. Dankers, Heuberger, Peter S. C., Van den Hof, Paul M. J.

Publication date: 23 December 2015

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.automatica.2015.09.021

zbMATH Keywords

system identificationerrors-in-variablesinstrumental variablesdynamic networksclosed-loop system identification

Mathematics Subject Classification ID

Stochastic network models in operations research (90B15) System identification (93B30)

Related Items

A scalable multi-step least squares method for network identification with unknown disturbance topology ⋮ Identifiability of linear dynamic networks ⋮ An empirical Bayes approach to identification of modules in dynamic networks ⋮ A frequency domain approach for local module identification in dynamic networks ⋮ Learning linear modules in a dynamic network using regularized kernel-based methods ⋮ Abstractions of linear dynamic networks for input selection in local module identification ⋮ Instrumental variable‐based multi‐innovation gradient estimation for nonlinear systems with scarce measurements ⋮ Recursive identification of errors-in-variables systems based on the correlation analysis ⋮ Optimal excitation and measurement pattern for cascade networks ⋮ Prediction error identification of linear dynamic networks with rank-reduced noise ⋮ Variance analysis of linear SIMO models with spatially correlated noise

Uses Software

• glasso

Cites Work

• Unnamed Item
• Robust dynamical network structure reconstruction
• On covariance function tests used in system identification
• Instrumental variable methods for system identification
• Closed-loop identification revisited
• Frequency-domain system identification using non-parametric noise models estimated from a small number of data sets
• Instrumental variable methods for closed-loop system identification
• Can errors-in-variables systems be identified from closed-loop experiments?
• Identification of dynamic models in complex networks with prediction error methods-basic methods for consistent module estimates
• Subspace identification of circulant systems
• Variance results for identification of cascade systems
• A Bayesian approach to sparse dynamic network identification
• Identification of Dynamic Models in Complex Networks With Prediction Error Methods: Predictor Input Selection
• Identification of Causal Effects Using Instrumental Variables
• Feedback between stationary stochastic processes
• Frequency domain system identification with missing data
• Representations of jointly stationary stochastic feedback processes†
• Topological Identification in Networks of Dynamical Systems
• On the Problem of Reconstructing an Unknown Topology via Locality Properties of the Wiener Filter
• Errors in Variables
• Errors-in-variables methods in system identification