Parameter-based conditions for closed-loop system identifiability of ARX models with routine operating data

DOI10.1016/j.jfranklin.2016.10.027zbMath1355.93197OpenAlexW2539606437MaRDI QIDQ509344

Biao Huang, Yuri A. W. Shardt

Publication date: 9 February 2017

Published in: Journal of the Franklin Institute (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jfranklin.2016.10.027

zbMATH Keywords

complexityMonte Carlo simulationsclosed-loop system identificationfirst-order autoregressive modelabsence of external excitationexpectation-based analysis of Fisher information matrixlocal identifiabilityno global identifiability

Mathematics Subject Classification ID

Feedback control (93B52) Identification in stochastic control theory (93E12) Stochastic systems in control theory (general) (93E03)

Related Items (1)

Identification of errors-in-variables ARX models using modified dynamic iterative PCA

Uses Software

• astsa

Cites Work

• AN APPROACH TO TIME SERIES SMOOTHING AND FORECASTING USING THE EM ALGORITHM
• On covariance function tests used in system identification
• Closed-loop identification condition for ARMAX models using routine operating data
• Finite-horizon reliable control with randomly occurring uncertainties and nonlinearities subject to output quantization
• The Analysis of Closed-Loop Dynamic-Stochastic Systems
• Identifiability conditions for linear systems operating in closed loop†
• Parameter Estimation with Closed-Loop Operating Data
• Identification and the Information Matrix: How to Get Just Sufficiently Rich?

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