Non-asymptotic state-space identification of closed-loop stochastic linear systems using instrumental variables

DOI10.1016/j.sysconle.2023.105565zbMath1520.93585arXiv2301.12537OpenAlexW4380201139MaRDI QIDQ6137801

Szabolcs Szentpéteri, Balázs Csanád Csáji

Publication date: 4 September 2023

Published in: Systems \& Control Letters (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2301.12537

zbMATH Keywords

closed-loop identificationinstrumental variablesdistribution-free methodsnon-asymptotic guarantees

Mathematics Subject Classification ID

Linear systems in control theory (93C05) Identification in stochastic control theory (93E12)

Cites Work

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• On covariance function tests used in system identification
• Non-asymptotic confidence regions for model parameters in the presence of unmodelled dynamics
• Closed-loop identification revisited
• Finite time identification in unstable linear systems
• Facing undermodelling in sign-perturbed-sums system identification
• Perturbed datasets methods for hypothesis testing and structure of corresponding confidence sets
• Asymptotic properties of SPS confidence regions
• Guaranteed non-asymptotic confidence regions in system identification
• Guaranteed characterization of exact non-asymptotic confidence regions as defined by LSCR and SPS
• CVXPY: A Python-Embedded Modeling Language for Convex Optimization
• Finite sample properties of linear model identification
• Sign-Perturbed Sums: A New System Identification Approach for Constructing Exact Non-Asymptotic Confidence Regions in Linear Regression Models
• Non-Asymptotic Confidence Sets for the Parameters of Linear Transfer Functions
• Finite sample properties of system identification methods
• Shape Sensitivity Analysis and Gradient-Based Optimization of Large Structures Using MLFMA

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