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A finite-sample bound for identifying partially observed linear switched systems from a single trajectory

Year: 2025

Type: preprint

Abstract: We derive a finite-sample probabilistic bound on the parameter estimation error of a system identification algorithm for Linear Switched Systems. The algorithm estimates Markov parameters from a single trajectory and applies a variant of the Ho-Kalman algorithm to recover the system matrices. Our bound guarantees statistical consistency under the assumption that the true system exhibits quadratic stability. The proof leverages the theory of weakly dependent processes. To the best of our knowledge, this is the first finite-sample bound for this algorithm in the single-trajectory setting.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2503.13766

Authors: Racz, Daniel, Petreczky, Mihaly, Daroczy, Balint

Institutions: Eötvös Loránd University, HUN-REN Institute for Computer Science and Control, Centre National de la Recherche Scientifique, Université de Lille, Centre de Recherche en Informatique, Signal et Automatique de Lille, Centrale Lille Institut

Language: English

Topic: Control Systems and Identification

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W6892099273

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