A Behavioral Approach to Data-Driven Control With Noisy Input-Output Data

H. J. van Waarde*, J. Eising, M. K. Camlibel, H. L. Trentelman

*Bijbehorende auteur voor dit werk

OnderzoeksoutputAcademicpeer review

1 Citaat (Scopus)


This paper deals with data-driven stability analysis and feedback stabilization of linear input-output systems in auto-regressive (AR) form. We assume that noisy input-output data on a finite time-interval have been obtained from some unknown AR system. Data-based tests are then developed to analyse whether the unknown system is stable, or to verify whether a stabilizing dynamic feedback controller exists. If so, stabilizing controllers are computed using the data. In order to do this, we employ the behavioral approach to systems and control, meaning a departure from existing methods in data driven control. Our results heavily rely on a characterization of asymptotic stability of systems in AR form using the notion of quadratic difference form (QDF) as a natural framework for Lyapunov functions of autonomous AR systems. We introduce the concepts of informative data for quadratic stability and quadratic stabilization in the context of input-output AR systems and establish necessary and sufficient conditions for these properties to hold. In addition, this paper will build on results on quadratic matrix inequalities (QMIs) and a matrix version of Yakubovich's S-lemma.

Originele taal-2English
Pagina's (van-tot)813-827
Aantal pagina's14
TijdschriftIEEE Transactions on Automatic Control
Nummer van het tijdschrift2
StatusPublished - feb.-2024

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