Comments on “Data driven stability analysis of black-box switched linear systems” [Automatica 109 (2019) 108533]

Comments on “Data driven stability analysis of black-box switched linear systems” [Automatica 109 (2019) 108533]

This item explains a technical problem in the justification of Theorem 10 in Kenanian et al. (2019). The theorem refers to a result in chance-constrained convex programming, but the hypotheses for applying this result are not satisfied since the optimization problem involved in Theorem 10 is nonconv...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Automatica (Oxford) 2022-08, Vol.142, p.110412, Article 110412
Hauptverfasser: Berger, Guillaume O., Wang, Zheming
Format: Artikel
Sprache:eng
Schlagworte:
Data-driven verification
Learning algorithms
Lyapunov methods
Optimization
Stability
Switched systems
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:This item explains a technical problem in the justification of Theorem 10 in Kenanian et al. (2019). The theorem refers to a result in chance-constrained convex programming, but the hypotheses for applying this result are not satisfied since the optimization problem involved in Theorem 10 is nonconvex. However, under an additional mild assumption on the system, the conclusions of Theorem 10 hold, as shown in this item.
ISSN:0005-1098
1873-2836
DOI:10.1016/j.automatica.2022.110412