Learning Safety-Compatible Observers for Unknown Systems

Fuente: arXiv
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Autori principali: Bae, Juho, Roh, Daegyeong, Choi, Han-Lim
Natura: Preprint
Pubblicazione: 2025
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author Bae, Juho
Roh, Daegyeong
Choi, Han-Lim
author_facet Bae, Juho
Roh, Daegyeong
Choi, Han-Lim
contents This paper presents a data-driven approach for jointly learning a robust full-state observer and its robustness certificate for systems with unknown dynamics. Leveraging incremental input-to-state stability (delta ISS) notions, we jointly learn a delta ISS Lyapunov function that serves as the robustness certificate and prove practical convergence of the estimation error under standard fidelity assumptions on the learned models. This renders the observer safety-compatible: they can be consumed by certificate-based safe controllers so that, when the controller tolerates bounded estimation error, the controller's certificate remains valid under output feedback. We further extend the approach to interconnected systems via the small-gain theorem, yielding a distributed observer design framework. We validate the approach on a variety of nonlinear systems.
format Preprint
id arxiv_https___arxiv_org_abs_2510_03609
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Learning Safety-Compatible Observers for Unknown Systems
Bae, Juho
Roh, Daegyeong
Choi, Han-Lim
Systems and Control
This paper presents a data-driven approach for jointly learning a robust full-state observer and its robustness certificate for systems with unknown dynamics. Leveraging incremental input-to-state stability (delta ISS) notions, we jointly learn a delta ISS Lyapunov function that serves as the robustness certificate and prove practical convergence of the estimation error under standard fidelity assumptions on the learned models. This renders the observer safety-compatible: they can be consumed by certificate-based safe controllers so that, when the controller tolerates bounded estimation error, the controller's certificate remains valid under output feedback. We further extend the approach to interconnected systems via the small-gain theorem, yielding a distributed observer design framework. We validate the approach on a variety of nonlinear systems.
title Learning Safety-Compatible Observers for Unknown Systems
topic Systems and Control
url https://arxiv.org/abs/2510.03609