Robust stability of event-triggered nonlinear moving horizon estimation

Fuente: arXiv
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Main Authors: Krauss, Isabelle, Lopez, Victor G., Müller, Matthias A.
Format: Preprint
Published: 2025
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author Krauss, Isabelle
Lopez, Victor G.
Müller, Matthias A.
author_facet Krauss, Isabelle
Lopez, Victor G.
Müller, Matthias A.
contents In this work, we propose an event-triggered moving horizon estimation (ET-MHE) scheme for the remote state estimation of general nonlinear systems. In the presented method, whenever an event is triggered, a single measurement is transmitted and the nonlinear MHE optimization problem is subsequently solved. If no event is triggered, the current state estimate is updated using an open-loop prediction based on the system dynamics. Moreover, we introduce a novel event-triggering rule under which we demonstrate robust global exponential stability of the ET-MHE scheme, assuming a suitable detectability condition is met. In addition, we show that with the adoption of a varying horizon length, a tighter bound on the estimation error can be achieved. Finally, we validate the effectiveness of the proposed method through two illustrative examples.
format Preprint
id arxiv_https___arxiv_org_abs_2510_04814
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Robust stability of event-triggered nonlinear moving horizon estimation
Krauss, Isabelle
Lopez, Victor G.
Müller, Matthias A.
Systems and Control
In this work, we propose an event-triggered moving horizon estimation (ET-MHE) scheme for the remote state estimation of general nonlinear systems. In the presented method, whenever an event is triggered, a single measurement is transmitted and the nonlinear MHE optimization problem is subsequently solved. If no event is triggered, the current state estimate is updated using an open-loop prediction based on the system dynamics. Moreover, we introduce a novel event-triggering rule under which we demonstrate robust global exponential stability of the ET-MHE scheme, assuming a suitable detectability condition is met. In addition, we show that with the adoption of a varying horizon length, a tighter bound on the estimation error can be achieved. Finally, we validate the effectiveness of the proposed method through two illustrative examples.
title Robust stability of event-triggered nonlinear moving horizon estimation
topic Systems and Control
url https://arxiv.org/abs/2510.04814