Robust stability of event-triggered nonlinear moving horizon estimation
Abstract
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.
Cite
@article{arxiv.2510.04814,
title = {Robust stability of event-triggered nonlinear moving horizon estimation},
author = {Isabelle Krauss and Victor G. Lopez and Matthias A. Müller},
journal= {arXiv preprint arXiv:2510.04814},
year = {2026}
}