Risk averse deterministic Kalman filters for uncertain dynamical systems
Optimization and Control
2025-11-17 v1 Dynamical Systems
Abstract
Taking a deterministic viewpoint this work investigates extensions of the Kalman-Bucy filter for state reconstruction to systems containing parametric uncertainty in the state operator. The emphasis lies on risk averse designs reducing the probability of large reconstruction errors. In a theoretical analysis error bounds in terms of the variance of the uncertainties are derived. The article concludes with a numerical implementation of two examples allowing for a comparison of risk neutral and risk averse estimators.
Keywords
Cite
@article{arxiv.2511.11350,
title = {Risk averse deterministic Kalman filters for uncertain dynamical systems},
author = {Karl Kunisch and Jesper Schröder},
journal= {arXiv preprint arXiv:2511.11350},
year = {2025}
}