8 citations · 9 across the 8 of their papers we have counts for
9 papers
Sample-based detectability and moving horizon state estimation of continuous-time systems
Isabelle Krauss, Victor G. Lopez, Matthias A. Müller
In this paper we propose a detectability condition for nonlinear continuous-time systems with irregular/infrequent output measurements, namely a sample-based version of incremental…
Data-based Moving Horizon Estimation under Irregularly Measured Data
Tobias M. Wolff, Isabelle Krauss, Victor G. Lopez +1
In this work, we introduce a sample- and data-based moving horizon estimation framework for linear systems. We perform state estimation in a sample-based fashion in the sense that…
Estimating Hormone Concentrations in the Pituitary-Thyroid Feedback Loop from Irregularly Sampled Measurements
Seth Siriya, Tobias M. Wolff, Isabelle Krauss +2
Model-based control techniques have recently been investigated for the recommendation of medication dosages to address thyroid diseases. These techniques often rely on knowledge of…
Sample-based Moving Horizon Estimation
Isabelle Krauss, Victor G. Lopez, Matthias A. Müller
In this paper, we propose a sample-based moving horizon estimation (MHE) scheme for general nonlinear systems to estimate the current system state using irregularly and/or infreque…
Robust stability of event-triggered nonlinear moving horizon estimation
Isabelle Krauss, Victor G. Lopez, Matthias A. Müller
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, wheneve…
On sample-based functional observability of linear systems
Isabelle Krauss, Victor G. Lopez, Matthias A. Müller
Sample-based observability characterizes the ability to reconstruct the internal state of a dynamical system by using limited output information, i.e., when measurements are only i…
Event-triggered moving horizon estimation for nonlinear systems
Isabelle Krauss, Julian D. Schiller, Victor G. Lopez +1
This work proposes an event-triggered moving horizon estimation (ET-MHE) scheme for general nonlinear systems. The key components of the proposed scheme are a novel event-triggerin…
Sample-based nonlinear detectability for discrete-time systems
Isabelle Krauss, Victor G. Lopez, Matthias A. Müller
This paper introduces two sample-based formulations of incremental input/output-to-state stability (i-IOSS), a suitable detectability notion for general nonlinear systems. In this…
Sample-based observability of linear discrete-time systems
Isabelle Krauss, Victor G. Lopez, Matthias A. Müller
In this work, sample-based observability of linear discrete-time systems is studied. That is, we consider the case where the system output measurements are not available at every t…