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eess.SY2024

Gaussian Process-Based Nonlinear Moving Horizon Estimation

Tobias M. Wolff, Victor G. Lopez, Matthias A. Müller

In this paper, we propose a novel Gaussian process-based moving horizon estimation (MHE) framework for unknown nonlinear systems. On the one hand, we approximate the system dynamic…

eess.SY2023

An efficient data-based off-policy Q-learning algorithm for optimal output feedback control of linear systems

Mohammad Alsalti, Victor G. Lopez, Matthias A. Müller

In this paper, we present a Q-learning algorithm to solve the optimal output regulation problem for discrete-time LTI systems. This off-policy algorithm only relies on using persis…

eess.SY2023

Notes on data-driven output-feedback control of linear MIMO systems

Mohammad Alsalti, Victor G. Lopez, Matthias A. Müller

Recent works have approached the data-driven design of dynamic output-feedback controllers for discrete-time LTI systems by constructing non-minimal state vectors composed of past…

eess.SY2023

Model predictive control for the prescription of antithyroid agents

Maylin Menzel, Tobias M. Wolff, Johannes W. Dietrich +1

Although hyperthyroidism is a common disease, the pharmaceutical therapy is based on a trial-and-error approach. We extend a mathematical model of the pituitary-thyroid feedback lo…

eess.SY2023

On an integral variant of incremental input/output-to-state stability and its use as a notion of nonlinear detectability

Julian D. Schiller, Matthias A. Müller

We propose a time-discounted integral variant of incremental input/output-to-state stability (i-iIOSS) together with an equivalent Lyapunov function characterization. Continuity of…

eess.SY2023

Robust Stability of Gaussian Process Based Moving Horizon Estimation

Tobias M. Wolff, Victor G. Lopez, Matthias A. Müller

In this paper, we introduce a Gaussian process based moving horizon estimation (MHE) framework. The scheme is based on offline collected data and offline hyperparameter optimizatio…