5 papers
A Unified Bayesian Framework for Data-Driven Smoothing, Prediction, and Control
Mingzhou Yin, Andrea Iannelli, Seyed Ali Nazari +1
Extending data-driven algorithms based on Willems' fundamental lemma to stochastic data often requires empirical and customized workarounds. This work presents a unified Bayesian f…
The Cesà ro Value Iteration
Jonas Mair, Lukas Schwenkel, Matthias A. Müller +1
In this paper, we consider undiscouted infinite-horizon optimal control for deterministic systems with an uncountable state and input space. We specifically address the case when t…
Physics-based Approximation and Prediction of Speedlines in Compressor Performance Maps
Abdul-Malik Akiev, Danyal Ergür, Alexander Schirger +3
Speedlines in compressor performance maps (CPMs) are critical for understanding and predicting compressor behavior under various operating conditions. We investigate a physics-base…
Data-Driven Prediction and Control of Hammerstein-Wiener Systems with Implicit Gaussian Processes
Mingzhou Yin, Matthias A. Müller
This work investigates data-driven prediction and control of Hammerstein-Wiener systems using physics-informed Gaussian process (GP) models that encode the block-oriented model str…
Modeling and Predictive Control for the Treatment of Hyperthyroidism
Tobias M. Wolff, Maylin Menzel, Johannes W. Dietrich +1
In this work, we propose an approach to determine the dosages of antithyroid agents to treat hyperthyroid patients. Instead of relying on a trial-and-error approach as it is common…