PhD Candidate in Mechanical and Process Engineering

Institute for Dynamic Systems and Control

ETH Zürich


Amon Lahr was born in Berlin, Germany, in 1996. He completed his Bachelor’s studies in Engineering

Science in 2018, with two semester-long stays at New York University and the German Aerospace

Center in Stuttgart, Germany, respectively. Redirecting his study focus towards numerical mathematics, control theory and model reduction, Amon later received a Master’s degree in Scientific Computing from TU Berlin in 2021, with his thesis on “ℋ-∞ Control for Large-Scale Linear Systems”. During his studies, Amon has worked as a Linux and web developer for IoT devices in the automotive industry, shaping his interests in embedded systems and data-driven control methods.

Project description

While the performance and potential of learning-based control has been recently demonstrated, the associated computational challenges remain a key limiting factor for moving these techniques into industrial applications. On embedded hardware in particular, the feasible model complexity and sampling times are restricted by the limited storage and computational power. The aim of this PhD project is to develop new controllers and computational methods for embedded control systems. Possible research directions include the development of tailored real-time optimization routines, controller approximation using learning-based function approximation schemes, as well as efficient data selection and reduction.



Lahr, Amon; Tronarp, Filip; Schmidt, Nathanael Bosch Jonathan; Hennig, Philipp; Zeilinger, Melanie N.

Probabilistic ODE Solvers for Integration Error-Aware Model Predictive Control Working paper

2024, (Submitted to the 6th Annual Learning for Dynamics & Control Conference (L4DC 2024)).

Abstract | Links | BibTeX


Leeman, Antoine P.; Köhler, Johannes; Messerer, Florian; Lahr, Amon; Diehl, Moritz; Zeilinger, Melanie N.

Fast System Level Synthesis: Robust Model Predictive Control Using Riccati Recursions Working paper

2024, (Submitted to the 2024 IFAC Conference on Nonlinear Model Predictive Control (NMPC)).

Abstract | Links | BibTeX


Frey, Jonathan; Gao, Yunfan; Messerer, Florian; Lahr, Amon; Zeilinger, Melanie N.; Diehl, Moritz

Efficient Zero-Order Robust Optimization for Real-Time Model Predictive Control with Acados Working paper


Abstract | Links | BibTeX


Lahr, Amon; Zanelli, Andrea; Carron, Andrea; Zeilinger, Melanie N.

Zero-Order Optimization for Gaussian Process-based Model Predictive Control Journal Article

In: European Journal of Control, pp. 100862, 2023, ISSN: 0947-3580.

Abstract | Links | BibTeX