45 citations · 144 across the 50 of their papers we have counts for
17 papers · 1 filter
Optimal energy conversion -- A port-Hamiltonian approach
Guanru Pan, Karl Worthmann, Manuel Schaller +1
This paper studies optimal energy conversion in port-Hamiltonian systems. We analyze state- and control-constrained finite-horizon optimal control problems that maximize energy con…
Energy-optimal predictive control of discrete-time port-Hamiltonian systems: Closed-loop practical stability
Vaibhav Kumar Singh, Manuel Schaller, Timm Faulwasser +1
We study a dissipativity-based model predictive control (MPC) scheme for energy-optimal constrained output stabilization of a discrete-time nonlinear SISO port-Hamiltonian system d…
Koopman meets input-output data: Data-driven output-feedback control of nonlinear systems with closed-loop guarantees
Robin Strässer, Julian Berberich, Manuel Schaller +2
Data-driven control of nonlinear systems from input-output measurements remains a fundamental challenge, as existing approaches with rigorous closed-loop guarantees predominantly r…
An overview of Koopman-based control: From error bounds to closed-loop guarantees
Robin Strässer, Karl Worthmann, Igor Mezić +3
Controlling nonlinear dynamical systems remains a central challenge in a wide range of applications, particularly when accurate first-principle models are unavailable. Data-driven…
Energy-optimal control of discrete-time port-Hamiltonian systems
Arijit Sarkar, Vaibhav Kumar Singh, Manuel Schaller +1
In this letter, we study the energy-optimal control of nonlinear port-Hamiltonian (pH) systems in discrete time. For continuous-time pH systems, energy-optimal control problems are…
Kernel-based error bounds of bilinear Koopman surrogate models for nonlinear data-driven control
Robin Strässer, Manuel Schaller, Julian Berberich +2
We derive novel deterministic bounds on the approximation error of data-based bilinear surrogate models for unknown nonlinear systems. The surrogate models are constructed using ke…
Koopman-based control of nonlinear systems with closed-loop guarantees
Robin Strässer, Julian Berberich, Manuel Schaller +2
In this paper, we provide a tutorial overview and an extension of a recently developed framework for data-driven control of unknown nonlinear systems with rigorous closed-loop guar…
Data-driven MPC with terminal conditions in the Koopman framework
Karl Worthmann, Robin Strässer, Manuel Schaller +2
We investigate nonlinear model predictive control (MPC) with terminal conditions in the Koopman framework using extended dynamic mode decomposition (EDMD) to generate a data-based…
Modularized data-driven approximation of the Koopman operator and generator
Yang Guo, Manuel Schaller, Karl Worthmann +1
Extended Dynamic Mode Decomposition (EDMD) is a widely-used data-driven approach to learn an approximation of the Koopman operator. Consequently, it provides a powerful tool for da…
SafEDMD: A Koopman-based data-driven controller design framework for nonlinear dynamical systems
Robin Strässer, Manuel Schaller, Karl Worthmann +2
The Koopman operator serves as the theoretical backbone for machine learning of dynamical control systems, where the operator is heuristically approximated by extended dynamic mode…
Koopman-based feedback design with stability guarantees
Robin Strässer, Manuel Schaller, Karl Worthmann +2
We present a method to design a state-feedback controller ensuring exponential stability for nonlinear systems using only measurement data. Our approach relies on Koopman-operator…
Energy-optimal control of adaptive structures
Manuel Schaller, Amelie Zeller, Michael Böhm +3
Adaptive structures are equipped with sensors and actuators to actively counteract external loads such as wind. This can significantly reduce resource consumption and emissions dur…
Structured Optimization-Based Model Order Reduction for Parametric Systems
Paul Schwerdtner, Manuel Schaller
We develop an optimization-based algorithm for parametric model order reduction (PMOR) of linear time-invariant dynamical systems. Our method aims at minimizing the $\mathcal{H}_\i…
Model predictive control for retinal laser treatment at 1 kHz
Manuel Schaller, Viktoria Kleyman, Mario Mordmüller +5
Laser photocoagulation is a technique applied in the treatment of retinal diseases. While this is often done manually or using simple control schemes, we pursue an optimization-bas…
State and parameter estimation for retinal laser treatment
Viktoria Kleyman, Manuel Schaller, Mario Mordmuller +4
Adequate therapeutic retinal laser irradiation needs to be adapted to the local absorption. This leads to time-consuming treatments as the laser power needs to be successively adju…
Parameter estimation and model reduction for retinal laser treatment
Manuel Schaller, Mitsuru Wilson, Viktoria Kleyman +4
Laser photocoagulation is one of the most frequently used treatment approaches for retinal diseases such as diabetic retinopathy and macular edema. The use of model-based control,…
State and parameter estimation for model-based retinal laser treatment
Viktoria Kleyman, Manuel Schaller, Mitsuru Wilson +4
We present an approach for state and parameter estimation in retinal laser treatment by a novel setup where both measurement and heating is performed by a single laser. In this med…