works on

From the 1 of 7 linked papers with an AI index.

activity
20242026
collaborators

7 papers

math.OC2026

Stabilize-then-optimize: Feedback transformations as preconditioners in optimal control

Till Preuster, Manuel Schaller, Anton Schiela +1

The paper proposes using feedback transformations as preconditioners to reformulate optimal control problems, reducing the norm of the control-to-state map and improving condition…

math.OC2026

Coupling optimization algorithms and monotone control systems: Suboptimal model predictive control as an operator splitting scheme

Till Preuster, Hannes Gernandt, Manuel Schaller

We propose a framework for suboptimal model predictive control (MPC) based on the interconnection of monotone dynamical systems, such as port-Hamiltonian systems. In contrast to cl…

math.OC2026

Stabilization of monotone control systems with input constraints

Till Preuster, Hannes Gernandt, Manuel Schaller

We present a stabilizing output-feedback controller for nonlinear finite and infinite-dimensional control systems governed by monotone operators that respects given input constrain…

math.OC2026

Optimization-based control by interconnection of nonlinear port-Hamiltonian systems

Till Preuster, Hannes Gernandt, Manuel Schaller

In this paper, we develop a control-by-interconnection approach for the stabilization of nonlinear port-Hamiltonian systems. Motivated by model predictive control, the controller i…

math.AP2025

Extension theory via boundary triplets for infinite-dimensional implicit port-Hamiltonian systems

Hannes Gernandt, Friedrich Philipp, Till Preuster +1

The solution of constrained linear partial-differential equations can be described via parametric representations of linear relations. To study these representations, we provide a…

math.AP2025

Abstract second-order boundary control systems

Till Preuster, Timo Reis, Manuel Schaller

We consider abstract second order systems of the form , which are typically analyzed via the operator matrix $\mathcal{A}=\left[\begin{smallma…