activity
20192025
most citedSafe and Fast Tracking on a Robot Manipulator: Robust MPC and Neural Network Control

230 citations · 230 across the 1 of their papers we have counts for

collaborators

21 papers

eess.SY2025

Beyond Asymptotics: Targeted exploration with finite-sample guarantees

Janani Venkatasubramanian, Johannes Köhler, Frank Allgöwer

In this paper, we introduce a targeted exploration strategy for the non-asymptotic, finite-time case. The proposed strategy is applicable to uncertain linear time-invariant systems…

eess.SY2025

Output-feedback model predictive control under dynamic uncertainties using integral quadratic constraints

Lukas Schwenkel, Johannes Köhler, Matthias A. Müller +1

In this work, we propose an output-feedback tube-based model predictive control (MPC) scheme for linear systems under dynamic uncertainties that are described via integral quadrati…

math.OC2024

Robust targeted exploration for systems with non-stochastic disturbances

Janani Venkatasubramanian, Johannes Köhler, Mark Cannon +1

We propose a novel targeted exploration strategy designed specifically for uncertain linear time-invariant systems with energy-bounded disturbances, i.e., without any assumptions o…

eess.SY2022

Robust peak-to-peak gain analysis using integral quadratic constraints

Lukas Schwenkel, Johannes Köhler, Matthias A. Müller +1

This work provides a framework to compute an upper bound on the robust peak-to-peak gain of discrete-time uncertain linear systems using integral quadratic constraints (IQCs). Such…

eess.SY2021

Robust output feedback model predictive control using online estimation bounds

Johannes Köhler, Matthias A. Müller, Frank Allgöwer

We present a framework to design nonlinear robust output feedback model predictive control (MPC) schemes that ensure constraint satisfaction under noisy output measurements and dis…

eess.SY2021

Stability and performance in MPC using a finite-tail cost

Johannes Köhler, Frank Allgöwer

In this paper, we provide a stability and performance analysis of model predictive control (MPC) schemes based on finite-tail costs. We study the MPC formulation originally propose…