258 citations · 2.4k across the 118 of their papers we have counts for
19 papers · 1 filter
Towards targeted exploration for non-stochastic disturbances
Janani Venkatasubramanian, Johannes Köhler, Mark Cannon +1
We present a novel targeted exploration strategy for linear time-invariant systems without stochastic assumptions on the noise, i.e., without requiring independence or zero mean, a…
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…
Decrypting Nonlinearity: Koopman Interpretation and Analysis of Cryptosystems
Robin Strässer, Sebastian Schlor, Frank Allgöwer
Public-key cryptosystems rely on computationally difficult problems for security, traditionally analyzed using number theory methods. In this paper, we introduce a novel perspectiv…
Data-Driven Min-Max MPC for Linear Systems
Yifan Xie, Julian Berberich, Frank Allgower
Designing data-driven controllers in the presence of noise is an important research problem, in particular when guarantees on stability, robustness, and constraint satisfaction are…
Performance implications of different -norms in level-triggered sampling
David Meister, Frank Allgöwer
This work studies the performance of an event-based control approach, namely level-triggered sampling, in a standard multidimensional single-integrator setup. We falsify a conjectu…
Analysis and design of model predictive control frameworks for dynamic operation -- An overview
Johannes Köhler, Matthas A. Müller, Frank Allgöwer
This article provides an overview of model predictive control (MPC) frameworks for dynamic operation of nonlinear constrained systems. Dynamic operation is often an integral part o…
Guarantees for data-driven control of nonlinear systems using semidefinite programming: A survey
Tim Martin, Thomas B. Schön, Frank Allgöwer
This survey presents recent research on determining control-theoretic properties and designing controllers with rigorous guarantees using semidefinite programming and for nonlinear…
Robust data-driven control for nonlinear systems using the Koopman operator
Robin Strässer, Julian Berberich, Frank Allgöwer
Data-driven analysis and control of dynamical systems have gained a lot of interest in recent years. While the class of linear systems is well studied, theoretical results for nonl…
On -performance of weakly-hard real-time control systems
Marc Seidel, Simon Lang, Frank Allgöwer
This paper considers control systems with failures in the feedback channel, that occasionally lead to loss of the control input signal. A useful approach for modeling such failures…
Stochastic Model Predictive Control using Initial State and Variance Interpolation
Henning Schlüter, Frank Allgöwer
We present a Stochastic Model Predictive Control (SMPC) framework for linear systems subject to Gaussian disturbances. In order to avoid feasibility issues, we employ a recent init…
Convolutional Neural Networks as 2-D systems
Dennis Gramlich, Patricia Pauli, Carsten W. Scherer +2
This paper introduces a novel representation of convolutional Neural Networks (CNNs) in terms of 2-D dynamical systems. To this end, the usual description of convolutional layers w…
Distributed Model Predictive Control for Periodic Cooperation of Multi-Agent Systems
Matthias Köhler, Matthias A. Müller, Frank Allgöwer
We consider multi-agent systems with heterogeneous, nonlinear agents subject to individual constraints that want to achieve a periodic, dynamic cooperative control goal which can b…
Control of bilinear systems using gain-scheduling: Stability and performance guarantees
Robin Strässer, Julian Berberich, Frank Allgöwer
In this paper, we present a state-feedback controller design method for bilinear systems. To this end, we write the bilinear system as a linear fractional representation by interpr…
Self-triggered output feedback control for nonlinear networked control systems based on hybrid Lyapunov functions
Michael Hertneck, Frank Allgöwer
Most approaches for self-triggered control (STC) of nonlinear networked control systems (NCS) require measurements of the full system state to determine transmission times. However…
Lipschitz-bounded 1D convolutional neural networks using the Cayley transform and the controllability Gramian
Patricia Pauli, Ruigang Wang, Ian R. Manchester +1
We establish a layer-wise parameterization for 1D convolutional neural networks (CNNs) with built-in end-to-end robustness guarantees. In doing so, we use the Lipschitz constant of…
Time- versus event-triggered consensus of a single-integrator multi-agent system
David Meister, Frank Aurzada, Mikhail A. Lifshits +1
Event-triggered control has shown the potential for providing improved control performance at the same average sampling rate when compared to time-triggered control. While this obs…
Data-driven Dissipativity Analysis of Linear Parameter-Varying Systems
Chris Verhoek, Julian Berberich, Sofie Haesaert +2
We derive direct data-driven dissipativity analysis methods for Linear Parameter-Varying (LPV) systems using a single sequence of input-scheduling-output data. By means of construc…
Transient Performance of MPC for Tracking
Matthias Köhler, Lisa Krügel, Lars Grüne +2
We analyse the closed-loop performance of a model predictive control (MPC) for tracking formulation with artificial references. It has been shown that such a scheme guarantees clos…
Sequential learning and control: Targeted exploration for robust performance
Janani Venkatasubramanian, Johannes Köhler, Julian Berberich +1
We present a novel dual control strategy for uncertain linear systems based on targeted harmonic exploration and gain-scheduling with performance and excitation guarantees. In the…