258 citations · 2.4k across the 118 of their papers we have counts for
22 papers · 1 filter
Event-Triggered Discrete-Time Multivariable Extremum Seeking Systems
Victor Hugo Pereira Rodrigues, Tiago Roux Oliveira, Miroslav Krstić +1
This paper introduces a discrete-time event-triggered extremum seeking framework for real-time optimization of multivariable nonlinear systems. In contrast to conventional discrete…
On discount functions for economic model predictive control without terminal conditions
Lukas Schwenkel, Daniel Briem, Matthias A. Müller +1
In this paper, we investigate discounted economic model predictive control (E-MPC) schemes without terminal conditions in scenarios where the optimal operating behavior is a period…
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…
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…
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…
Gaussian inference for data-driven state-feedback design of nonlinear systems
Tim Martin, Thomas B. Schön, Frank Allgöwer
Data-driven control of nonlinear systems with rigorous guarantees is a challenging problem as it usually calls for nonconvex optimization and requires often knowledge of the true b…
A quantitative and constructive proof of Willems' Fundamental Lemma and its implications
Julian Berberich, Andrea Iannelli, Alberto Padoan +3
Willems' Fundamental Lemma provides a powerful data-driven parametrization of all trajectories of a controllable linear time-invariant system based on one trajectory with persisten…
Safe Exploration and Escape Local Minima with Model Predictive Control under Partially Unknown Constraints
Raffaele Soloperto, Ali Mesbah, Frank Allgöwer
In this paper, we propose a novel model predictive control (MPC) framework for output tracking that deals with partially unknown constraints. The MPC scheme optimizes over a learni…
Practical exponential stability of a robust data-driven nonlinear predictive control scheme
Mohammad Alsalti, Victor G. Lopez, Julian Berberich +2
We provide theoretical guarantees for recursive feasibility and practical exponential stability of the closed-loop system of a feedback linearizable nonlinear system when controlle…
Data-based Control of Feedback Linearizable Systems
Mohammad Alsalti, Victor G. Lopez, Julian Berberich +2
We present an extension of Willems' Fundamental Lemma to the class of multi-input multi-output discrete-time feedback linearizable nonlinear systems, thus providing a data-based re…
Linear tracking MPC for nonlinear systems Part II: The data-driven case
Julian Berberich, Johannes Köhler, Matthias A. Müller +1
We present a novel data-driven model predictive control (MPC) approach to control unknown nonlinear systems using only measured input-output data with closed-loop stability guarant…
Linear tracking MPC for nonlinear systems Part I: The model-based case
Julian Berberich, Johannes Köhler, Matthias A. Müller +1
We develop a tracking model predictive control (MPC) scheme for nonlinear systems using the linearized dynamics at the current state as a prediction model. Under reasonable assumpt…
Model predictive control for linear uncertain systems using integral quadratic constraints
Lukas Schwenkel, Johannes Köhler, Matthias A. Müller +1
In this work, we propose a tube-based MPC scheme for state- and input-constrained linear systems subject to dynamic uncertainties characterized by dynamic integral quadratic constr…
Robust stability analysis of a simple data-driven model predictive control approach
Joscha Bongard, Julian Berberich, Johannes Köhler +1
In this paper, we provide a theoretical analysis of closed-loop properties of a simple data-driven model predictive control (MPC) scheme. The formulation does not involve any termi…
On the design of terminal ingredients for data-driven MPC
Julian Berberich, Johannes Köhler, Matthias A. Müller +1
We present a model predictive control (MPC) scheme to control linear time-invariant systems using only measured input-output data and no model knowledge. The scheme includes a term…
Data-driven analysis and control of continuous-time systems under aperiodic sampling
Julian Berberich, Stefan Wildhagen, Michael Hertneck +1
We investigate stability analysis and controller design of unknown continuous-time systems under state-feedback with aperiodic sampling, using only noisy data but no model knowledg…
Structured Optimal Feedback in Multi-Agent Systems: A Static Output Feedback Perspective
Shen Zeng, Frank Allgöwer
In this paper we demonstrate how certain structured feedback gains necessarily emerge as the optimal controller gains in two linear optimal control formulations for multi-agent sys…
Fekete points, formation control, and the balancing problem
Jan Maximilian Montenbruck, Daniel Zelazo, Frank Allgöwer
We study formation control problems. Our approach is to let a group of systems maximize their pairwise distances whilst bringing them all to a given submanifold, determining the sh…
Iterative Learning and Extremum Seeking for Repetitive Time-Varying Mappings
Zhixing Cao, Hans-Bernd Dürr, Christian Ebenbauer +2
In this paper, we develop an extremum seeking control method integrated with iterative learning control to track a time-varying optimizer within finite time. The behavior of the ex…
Ensemble Observability of Linear Systems
Shen Zeng, Steffen Waldherr, Christian Ebenbauer +1
We address the observability problem for ensembles that are described by probability distributions. The problem is to reconstruct a probability distribution of the initial state fr…
Optimal pricing control in distribution networks with time-varying supply and demand
Mathias Bürger, Claudio De Persis, Frank Allgöwer
This paper studies the problem of optimal flow control in dynamic inventory systems. A dynamic optimal distribution problem, including time-varying supply and demand, capacity cons…
Duality and Network Theory in Passivity-based Cooperative Control
Mathias Bürger, Daniel Zelazo, Frank Allgöwer
This paper presents a class of passivity-based cooperative control problems that have an explicit connection to convex network optimization problems. The new notion of maximal equi…