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20192021
most citedRobust data-driven state-feedback design

187 citations · 621 across the 10 of their papers we have counts for

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12 papers · 1 filter

eess.SY2021★ 63 cited

Data-Driven Reachability Analysis from Noisy Data

Amr Alanwar, Anne Koch, Frank Allgöwer +1

We consider the problem of computing reachable sets directly from noisy data without a given system model. Several reachability algorithms are presented for different types of syst…

eess.SY2021★ 42 cited

Fundamental Lemma for Data-Driven Analysis of Linear Parameter-Varying Systems

Chris Verhoek, Roland Tóth, Sofie Haesaert +1

Based on the Fundamental Lemma by Willems et al., the entire behaviour of a Linear Time-Invariant (LTI) system can be characterised by a single data sequence of the system as long…

eess.SY2021

Data-Driven Controller Design via Finite-Horizon Dissipativity

Nils Wieler, Julian Berberich, Anne Koch +1

Given one open-loop measured trajectory of a single-input single-output discrete-time linear time-invariant system, we present a framework for data-driven controller design for clo…

eess.SY2020★ 6 cited

Offset-free setpoint tracking using neural network controllers

Patricia Pauli, Johannes Köhler, Julian Berberich +2

In this paper, we present a method to analyze local and global stability in offset-free setpoint tracking using neural network controllers and we provide ellipsoidal inner approxim…

eess.SY2020★ 2 cited

Data-Driven Reachability Analysis Using Matrix Zonotopes

Amr Alanwar, Anne Koch, Frank Allgöwer +1

In this paper, we propose a data-driven reachability analysis approach for unknown system dynamics. Reachability analysis is an essential tool for guaranteeing safety properties. H…

eess.SY2020

Provably robust verification of dissipativity properties from data

Anne Koch, Julian Berberich, Frank Allgöwer

Dissipativity properties have proven to be very valuable for systems analysis and controller design. With the rising amount of available data, there has therefore been an increasin…

eess.SY2020

Verifying dissipativity properties from noise-corrupted input-state data

Anne Koch, Julian Berberich, Frank Allgöwer

There exists a vast amount of literature how dissipativity properties can be exploited to design controllers for stability and performance guarantees for the closed loop. With the…

eess.SY2020

Determining optimal input-output properties: A data-driven approach

Anne Koch, Julian Berberich, Johannes Köhler +1

Due to their relevance in systems analysis and (robust) controller design, we consider the problem of determining control-theoretic system properties of an a priori unknown system…

eess.SY2019★ 17 cited

Sampling Strategies for Data-Driven Inference of Input-Output System Properties

Anne Koch, Jan Maximilian Montenbruck, Frank Allgöwer

Due to their relevance in controller design, we consider the problem of determining the -gain, passivity properties and conic relations of an input-output system. Wh…

eess.SY2019★ 187 cited

Robust data-driven state-feedback design

Julian Berberich, Anne Romer, Carsten W. Scherer +1

We consider the problem of designing robust state-feedback controllers for discrete-time linear time-invariant systems, based directly on measured data. The proposed design procedu…

eess.SY2019★ 3 cited

Monitoring Link Faults in Nonlinear Diffusively-coupled Networks

Miel Sharf, Daniel Zelazo

Fault detection and isolation is an area of engineering dealing with designing on-line protocols for systems that allow one to identify the existence of faults, pinpoint their exac…

eess.SY2019★ 3 cited

Model-Free Practical Cooperative Control for Diffusively Coupled Systems

Miel Sharf, Anne Koch, Daniel Zelazo +1

In this paper, we develop a data-based controller design framework for diffusively coupled systems with guaranteed convergence to an -neighborhood of the desired formation. The…