808 citations · 2.6k across the 51 of their papers we have counts for
9 papers · 1 filter
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…
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…
State space models vs. multi-step predictors in predictive control: Are state space models complicating safe data-driven designs?
Johannes Köhler, Kim P. Wabersich, Julian Berberich +1
This paper contrasts recursive state space models and direct multi-step predictors for linear predictive control. We provide a tutorial exposition for both model structures to solv…
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…
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…