The development of control methods based on data has seen a surge of interest in recent
years. When applying data-driven controllers in real-world applications, providing theoretical …

The fundamental lemma by Jan C. Willems and co-workers is deeply rooted in behavioral
systems theory and it has become one of the supporting pillars of the recent progress on …

Data-driven predictive control (DPC) has gained an increased interest as an alternative to
model predictive control in recent years, since it requires less system knowledge for …

This paper investigates data-driven output-feedback predictive control of linear systems
subject to stochastic disturbances. The scheme relies on the recursive solution of a suitable …

We propose a data-driven receding-horizon control method dealing with the chance-
constrained output-tracking problem of unknown stochastic linear time-invariant (LTI) …

We propose a novel learning-based tracking controller for nonlinear systems of arbitrary
relative degree. Here, we use sample-and-hold input signals and derive a bound on the …

A powerful result from behavioral systems theory known as the fundamental lemma allows
for predictive control akin to Model Predictive Control (MPC) for linear time-invariant (LTI) …

We consider the problem of direct data-driven predictive control for unknown stochastic
linear time-invariant (LTI) systems with partial state observation. Building upon our previous …

The fundamental lemma by Jan C. Willems and co-authors enables the representation of all
input-output trajectories of a linear time-invariant system by measured input-output data …

We study output reference tracking for unknown continuous-time systems with arbitrary
relative degree. The control objective is to keep the tracking error within predefined time …