This survey presents recent research on determining control-theoretic properties and
designing controllers with rigorous guarantees using semidefinite programming and for …

A data-driven approach to control design has been developing, since the early 1990's, upon
the concepts and the methods of classical control theory; to this approach we refer as data …

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 …

We derive novel methods that allow to synthesize LPV state-feedback controllers directly
from a single sequence of data and guarantee stability and performance of the closed-loop …

Through the use of the Fundamental Lemma for linear systems, a direct data-driven state-
feedback control synthesis method is presented for a rather general class of nonlinear (NL) …

In this article, 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 …

In this paper we propose an end-to-end algorithm for indirect data-driven control for bilinear
systems with stability guarantees. We consider the case where the collected iid data is …

Data-driven control of discrete-time and continuous-time systems is of tremendous research
interest. In this paper, we explore data-driven optimal control of continuous-time linear …

The Koopman operator serves as the theoretical backbone for machine learning of
dynamical control systems, where the operator is heuristically approximated by extended …

A promising step from linear towards nonlinear data-driven control is via the design of
controllers for linear parameter-varying (LPV) systems, which are linear systems whose …