The behavioral approach to systems theory, put forward 40 years ago by Jan C. Willems,
takes a representation-free perspective of a dynamical system as a set of trajectories. Till …

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

In this article, we propose a new method to obtain feedback controllers of an unknown
dynamical system directly from noisy input/state data. The key ingredient of our design is a …

We address the problem of designing a stabilizing closed-loop control law directly from input
and state measurements collected in an experiment. In the presence of a process …

In a recent article, we have shown how to learn controllers for unknown linear systems using
finite-length noisy data by solving linear matrix inequalities. In this article, we extend this …

This article provides an overview of a new approach to designing controllers for nonlinear
systems using data-driven control. Data-driven control is an important area of research in …

In this article, we introduce a method to deal with the data-driven control design of nonlinear
systems. We derive conditions to design controllers via (approximate) nonlinearity …

Behavioral systems theory decouples the behavior of a system from its representation. A key
result is that, under a persistency of excitation condition, the image of a Hankel matrix …

Data-driven control approaches for the minimization of energy consumption of buildings
have the potential to significantly reduce deployment costs and increase the uptake of …

In data-driven control, a central question is how to handle noisy data. In this work, we
consider the problem of designing a stabilizing controller for an unknown linear system …