Roughly speaking, systems and control theory deals with the problem of making a concrete
physical system behave according to certain desired specifications. To achieve this desired …

We use polynomial approximation theory to perform data-driven analysis and control of
linear, continuous-time invariant systems. We transform the continuous-time input …

This article introduces a notion of data informativity for stabilization tailored to continuous-
time signals and systems. We establish results comparable to those known for discrete-time …

This work presents a (SOS) based framework to perform data-driven stabilization and robust
control tasks on discrete-time linear systems where the full-state observations are corrupted …

This paper presents a linear-programming based algorithm to perform data-driven
stabilizing control of linear positive systems. A set of state-input-transition observations is …

An important trend about data-driven systems has recently emerged motivated for practical
issues, that are the difficulties to identify a model of the plant. In this direction some recent …

This paper considers the stabilization of unknown switched linear systems using data.
Instead of a full system model, we have access to a finite number of trajectories of each of …

This work presents a sum-of-squares (SOS) based framework to perform data-driven
stabilization and robust control tasks on discrete-time linear systems where the full-state …

This paper is concerned with the noiseless and noisy data-driven consensus problem of
general linear multi-agent systems (MASs) with unknown agent dynamics. First, a data …

This paper investigates the problem of data-driven stabilization for linear discrete-time
switched systems with unknown switching dynamics. In the absence of noise, a data-based …