7 citations · 7 across the 2 of their papers we have counts for
3 papers
eess.SY2022★ 7 cited
Learning Controllers from Data via Approximate Nonlinearity Cancellation
Claudio De Persis, Monica Rotulo, Pietro Tesi
We introduce a method to deal with the data-driven control design of nonlinear systems. We derive conditions to design controllers via (approximate) nonlinearity cancellation. Thes…
eess.SY2021
Online learning of data-driven controllers for unknown switched linear systems
Monica Rotulo, Claudio De Persis, Pietro Tesi
Motivated by the goal of learning controllers for complex systems whose dynamics change over time, we consider the problem of designing control laws for systems that switch among a…
eess.SY2019
Data-driven Linear Quadratic Regulation via Semidefinite Programming
Monica Rotulo, Claudio De Persis, Pietro Tesi
This paper studies the finite-horizon linear quadratic regulation problem where the dynamics of the system are assumed to be unknown and the state is accessible. Information on the…