This paper addresses the problem of finite horizon constrained robust optimal control for
nonlinear systems subject to norm-bounded disturbances. To this end, the underlying …

This paper addresses the problem of optimally controlling nonlinear systems with norm-
bounded disturbances and parametric uncertainties while robustly satisfying con-straints …

The growing scale and complexity of safety-critical control systems underscore the need to
evolve current control architectures aiming for the unparalleled performances achievable …

Linear high-pass phenomena matter in signal processing, circuits, and control. In nonlinear
systems, however, there is no working definition of high-pass behavior. Any definition would …

We introduce a method for controlling systems with nonlinear dynamics and full actuation by
approximating the dynamics with polynomials and applying a system level synthesis …

Over the past few decades, our physical and digital worlds have become increasingly
intertwined and reliant on each other. Advancements in areas such as machine learning …

The work presented in this thesis lies at the intersection of Machine Learning (ML) and
control theory. The first part is dedicated to the design of Deep Neural Network (DNN) …