Mathematical optimization is one of the cornerstones of modern engineering research and
practice. Yet, throughout all application domains, mathematical optimization is, for the most …

Optimization underpins many of the challenges that science and technology face on a daily
basis. Recent years have witnessed a major shift from traditional optimization paradigms …

This article investigates the problem of regulating, at every time, a linear dynamical system
to the solution trajectory of a time-varying constrained convex optimization problem. The …

This paper studies the design of feedback controllers to steer a switching linear dynamical
system to the solution trajectory of a time-varying convex optimization problem. We propose …

We propose an algorithm based on online convex optimization for controlling discrete-time
linear dynamical systems. The algorithm is data-driven, ie, does not require a model of the …

This paper considers the problem of controlling a dynamical system when the state cannot
be directly measured and the control performance metrics are unknown or only partially …

In this work, we study the relations between bounded dynamic regret and the classical
notion of asymptotic stability for the case of a priori unknown and time-varying cost functions …

In this work, we propose a control scheme for linear systems subject to pointwise in time
state and input constraints that aims to minimize time-varying and a priori unknown cost …

This paper considers a convex optimization problem with cost and constraints that evolve
over time. The function to be minimized is strongly convex and possibly non-differentiable …

This paper considers the problem of regulating a linear dynamical system to the solution of a
convex optimization problem with an unknown or partially-known cost. We design a data …