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 …

Learning algorithms have become an integral component to modern engineering solutions.
Examples range from self-driving cars and recommender systems to finance and even …

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 …

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 …

This letter considers the problem of linear time-invariant (LTI) system identification using
input/output data. Recent work has provided non-asymptotic results on partially observed …

Machine and reinforcement learning (RL) are increasingly being applied to plan and control
the behavior of autonomous systems interacting with the physical world. Examples include …

This paper studies a class of partially observed Linear Quadratic Gaussian (LQG) problems
with unknown dynamics. We establish an end-to-end sample complexity bound on learning …

The paper explores the standard advanced control elements commonly used in industry for
designing advanced control systems. These elements include cascade, ratio, feedforward …

Motivated by vision-based control of autonomous vehicles, we consider the problem of
controlling a known linear dynamical system for which partial state information, such as …

This text presents an introduction to an emerging paradigm in control of dynamical systems
and differentiable reinforcement learning called online nonstochastic control. The new …