We study square loss in a realizable time-series framework with martingale difference noise.
Our main result is a fast rate excess risk bound which shows that whenever a trajectory …

In this article, we present a quasi-infinite horizon nonlinear model predictive control (MPC)
scheme for tracking of generic reference trajectories. This scheme is applicable to nonlinear …

In this paper, we study the system theoretic properties of a reference tracking model
predictive control (MPC) scheme for general reference trajectories and nonlinear discrete …

We study the following question in the context of imitation learning for continuous control:
how are the underlying stability properties of an expert policy reflected in the sample …

We study predictive control in a setting where the dynamics are time-varying and linear, and
the costs are time-varying and well-conditioned. At each time step, the controller receives …

Control barrier functions (CBFs) are a powerful tool to guarantee safety of autonomous
systems, yet they rely on the computation of control invariant sets, which is notoriously …

In this paper, we present a novel constraint tightening approach for nonlinear robust model
predictive control (MPC). This approach uses a simple constructive constraint tightening …

Incremental input/output-to-state stability (i-IOSS) is a popular characterization of
detectability for nonlinear systems. For instance, it is known that any system that admits a …

Motivated by the fragility of neural network (NN) controllers in safety-critical applications, we
present a data-driven framework for verifying the risk of stochastic dynamical systems with …

This paper develops a control scheme, based on the use of Long Short-Term Memory neural
network models and Nonlinear Model Predictive Control, which guarantees recursive …