This paper proposes a two-level, data-driven, digital twin concept for the autonomous
landing of aircraft, under some assumptions. It features a digital twin instance (DTI) for model …

Accurate control of robots at high speeds requires a control system that can take into
account the kinodynamic interactions of the robot with the environment. Prior works on …

The biopharmaceutical industry is rapidly advancing, driven by the need for cutting‐edge
technologies to meet the growing demand for life‐saving treatments. In this context, Model …

Model predictive controllers use dynamics models to solve constrained optimal control
problems. However, computational requirements for real-time control have limited their use …

Many problems in modern robotics can be addressed by modeling them as bilevel
optimization problems. In this work, we leverage augmented Lagrangian methods and …

A tube-based robust Model Predictive Control (MPC) formulation is presented for systems
with slow and fast timescale dynamics. The controller uses a reduced-order model that …

We propose a method to control linear time-varying (LTV) discrete-time systems subject to
bounded process disturbances and measurable outputs with bounded noise, and …

Laser photocoagulation is a technique applied in the treatment of retinal disease, which is
often done manually or using simple control schemes. We pursue an optimization-based …

Over the next few decades, much of the western world will have to wrestle with the
consequences of an aging population. Indeed, the declining population growth rates in the …

Model predictive control is a powerful framework for enabling optimal control of constrained
systems. However, for systems that are described by high-dimensional state spaces this …