This paper presents a deep learning-based model predictive control (MPC) method for
operational supply chain optimization in real time. The method follows an offline-online …

Neural ordinary differential equations (Neural ODEs) define continuous time dynamical
systems with neural networks. The interest in their application for modelling has sparked …

This paper presents an end-to-end learning approach to develo** a Nonlinear Model
Predictive Control (NMPC) policy, which does not require an explicit first-principles model …

Abstract Model predictive control is a powerful advanced control technique to deal with
complex nonlinear systems with constraints. Despite recent advances in computing …

Learning-based control with safety guarantees usually requires real-time safety certification
and modifications of possibly unsafe learning-based policies. The control barrier function …

The prevalence of neural networks in many application areas is expanding at an increasing
rate, with the potential to provide huge benefits across numerous sectors. However, one of …