6 papers
Learning myopic mixed-integer nonlinear model predictive control from expert demonstrations
Christopher Anthony Orrico, W. P. M. H. Heemels, Dinesh Krishnamoorthy
Applying nonlinear model predictive control (NMPC) to systems with hybrid dynamics or discrete actions typically yields mixed-integer nonlinear programs (MINLPs), whose real-time s…
On Building Myopic MPC Policies using Supervised Learning
Christopher A. Orrico, Bokan Yang, Dinesh Krishnamoorthy
The application of supervised learning techniques in combination with model predictive control (MPC) has recently generated significant interest, particularly in the area of approx…
Value Function Approximation for Nonlinear MPC: Learning a Terminal Cost Function with a Descent Property
T. M. J. T. Baltussen, C. A. Orrico, A. Katriniok +2
We present a novel method to synthesize a terminal cost function for a nonlinear model predictive controller (MPC) through value function approximation using supervised learning. E…
MPC strategies for density profile control with pellet fueling in nuclear fusion tokamaks under uncertainty
Christopher A. Orrico, Hari Prasad Varadarajan, Matthijs van Berkel +4
Control of the density profile based on pellet fueling for the ITER nuclear fusion tokamak involves a multi-rate nonlinear system with safety-critical constraints, input delays, an…
A Scenario-based Model Predictive Control Scheme for Pandemic Response through Non-pharmaceutical Interventions
Domagoj Herceg, Marco DellOro, Riccardo Bertollo +5
This paper presents a scenario-based model predictive control (MPC) scheme designed to control an evolving pandemic via non-pharmaceutical intervention (NPIs). The proposed approac…
A Comparative Study of Distributed Feedback Optimizing Control Architectures
Risvan Dirza, Hari Prasad Varadarajan, Vegard Aas +2
This paper considers the problem of steady-state real-time optimization (RTO) of interconnected systems with a common constraint that couples several units, for example, a shared r…