Title: Model Predictive Control with MPCcode: Theory and Implementation
by Marco Vaccari (University of Pisa, Italy)
SCOPE: This workshop introduces Model Predictive Control (MPC) using the MPCcode software, covering both theoretical concepts and practical implementation. Participants will review key MPC principles, including predictive modeling, constraint handling, and optimization, and apply them to selected case studies. The focus will be on chemical engineering applications, though the methodology extends naturally to broader industrial automation problems. Through guided exercises, attendees will learn how to use MPCcode to modify controller architectures and internal models with simple yet useful options. Prior knowledge of MPC and Python is helpful but not required.
SPEAKERS: Marco Vaccari (University of Pisa, Italy)
Bio: Marco Vaccari graduated in Chemical Engineering in 2015 (Laurea degree) from the University of Pisa, where he also received the PhD degree in Chemical Engineering in 2019. From 2019 to 2023, he was a PostDoc at the Department of Chemical Engineering of University of Pisa. He is an Assistant Professor in Chemical Plants (ING-IND/25 IMPIANTI CHIMICI) since 2023 at the Chemical Engineering Section of the Department of Civil and Industrial Engineering of the University of Pisa. His main research activities are within the area of process modeling, simulation, and optimization, and he teaches Paper production plants in the MS program in Engineering of Paper and Cardboard and Sustainability Analysis of Industrial Processes in the MS program in Chemical Engineering, at the University of Pisa.