Fundamentals of Model Predictive Control (Ph.D. course)

This Ph.D. course aims to provide the fundamental concepts of the Model Predictive Control theory. In particular, the course will focus on MPC stability, robustness, tracking MPC, and economic MPC.

Lesson 1: Preliminaries
Lesson 2: Stability
Lesson 3: Tracking MPC
Lesson 4: Economic MPC

Teaching material can be found here.

Dynamic Systems Identification (9 CFU)

The Dynamical Systems Identification (148004) course is part of the Master Degree in Engineering and Management for Health and Smart Technology Engineering.

The aim of the course is to provide:

  1. knowledge of machine learning for static systems, regression and classification problems
  2. knowledge of dynamical systems, their property and how to estimate them using experimental data.

Teaching material and solved exercises can be found here.

Data Analysis Lab (3 CFU)

The Data Analysis Lab (148021-1) is part of both the Technological Lab and the Management Lab in the Master Degree in Engineering and Management for Health

The aim of the course is to train the student to work in team to address an assigned project. The practical activities of the laboratory are aimed at improving technical and communication skills.

The lab activities will concern on practical activities focused on learning static and dynamic systems. The explored techniques will mainly be linear and logistic regression for static systems and PEM techniques for dynamic systems identification.

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