Studying at the University of Verona

Here you can find information on the organisational aspects of the Programme, lecture timetables, learning activities and useful contact details for your time at the University, from enrolment to graduation.

Study Plan

This information is intended exclusively for students already enrolled in this course.
If you are a new student interested in enrolling, you can find information about the course of study on the course page:

Laurea magistrale in Computer Engineering for intelligent Systems - Enrollment from 2025/2026

The Study Plan includes all modules, teaching and learning activities that each student will need to undertake during their time at the University.
Please select your Study Plan based on your enrollment year.

CURRICULUM TIPO:

2° Year   It will be activated in the A.Y. 2025/2026

ModulesCreditsTAFSSD
It will be activated in the A.Y. 2025/2026
ModulesCreditsTAFSSD
Modules Credits TAF SSD
Between the years: 1°- 2°
4 modules among the following:
- 1st year: Advanced visual computing and 3d modeling, Computer vision, Embedded & IoT systems design, Embedded operating systems, Robotics 
- 2nd year: Advanced control systems
6
B
ING-INF/05
6
B
ING-INF/04
Between the years: 1°- 2°
Between the years: 1°- 2°
Further activities
6
F
-

Legend | Type of training activity (TTA)

TAF (Type of Educational Activity) All courses and activities are classified into different types of educational activities, indicated by a letter.




S Placements in companies, public or private institutions and professional associations

Teaching code

4S009008

Credits

6

Scientific Disciplinary Sector (SSD)

ING-INF/04 - AUTOMATICA

Learning objectives

The course aims to provide the following knowledge: theoretical and practical tools for modeling, analyzing and controlling a complex dynamic system using the most modern techniques based on the theory of nonlinear systems and optimization. At the end of the course the student will have to demonstrate that s/he has the following skills to apply the acquired knowledge: ability to model and analyze a dynamic system, even non-linear; ability to design (linear and/or nonlinear) controllers and observers based on optimality principles; ability to model a complex nonlinear dynamic system and to analyze its properties; ability to design a controller solving an optimal control problem and/or exploiting the theory of passivity; ability to deal with problems of estimation and identification; ability to synthesize a controller for complex mechatronic systems, possibly non-linear and/or time-varying; ability to continue studies independently in the context of advanced control systems. Student must also have the ability to define the technical specifications for designing an advanced controller for complex dynamic systems described by differential or difference equations.