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
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.
1° Year
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2° Year It will be activated in the A.Y. 2026/2027
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4 modules among:
- 1st year - Embedded operating systems, Embedded & IoT Systems design, Robotics, Computer vision, Advanced visual computing and 3D modeling - delivered in 2025/2026
- 2nd year - Advanced control systems - delivered in 2026/20273 modules among:
- 2nd year - Advanced methods for biomedical signal processing, Neurohealth, Medical robotics, Internet of Medical things - delivered in 2026/2027
- 1st or 2nd year - Mathematical modeling for Industrial and medical digital twins, Cloud computing and distributed systems - delivered in 2025/2026 or in 2026/2027 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.
Advanced control systems (2026/2027)
Teaching code
4S009008
Teacher
Coordinator
Credits
6
Language
English
Scientific Disciplinary Sector (SSD)
ING-INF/04 - SYSTEMS AND CONTROL ENGINEERING
Period
I semestre dal Oct 1, 2026 al Jan 29, 2027.
Courses Single
Authorized
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.