Electronic Interfaces – 6 CFU (block E, optB, optC1.b, optC2.b)

Electronic Interfaces – 6 CFU (block E, optB, optC1.b, optC2.b)
1 YEAR II semester  6 CFU
Christian Falconi A.Y. 2022-23 (since)
A.Y. 2023-24 (new block E) 
Christian Falconi (4)

Usman Khan (2)

A.Y. 2025-26
didatticaweb

Syllabus📑

Code: 80300103
SSD: ING-INF/01

Adaptive Systems (block C-opt) –> Identification and Neural Networks (24-25)

Adaptive Systems (block C-opt) –> Identification and Neural Networks (24-25)
2 YEAR II semester  6 CFU
Patrizio Tomei (4cfu)
Eugenio Martinelli (2cfu)
A.Y. 2023-24
SANTOSUOSSO Giovanni Luca A.Y. 2024-25 not be activated
A.Y. 2025-26
(new name “Identification and Neural Networks”
Didatticaweb
Code: 80300088
SSD: ING-INF/04

Pre-requirement: The basics of systems theory and control are required.

LEARNING OUTCOMES: The course aims to provide the basic techniques for the design of predictors, filters, and adaptive controllers.

KNOWLEDGE AND UNDERSTANDING: Students must obtain a detailed understanding of design techniques with the help of MATLAB-SIMULINK to solve industrial problems of adaptive filtering, adaptive prediction, and adaptive control.

APPLYING KNOWLEDGE AND UNDERSTANDING: Students must be able to apply the project techniques learned in the course even in different industrial situations than those examined in the various phases of the course.

MAKING JUDGEMENTS: Students must be able to apply the appropriate design technique to the specific cases examined, choosing the most effective algorithms.

COMMUNICATION SKILLS: Students must be able to communicate using the terminology used for filtering, prediction, and adaptive control. They must also be able to provide logical and progressive exposures starting from the basics, from structural properties, from modeling to the design of algorithms, without requiring particular prerequisites. Students are believed to be able to understand the main results of a technical publication on the course topics. Guided individual projects (which include the use of Matlab-Simulink) require assiduous participation and exchange of ideas.

LEARNING SKILLS: Students must be able to identify the appropriate techniques and algorithms in real cases that arise in industrial applications. Furthermore, it is believed that students have the ability to modify the algorithms learned during the course in order to adapt them to particular situations under consideration.

Texts

Adaptive Filtering Prediction and Control, Graham C. Goodwin, Kwai Sang Sin, Dover Publications, 2009.

CONTROL OF ELECTRICAL MOTORS AND VEHICLES (B-C1-C2-E) (25-26)

CEM
2 YEAR II semester 6 CFU
Cristiano M. Verrelli A.Y. 2021-22 to A.Y. 2024-25 (Control of Electrical Machines (B-C-E))
 

 

A.Y. 2025-26 (new name CONTROL OF ELECTRICAL MOTORS AND VEHICLES )
didatticaweb
All syllabi📑

Code:8039782
SSD: ING-INF/04

 

MEASUREMENT SYSTEMS FOR MECHATRONICS – 6 cfu (2023-24 last year)

MEASUREMENT SYSTEMS FOR MECHATRONICS – 6 cfu (2023-24 last year)
2 YEAR II semester  6 CFU
Arianna Mencattini A.Y. 2021-22

A.Y. 2022-23

A.Y. 2023-24 Measurement Systems for Mechatronics

A.Y. 2024-25: Computer Vision – program

Code: 8039787
SSD: ING/INF/07

LEARNING OUTCOMES: Learning basic concepts in digital image processing and analysis as a novel measurement system in biomedical fields. The main algorithms will be illustrated particularly devoted to the image medical fields.

KNOWLEDGE AND UNDERSTANDING: The student acquires knowledge related to the possibility to use an image analysis platform to monitor the dynamics of a given phenomenon and to extract quantitative information from digital images such as object localization and tracking in digital videos.

APPLYING KNOWLEDGE AND UNDERSTANDING: The student acquires the capability to implement the algorithms in Matlab through dedicated lessons during the course with the aim of being able to autonomously develop new codes for the solution of specific problems in different application fields.

MAKING JUDGEMENTS: :
The student must be able to integrate the basic knowledge provided with those deriving from the other courses such as probability, signal theory, and pattern recognition. some fundamentals of measurement systems as well as basic metrological definitions will be provided in support of background knowledge.

COMMUNICATION SKILLS:
The student solves a written test and develops a project in Matlab that illustrates during the oral exam. The project can be done in a group to demonstrate working group capabilities.

LEARNING SKILLS:
Students will be able to read and understand scientific papers and books in English and also to deepen some topics. In some cases, students will develop also experimental tests with time-lapse microscopy acquisition in the department laboratory.

 

SYLLABUS:

Fundamentals of metrology. Basic definitions: resolution, accuracy, precision, reproducibility, and their impact over an image based measurement system. Image processing introduction. Image representation. Spatial and pixel resolution. Image restoration. Deconvolution. Deblurring. Image quality assessment. Image enhancement. Image filtering for smoothing and sharpening. Image segmentation: pixel based (otsu method), edge based, region based (region growing), model based (active contour, Hough transform), semantic segmentation. Morphological operators. Object recognition and image classification. Case study: defects detection, object tracking in biology, computer assisted diagnosis, facial expression in human computer interface.
Matlab exercises.

POWERTRAIN TECHNOLOGIES FOR FUTURE MOBILITY – 9 CFU

POWERTRAIN TECHNOLOGIES FOR FUTURE MOBILITY – 9 CFU
2 YEAR  II semester  9 CFU
Stefano CORDINER (6/9 cfu)
Lorenzo BARTOLUCCI (3/9 cfu)
A.Y. 2021-22

Internal Combustion Engines

Since A.Y. 2022-23

POWERTRAIN TECHNOLOGIES FOR FUTURE MOBILITY

didatticaweb
✅ Syllabus📑

Code: 80300079

80300077 M-6264
SSD: ING/IND/08
(by Mechanical Engineering)

Digital Signal Processing – 6 CFU (optC1.b/optC2.b)

Digital Signal Processing – 6 CFU (optC1.b/optC2.b)
1 YEAR II semester  6 CFU
ICT and Internet Engineering
Marina RUGGIERI (5cfu)

Tommaso ROSSI (1cfu)

A.Y. 2025-26
Syllabus📑

 
Code: 8039514
SSD: ING-INF/03

The Digital Signal Processing teaching modules offer students the opportunity to become designers, providing a solid theoretical basis, multiple design techniques, and Matlab script development skills.

DSP is offered to Mechatronics students with the option of 6 credits and 9 credits format. Students who select the 6-credit option might be interested in adding a +3 credits of formative activities, with focus on pre-assigned additional topics of the DSP realm.

Thermodynamics and Heat Transfer (block A)

Thermodynamics and Heat Transfer (block A)
1 YEAR II semester  6 CFU
Michela GELFUSA A.Y. 2021-22 (by Engineering Sciences)

A.Y. 2024-25 (last year)

Code: 80300063
SSD: ING-IND/10
(by Engineering Sciences)
  • Prerequisites: Knowledge of basic notions from physics courses, above all physical quantities, units of measurement, fundamental laws of mechanics, optics and electromagnetism.
  • Objectives:
  • LEARNING OUTCOMES: The course aims to provide students with the basic principles, physical laws, and applications of thermodynamics and heat transfer, with the dual purpose of preparing them to afford more applicative courses, and use the acquired knowledge for design and sizing simple components and thermal systems.
  • KNOWLEDGE AND UNDERSTANDING: Students will have to understand the laws of applied thermodynamics and heat transfer, and understand the structure and operation of simplest components and systems. They will also demonstrate that they have acquired the basic methodologies for verifying and designing the studied devices.
  • APPLYING KNOWLEDGE AND UNDERSTANDING: Students should be able to size and/or verify simple components and systems, such as, for example engine systems.
  • MAKING JUDGEMENTS: Students will have to acquire the autonomous ability to face subsequent studies for which this course is preparatory, and to draw up simple projects of thermal systems that use the components studied. They will also have to be able to evaluate projects drawn up by other parties, checking that the project specifications are respected. COMMUNICATION SKILLS: Students must be able to illustrate in a complete and exhaustive way the acquired information, the results of their study and of their project activity, also through the normally used means of communication (discussion of the results obtained, report on the performed activity, Power Point presentations, etc.).
  • LEARNING SKILLS: Students must be able to apply the physical laws underlying the studied phenomena, and to face further studies that use the acquired knowledge. They will have to be able to expand the already owned information through the analysis of technical-scientific literature, and to modify their curricula choosing future knowledge to be acquired on the base of their knowledge and tendency.

 

Mechanics of Materials and Structures – 6 CFU (block A-E)

Mechanics of Materials and Structures – 6 CFU (block A-E)
1 YEAR II semester  6 CFU
Andrea Micheletti

Edoardo Artioli

A.Y. 2021-22 (9 cfu)
Andrea Micheletti A.Y. 2022-23
A.Y. 2024-25 (6 cfu)
ES – Mechanics of Materials and Structures (MMS)A. Micheletti
✅ Syllabus📑

Code: 80300064
SSD: ICAR/08
(by Engineering Sciences)