UNIVERSITA' DEGLI STUDI ROMA "TOR VERGATA"| 1 YEAR |
1 semester | 6 CFU |
| Vincenzo MULONE (3cfu)
Pietro MELE (3cfu) |
A.Y. 2025-26 |
| Program
Code: |
Digital Modeling of Energy Conversion – 6 CFU (block A-B) (since 2025-26)
Block B
Mechanics of Systems for Simulations – 6 CFU (block A-B) (since 2025-26)
| 1 YEAR |
1 semester | 6 CFU |
| Marco Ceccarelli | A.Y. 2025-26 program 📑 |
| Code: 80300216 SSD: ING-IND-13 (by Engineering Sciences) |
OBJECTIVES
LEARNING OUTCOMES: The course aims to teach students the knowledge and tools that are needed to address the issues that are related to the identification, modeling, analysis, and design of multi-body planar systems in English language and terminology
KNOWLEDGE AND UNDERSTANDING: modeling and procedures to recognize the structure and characteristics of mechanisms and machines
APPLYING KNOWLEDGE AND UNDERSTANDING: acquisition of analysis procedures for the understanding of kinematic and dynamic characteristics of mechanisms and machines
MAKING JUDGEMENTS: possibility of judging the functionality of mechanisms and machines with their own qualitative and quantitative assessments
COMMUNICATION SKILLS: learning technical terminology and procedures for presenting the performance of mechanisms
LEARNING SKILLS: learning technical terminology and procedures for the presentation of the performance of mechanisms
PREREQUISITES: knowledge of basic mechanics of rigid bodies and computation skills
SYLLABUS
Structure and classification of planar mechanical systems, kinematic modeling, mobility analysis, graphical approaches of kinematics analysis, kinematic analysis with computer-oriented algorithms; dynamics and statics modeling, graphical approaches of dynamics analysis, dynamic analysis with computer-oriented algorithms, performance evaluation; elements of mechanical transmissions.
BOOKS:
Lopez-Cajùn C., Ceccarelli M., Mecanismos, Trillas, Città del Messico
Shigley J.E., Pennock G.R., Uicker J.J., “Theory of Machines and Mechanisms”, McGraw-Hill, New York
Handnotes and papers by the teachers
Radar and Localization – 6 CFU (block C2)
| 2 YEAR | II semester | 6 CFU |
| Prof. Mauro Leonardi | A.Y. 2025-26 |
|
|
(By ICT) |
| Code: 80300159 SSD: ING-INF/03 |
LEARNING OUTCOMES: Knowledge of the main applications and operations of radar systems with the necessary basic elements (both theoretical and technical-operational).
KNOWLEDGE AND UNDERSTANDING: Being aware, at the system level, performance in terms of scope, discrimination, ambiguity, Doppler filtering
APPLYING KNOWLEDGE AND UNDERSTANDING: knowing how to deal with new problems with the methods learned
MAKING JUDGEMENTS: the ability to choose among the various methods learned the proper one to face new problems and radar design.
Syllabus – Radar Systems
1. Fundamentals
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General information on radar.
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Spectrum usage.
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Radar measurements:
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Distance.
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Radial velocity.
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Angular location.
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2. Radar Equation and Propagation
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Fundamental radar equation.
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Receiver and antenna noise.
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Propagation: attenuation and reflections.
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Losses.
3. Radar Cross Section and Target Models
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Radar Cross Section (RCS).
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Target fluctuation models:
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Slow fluctuation.
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Rapid fluctuation.
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4. Target Detection
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Detection of fixed targets.
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Detection of moving targets.
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Pulse integration.
5. Decision Theory and Radar Detection
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Decision criteria.
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Detection with a single pulse.
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Detection with N pulses.
6. Radar Types
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Pulsed radar.
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Continuous Wave (CW) radar.
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Frequency Modulated Continuous Wave (FMCW) radar.
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Automotive radar.
Block B – Electronics
—> Dedicated to BS: Mechanical Engineering – Biomedical Engineering with a background in Mechanics
| SPECIFIC SUBJECTS – BLOCK B |
Year | sem | CFU | SSD | class hours |
| DIGITAL ELECTRONICS | 1 | I | 6 | ING-INF/01 | 60 |
| INNOVATIVE MATERIALS WITH LABORATORY | 1 | I | 6 | ING-IND/21 | 60 |
| One of the following: | |||||
| Analogue Electronics* | 1 | II | 6+3 | ING-INF/01 | 60 |
| Electronic Interfaces** | 1 | II | 6 | ING-INF/01 | 60 |
| One of the following: | |||||
| Feedback Control Systems | 1 | II | 6 | ING-INF/04 | 60 |
| Control of Electrical Machines | 2 | II | |||
| TOTAL ECTS | 24(+3) | ||||
* A.Y. 2023-24 Analogue Electronics changes in 9 credits. (3 credits extra).
** new subject since February 2022-2023
Subjects 1st Year – I sem – II sem
Subjects 2nd Year – I sem – II sem
Optional Courses
COMPUTER VISION – 6 CFU (since 2024-25)
| 2 YEAR | II semester | 6 CFU |
| Arianna Mencattini | A.Y. 2023-24 (ex MEASUREMENT SYSTEMS FOR MECHATRONICS) |
| A.Y. 2024-25: Computer Vision – program | |
| Code: 8039787 SSD: ING/INF/07 |
LEARNING OUTCOMES:
Learning of 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 mechatronics fields.
KNOWLEDGE AND UNDERSTANDING:
The student acquires the 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 to 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 of basic metrological definitions will be provided in support of background knwoledge.
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 group to demonstrate working group capabilities.
LEARNING SKILLS:
Students will be able to read and understand scientific papers and books in English also to deepen some topics. In some cases, students will develop also experimental tests with time-lapse microscopy acquisition in 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.
TEXTS
Digital image processing, Gonzalez and Woods, Prentice Hall, New York, 2002.
BiPM, I. E. C., IFCC, I., IUPAC, I., & ISO, O. (2012). The international vocabulary of metrology— basic and general concepts and associated terms (VIM). JCGM, 200, 2012.
ATTENDANCE
Although attendance is optional, it is strongly recommended to follow the lessons. The professor recommends the students to subscribe the course on the Delphi website. The teams platform will be used as a consequence to communicate with the Professor, ask for doubts, and download the materials used for the lessons.
Electronic Interfaces – 6 CFU (block B-opt – E) (since 2022-23)
| 1 YEAR | II semester | 6 CFU |
| Christian Falconi | A.Y. 2022-23 (since) |
| since A.Y. 2023-24 (new block E) – program | |
| Code: 80300103 SSD: ING-INF/01 |
FORMATIVE OBJECTIVES
LEARNING OUTCOMES:
The goal is to teach the fundamental principles and tools for designing electronic interfaces.
The contents of the course have general validity, but the focus will be on electronic interfaces for mechatronics.
The course is oriented toward design.
KNOWLEDGE AND UNDERSTANDING:
Students will need to know and understand the fundamental principles and tools for the analysis and design of electronic interfaces.
APPLYING KNOWLEDGE AND UNDERSTANDING:
Students will have to demonstrate that they are able to design electronic interfaces.
MAKING JUDGEMENTS:
Students will be able to evaluate the design of electronic interfaces.
COMMUNICATION SKILLS:
The students, in addition to illustrating the fundamental principles and tools for the design of electronic interfaces, must be able to explain each design choice.
LEARNING SKILLS:
Students must be able to read and understand scientific texts and articles (also in English) concerning electronic interfaces.
PREREQUISITES
Thévenin equivalent circuit.
Norton equivalent circuit.
Laplace transform
Fourier transform
Syllabus:
Fundamentals on electronic devices.
Equivalent circuits (mechanic systems, thermal systems,…).
Diode circuits.
Transistor circuits.
Nullors.
Operational amplifiers (op amps).
Universal active devices.
Non-idealities of op-amps and other universal active devices.
Op-amp circuits.
Simulations of electronic circuits (SPICE).
Electronic interfaces.
Circuits for mechatronics (design examples).
Control of Electrical Machines (B-C-E) –> CONTROL OF ELECTRICAL MOTORS AND VEHICLES (B-C1-C2-E) (25-26)
| 2 YEAR | II semester | 6 CFU |
| Cristiano M. Verrelli | A.Y. 2021-22 to A.Y. 2024-25 |
|
|
A.Y. 2025-26 (new name CONTROL OF ELECTRICAL MOTORS AND VEHICLES ) |
| Code:8039782 SSD: ING-INF/04 |
LEARNING OUTCOMES: The course aims to provide a unified exposition of the most important steps and concerns in mathematical modeling and design of estimation and control algorithms for electrical machines such as:
– permanent magnet synchronous motors
– permanent magnet stepper motors
– synchronous motors with damping windings
– induction (asynchronous) motors
– synchronous generators.
KNOWLEDGE AND UNDERSTANDING: Students should be able to gain profound insight into the fundamental mathematical modeling and control design techniques for electrical machines, which are of interest and value not only to engineers engaged in the control of electric machines but also to a broader audience interested in (nonlinear) control design.
APPLYING KNOWLEDGE AND UNDERSTANDING: Students should be able to deeply understand mathematical modeling through nonlinear differential equations, stability and nonlinear control theory concepts, and design of (nonlinear) adaptive controls containing parameter estimation algorithms (important for applications). Students should be able to apply the related knowledge to learning control of robotic manipulators and cruise/yaw rate control of electric vehicles.
MAKING JUDGEMENTS: Students should be able to identify the specific design scenario and apply the most suitable techniques. Students should be able to compare the effectiveness of different controls while analyzing theoretical/experimental advantages and drawbacks.
COMMUNICATION SKILLS: Students should be able to use a single notation and modern (nonlinear) control terminology. Students should be able to exhibit a logical and progressive exposition starting from basic assumptions, structural properties, modeling, control, and estimation algorithms. Students are also expected to be able to read and capture the main results of a technical paper concerning the topics of the course, as well as to effectively communicate in a precise and clear way the content of the course. Tutor-guided individual projects (including Maple and Matlab-Simulink computer simulations and lab visits) invite intensive participation and exchanging ideas.
LEARNING SKILLS: Being enough skilled in the specific field to undertake the following studies characterized by a high degree of autonomy.
TEXTS
R. Marino, P. Tomei, C.M. Verrelli, Induction Motor Control Design, Springer, 2010.
Latest journal papers.
VERIFICATION OF THE KNOWLEDGE
Verify the knowledge and skills acquired by the student on the topics covered by the program. The intermediate exams, the final written tests, and the oral exam will consist of questions related to the topics covered by the program of the course. The questions are aimed at ascertaining the student’s knowledge and his/her reasoning skills in making logical connections between the different topics.
The final vote of the exam is expressed out of thirty and will be obtained through the following graduation system:
Not pass: important deficiencies in the knowledge and in the understanding of the topics; limited capacity for analysis and synthesis, frequent mistakes and limited critical and judgmental capacity, inconsistent reasoning, inappropriate language.
18-21: the student has acquired the basic concepts of the discipline and has an analytical capacity that comes out only with the help of the teacher. The way of speaking and the language used are almost correct, though not precise.
22-25: the student has acquired the basic concepts of the discipline in a discrete way; he/she knows how to discuss the various topics; he/she has an autonomous analysis capacity while adopting a correct language.
26-29: the student has a well-structured knowledge base. He/She is able to independently adopt a correct logical reasoning; notations and technical language are correct.
30 and 30 cum laude: the student has a complete and in-depth knowledge base. The cultural references are rich and up-to-date while being expressed by means of brilliant technical language.
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.
ELECTRONICS OF IOT AND EMBEDDED SYSTEMS – 12 CFU
| 2 YEAR | 1 semester | 12 CFU |
| Patrick LONGHI (3cfu) Giancarlo ORENGO (3cfu) Gian Carlo CARDARILLI (4cfu) Luca DI NUNZIO (2cfu) |
since A.Y. 2019-20 |
| M-5519 – ELECTRONICS OF IOT (6cfu) M-5520 – DESIGN OF EMBEDDED SYSTEMS FOR MECHATRONICS (6cfu) |
|
| Code: 8039795 SSD: ING-INF/01 |
EDUCATIONAL OBJECTIVES:
The objectives of the course are:
1) to provide the tools to carry out a radio link assessment in a real application context.
2) learn the fundamental parameters of the antennas used in IoT applications
3) provide the tools to interpret the electrical diagram of the RF front end of a typical trans receiver.
KNOWLEDGE AND UNDERSTANDING:
Provide the fundamental tools to understand the most advanced and updated content from publications, magazines, forums, blogs, etc., to always be updated on the state of the art.
ABILITY TO APPLY KNOWLEDGE AND UNDERSTANDING:
Practical radio link budget, electronic noise evaluation on receiver behavior, installation effects of the antennas, understanding of key parameters of commonly used antennas in the targeted scenario, analysis of an RF transceiver block diagram
AUTONOMY OF JUDGMENT:
With the enormous amount of information that is available today to developers of IoT applications, the course seeks to develop the ability of the student to select the highest quality and most validated content.
COMMUNICATION SKILLS:
The final test is based on an oral exam in which the student illustrates a part of the module
LEARNING ABILITY:
The course aims to develop in the student the ability to independently learn new and constantly updated content because the knowledge acquired today soon becomes obsolete.
SYLLABUS:
(Longhi):
Introduction to radiating elements and their key parameters.
Ideal and practical link budget.
The effect of noise in electronic receivers, figures of merit and mathematical modelling. Receiver G/T.
Practical aspects of IoT RF systems
RFID
Radiating elements key parameters, gain, directivity, HPBW, nulls, radiation pattern, polarization, and input impedance. Some practical cases: the mono/di-pole family, microstrip antennas, parabolic reflector, wearables
Introduction to RF transceiver systems and key-components (switches, HPA, LNA, mixers, frequency generators).
(G.Orengo):
Summary of Digital Electronics: digital encoding of information, binary (fixed and floating point), hexadecimal and ASCII; operators and main logic circuits, registers and memories, programmable devices. Prototyping boards for IoT (Arduino, Rasberry), Systems on Chip (SoC), architecture of a microcontroller, description of the Arduino Uno board. Programming languages (assembly, compiled, interpreted), structure of an Arduino sketch (libraries, setups, loops, functions, interrupts), programming elements in C (variables, math and logical operations, cycles, conditional statements). Use of digital and analog I/O ports (A/D conversion, PWM output). Synchronous and asynchronous serial communication modes, wired (USB) and wireless with Bluetooth, RF and WiFi modules. Remote control of electronic modules (sensors, dc stepper and servo motors, LED/LCD displays etc.) from portable devices (Windows, IoS), through applications developed in Processing and Python, and mobile (Android), through Apps developed with the MIT App Inventor platform. Internet protocols for device local/remote control through WiFi modules connected as access points/clients to web platforms or public/private cloud servers controlled by laptops and/or mobile devices.
(G.Cardarilli):
– Introduction to the Internet of Things (IoT) and embedded systems
– Wireless and mobile communications
– The Sensors
– Low power processing
– IoT and machine learning applications
– Future developments in the field of IoT and embedded systems
CONTROL OF MECHANICAL SYSTEMS – 9 CFU
| 2 YEAR |
1 semester | 9 CFU |
| Riccardo MARINO | Since 2019-20 |
| Code: 8039823 SSD: ING-INF/04 |
LEARNING OUTCOMES:
Ability to understand scientific papers on the control of mechanical systems
KNOWLEDGE AND UNDERSTANDING:
Knowledge of dynamic modeling of mechanical systems. Knowledge of basic feedback control techniques for single input single output systems and of decoupling techniques for multi input multi output nonlinear systems
APPLYING KNOWLEDGE AND UNDERSTANDING:
Ability to simulate using Matlab Simulink complex controlled mechanical systems
MAKING JUDGEMENTS:
Ability to evaluate stability, robustness, and performance of a control system
COMMUNICATION SKILLS: Ability to present and discuss an autonomous design project
LEARNING SKILLS: Ability to fully understand a scientific paper on the control of mechanical systems
SYLLABUS:
BASIC CONTROL TOOLS
Bounded- input bounded- output linear systems. Pole placement theorem for controllable and observable linear systems. Luenberger observers for observable systems. Design of dynamic compensators for linear systems. Integral feedback control to reject constant disturbances. PID control. System inverses for minimum phase linear systems. The combination of feedback and feedforward control actions.
ADVANCED CONTROL TOOLS
Linear approximations of nonlinear control systems about operating conditions. The definition of region of attraction for an operating condition. Output feedback compensators with integral actions to control nonlinear systems about a given operating condition. Liapunov matrix equations to determine quadratic Liapunov functions and assess the region of attraction. The definition of the sensitivity transfer function and its properties. The gang of four: sensitivity, complementary sensitivity, load sensitivity and noise sensitivity functions. How to determine the robustness of a control loop using the gang of four functions. Bode’s integral formula and the limitations imposed by unstable open loop poles. Youla parametrization to design stable compensation. Kalman filters, Riccati equations and robust control design.
CONTROL DESIGN FOR MULTIVARIABLE NONLINEAR SYSTEMS
Relative degree for a single input single output nonlinear system. State feedback control design for input-output linearization. State feedback linearization when the relative degree is equal to the state space dimension. The definition of nonlinear inverse systems. Relative degrees or decoupling indices for multivariable (multi-input, multi-output) nonlinear systems. The definition of the decoupling matrix. State feedback control design for input-output linearization when the decoupling matrix is full rank using the Penrose pseudoinverse. State feedback linearization when the sum of relative degrees is equal to the state space dimension and the decoupling matrix is full rank.
CASE STUDIES OF NONLINEAR MECHANICAL CONTROL SYSTEMS
Control of bycicles, robots, vehicles and aircrafts