Schedule 1st semester 2023-2024

2 YEAR | I semester | 6 CFU |
Mauro De Sanctis | ICT and Internet Engineering |
A.Y. 2023-24 | |
Code: SSD: ING-INF/03 |
2 YEAR | I semester | 6 CFU |
Tommaso Rossi
Cesare Roseti |
ICT and Internet Engineering |
A.Y. 2023-24 | |
Code: SSD: ING-INF/03 |
FORMATIVE OBJECTIVES
The course module provides an overview of the technologies involved in the multimedia application evolution from analogue to digital, from linear television to video on demand. To this aim, the module addresses the main TV standards, the TCP/IP protocols involved in modern streaming services, the network architectures and the different service modes.
PREREQUISITES: A good background in TCP/IP protocols.
SYLLABUS:
PARTE I – Digital TV standards, MPEG-2 and Transport Stream, IP encapsulation over DVB.
PARTE II – IP multicast, IGMP, IP multicast routing
PARTE III – Transport protocols for IP multimedia applications; Video streaming applications and CDN, the multimedia protocol stack, RTP and RTCP, multimedia signalling protocols: RTSP, SDP and SIP, Key Performance Indicators.
PARTE IV -Adaptive Streaming over HTTP, MPEG-DASH, Support to multimedia applications over 5G.
2 YEAR | 1 semester | 12 CFU |
Patrick LONGHI (3cfu)
Giancarlo ORENGO (3cfu) Gian Carlo CARDARILLI (4cfu) Luca DI NUNZIO (2cfu) |
A.Y. 2021-22
A.Y. 2022-23 |
MODULI:
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 behaviour, 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:
In the enormous amount of information that is available today to developers of IoT applications, the course seeks to develop in the student the ability 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
2 YEAR |
1 semester | 9 CFU |
Riccardo MARINO | A.Y. 2021-22
A.Y. 2022-23 |
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
1 YEAR | I semester | 6 CFU |
Marco Re |
A.Y. 2021-22 |
A.Y. 2022-23 | |
Code: 80300061 SSD: ING-INF/01 (by Engineering Sciences) |
1 YEAR |
1 semester | 6 CFU |
Marco Ceccarelli | A.Y. 2021-22
A.Y. 2022-23 |
Code: 803000062 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
1 YEAR (Blocks B|C) 2 YEAR (Blocks A) |
1 semester | 9 CFU |
Marco Ceccarelli (6/9 cfu)
Matteo Russo (3/6 cfu) |
A.Y. 2021-22
A.Y. 2022-23 |
Matteo Russo | A. Y. 2023-24 |
Code: 8039785 SSD: ING-IND/13 |
LEARNING OUTCOMES:
The aims of the course are related to explaining the modeling and algorithms for the analysis and design of the functioning of robot mechanisms in terms of mechanical performance. The students will learn how to handle the mechanics of robot by acquiring skills in analyzing and design robots for manipulation tasks in industrial and service applications.
KNOWLEDGE AND UNDERSTANDING:
during the course, problems and characteristics of robotic systems structures and operations are presented to increase students’ knowledge and to allow them to understand problems and solutions in the specific area of robotics
APPLYING KNOWLEDGE AND UNDERSTANDING:
Students are required to apply the characteristics and algorithms for the analysis of manipulations and robotizations of specific robotic systems for merit assessments and demonstrate specific presentation and discussion skills of robotics issues.
MAKING JUDGEMENTS:
Students are involved in the presentation of the modeling and in the discussion of the problems to learn to examine in an autonomous and critical way the problems of analysis of robotic systems.
COMMUNICATION SKILLS:
During the course, the students take part in the discussion of the presented topics and at the end of the course present a report of manipulation and robotization analysis of their choice.
LEARNING SKILLS:
During the course, the students are involved in the discussion for a continuous stimulus to verify the learning and presentation of robot mechanics. the learning achieved is also verified in the presentation of the elaboration of manipulation and robotization analysis of their choice
SYLLABUS:
types of robots and industrial and service applications; components, technical characteristics, and evaluation; analysis and evaluation of manipulative movements; types of manipulators; Denavit-Hartenberg’s notation; fundamentals of direct kinematics; workspace analysis, trajectory planning; fundamentals of statics and dynamics: modeling, actions, equilibrium conditions; equation of motion; fundamentals of the regulation and control of the motion; types and functionality of grippers; grasp mechanics: modeling, actions, equilibrium conditions; mobile service robots: structures and operation; parallel architecture robots; service robots for medical applications: structures and operation; preparation of performance analysis reports of a robot.
1 YEAR (Block A|C) 2 YEAR (Block B) |
1 semester | 9 CFU |
Corrado Di Natale | A.Y. 2019-20 (new name, ex Electronic Devices and Sensors )
A.Y. 2021-22 |
Alexandro Catini (6cfu)
Corrado Di Natale (3cfu) |
A.Y. 2022-23
A.Y. 2023-24 |
Code: 8039927 SSD: ING-INF/01 |
LEARNING OUTCOMES:
To introduce the student to modern sensor technologies and their major applications.
KNOWLEDGE AND UNDERSTANDING:
To make the student condition to analyze the sensor performance and to design simple sensors’ interface circuit.
APPLYING KNOWLEDGE AND UNDERSTANDING:
Capability to select sensors for each specific application MAKING JUDGEMENTS:
Evaluate in the different contexts which are the most suitable sensors and evaluate the performance using standardized parameters set.
COMMUNICATION SKILLS:
Capability to write synthetic reports about the working principles of sensors
LEARNING SKILLS:
To learn how to solve sensors’ circuits in order to determine their performance and to optimally design sensor systems.
SYLLABUS:
Electronic properties of materials: semiconductors.
General properties of sensors;
Sensitivity and resolution.
Temperature sensors: thermistors, integrated sensors, thermocouples;
Mechanic sensors: Strain gauges: Introduction to MEMS: accelerometer, gyroscope, pressure and flow sensors;
Magnetic sensors;
Optical sensors: photodiodes and image sensors;
infrared sensors; interface circuits for resistive and capacitive sensors