Fundamentals of Mechanisms of Systems (block A) (since 2022-23)

Fundamentals of Mechanisms of Systems (block A) (since 2022-23)
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

Machine Design (block A)

Machine Design (block A)
2 YEAR II semester  6 CFU
Luciano CANTONE A.Y. 2023-24
(by Engineering Sciences)
Code: 80300065
SSD:

LEARNING OUTCOMES: Designing mechanical components considering the need to save weight, material and energy while respecting safety, to promote the usefulness and social impact of the designed product.
KNOWLEDGE AND UNDERSTANDING: The design of mechanical systems, in particular, basic knowledge of the design methodologies of important machine components.
APPLYING KNOWLEDGE AND UNDERSTANDING: Know how to recognise, distinguish, and use the main techniques and tools to design mechanical components.
MAKING JUDGEMENTS: Students must assume the missing data of a problem and be able to independently formulate basic hypotheses (such as that on safety coefficients) based on the operational and functional context of the system/component they have to design.
COMMUNICATION SKILLS: Transfer information, ideas and solutions to specialist and non-specialist interlocutors through intensive use of English terminology.
LEARNING SKILLS: Students, by learning the basics of design, acquire the tools to learn the necessary design techniques of systems/components not directly addressed during the course.

VERIFICATION CRITERIA

Solution of the assignments given during the teaching. The written exam consists of 4 exercises, similar to those solved during the lessons. After passing the written test, there is an oral examination with two questions. The student’s evaluation is related to the understanding and mastery of the principles and methods of design for both written and oral exams.
The oral exam questions aim to ascertain the student’s knowledge and reasoning skills in connecting the different topics covered within the course.
The final vote of the exam is expressed out of thirty and follows the next graduation system:
Not pass, essential deficiencies in the knowledge and understanding of the topics; limited capacity for analysis and synthesis, frequent generalizations and limited critical and judgmental capacity, the topics are set out inconsistently and with inappropriate language
18-21, the student has acquired the basic concepts of the discipline and has an analytical capacity that emerges only with the teacher’s help. The way of speaking and the language used are, on the whole, correct.
22-25, the student has acquired the basic concepts of the discipline discreetly, knows how to orient himself or herself among the various topics covered and has an autonomous analysis capacity that knows how to express with the correct language.
26-29, the student has a well-structured knowledge base. He/She can independently rework the knowledge acquired in the context of the choice of conventional and unconventional materials according to the application; the way of speaking and the 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, expressed with brilliance and properties of technical language.

The midterm tests are optional and allow you to avoid the oral examination with an overall mark of at least 18/30.

Syllabus

Consolidation of basic knowledge to put the student in the right conditions to face a generic machine design problem: Mechanical Engineering design in Broad, Perspective, Load Analysis, Materials, Static Body Stresses, Elastic strain, Deflection, Stability (Eulerian buckling), Vibrations (beam Eigen-modes), Failure Theories,Safety Factors, Reliability, High cycles Fatigue, Low cycles Fatigue, Surface Damage, Contact and impact problems. During the course, several design activities will be demonstrated by exercises and by real life applications.

TEXTS

Machine Component Design, 7th Edition International Student Version Robert C. Juvinall – (University of Michigan), Kurt M. Marshek (University of Texas at Austin)
Teacher’s slides

POWERTRAIN TECHNOLOGIES FOR FUTURE MOBILITY (ex Internal Combustion Engines)

POWERTRAIN TECHNOLOGIES FOR FUTURE MOBILITY (ex Internal Combustion Engines)
1 YEAR (Block C)

2 YEAR (Blocks A|B|D|E)

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

Code: 80300079
SSD: ING/IND/08
(by Mechanical Engineering)

PREREQUISITES: Technical Physics, Fluid Machinery

FORMATIVE OBJECTIVES

LEARNING OUTCOMES:

The course aims to provide students with in-depth scientific training to correctly address the problems of designing, choosing and managing new propulsion systems for sustainable mobility starting from current solutions with internal combustion engines as well as creating the conditions for the development of innovative and low environmental impact solutions. To this end, students will develop in-depth knowledge of the operating principles of propulsion systems for transport and will learn simulation procedures for their verification and sizing. Finally, particular attention is dedicated to the most recent technological development of internal combustion engine technology aimed at overcoming current limits in terms of emissions and efficiency and defining innovative scenarios for sustainable mobility.

KNOWLEDGE AND UNDERSTANDING:
Course aim is to provide the students with tools for the analysis of the performances and the evaluation of proper design solution for internal combustion engines and their core components. At the end of the course, the student will be able to independently understand the functional link between design variables and the performance of internal combustion engines also in case of innovative design,

APPLYING KNOWLEDGE AND UNDERSTANDING:
The course, through the analysis of specific problems and quantitative data, is aimed at providing the tools for analysis and evaluation of the effects of different design choices. The theme of energy efficiency and pollution reduction are at the heart of the teaching organization. The student will be able to interpret and propose design solutions, even innovative ones, adapted to the specificity of the problems that are presented to him.

MAKING JUDGEMENTS:
By studying theoretical and practical aspects of engine design and critically assessing the influence of different design variables, the student will be able to improve his judgment and proposal in relation to design. and the management of internal combustion engines.

COMMUNICATION SKILLS:
The presentation of the theoretical and application profiles underlying the operation of internal combustion engines will be carried out to allow the knowledge of the technical language of the appropriate specialist terminology; The development of communication skills, both oral and written will also be stimulated through classroom discussion, participation in seminary activities and through final tests.

LEARNING SKILLS:
The learning capacity, even individual, will be stimulated through numerical exercises, the drafting of papers on specialized topics, the discussion in the classroom, also aimed at verifying the actual understanding of the topics treated. The learning capacity will also be stimulated by integrative educational aids (journal articles and economic newspapers) in order to develop autonomous application capabilities.

SYLLABUS:

Legislation evolution on Internal Combustin Engines. Definition of the performance of the propulsion systems and their operating characteristics in relation to the mission, driving cycles. Generalities on reciprocating internal combustion engines: Characteristics and classification, thermodynamic and performance analysis of reciprocating internal combustion engines.
Air supply for 4-stroke engines: volumetric efficiency and its evaluation; Design elements of intake systems: quasi-stationary effects; valve sizing; influence of other engine parameters; Variable Valve Actuation systems. 2-stroke engines: construction schemes; Non-stationary phenomena in intake and exhaust ducts: inertia and wave propagation; variable geometry systems; calculation models; Supercharging.
In cylinder charge Motion: Turbulence; swirl, squish, tumble; stratified charge engines.
Traditional and alternative fuels; Properties of motor fuels. Generalities: combustibles; stoichiometric air; calorific value Gaseous fuels: natural gas, hydrogen and mixtures. bio-ethanol, bio-diesel and DME. Characteristics and their use in engines: technical solutions, performance and emissions.
Fuel supply Premixed combustion engines; Non-pre-mixed combustion engines.
Combustion : Analytical elements of combustion; thermodynamics of combustion processes; calculation of the chemical composition and of the adiabatic equilibrium temperature ; transport phenomena ; chemical kinetics.
Pollutant emissions and abatement systems; Emissions: formation mechanisms, effects on health and the environment, measurement of emissions; influence of engine parameters; Innovative combustion solutions, Advanced Thermodynamic Cycles. Sustainable mobility. Operating principles of hybrid vehicles: series and parallel solution; motors a.c. and electrical employees; regenerative braking; lithium batteries, performance and prospects. Plug-in hybrid vehicles, i.c. engines “range extender”. Innovative control logics for optimal powersplitting between the different energy sources. Electric vehicles, characteristics and prospects. Numerical simulation tools will be presented for all course topics

ATTENDANCE

Course attendance is strongly recommended. During the course, students are invited to interact with the Professor during the class or office hours for any clarification or insight in specific topics related to the program.

Digital Signal Processing (block C1-C2-opt)

Digital Signal Processing (block C1-C2-opt)
1 YEAR II semester  6 CFU
ICT and Internet Engineering
Marina RUGGIERI (5cfu)

Tommaso ROSSI (1cfu)

A.Y. 2023-24
A.Y. 2024-25
Code: 8039514
SSD: ING-INF/03

OBJECTIVES

LEARNING OUTCOMES: The course aims at providing to the students the theoretical and practical tools for the development of design capabilities and implementation awareness of Digital Signal Processing (DSP) systems and applications.

KNOWLEDGE AND UNDERSTANDING: Students are envisaged to understand the DSP theoretical, design and algorithm elements and to be able to apply them in design exercises.

APPLYING KNOWLEDGE AND UNDERSTANDING: Students are envisaged to apply broadly and to personalize the design techniques and algorithm approaches taught during the lessons.

MAKING JUDGEMENTS: Students are envisaged to provide a reasoned description of the design and algorithm techniques and tools, with proper integrations and links.

COMMUNICATION SKILLS: Students are envisaged to describe analytically the theoretical elements and to provide a description of the design techniques and the algorithm steps, also providing eventual examples.

LEARNING SKILLS: Students are envisaged to deal with design tools and manuals. The correlation of topics is important, particularly when design trade-offs are concerned.

BACKGROUND

A good mathematical background (in particular on complex numbers, series, functions of complex variable) is strongly recommended.

PROGRAMME

(Prof. M.RUGUERI)

PART I – Discrete-time signals and systems; sampling process; Discrete-time Fourier transform (DTFT); Z-transform; Discrete Fourier Series (DFS).
PART II – Processing algorithms: introduction to processing; Discrete Fourier Transform (DFT); finite and long processing; DFT-based Processing; Fast Fourier Transform (FFT); processing with FFT.
PART III – Filter Design: introduction to digital filters: FIR and IIR classification; structures, design and implementation of IIR and FIR filters; analysis of finite word length effects; DSP system design and applications;
PART IV – Random sequences; processing of random sequences with digital filters; introduction to random sequence estimation; estimators of mean, variance and auto-covariance of random sequences with performance analysis; power spectrum estimation; periodogram and performance analysis; smoothed estimators of the power spectrum and performance analysis; use of FFT in power spectrum estimation.

(Dott. Tommaso ROSSI)

PART V – VLAB: applications with design examples and applications of IIR and FIR filters, Matlab-based lab and exercises; use of Matlab in the power spectrum estimation.

 

VERIFICATION CRITERIA

a) Combination of: design test (written); deepening on DSP System development (written); oral.
The design test is propedeutic to the oral one.
The course offers a verify in progress (with a related recovery date) that if passed exempts from the design test of the exam session.

b) The written exam includes design exercises.
The oral part envisages questions on the whole program and a discussion on the design test.

c) The written exam is scored from FAIL to EXCELLENT. The design test and the oral concur almost evenly to the final score (x/30).

d) The final score is based on the level of knowledge of the theoretical, design and algorithm elements and tools as well as on their effective use in design exercises; in particular, the final evaluation refers to 70% of the student’s knowledge level and for 30% to her/his capability of expressing the knowledge and providing an autonomous judgment in the design and oral exam phases.

The detailed final evaluation criteria are as follows:

Failed exam: deep lack and/or inaccuracy of knowledge and comprehension of topics and design techniques; limited capabilities in analysis and synthesis, critical ability and judgment; designs and topics are presented with a non-coherent and technically inadequate approach.
18-20: sufficient knowledge and comprehension of topics and design techniques with possible imperfections; sufficient capabilities in analysis, synthesis and autonomous judgment; designs and topics are presented with a not too much coherent and technically appropriate approach.
21-23: flat knowledge and comprehension of topics and design techniques; appropriate capabilities in analysis and synthesis with fair autonomous judgment; designs and topics are presented with sufficient coherency and technically appropriate approach.
24-26: more than fair knowledge and comprehension of topics and design techniques; good capabilities in analysis and synthesis with good autonomous judgment; designs and topics are presented with coherency and technically appropriate approach.
27-29: complete knowledge and very good comprehension of topics and design techniques; remarkable capabilities in analysis and synthesis with very good autonomous judgment; designs and topics are presented with a rigorous and technically very appropriate approach.
30-30L: excellent knowledge and complete comprehension of topics and design techniques; excellent capabilities in analysis and synthesis with excellent autonomous judgment and originality; designs and topics are presented with a rigorous and technically excellent approach.

TEXTBOOKS

[1] “Digital Signal Processing Exercises and Applications”, Marina Ruggieri, Michele Luglio, Marco Pratesi. Aracne Editrice, ISBN: 88-7999-907-9.
[2] The River Publishers’ Series in Signal, Image & Speech Processing, “An Introduction to Digital Signal Processing: A Focus on Implementation”, Stanley Henry Mneney. River Publishers, ISBN: 978-87-92329-12-7.
[3] Slides (exercises are also included therein) published on the teaching website.

Mechanics of Materials and Structures (block A-E)

Mechanics of Materials and Structures (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 (6 cfu)
Code: 80300064
SSD: ICAR/08
(by Engineering Sciences)

FORMATIVE OBJECTIVES

LEARNING OUTCOMES: The goal of this course, composed of two Modules, is to provide the student with basic knowledge of the mechanics of linearly elastic structures and of the strength of materials. By completing this class successfully, the student will be able to compute simple structural elements and reasonably complex structures.

KNOWLEDGE AND UNDERSTANDING: At the end of this course, the student will be able to:
– compute constraint reactions and internal actions in rigid-body systems and beams subjected to point/distributed forces and couples
– compute centroid position and central principal second-order moments of area distributions
– understand the formal structure of the theory of linear elasticity for beams and 3D bodies
– analyze strain and stress states in 3D bodies
– compute the stress state in beams subjected to uniaxial bending, biaxial bending, eccentric axial force
– understand the behaviour of beams subjected to shear with bending and torsion
– understand how to compute displacements/rotations in isostatic beam systems, how to solve statically underdetermined systems, how to apply yield criteria, and how to design beams against buckling

APPLYING KNOWLEDGE AND UNDERSTANDING: The student will apply the knowledge and understanding skills developed during the course to the analysis of practical problems. This includes the analysis of linearly elastic structures and structural members in terms of strength and stiffness.

MAKING JUDGEMENTS: The student will have to demonstrate his awareness of the modeling assumptions useful to describe and calculate structural elements, as well as his critical judgement on the static response of elastic structures under loads, in terms of stresses, strains, and displacements.

COMMUNICATION SKILLS: The student will demonstrate, mostly during the oral test, his capacity of analyzing and computing the static response of linearly elastic structures, as well as his knowledge of the underlying theoretical models.

LEARNING SKILLS: The student will get familiar with the modeling of structures and structural elements in practical problems, mostly during the development of his skills for the written test. This mainly concerns beams and three-dimensional bodies.

PREREQUISITES: The student should have already attended the basic courses of calculus, geometry, and physics.
It is required that the student has good skills with regard to differential and integral calculus, linear algebra and matrix calculations.

SYLLABUS:

Together with the other Module of this course, the following topics are covered.

Review of basic notions of vector and tensor algebra and calculus.
Kinematics and statics of rigid-body systems.
Geometry of area distributions.
Strain and stress in 3D continuous bodies and beam-like bodies.
Virtual power and virtual work equation for beams and 3D bodies.
One-dimensional beam models: Bernoulli-Navier model, Timoshenko model, constitutive equations, governing differential equations.
Constitutive equation for linearly elastic and isotropic bodies, material moduli.
Hypothesis in linear elasticity, equilibrium problem for linearly elastic beams and 3D bodies.
Three-dimensional beam model: the Saint-Venant problem, uniaxial and biaxial bending, eccentric axial force, shear and bending, torsion.
Elastic energy of beams and 3D bodies, work-energy theorem, Betti’s reciprocal theorem, Castigliano’s theorem.
Yield criteria (maximum normal stress, maximum tangential stress, maximum elastic energy, maximum distortion energy).
Buckling instability, bifurcation diagrams, load and geometry imperfections, Euler buckling load, design against buckling.
Basic notions on the finite element method and structural analysis software.

Analogue Electronics (block B-opt)

Analogue Electronics (block B-opt)
1 YEAR II semester  6 CFU + 3 cfu extra
Rocco Giofre’ A.Y. 2021-22

A.Y. 2022-23

Paolo Colantonio A.Y. 2023-24
Code: 80300060
SSD: ING-INF/01
(by Engineering Sciences)

The students who include Analogue Electronics in their study plan are strongly advised to include it in its 9-CFU version, with the last 3 CFUs (out of 9) working as Extra Credits.


LEARNING OUTCOMES:
Learning the basic concept of analogue electronic systems and circuits and developing the competencies to design electronic circuits.
The educational objectives are pursued through lectures and exercises.

KNOWLEDGE AND UNDERSTANDING:
The student acquires the basic conceptual and analytical knowledge, both theoretical and applied, of the main basic electronic components. Subsequently, it acquires knowledge related to the integration of basic electronic components for the development of more complex electronic systems, such as amplifiers, oscillators, rectifiers, etc.

APPLYING KNOWLEDGE AND UNDERSTANDING:
The student will demonstrate to have acquired the methodologies for the analysis and synthesis (design) of simple electronic circuits.

MAKING JUDGEMENTS:
The student must be able to integrate the basic knowledge provided with those deriving from physics, mathematics, and electrical engineering courses, in order to correctly select the most appropriate analytical and circuit synthesis options.

COMMUNICATION SKILLS:
Students must be able to illustrate the basic themes of the course synthetically and analytically, linking together the different concepts that are integrated into more complex electronic systems.


Prerequisite: Knowledge of network analysis in general.

SYLLABUS:

Diode semiconductor devices and circuit applications: clipper, clamper, peak detector, etc. Bipolar Junction and Field Effect Transistors. Biasing techniques for Transistors. Amplifiers classification, analysis, and circuit design. Frequency response of single and cascaded amplifiers. Differential amplifiers and Cascode. Current mirrors. Feedback amplifiers and stability issues. Power amplifiers. Operational amplifiers and related applications. Oscillator circuits. Integrated circuits and voltage waveform generators.

Books for references
“Electronics: a systems approach”, Neil Storey, Prentice Hall
“Elettronica di Millman”, J. Millman, A. Grabel, P. Terreni, McGraw-Hill

HOW TO ATTEND LESSONS:

Although attendance is optional, given the complexity of the topics covered, it is strongly recommended to follow the lessons.

NANOTECHNOLOGY

NANOTECHNOLOGY
1 YEAR II semester  6 CFU
Antonio Agresti (3cfu)
Francesca De Rossi (3cfu)
A.Y. 2021-22
Antonio Agresti (3cfu)
Fabio Matteocci (3cfu)
A.Y. 2022-23
A.Y. 2023-24
Antonio Agresti A.Y. 2024-25
Code: 8039791
SSD: ING-INF/01

(to be updated for A.A. 24-25)

LEARNING OBJECTIVES AND EXPECTED LEARNING OUTCOMES:

LEARNING OUTCOMES:
The first part of the Nanotechnology course introduces thin film depositions using both physical and chemical vapour depositions. The main objective is the knowledge of the potential and limits of the different thin film depositions in the nanotechnology field. Particular attention is destinated to the deposition technique used in micro and nanoelectronics based on semiconductors using top-down and bottom-up approaches. The interaction of both approaches has been discussed with the student in order to share the importance of multidisciplinary knowledge (physics, chemistry and engineering) where the nanotechnology field is based. The final part of module 1 is destinated to the introduction of the case study of the course about the thin film fabrication of an emergent photovoltaic technology: the perovskite solar cells. In particular, the study of the optoelectronic properties of the materials and the fabrication of several device architectures is important to understand the important role of the manufacturing design in thin film photovoltaic technologies destinated at the industrial level.

KNOWLEDGE AND UNDERSTANDING:
Regarding the first module, at the end of the course, the student will have a clear overview of the main deposition technique studied and applied in nanotechnology for different application fields.
Regarding the second module, at the end of the course, the student will know the main characterization techniques for nanostructured materials and electronic and optoelectronic devices till nanometric size.

APPLYING KNOWLEDGE AND UNDERSTANDING:
The student will be able to recognize the applicability areas for the various characterization and realization techniques at nanometric scales. She/He will also be able to apply the knowledge and understanding developed during the course to study and understand recent literature.

MAKING JUDGEMENTS:
The transversal preparation provided by the course implies
1) the student’s capability to integrate knowledge and manage complexity
2) the student’s ability to deal with new and emerging areas in nanotechnology application to energy and nanoelectronics.

COMMUNICATION SKILLS:
The student will be able to clearly and unequivocally communicate the course content to specialized interlocutors. He will also be able to communicate the main physico-chemical characteristics of nanostructured materials and to indicate the most appropriate deposition/processing technique of these materials to technical interlocutors (example: other engineers, physicists, chemists) but not specialists in the field of electronics or devices. The student will also have a sufficient background to undertake a thesis/research work in modern nanotechnology laboratories.

LEARNING SKILLS:
The structure of the course contents, characterized by various topics apparently separated but connected by an interdisciplinary and modular vision, will contribute to developing a systemic learning capacity that will allow the student to approach in a self-directed or autonomous way to other frontier problems on nanotechnology application to energy and nanoelectronics. Furthermore, the student will be able to read and understand recent scientific literature.

 

SYLLABUS

 

First Module: 1 Prof. Antonio Agresti (3 cfu)

1) Quantum Mechanics and p-n junction

2 )Solar Cells: main electrical characterization techniques

3) Absorbance and Fluorescence Spectroscopy

4) Electron scanning microscopy (SEM)

5) Electron transmission microscopy (TEM)

6) Scanning tunneling microscopy (STM)

7) Atomic force microscopy (AFM)

8) Kelvin Probe Microscopy (KPFM)

9) Raman spectroscopy

10) Bi-Dimensional Materials

 

Second module – Prof. Fabio Matteocci (3cfu)

 

1) Introduction to nanotechnology and thin film properties;
2) Thin Film Deposition: the importance of vacuum and plasma;
3) Thermal Evaporation: Working mechanism, material properties, deposition parameters and applications;
4) DC and RF Sputtering: Working mechanism, material properties, deposition parameters and applications;
5) Pulsed Laser Deposition: Working mechanism, material properties, deposition parameters and applications;
6) Chemical Vapour Deposition: Working mechanism, material properties, deposition parameters and applications;
7) Atomic Layer Deposition: Working mechanism, material properties, deposition parameters and applications;
8) Solution Processing: Spin coating, Screen Printing, Blade Coating, Slot die coating;
9) Patterning Procedures: Photolithography and Laser Ablation;
10) Introduction to Perovskite Solar Cell: Working mechanism, material properties, deposition techniques, up-scaling process and applications;
11) Building Integration Photovoltaics;

VLSI CIRCUIT AND SYSTEM DESIGN

VLSI
1 YEAR II semester  9 CFU
Luca DI NUNZIO A.Y. 2021-22
Luca DI NUNZIO (5 cfu)

Vittorio MELINI (2 cfu)

Sergio SPANO’ (2 cfu)

since A.Y. 2022-23
Code:
SSD: ING-INF/01

PREREQUISITES:

It is strictly suggested to take the “Digital Electronics” exam before attending this course. You can contact Prof. Luca DI NUNZIO for any doubts regarding the topic.

LEARNING OUTCOMES:

The VLSI CIRCUIT AND SYSTEM DESIGN course aims to teach the basics of combinational and sequential circuits that represent the basic blocks of any modern digital system. In addition, the course will provide the basic concepts of the VHDL language

KNOWLEDGE AND UNDERSTANDING:

At the end of the course, the student will learn the basic concepts of combinational and sequential circuits that are the basis of any system and the basic concepts of the VHDL language useful for the design of digital systems

APPLYING KNOWLEDGE AND UNDERSTANDING:

Ability to analyze the characteristics of digital circuits with particular emphasis on timing and power consumption.

MAKING JUDGEMENTS:

The student will understand the acquired knowledge independently and critically to be able to connect and integrate the various aspects related to the design of digital systems

COMMUNICATION SKILLS:

The student must be able to communicate their knowledge acquired during the course in clear, correct, and technical language.

LEARNING SKILLS:

Ability to critically approach a digital circuit design problem, know how to manage it, and find implementation solutions using the VHDL language

SYLLABUS:

(L. DI NUNZIO)

Digital electronics basic concepts
Floating-point and fixed-point numeric representation formats
Combinatorial circuits: encoders, decoders, multiplexers
Sequential circuits: flip flops, latch registers, counters, memories
Introduction to VHDL: entity and architecture, levels of abstraction, HDL design flow, combinatorial and sequential processes, objects in VHDL test bench
Practical activities of circuit design in VHDL

(S. SPANO’)

Central unit
ALU
System registers
Address logic
System buses
Scheduler
Branching of instructions
Interrupts
Bus synchronization
RAM memories
ROM memories
Flash memories
CAM memories

 

Feedback Control Systems (block B)

Feedback Control Systems (block B)
1 YEAR II semester  6 CFU
Cristiano M. VERRELLI A.Y. 2021-22
A.Y. 2022-23
Code:
SSD: ING-INF/04

FORMATIVE OBJECTIVES

LEARNING OUTCOMES:

The theory of differential equations is successfully used to gain profound insight into the fundamental mathematical control design techniques for linear and nonlinear dynamical systems.

KNOWLEDGE AND UNDERSTANDING:

Students should be able to deeply understand (and be able to use) the theory of differential equations and of systems theory, along with related mathematical control techniques.

APPLYING KNOWLEDGE AND UNDERSTANDING:

Students should be able to design feedback controllers for linear (and even nonlinear) dynamical systems.

MAKING JUDGEMENTS:

Students should be able to identify the specific design scenario and to 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 are 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 as well as visits to labs) invite intensive participation and ideas exchange.

LEARNING SKILLS:

Being enough skilled in the specific field to undertake the following studies characterized by a high degree of autonomy.

SYLLABUS:

The matrix exponential; the variation of constants formula.

Computation of the matrix exponential via eigenvalues and eigenvectors and via residual matrices. Necessary and sufficient conditions for exponential stability: Routh-Hurwitz criterion. Invariant subspaces.

Impulse responses, step responses and steady state responses to sinusoidal inputs. Transient behaviours. Modal analysis: mode excitation by initial conditions and by impulsive inputs; modal observability from output measurements; modes which are both excitable and observable. Popov conditions for modal excitability and observability. Autoregressive moving average (ARMA) models and transfer functions.

Kalman reachability conditions, gramian reachability matrices and the computation of input signals to drive the system between two given states. Kalman observability conditions, gramian observability matrices and the computation of initial conditions given input and output signals. Equivalence between Kalman and Popov conditions.

Kalman decomposition for non-reachable and non-observable systems.

Eigenvalues assignment by state feedback for reachable systems. Design of asymptotic observers and Kalman filters for state estimation of observable systems. Design of dynamic compensators to stabilize any reachable and observable system. Design of regulators to reject disturbances generated by linear exosystems.

Bode plots. Static gain, system gain and high-frequency gain.

Zero-pole cancellation.

STATISTICS:

A.Y.  Mechatronics students Other courses Students Mechatronics average Other courses average
2019/2020 10 62 24 23
2020/2021 19 25 23 24
2021/2022 13 44 21 22