CONTROL OF MECHANICAL SYSTEMS

CONTROL OF MECHANICAL SYSTEMS
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

Digital Electronics (block B)

Digital Electronics (block B)
1 YEAR I semester  6 CFU
Marco Re
A.Y. 2021-24
A.Y. 2024-25
Didatticaweb

Code: 80300061
SSD: ING-INF/01
(by Engineering Sciences)

PREREQUISITES

CIRCUIT THEORY, PHYSICS, MATHEMATICAL ANALYSIS

 

FORMATIVE OBJECTIVES

EDUCATIONAL OBJECTIVES:
The objective of this course is to provide students with the knowledge for the analysis and synthesis of the electronic systems presented during the course and the means for their resolution. The course has both theoretical and practical character, it is therefore important that the student is able to carry out concrete problems, such as those presented during the exercises.

KNOWLEDGE AND UNDERSTANDING:
Students will learn the analysis techniques used in the analysis of electronic systems in different operating regimes, and acquire the necessary knowledge to carry out circuit simulations through different software.

ABILITY TO APPLY KNOWLEDGE AND UNDERSTANDING: students will be able to evaluate which of the existing methods has to be used to analyze and synthesize the system under consideration with the aim of simplifying the resolution of the problem. Finally, they will be able to apply the software presented to perform the analysis of electronic systems in different operating regimes.

COMMUNICATION SKILLS:
The verification methods implemented will lead the students to 1) know how to quickly choose the methodology to be adopted for solving the proposed problems, and 2) be able to illustrate in a synthetic and analytical way the topics covered by the course using equations and schemes .

LEARNING SKILLS and AUTONOMY OF JUDGMENT:
With the didactic material presented during the course (both written and video) and the list of bibliographic references proposed by the teachers, students have the opportunity to autonomously expand their knowledge on the subject by integrating topics not directly addressed in the course.

SYLLABUS

  Specification of Combinational Systems: definitions and specification level, data representation and coding, binary specification of combinational systems.

     Combinational Integrated Circuits – Characteristics and Capabilities: representation of binary variables, structure and operation of CMOS gates, propagation delays, voltage variations and noise margins, power dissipation and delay-power product, Buses and three-state drivers, circuit characterization of a CMOS-family.

     Description and Analysis of Gate Networks: definition, description and characteristics, sets of gates.

     Design of Combinational Systems – two-level gate networks: minimal two-level networks, Karnaugh maps, minimization of sum of products and product of sums, design of multiple-output two-level gate networks, two-level NAND-NAND and NOR-NOR networks, limitations of two-level networks, programmable modules: PLA and PLA.

     Design of Combinational Systems – Multilevel Gates Networks:

Transformations, alternative implementations, networks with XOR and XNOR gates, and networks with two-input multiplexers.

     Specification of Sequential Systems: synchronous sequential systems, representation of the state transition and output functions, time behavior and finite state machines, finite memory sequential systems, controllers, equivalent sequential systems and minimization of the number of states, binary specification of sequential systems, specification of different types of sequential systems.

     Sequential Networks: canonical form, high-level and binary implementations, gated latch and D flip-flop, timing characteristics, analysis of canonical sequential networks, design of canonical sequential networks, other flip-flop modules: SR, JK, T, analysis of networks with flip-flops, design using special state assignments.

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

ROBOT MECHANICS

ROBOT MECHANICS
1 YEAR (Blocks B|C)
2 YEAR (Blocks A|D|E)
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
A.Y. 2024-25
Code: 8039785
SSD: ING-IND/13

LEARNING OUTCOMES: This course will provide students with the knowledge and tools needed to model and analyse robotic manipulators in terms of mechanical performance. Students will learn how to design, evaluate, and control industrial and service robots.

KNOWLEDGE AND UNDERSTANDING: The student will learn to analyse robotic systems by modelling their kinematics and dynamics and thus finding their key operational parameters. Furthermore, the student will learn how to design a manipulator from its operational requirements, such as workspace, velocity, and payload.

APPLYING KNOWLEDGE AND UNDERSTANDING: The student will apply this knowledge to design, model, and evaluate robots with examples of use cases. Once identified the joints and bodies that compose a robot, the student will be able to numerically characterize its operation and mobility. Furthermore, the student will be able to critically select a robot type for a given manipulation task.

MAKING JUDGEMENTS: The student will demonstrate their understanding of robot operation by developing and presenting a practical use case, in which they will examine autonomously and critically the challenges behind robot design and application.

COMMUNICATION SKILLS: During the course, students discuss key topics, working on a written project on manipulation analysis of their own choice. Project results are then presented at the end of the course.

LEARNING SKILLS: During the course, students are involved in the lecture for a continuous stimulus to verify their understanding of robot mechanics. The knowledge acquired during the course is also verified in the final project on manipulation analysis.

REQUIREMENTS: The student should have already attended the fundamental courses on calculus, geometry, and physics. The understanding of rigid body mechanics and basic programming skills (MATLAB) are required, as well as knowledge of mechanism design and analysis.

PROGRAMME:

  1. Architecture and classification of industrial and service robots
    1. Definitions: kinematic chains, joints, mobility
    2. Manipulation analysis
    3. Types of manipulators
  2. Kinematics
    1. Reference frames
    2. Denavit-Hartenberg notation
    3. Forward kinematics
    4. Inverse kinematics
    5. Jacobian and singularities
    6. Workspace
    7. Path planning
  3. Statics and dynamics
    1. Equilibrium
    2. Equation of motion
    3. Grasp mechanics
  4. Other designs
    1. Actuation technologies
    2. Parallel robots
    3. Compliant robots
    4. Soft and continuum robots

EXAM:

The exam is divided into a written and oral test. The written test consists of three exercises regarding practical use-cases of industrial and service robots. In alternative, a project report developed during the course can be evaluated. In the oral test, the student will discuss with a critical perspective robot functioning. In alternative, the developed project on manipulation analysis can be presented and discussed.

INTEGRATED SENSORS

INTEGRATED SENSORS
1 YEAR (Block A|C|D|E)
2 YEAR (Block B)
1 semester 9 CFU
Corrado Di Natale A.Y. 2019-20 (new name, ex Electronic Devices and Sensors)
Alexandro Catini (6cfu)
Corrado  Di Natale (3cfu)
A.Y. 2022-23
A.Y. 2023-24
Alexandro Catini (8cfu)
Corrado  Di Natale (1cfu)
A.Y. 2024-25
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 a 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 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

Innovative Materials with Laboratory (blocks B-C-C1-E)

Innovative Materials with Laboratory (blocks B-C-C1-E)
1 YEAR 1 semester 6 CFU
TATA MARIA ELISA (1cfu)
COSTANZA GIROLAMO (1cfu)
VARONE ALESSANDRA (4cfu)
A.Y. 2021-22
A.Y. 2022-23
A.Y. 2023-24 (MS TEAMS)
A.Y. 2024-25 (C1-E)
Code: 8039786
SSD: ING-IND/21

LEARNING OUTCOMES:
The aim of the course is to provide an overview of novel materials recently developed and investigated for applications in mechanics, electronics, and mechatronics. Different types of materials are considered and described with particular attention on the preparation route, specific characteristics, and applications. Some of them are of basic importance for new technologies gaining increasing attention in industrial practice. The knowledge of innovative materials is strictly connected to the possibility and capability of designing new products.

KNOWLEDGE AND UNDERSTANDING:
Deep knowledge of the metallic structure and their mechanical behavior; in particular knowledge of innovative materials for mechatronics applications; selection of conventional material or not as a function of application, structure and properties.

APPLYING KNOWLEDGE AND UNDERSTANDING:
Ability to define materials properties and the most suitable production technologies for the components realization; Ability to perform tests in laboratory; Ability to define appropriate treatments in order to obtain the suitable mechanical properties as a function of service conditions. Ability to select innovative materials; ability to evaluate innovative materials properties.

MAKING JUDGEMENTS:
Ability to investigate, select and choose metallic materials as a function of the application.

COMMUNICATION SKILLS:
Clear and correct expression, in English language, skills on the topics covered in the course.

LEARNING SKILLS:

Ability to face a new problem, know how to manage it and find functional and correct solutions. learning ability will be evaluated by exam tests and laboratory activities.

SYLLABUS:

Metallurgy Fundamentals: crystal structure, defects, plastic deformation. Mechanical tests.

Amorphous alloys: production and applications of metallic glasses as mechatronic devices. Alloys with mixed structure (nanocrystalline and amorphous).

Ultrafine grained (UFG) materials: microstructural features and production routes.

Nanoporous and mesoporous materials: structural characterization and properties. Their applications for energy and gas storage.

Powder metallurgy, Additive Manufacturing Technologies.

Advanced composite materials: properties, applications and production routes.

Porous materials: metal foams, Open and closed porosity (micro and macro). Classification according to size and shape of the pores. Properties (sound, energy and vibration absorption, crash

behavior) and production methods. Functional and structural

applications: lightweight construction, automotive. Metal sandwich structures.

Functional and Smart Materials. Property change as a response of external stimulus: shape memory alloy (one-way and two-way shape memory), thermochromic, photomechanical. Energy conversion: piezoelectric, thermoelectric. Phase change materials. 

Applications: mechatronic, energy. Functionally graded materials.