Caricamento in corso...

04LSLLN, 04LSLLI

A.A. 2024/25

Course Language

Inglese

Degree programme(s)

1st degree and Bachelor-level of the Bologna process in Ingegneria Dell'Autoveicolo - Torino

1st degree and Bachelor-level of the Bologna process in Ingegneria Dell'Autoveicolo (Automotive Engineering) - Torino

Course structure

Teaching | Hours |
---|---|

Lezioni | 65 |

Esercitazioni in laboratorio | 15 |

Tutoraggio | 15 |

Lecturers

Teacher | Status | SSD | h.Les | h.Ex | h.Lab | h.Tut | Years teaching |
---|---|---|---|---|---|---|---|

Proskurnikov Anton | Professore Associato | IINF-04/A | 50 | 0 | 0 | 0 | 5 |

Co-lectures

Espandi

Riduci

Riduci

Teacher | Status | SSD | h.Les | h.Ex | h.Lab | h.Tut |
---|---|---|---|---|---|---|

Boggio Mattia | Assegnista di Ricerca | 0 | 0 | 0 | 15 | |

Carabelli Stefano | Ricercatore | IINF-04/A | 10 | 0 | 0 | 0 |

Pagone Michele | Ricercatore L240/10 | IINF-04/A | 5 | 0 | 15 | 0 |

Context

SSD | CFU | Activities | Area context |
---|---|---|---|

ING-INF/04 | 8 | B - Caratterizzanti | Ingegneria gestionale |

2024/25

Automatic Control is an important field of engineering allowing to design systems that work without (or with minimal) human intervention.
Modern vehicles contain numerous control systems, from invisible braking and engine controllers to high-level intelligent driving assisting systems. Automatic control will be ubiquitous in autonomous driving, which is a near future of the automotive industry.
This course provides a brief introduction into basic principles of automatic control design, focusing on linear control design methods in continuous and sampled time. At the end of the course, optional project will be proposed devoted to implementation of digital controllers and filters on programmable logic controllers.

Automatic Control is a cornerstone of modern engineering, opening doors to designing and optimizing systems that operate efficiently, safely, and autonomously, from miniaturized smart devices to industrial machinery and automated vehicles. As our world becomes increasingly automated, automatic control will play a key role in the future of intelligent systems and smart infrastructures. Modern vehicles feature numerous control systems ranging from invisible braking and engine controllers to high-level intelligent driving assistance systems.
The course introduces fundamental principles of automatic control analysis, design, and simulation in continuous and discrete time domains, equipping students with the skills necessary to contribute to the advancement of intelligent systems. Focused on the analysis and design of linear systems and determining their stability and robust performance, this course serves as a foundational pillar for more advanced disciplines within the fields of automation, mechatronics, and robotics.
Theoretical lectures in this course are complemented by hands-on laboratory sessions, where students learn to utilize Matlab and Simulink for efficient prototyping of control systems. At the end of the course, students will have the opportunity to engage in a project focused on the implementation of digital controllers and/or filters on programmable logic controllers.

- Basics of Matlab and Simulink;
- Knowledge of the concept of dynamical system together with its mathematical representations such as state equations and transfer functions.
- Skill in deriving mathematical models of dynamical systems.
- Skill in computing the solution of the system state equations.
- Skill in evaluating the behavior of a dynamical system through numeric simulation.
- Knowledge of structural properties (stability, reachability, observability) of dynamical systems.
- Knowledge of the concept of feedback control of dynamical systems.
- Skill in designing feedback controllers via (estimated) state feedback.
- Knowledge of the main performance requirements of feedback systems.
- Knowledge of the main feedback system analysis techniques based on harmonic tools.
- Skill in analyzing the stability and the performances of feedback control systems.
- Knowledge about simplest industrial controllers (PID).
- Knowledge about sampled data control systems and realization through digital filters.
- Skill in designing sampled data control systems.
- Skill in evaluating the behavior and performances of controlled systems through numerical simulation.

- Basics of Matlab (operations on matrices, Control Systems Toolbox) and Simulink;
- Knowledge of the concept of dynamical system together with its mathematical representations such as state equations and transfer functions; deriving mathematical models of dynamical systems.
- Skill in computing the solution of the system state equations - analytically (for linear systems) and numerically.
- Skill in evaluating the behavior of a dynamical system through numeric simulation.
- Knowledge of structural properties (stability, reachability, observability) of dynamical systems.
- Knowledge about simplest industrial controllers (PID). Self-tuning of PID controllers in Matlab.
- Knowledge of the concept of feedback control of dynamical systems.
- Skill in designing feedback controllers via (estimated) state feedback.
- Knowledge of the main performance requirements of feedback systems (raise time, overshoot).
- Knowledge of the main feedback system analysis techniques based on harmonic tools.
- Skill in analyzing the stability and the performances of feedback control systems.
- Knowledge about sampled data control systems and realization through digital filters.
- Skill in designing sampled data control systems.

Linear algebra: operations with vectors and matrices, inverse matrix, determinant, eigenvalues and eigenvectors;
Complex numbers;
Differential and integral calculus;
Basic notions of mechanics and electric circuits is desirable, but not a strict prerequisite.

MUST:
-Linear algebra: operations with vectors and matrices, inverse matrix, determinant, eigenvalues and eigenvectors;
-Complex numbers;
-Differential and integral calculus;
DESIRABLE yet not a strict prerequisite:
-Basic notions of mechanics and electric circuits;
-Basics of differential equations.

- Introduction to dynamical systems.
- Modeling and state space description.
- Solution of state equations.
- Modal analysis
- Stability of linear systems.
- Block algebra.
- Reachability (controllability) and observability.
- Introduction to feedback control.
- Control through feedback of the estimated states
- Bode, polar and Nyquist diagrams.
- Nyquist stability criterion.
- Stability margins.
- Feedback systems response due to polynomial inputs; steady state tracking errors, disturbance attenuation and rejection.
- Time and frequency response of first and second order systems.
- Feedback systems performance: transient and steady state.
- Industrial controllers (PID).
- Discrete-time systems. Analysis and design of sampled data control systems.

- Introduction to dynamical systems.
- Modeling and state space description.
- Solution of state equations.
- Modal analysis
- Stability of linear systems.
- Block algebra.
- Reachability (controllability) and observability.
- Introduction to feedback control.
- Industrial controllers (PID).
- Bode, polar and Nyquist diagrams.
- Nyquist stability criterion.
- Stability margins.
- Feedback systems response due to polynomial inputs; steady state tracking errors, disturbance attenuation and rejection.
- Pole placement.
- Control through feedback of the estimated states
- Time and frequency response of first and second order systems.
- Feedback systems performance: transient and steady state.
- Discrete-time systems. Analysis and design of sampled data control systems.

The course consists of lectures, laboratory practicums and seminar-style lectures at the end of the course.
Lectures cover
-- the theoretical topics of the course (the concepts of dynamical systems, state-space models, linear stability analysis and design of stabilizing controllers, frequency-domain techniques for linear systems,
basics of identification, PID controllers);
-- some numerical examples and solved problems;
-- seminar-style lectures on automotive applications.
In the case of mixed online-offline teaching, the theoretical material will be primarily taught online. The offline lectures will be devoted to consideration of examples and problems (the materials will also be available online).
The goal of LAB sessions is to enable students to use MATLAB and Simulink software for numerical simulation, rigorous analysis and design of control systems. The solutions to all problems will be available on the course webpage. The topics of the exercises are:
-- derivation and linearization of mathematical equations (state-space models), linearization;
-- implementation of models in Simulink, analysis of input-output response;
-- analytic and numerical stability analysis;
-- transfer functions, Laplace transforms, response to harmonic signals;
-- minimal state-space realizations, observability, controllability;
-- Nyquist criterion, frequency-domain analysis (stability margins);
-- Design of controllers satisfying certain specifications (rise time, overshoots);
-- LQR controller design;
-- Observer design.
The students are recommended to download Matlab with Campus licence to their laptops.
The seminar-style lectures at the course are devoted to
implementation of digital controllers and filters on programmable logic controllers. An optional project will
be proposed for the students (adds extra 2 points to the final exam).

The course consists of lectures, laboratory practicums and seminar-style lectures at the end of the course.
Lectures cover
-- the theoretical topics of the course (the concepts of dynamical systems, state-space models, linear stability analysis and design of stabilizing controllers, frequency-domain techniques for linear systems,
basics of identification, PID controllers);
-- some numerical examples and solved problems;
-- seminar-style lectures are devoted to practical implementation of digital controllers and filters.
The goal of LAB sessions is to enable students to use MATLAB and Simulink software for numerical simulation, rigorous analysis and design of control systems. The solutions to all problems will be available on the course webpage. The topics of the exercises are:
-- derivation and linearization of mathematical equations (state-space models), linearization;
-- implementation of models in Simulink, analysis of input-output response;
-- analytic and numerical stability analysis;
-- transfer functions, Laplace transforms, response to harmonic signals;
-- minimal state-space realizations, observability, controllability;
-- Nyquist criterion, frequency-domain analysis (stability margins);
-- PID controllers: self-tuning with Simulink
-- Design of controllers satisfying certain specifications (rise time, overshoots);
-- LQR controller design;
-- Observer design.
The students are recommended to download Matlab with Campus licence to their laptops.
The seminar-style lectures at the course are devoted to
implementation of digital controllers and filters on programmable logic controllers. An optional project will
be proposed for the students (adds extra 2 points to the final exam).

G.F. Franklin, J.D. Powell, A. Emami-Naeini, Feedback Control of Dynamic Systems, Prentice Hall, 2009.
N. Nise, Control systems engineering, Wiley, 4th ed., 2004.
K. Ogata, Modern Control engineering, Prentice Hall, 4th ed., 2004.
G. Calafiore, Elementi di Automatica, CLUT, 2007.
Lecture slides and laboratory practice handouts will be available.

G.F. Franklin, J.D. Powell, A. Emami-Naeini, Feedback Control of Dynamic Systems, Prentice Hall, 2009.
N. Nise, Control systems engineering, Wiley, 4th ed., 2004.
K. Ogata, Modern Control engineering, Prentice Hall, 4th ed., 2004.
G. Calafiore, Elementi di Automatica, CLUT, 2007.
Lecture slides and laboratory practice handouts will be available.

Esercizi; Video lezioni tratte da anni precedenti;

Exercises; Video lectures (previous years);

...
Duration of the exam is 3 hours.
Allowed material: a cheat sheet with main equations, Laplace transforms and key definitions (will be disseminated before the exam).
It can printed and brought to the exam, also will be available for downloading during the exam.
Matlab programs, printed lecture notes and exercise solutions are not allowed.
The students should bring their laptops to the exam. Other electronic devices are not allowed.
The students can use online Matlab through the exam platform (Matlab cannot be started from their own computers).
Simulink is also available in the online version, but is quite slow and not recommended during the exam.
The exam is organized as a computer-based tests with 8 open or multiple-choice questions, each gives up to 4 points.
Examples will be provided during the lectures and laboratory practicums, typical topics are
-- computation of equilibria for nonlinear systems;
-- linearization and stability analysis of equilibria;
-- solving linear equations via Laplace transforms;
-- computation of transfer functions;
-- modal analysis;
-- pole-placement design of controllers and observers;
-- discretization;
-- identification of discrete-time systems.
Some general theoretical questions can be given, e.g., what is a controllable system or what is the Nyquist curve?
A student can also receive 2 extra points (added to the exam mark) for the optional project, hence, the maximal mark is 34.
Marks 31-34 are registered as "30 e lode." The minimal mark to pass the exam is 18.

Gli studenti e le studentesse con disabilità o con Disturbi Specifici di Apprendimento (DSA), oltre alla segnalazione tramite procedura informatizzata, sono invitati a comunicare anche direttamente al/la docente titolare dell'insegnamento, con un preavviso non inferiore ad una settimana dall'avvio della sessione d'esame, gli strumenti compensativi concordati con l'Unità Special Needs, al fine di permettere al/la docente la declinazione più idonea in riferimento alla specifica tipologia di esame.

Duration of the exam is 2 hours.
The exam is held in LAIB, personal laptops and other electronic devices are not allowed. The students are supposed to use Matlab. Simulink can also be used, but is not necessary to solve the exam.
For the exam, students are permitted to use a distributed cheat sheet containing main equations, Laplace transforms, and key definitions, which will be provided before the exam. This cheat sheet can be printed and brought to the exam or downloaded in PDF format during the exam itself. However, the use of printed Matlab scripts, printed lecture notes, books and exercise solutions is strictly prohibited.
The exam is organized as a computer-based tests with 8 open or multiple-choice questions, each gives up to 4 points.
Examples will be provided during the lectures and laboratory practicums, typical topics are
-- computation of equilibria for nonlinear systems;
-- linearization and stability analysis of equilibria;
-- solving linear equations via Laplace transforms;
-- computation of transfer functions;
-- modal analysis;
-- pole-placement design of controllers and observers;
-- discretization;
-- identification of discrete-time systems.
Some general theoretical questions can be given, e.g., what is a controllable system or what is the Nyquist curve? In open questions, partial grading can be applied if the answer is not fully correct.
In addition to the exam, students have the opportunity to earn 2 extra points added to their exam mark by completing the optional project. This means the maximum achievable mark for the course is 34, with scores from 31 to 34 recognized as "30 e lode" (honors). The passing grade for the exam is set at 18, taking into account the additional points awarded for project completion.

In addition to the message sent by the online system, students with disabilities or Specific Learning Disorders (SLD) are invited to directly inform the professor in charge of the course about the special arrangements for the exam that have been agreed with the Special Needs Unit. The professor has to be informed at least one week before the beginning of the examination session in order to provide students with the most suitable arrangements for each specific type of exam.