01QYEQW

A.A. 2019/20

Course Language

Inglese

Course degree

Master of science-level of the Bologna process in Mechatronic Engineering (Ingegneria Meccatronica) - Torino

Course structure

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

Lezioni | 30 |

Esercitazioni in laboratorio | 30 |

Teachers

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

Regruto Tomalino Diego | Professore Associato | ING-INF/04 | 30 | 0 | 30 | 0 | 7 |

Teaching assistant

Context

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

ING-INF/04 | 6 | B - Caratterizzanti | Ingegneria dell'automazione |

2018/19

The aim of this course is to develop students’ ability to apply advanced methods for robust system identification and data-based control of uncertain systems. Proposed system identification and data-based control techiques are applied to a set of carefully selected laboratory processes. Theoretical results in robust system identification and control are introduced/reviewed in the first part of the course. In the second part, students will be offered the opportunity to face a number of problems arising while applying robust system identification and data-based control theory and algorithms to experimental setups and data.

The aim of this course is to develop students’ ability to apply advanced methods for robust system identification and data-based control of uncertain systems. Proposed system identification and data-based control techiques are applied to a set of carefully selected laboratory processes. Theoretical results in robust system identification and control are introduced/reviewed in the first part of the course. In the second part, students will be offered the opportunity to face a number of problems arising while applying robust system identification and data-based control theory and algorithms to experimental setups and data.

The aim of the course is to make available to the students the knowledge of the following topics:
- Methods and algorithms for building mathematical models of real-world dynamical systems from sets of noise-corrupted experimental data focusing in particular on system identification techniques devoted to the quantification of the model uncertainty (set-membership identification).
- Methods and algorithms for the data-based feedback control system design.
- Software and Hardware tools and methods for rapid prototyping of control systems.
Students are expected to develop the following skills:
- Ability to derive the mathematical model of a dynamical system from sets of noise-corrupted data collected by performing suitable experiments on a real plant, though the application of modeling and identification tools/algorithms.
- Ability to design a feedback control system able to guarantee fulfillment of the prescribed performance requirements on the real plant, through the application of data-based control methods and algorithms.
- Ability to practically implement and test on a real plant the designed robust control system by exploiting suitable software/hardware tools for rapid prototyping.

The aim of the course is to make available to the students the knowledge of the following topics:
- Methods and algorithms for building mathematical models of real-world dynamical systems from sets of noise-corrupted experimental data focusing in particular on system identification techniques devoted to the quantification of the model uncertainty (set-membership identification).
- Methods and algorithms for the data-based feedback control system design.
- Software and Hardware tools and methods for rapid prototyping of control systems.
Students are expected to develop the following skills:
- Ability to derive the mathematical model of a dynamical system from sets of noise-corrupted data collected by performing suitable experiments on a real plant, though the application of modeling and identification tools/algorithms.
- Ability to design a feedback control system able to guarantee fulfillment of the prescribed performance requirements on the real plant, through the application of data-based control methods and algorithms.
- Ability to practically implement and test on a real plant the designed robust control system by exploiting suitable software/hardware tools for rapid prototyping.

Students are assumed to own adequate knowledge of the following preliminary subjects:
- Basic facts on mathematical analysis, linear algebra, differential/difference equations, Laplace/Fourier/Zeta transform
- Basic facts on systems and control theory
The course will also make explicit reference to the content of the lessons of the course “Modern Design of Control Systems” that will be taught to the students in parallel to the course of Laboratory of robust identification and control.

Students are assumed to own adequate knowledge of the following preliminary subjects:
- Basic facts on mathematical analysis, linear algebra, differential/difference equations, Laplace/Fourier/Zeta transform
- Basic facts on systems and control theory
The course will also make explicit reference to the content of the lessons of the course “Modern Design of Control Systems” that will be taught to the students in parallel to the course of Laboratory of robust identification and control.

The course will focus on the following main subjects:
- Fundamental principles of set-membership identification theory [about 20 hours]
- Fundamental principles of data-based controller design [about 20 hours]
- Fundamental notions about hardware/software tools for rapid prototyping of control systems (MATLAB real-time toolbox, LAbview, National Instrument PXI) [about 5 hours]
- Application of set-membership identification and robust control methods and algorithms to real-world case studies and/or laboratory processes [about 15 hours].

The course will focus on the following main subjects:
- Fundamental principles of set-membership identification theory [about 20 hours]
- Fundamental principles of data-based controller design [about 20 hours]
- Fundamental notions about hardware/software tools for rapid prototyping of control systems (MATLAB real-time toolbox, LAbview, National Instrument PXI) [about 5 hours]
- Application of set-membership identification and robust control methods and algorithms to real-world case studies and/or laboratory processes [about 15 hours].

Theoretical and methodological lessons will be delivered, on a weekly scheduled basis, by face-to-face instruction in the classroom. Computer laboratory/experimental activities are scheduled in order to develop the student’s skill through proper training. Each student is supposed to practice individually with the aid of laboratory work stations. The primary purpose of the laboratory exercises is to apply the methodologies presented in class, through the use of MATLAB, Simulink, Control System Toolbox and rapid prototyping software/hardware platforms. Some exam simulations are presented in the last two weeks of the course.

Theoretical and methodological lessons will be delivered, on a weekly scheduled basis, by face-to-face instruction in the classroom. Computer laboratory/experimental activities are scheduled in order to develop the student’s skill through proper training. Each student is supposed to practice individually with the aid of laboratory work stations. The primary purpose of the laboratory exercises is to apply the methodologies presented in class, through the use of MATLAB, Simulink, Control System Toolbox and rapid prototyping software/hardware platforms. Some exam simulations are presented in the last two weeks of the course.

The subject of the course is almost entirely based on the research activity of the teacher and collaborators. Therefore, reading materials is made by:
- Selected chapters from the book "System Identification: Theory for the User (2nd Edition)" (author: Lennart Ljung; publisher: Prentice Hall, year: 1999)"
- Lecture slides and notes provided by the teacher
- Scientific publications by the teacher and co-workers
- Laboratory practice handouts

The subject of the course is almost entirely based on the research activity of the teacher and collaborators. Therefore, reading materials is made by:
- Selected chapters from the book "System Identification: Theory for the User (2nd Edition)" (author: Lennart Ljung; publisher: Prentice Hall, year: 1999)"
- Lecture slides and notes provided by the teacher
- Scientific publications by the teacher and co-workers
- Laboratory practice handouts

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.

The assessment will be performed through a written exam that will take place directly in the lab in order to check students’ ability to apply robust identification and data-based control techniques.
Written examination in computer laboratory. The aim is to check the ability of the students to perform system modeling, identification and feedback control design based on a set of input-output data collected on the plant. A detailed written report describing the proposed solution is required.
More precisely, the students is required to perform:
(i) analysis of the provided input-output data (4 points)
(ii) estimation of a plant model by means of system identfication techniques (12 points)
(ii) design a data-based controller able to satify a set of performance specifications (12 points)
(iii) write a summary report where (i) and (ii) are suitably documented (8 points)
The exam will last 3 hours. During the exam, the students are only allowed to use MATLAB software and related user manuals.

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.

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