Technology
Subject: INDUSTRIAL AUTOMATION (A.A. 2023/2024)
degree course in COMPUTER ENGINEERING
| Course year | 2 |
|---|---|
| CFU | 9 |
| Teaching units |
Unit Automazione industriale
Computer Engineering (lesson)
|
| Moodle portal | |
| Exam type | written |
| Evaluation | final vote |
| Teaching language | Italiano |
Teachers
Overview
The course provides methodological foundations to apply automatic control theory to industrial use cases. In particular, specific focus will be given to modeling, analysis and control of dynamic systems, which represent the greatest majority of abstract and physical systems (e.g., actuated subparts of an automatic machine).
Admission requirements
Knowledge related to principles of calculus, linear algebra, geometry and physics.
Course contents
1. Introduction to control systems, mathematical models of systems
2. Transfer function, Laplace transform, block diagram models
3. Stability
4. Frequency response methods, Fourier transform, Bode diagrams
5. Feedback control system characteristics
6. Root locus method
7. PID controllers
8. Software for system modeling and control design: Matlab and Simulink
Teaching methods
Frontal lessons and exercise classes on the use of MATLAB.
Assessment methods
Written and oral exam. The written exam is organized in two parts. The first (15/30) consists in multiple choice questions; the second one (15/30) consists in three exercises. The oral exam will focus on commenting the written exam and can increase and decrease the score achieved with the written exam.
Learning outcomes
Knowledge and understanding: students will learn methods of control theory for industrial automation applications.
Applying knowledge and understanding: students will learn how to apply the methodologies presented during classes to complex problems of industrial automation in real life.
Learning skills: students will be able to explore by themselves further topics in contro theory applied to industrial automation based on the methods developed during the course.
Communication skills: students will learn to defend their arguments about the topics of the course in a clear, rigorous and concise way.
Making judgements: students will possess the ability to choose the appropriate method of analysis and solution among the various approaches presented during the course.
Readings
Fondamenti di automatica
Roberto Vitelli, Massimiliano Petternella
Edizioni Efesto, 2016
Fondamenti di controlli automatici, IV edizione
Paolo Bolzern, Riccardo Scattolini, Nicola Schiavoni Mc Graw Hill, 2015
Tutte le slide proiettate a lezione saranno messe a disposizione dagli studenti.