Introduction to systems theory


This course is aimed at anyone who wants to learn the basics of systems theory and who has a university background in mathematical analysis (including Laplace transform), linear algebra, and physics.

State models with one input and one output will be covered, highlighting their importance and main properties; it will also be shown how to construct such models from the equations of physics.

The topics covered in the course are:

  • Definitions of state models, linear systems, construction of a state model, choice of state variables, equilibrium points and linearization, feedback linearization.
  • Analysis of linear systems: evolution of state and output of a linear system, “superposition of effects” principle, free and forced evolution of state and output, transfer function and impulse response.
  • Stability: stability in linear systems, stability conditions for equilibrium points of non-linear systems, BIBO stability. Examples: compartmental models, predator-prey model (Lotka-Volterra), electric motor model


Frequenza e Attestati

Frequenza
GRATUITO!
Attestato di Partecipazione
GRATUITO!

Categoria

Scienze

Ore di Formazione

30

Livello

Base

Modalità Corso

Autoapprendimento

Lingua

Italiano

Durata

5 Settimane

Tipologia

Online

Stato del Corso

Auto apprendimento

Avvio Iscrizioni

9 Giu 2024

Apertura Corso

24 Giu 2024

Chiusura Corso

Non impostato
Upon completion of this course, students will be able to: 

  • Understand the field of systems theory and its areas of application. 
  • Understand and apply state models. Build simple state models from physics equations. 
  • Understand the concept of an equilibrium point in a state model. 
  • Understand the concepts of simple and asymptotic stability of an equilibrium point. 
  • Linearize a state model around an equilibrium point. 
  • Describe the evolution of state and output of a linear system. 
  • Understand the concept of transfer function and its relationship with the state model. 
  • Understand the concept of feedback linearization. 
  • Understand the concepts of simple and asymptotic stability of a linear system. 
  • Understand the concept of BIBO stability of a linear system. 
  • Understand the relationship between the stability of an equilibrium point and the stability of the linearized system. 
  • Apply the learned concepts to simple physical systems.

In order to fully understand the material presented in this course, it is necessary to be familiar with the following concepts. 

  • Mathematical analysis: scalar and vector-valued functions of one or more variables. Continuity, derivability, development in Taylor series. Integrals. Complex numbers and their use. Complex exponentials. Polynomials and their representations. Differential equations. 
  • Linear algebra: linear functions, matrices and vectors, eigenvectors, eigenvalues and their multiplicities. Diagonalization. 
  • Physics: kinematics and dynamics. Electro-magnetic field. Resistors, capacitors and inductances. Kirchhoff's laws. Signals and systems: Laplace transform; inverse Laplace transform of rational functions.

All the material covered in this course can be found in the book: 

  • Augusto Ferrante, "Appunti di Automatica per Ingegneria Biomedica con esercizi e temi d'esame risolti", Edizioni Progetto, Padova, 2023. (In Italian) 

More advanced material for further study can be found in the books: 

  • Ettore Fornasini, "Appunti di teoria dei sistemi", Libreria Progetto, ISBN: 978-8896477328, 2011. (In Italian) 
  • Thomas Kailath, “Linear systems”, Englewood Cliffs, NJ: Prentice-Hall, 1980. 
  • Joao P. Hespanha, “Linear systems theory”, Princeton university press, 2018.

The course will be articulated in a series of short videos, accompanied by supplementary material for deeper understanding and evaluation/exercise sections. These resources will help students to accurately assess their learning progress and to improve their understanding of the course material.The teaching approach is based on: direct use of multimedia content, active teaching, problem solving.