LEARNING OUTCOMES

This course is intended to provide an introduction to the analysis and design of cyberphysical systems. This includes synchronous and asynchronous processes, safety and liveness requirements, and dynamic and timed systems. The course is also intended to provide an introduction to the Python language, with emphasis on application to data science and machine learning.

AIMS AND LEARNING OUTCOMES

By taking the course, the student should come to possess a broad knowledge about the various types of cyberphysical sytems in the state of the art, such as: synchronous, asynchronous, continuous-time dynamic, timed, and hybrid systems. For each type of system, modeling, simulation, and verification (model checking) topics are covered. The student will have the opportunity to learn the theoretical foundations, and to study some application examples. Exercises are proposed, and usually solved in class, for each topic in order to test the acquisition of knowledge. The student will also learn to use a development tool for each type of cyberphysical system covered (nuXmv, Spin, Uppaal, Matlab-Simulink/Stateflow).

Part of the course will introduce the python language, which is useful for processing data acquired from the above systems, with emphasis on data science and machine learning.

The project that will be agreed upon for the exam is aimed at stimulating and verifying the student's design and implementation skills, as well as the operational field verification of part of the acquired knowledge.

The learning outcomes concern the realization of the above training objectives, including through the implementation of a project. At the end of the course the student will be able to analyze and design engineering solutions based on various types of cyber-physical systems, in various types of applications.

PREREQUISITES

Digital Systems Electronics

Programming basics

Computer architecture basics

TEACHING METHODS

Lectures, with use of slides, and examples/exercises carried out both on blackboard and PC (or tele-learning, if made necessary), using the development/simulation tools indicated in class. Student reception. Proposal, implementation and discussion of a project.

SYLLABUS/CONTENT

Modeling, simulation and verification of cyberphysical systems

- Introduction.

- Synchronous models

- Safety requirements

- Asynchronous models

- Liveness requirements

- Dynamic systems

- Timed systems

- Hybrid systems

Introduction to the python language

- Data types

- Functions

- OOP

- File systems

- numpy library

- Pandas library

- (pyplot library)

RECOMMENDED READING/BIBLIOGRAPHY

R. Alur, Principles of Cyberphysical Systems: 
https://mitpress.mit.edu/books/principles-cyber-physical-systems

J. VanderPlas, Python Data Science Handbook, O'Reilly
https://www.oreilly.com/library/view/python-data-science/9781491912126/…;

Lecture notes and other material suggested by the lecturer during the course