Introduction

Loading...

From the course by University of California, Santa Cruz

Cyber-Physical Systems: Modeling and Simulation

6 ratings

University of California, Santa Cruz

Cyber-Physical Systems: Modeling and Simulation

6 ratings

Cyber-physical systems (CPS for short) combine digital and analog devices, interfaces, networks, computer systems, and the like, with the natural and man-made physical world. The inherent interconnected and heterogeneous combination of behaviors in these systems makes their analysis and design an exciting and challenging task. CPS: Modeling and Simulation provides you with an introduction to modeling and simulation of cyber-physical systems. The main focus is on models of physical process, finite state machines, computation, converters between physical and cyber variables, and digital networks. The instructor of this course is Ricardo Sanfelice (https://hybrid.soe.ucsc.edu), Associate Professor in the Department of Computer Engineering at the University of California Santa Cruz.

From the lesson

Basic Modeling Concepts: Discrete-time and Continuous-Time Systems

Welcome to the Course5:35

Introduction5:39

Modeling Cyber-Physical Systems5:47

Discrete-Time Systems Concepts (Part 1)9:18

Discrete-Time Systems Concepts (Part 2)8:35

A Discrete-Time Model of a Ground Vehicle8:35

Simulation of a Discrete-Time Model of a Ground Vehicle16:54

Continuous-Time Concepts (Part 1)6:40

A Continuous-Time Model of a Ground Vehicle8:34

Simulation of a Continuous-Time Model of a Ground Vehicle20:27

Continuous-Time Concepts (Part 2)8:13

A Continuous-Time Model of a Linear Time-Invariant System8:39

A Continuous-Time Model of the Temperature in a Room9:09

Simulation of the Temperature in a Room13:22

Meet the Instructors

Ricardo Sanfelice
Professor
Department of Electrical and Computer Engineering

[MUSIC]

In this lecture we will learn about cyber-physical systems,

the main definition of cyber-physical systems and

describe the main components of such a system.

A cyber-physical system, As the name suggests,

is a system that combines,

Physics, With cyber components,

Potentially, Networked,

And tightly, Interconnected.

The term physics is typically related to the actual systems,

the tangible part of the system.

And many times we relate to the physics under the term plant

process of our system itself.

The part corresponding to the cyber,

Is related to the computational components,

The software, The code itself.

When we think about a cyber-physical system,

we think about these two components being tightly interconnected.

And as we define it here potentially networked.

If we would like to take a diagram

view of this type of system, we can consider the following

interconnected system where we have two main blocks.

One corresponds to the physics, And the other one corresponds to the cyber.

So when we design the physical component,

we need to keep an eye also in how the code, the computational part,

will play around in this interconnection.

So these arrows represent how information can transfer

from physics to the cyber part.

And this information might have different type of, the nature might be different.

And therefore, we need to somehow convert between these signals.

And maybe there's some networking between this, for

which we will need to actually add to this diagram some sort of an interface.

And this is what these blocks are going to be doing for us.

Defining the way that information is translated

between these different pieces of the system.

As we mentioned, this interface could be actually a network.

It could be a converter.

In the case of this path from physics to cyber,

we will need a converter from analog to digital,

For short, ADC.

But we can have other type of interfaces.

On the side of connecting the completing part, the cyber part, with the physics,

we will also have a network, potentially, and also a converter,

From digital in this case, which is where

the cyber runs to analog, which for short is,

Which for short is DAC.

So now we have an interconnection of systems where now these

arrows will be going into the different portions of the system.

And our goal is to understand how to design all of these pieces so

that in time their connection evolves over time the way we would like it to evolve.

For instance, we would like the valuables of the physical system

to perhaps converge to a particular condition.

And in order to do that, we need to define the algorithmic

part that holistically interface to the physics and

accomplishes that particular convergence property we would like to have.

[MUSIC]

Explore our Catalog

Join for free and get personalized recommendations, updates and offers.

Coursera provides universal access to the world’s best education, partnering with top universities and organizations to offer courses online.

© 2018 Coursera Inc. All rights reserved.

Download on the App Store

Get it on Google Play