Analog to Digital Conversion

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来自 University of California, Santa Cruz 的课程

Cyber-Physical Systems: Modeling and Simulation

6 个评分

University of California, Santa Cruz

Cyber-Physical Systems: Modeling and Simulation

6 个评分

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.

从本节课中

Modeling Interfaces for Cyber-Physical Systems: Conversion, Networks, and Complete CPS Models

Analog to Digital Conversion6:08

A Model of an Analog to Digital Converter9:38

Digital to Analog Conversion10:28

A Model of a Digital to Analog Converter4:01

Simulation of an Analog to Digital Converter5:34

A Model of an Implemented Finite-State Machine8:56

Simulation of an Implemented Finite State Machine4:54

A Digital Communication Network13:16

Simulation of a Digital Communication Network7:52

A Cyber-Physical System Model for Estimation Over a Network12:10

Simulation of a Cyber-Physical System Model for Estimation Over a Network6:32

A Cyber-Physical System Model for Sample and Hold Control9:03

Simulation of a Cyber-Physical System Model for Sample and Hold Control10:17

与讲师见面

Ricardo Sanfelice
Associate Professor
Department of Computer Engineering

With the model of the physics given by

differential equations and of the cyber given by difference equation,

what we would like to understand now is how to interconnect these systems.

I mean, we think about how the interconnection occurs in

the cyber physical system itself in the hardware.

What we typically have is the physics and

the cyber connected through some interfaces.

You can think about these interfaces as single conditioners,

converters, or even networks.

The interfaces will allow the signals that

the physics generates to be compatible with

the signals that the cyber requires on the other way around.

So you can think of having

a closed loop system where information flows in this direction,

but different interconnections might be possible based on the application of interest.

Now, we already know that

one possible and powerful way to model the physical components is using

differential equations with constraints.

The constraints will potentially be on the state.

Remember Z or in the input U.

A similar type of model can be used for the cyber.

But now, it will be based on difference equations,

because the natural behavior in

this component is discrete.

For the interfaces, because they do these translation of the signals,

we might expect that we will have models that involve the two type of objects,

differential equations and difference equations.

So there is some sort of partition here on the dynamics.

So we are going to believe for a second that

this combined differential and

difference equations of course with potential constraints,

and with these models,

we can actually have our events triggered

by state and inputs of each

of the systems where the inputs now for these interfaces will be

the outputs of the components that we will describe.

For the interfaces themselves,

we're going to touch on a few of these.

The first one that we're going to work on will be

one that will be useful to convert analog signals

into digital signals and would be useful to

motivate the idea of modern interfaces in general.

This will be an analog to digital converter,

ADC for short, and then digital to analog converter, DAC.

And then, using the ideas to model these two,

we will arrive to a digital network model.

When I mention key events,

if you consider these converter,

you could envision that every time that the signal here,

a sample, and convert it into digital number,

that is an event.

So we have here conversion events and the same here.

On the other hand, in the network model where we will have our communication events.

The idea for us will be to come up with models

of each of these that we're going to do in the forthcoming videos.

And then, once we have those models,

we can come up with a full CPS model that

uses the models that we already know for the physics.

And if you use a finite state machine or if you use a discrete algorithm,

we know that already.

And then within your model that we are about to derive,

we will be able to actually build

that big model which will involve necessarily differential equations,

difference equations, and these events that we're talking about.

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