identification and analysis of data

First lesson.
I will explain the main content of the course
Aim of the course is the following:

To understand how to extract, to get the rigth parameters and the interactions, the model, starting from data (measuerements of the sytems).
How to deal with noisy measurements and how to filter the noise.

Today I will talk about stochastic variables. I will revise some probability concept, talking about indipendent and uncorrelated variable. I will intrroduce the probability density.

control

Today first lesson.
I wil describe the aim of the course.
What you need to acquire at teh end of the course?

To be able to model a system and design for it a controller in order to
impose to the system (natural or artificial) a desired behaviour.

The course will be devoted to a first part of analysis and a second part of controller syntesys .

I will describe what is a control system.
I will show some example taken from reality: driving a car, a manifacturing system, the control of a tank, the conditioning of temperature in a building.
The main concept is the definition of controlled and manipulating variables, the classical input and output definition. I will introduce the concept of state.

system identification

An interesting recent paper on the story of system identification
is the following:

	A personal view of the development of system identification: A 30-year journey through an exciting field Gevers, M.; Control Systems Magazine, IEEE Volume 26, Issue 6, Dec. 2006 Page(s):93 - 105 Digital Object Identifier 10.1109/MCS.2006.252834 Summary: In this article the author describes the development of system identification in the control community as he has observed it over the last 30 years, both as a student of the subject eager to learn and understand the work of his colleagues and as an a.....
		AbstractPlus | Full Text: PDF(698 KB) IEEE JNL