EL3201 Datadriven modellering, grundläggande kurs 8,0 hp

Data-Driven Modeling, Basic Course

  • Utbildningsnivå

    Forskarnivå
  • Huvudområde

  • Betygsskala

    P, F

Kurstillfällen/kursomgångar

HT18 för programstuderande

  • Perioder

    HT18 P2 (4,0 hp)

    VT19 P3 (4,0 hp)

  • Anmälningskod

    51642

  • Kursen startar

    2018-10-29

  • Kursen slutar

    2019-03-15

  • Undervisningsspråk

    Engelska

  • Studielokalisering

    KTH Campus

  • Undervisningstid

    Dagtid

  • Undervisningsform

    Normal

  • Antal platser

    Ingen begränsning

Information för forskarstuderande om när kursen ges

181017-190320

Lärandemål

After the course, the student should be able to:

·         describe the general principles for system identification.

·         identify systems in a satisfactory manner. This includes choice of excitation signals, model structure and estimation algorithm as well as proper use of model validation.

·         analyse basic model properties, such as identifiability and  accuracy (bias and variance errors).

Kursens huvudsakliga innehåll

Signal spectra, linear time-invariant sytems, prediction and filtering, linear and non-linear models, identifiability, non-parametric methods, parameter estimation, maximum likelihood estimation, linear regression, least-squares estimation, the prediction error method, the instrumental variable method, subspace identification, kernel methods, support vector machines, convergence and consistency, modeling accuracy, Cramér-Rao lower bound, numerical optimization, recursive estimation, bias and variance errors, experiment design, applications oriented system identification, choice of identification criterion, model validation, model structure selection, system identification in practice.

Kursupplägg

Lectures, exercises, presentations on selected topics by the participants, homework problems, 72 h take home exam

Behörighet

Litteratur

Lennart Ljung, System identification: Theory for the user, 2nd ed. Prentice-Hall 1999. Handouts.  

A good complement is:

Torsten Söderström and Petre Stoica. System Identification, 1989

Utrustningskrav

Compulsory information

Examination

Krav för slutbetyg

·         15 min oral presentation of a selected topic in one of the lectures

·         80% on weekly home-work problems

·         project (preferably on a problem related to the student’s own research)

·         50 % on 72 h take home exam

Ges av

EECS/Reglerteknik

Examinator

Håkan Hjalmarsson <hjalmars@kth.se>

Versionsinformation

Kursplan gäller från och med VT2014.
Examinationsinformation gäller från och med VT2019.