Computer Science, Electrical Engineering
SMR012 Identification 6.0 ECTS credits
DENNA SIDA FINNS OCKSÅ PÅ SVENSKA
General information about studying at Luleå University
TIMEPERIOD: Lp I
LANGUAGE: English/Swedish
EXAMINER
A Medvedev Univ lekt
PREREQUISITES
SMS020 and SMS021 Signal and Systems I and II
COURSE AIM
The course is aimed to give a working knowledge of the mathematical methods for modeling of systems from experimental data.
CONTENTS
Introduction. Stochastic background. Nonparametric methods in identification. Least--squares, static models, BLUE estimators.
Input signals, persistent excitation Least-squares, dynamic methods. Prediction error methods, dynamic models. Instrumental variable methods. Recursive identification methods. Closed loop systems identification. Model validation.
LABS
1. Least-squares method
2. Instrumental variabel method
3. Method's benchmark
4. Recursive identification
TEACHING
The teaching consists of lectures, and four compulsory laboratory excercises.
EXAMINATION
COURSE GRADE SCALE: U, 3, 4, 5
ITEMS AND CREDITS
Laboratory work 2.2 ECTS
Written exam 3.7 ECTS
COURSE LITERATURE
Söderström, Stoica: System Identification. Prentice Hall 1989
Laboration-PM.
REMARKS
Last modified 97-03-05
Further information: Alexander Medvedev, Tel. 0920-91302
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