Comparison of different approaches to continuous-time system identification from sampled data

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26620%2F18%3APU129119" target="_blank" >RIV/00216305:26620/18:PU129119 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1109/EECS.2017.21" target="_blank" >http://dx.doi.org/10.1109/EECS.2017.21</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/EECS.2017.21" target="_blank" >10.1109/EECS.2017.21</a>

Result language

angličtina

Original language name

Comparison of different approaches to continuous-time system identification from sampled data

Original language description

This article deals with different approaches to continuous-time system identification from sampled data. Continuous-time system identification is important problem in control theory. Continuous time models provide many advantages against discrete time models because of better physical insight into the system properties. The traditional approach with least squares method with state variable filters is presented. Two alternative approaches to continuous-time identification are proposed. The generalized Laguerre functions method and the method based on least squares estimation with numerical solution of differential equation are introduced. These three different approaches to continuous-time system identification from sampled data are compared on the example. It is shown that proposed alternative methods can give better results in terms of relative root mean square error of the outputs of the identified systems than the least squares method with state variable filters.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2017

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

2017 European Conference on Electrical Engineering and Computer Science (EECS) (2017)

ISBN

978-1-5386-2085-4

ISSN

—

e-ISSN

—

Number of pages

5

Pages from-to

61-65

Publisher name

Neuveden

Place of publication

Neuveden

Event location

Bern

Event date

Nov 17, 2017

Type of event by nationality

EUR - Evropská akce

UT code for WoS article

000455867600013